From 2c46dae37787e36f68db954f37addf2ddaa69458 Mon Sep 17 00:00:00 2001
From: Daniele Morotti <58258368+DanieleMorotti@users.noreply.github.com>
Date: Wed, 14 May 2025 17:31:42 +0200
Subject: [PATCH 01/68] Fixed a bug for "detail" attribute in input image
(#685)
When an input image is given as input, the code tries to access the
'detail' key, that may not be present as noted in #159.
With this pull request, now it tries to access the key, otherwise set
the value to `None`.
@pakrym-oai or @rm-openai let me know if you want any changes.
---
src/agents/models/chatcmpl_converter.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/src/agents/models/chatcmpl_converter.py b/src/agents/models/chatcmpl_converter.py
index 613a37453..1d599e8c0 100644
--- a/src/agents/models/chatcmpl_converter.py
+++ b/src/agents/models/chatcmpl_converter.py
@@ -234,7 +234,7 @@ def extract_all_content(
type="image_url",
image_url={
"url": casted_image_param["image_url"],
- "detail": casted_image_param["detail"],
+ "detail": casted_image_param.get("detail", "auto"),
},
)
)
From 1994f9d4c4bb807fd5460919b4352b715ef1324a Mon Sep 17 00:00:00 2001
From: Ashok Saravanan <90977640+AshokSaravanan222@users.noreply.github.com>
Date: Wed, 14 May 2025 11:34:27 -0500
Subject: [PATCH 02/68] feat: pass extra_body through to LiteLLM acompletion
(#638)
**Purpose**
Allow arbitrary `extra_body` parameters (e.g. `cached_content`) to be
forwarded into the LiteLLM call. Useful for context caching in Gemini
models
([docs](https://ai.google.dev/gemini-api/docs/caching?lang=python)).
**Example usage**
```python
import os
from agents import Agent, ModelSettings
from agents.extensions.models.litellm_model import LitellmModel
cache_name = "cachedContents/34jopukfx5di" # previously stored context
gemini_model = LitellmModel(
model="gemini/gemini-1.5-flash-002",
api_key=os.getenv("GOOGLE_API_KEY")
)
agent = Agent(
name="Cached Gemini Agent",
model=gemini_model,
model_settings=ModelSettings(
extra_body={"cached_content": cache_name}
)
)
---
src/agents/extensions/models/litellm_model.py | 2 +
tests/models/test_litellm_extra_body.py | 45 +++++++++++++++++++
2 files changed, 47 insertions(+)
create mode 100644 tests/models/test_litellm_extra_body.py
diff --git a/src/agents/extensions/models/litellm_model.py b/src/agents/extensions/models/litellm_model.py
index dc672acd4..d3b25a198 100644
--- a/src/agents/extensions/models/litellm_model.py
+++ b/src/agents/extensions/models/litellm_model.py
@@ -269,6 +269,8 @@ async def _fetch_response(
extra_kwargs["extra_query"] = model_settings.extra_query
if model_settings.metadata:
extra_kwargs["metadata"] = model_settings.metadata
+ if model_settings.extra_body and isinstance(model_settings.extra_body, dict):
+ extra_kwargs.update(model_settings.extra_body)
ret = await litellm.acompletion(
model=self.model,
diff --git a/tests/models/test_litellm_extra_body.py b/tests/models/test_litellm_extra_body.py
new file mode 100644
index 000000000..ac56c25cf
--- /dev/null
+++ b/tests/models/test_litellm_extra_body.py
@@ -0,0 +1,45 @@
+import litellm
+import pytest
+from litellm.types.utils import Choices, Message, ModelResponse, Usage
+
+from agents.extensions.models.litellm_model import LitellmModel
+from agents.model_settings import ModelSettings
+from agents.models.interface import ModelTracing
+
+
+@pytest.mark.allow_call_model_methods
+@pytest.mark.asyncio
+async def test_extra_body_is_forwarded(monkeypatch):
+ """
+ Forward `extra_body` entries into litellm.acompletion kwargs.
+
+ This ensures that user-provided parameters (e.g. cached_content)
+ arrive alongside default arguments.
+ """
+ captured: dict[str, object] = {}
+
+ async def fake_acompletion(model, messages=None, **kwargs):
+ captured.update(kwargs)
+ msg = Message(role="assistant", content="ok")
+ choice = Choices(index=0, message=msg)
+ return ModelResponse(choices=[choice], usage=Usage(0, 0, 0))
+
+ monkeypatch.setattr(litellm, "acompletion", fake_acompletion)
+ settings = ModelSettings(
+ temperature=0.1,
+ extra_body={"cached_content": "some_cache", "foo": 123}
+ )
+ model = LitellmModel(model="test-model")
+
+ await model.get_response(
+ system_instructions=None,
+ input=[],
+ model_settings=settings,
+ tools=[],
+ output_schema=None,
+ handoffs=[],
+ tracing=ModelTracing.DISABLED,
+ previous_response_id=None,
+ )
+
+ assert {"cached_content": "some_cache", "foo": 123}.items() <= captured.items()
From 02b6e7013cf00de92b453610f459be40f344e6a8 Mon Sep 17 00:00:00 2001
From: leohpark <135409779+leohpark@users.noreply.github.com>
Date: Wed, 14 May 2025 09:37:06 -0700
Subject: [PATCH 03/68] Update search_agent.py (#677)
Added missing word "be" in prompt instructions.
This is unlikely to change the agent functionality in most cases, but
optimal clarity in prompt language is a best practice.
---
examples/research_bot/agents/search_agent.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/examples/research_bot/agents/search_agent.py b/examples/research_bot/agents/search_agent.py
index 0212ce5b5..61f91701f 100644
--- a/examples/research_bot/agents/search_agent.py
+++ b/examples/research_bot/agents/search_agent.py
@@ -3,7 +3,7 @@
INSTRUCTIONS = (
"You are a research assistant. Given a search term, you search the web for that term and "
- "produce a concise summary of the results. The summary must 2-3 paragraphs and less than 300 "
+ "produce a concise summary of the results. The summary must be 2-3 paragraphs and less than 300 "
"words. Capture the main points. Write succinctly, no need to have complete sentences or good "
"grammar. This will be consumed by someone synthesizing a report, so its vital you capture the "
"essence and ignore any fluff. Do not include any additional commentary other than the summary "
From 1847008e0f247e5468d691e4e9d780f984db9a18 Mon Sep 17 00:00:00 2001
From: Akshit97 <akshitagarwal97@gmail.com>
Date: Thu, 15 May 2025 00:15:14 +0530
Subject: [PATCH 04/68] feat: Streamable HTTP support (#643)
Co-authored-by: aagarwal25 <akshit_agarwal@intuit.com>
---
examples/mcp/streamablehttp_example/README.md | 13 +++
examples/mcp/streamablehttp_example/main.py | 83 ++++++++++++++
examples/mcp/streamablehttp_example/server.py | 33 ++++++
pyproject.toml | 2 +-
src/agents/mcp/__init__.py | 4 +
src/agents/mcp/server.py | 106 ++++++++++++++++--
uv.lock | 20 +++-
7 files changed, 247 insertions(+), 14 deletions(-)
create mode 100644 examples/mcp/streamablehttp_example/README.md
create mode 100644 examples/mcp/streamablehttp_example/main.py
create mode 100644 examples/mcp/streamablehttp_example/server.py
diff --git a/examples/mcp/streamablehttp_example/README.md b/examples/mcp/streamablehttp_example/README.md
new file mode 100644
index 000000000..a07fe19be
--- /dev/null
+++ b/examples/mcp/streamablehttp_example/README.md
@@ -0,0 +1,13 @@
+# MCP Streamable HTTP Example
+
+This example uses a local Streamable HTTP server in [server.py](server.py).
+
+Run the example via:
+
+```
+uv run python examples/mcp/streamablehttp_example/main.py
+```
+
+## Details
+
+The example uses the `MCPServerStreamableHttp` class from `agents.mcp`. The server runs in a sub-process at `https://localhost:8000/mcp`.
diff --git a/examples/mcp/streamablehttp_example/main.py b/examples/mcp/streamablehttp_example/main.py
new file mode 100644
index 000000000..cc95e798b
--- /dev/null
+++ b/examples/mcp/streamablehttp_example/main.py
@@ -0,0 +1,83 @@
+import asyncio
+import os
+import shutil
+import subprocess
+import time
+from typing import Any
+
+from agents import Agent, Runner, gen_trace_id, trace
+from agents.mcp import MCPServer, MCPServerStreamableHttp
+from agents.model_settings import ModelSettings
+
+
+async def run(mcp_server: MCPServer):
+ agent = Agent(
+ name="Assistant",
+ instructions="Use the tools to answer the questions.",
+ mcp_servers=[mcp_server],
+ model_settings=ModelSettings(tool_choice="required"),
+ )
+
+ # Use the `add` tool to add two numbers
+ message = "Add these numbers: 7 and 22."
+ print(f"Running: {message}")
+ result = await Runner.run(starting_agent=agent, input=message)
+ print(result.final_output)
+
+ # Run the `get_weather` tool
+ message = "What's the weather in Tokyo?"
+ print(f"\n\nRunning: {message}")
+ result = await Runner.run(starting_agent=agent, input=message)
+ print(result.final_output)
+
+ # Run the `get_secret_word` tool
+ message = "What's the secret word?"
+ print(f"\n\nRunning: {message}")
+ result = await Runner.run(starting_agent=agent, input=message)
+ print(result.final_output)
+
+
+async def main():
+ async with MCPServerStreamableHttp(
+ name="Streamable HTTP Python Server",
+ params={
+ "url": "http://localhost:8000/mcp",
+ },
+ ) as server:
+ trace_id = gen_trace_id()
+ with trace(workflow_name="Streamable HTTP Example", trace_id=trace_id):
+ print(f"View trace: https://platform.openai.com/traces/trace?trace_id={trace_id}\n")
+ await run(server)
+
+
+if __name__ == "__main__":
+ # Let's make sure the user has uv installed
+ if not shutil.which("uv"):
+ raise RuntimeError(
+ "uv is not installed. Please install it: https://docs.astral.sh/uv/getting-started/installation/"
+ )
+
+ # We'll run the Streamable HTTP server in a subprocess. Usually this would be a remote server, but for this
+ # demo, we'll run it locally at http://localhost:8000/mcp
+ process: subprocess.Popen[Any] | None = None
+ try:
+ this_dir = os.path.dirname(os.path.abspath(__file__))
+ server_file = os.path.join(this_dir, "server.py")
+
+ print("Starting Streamable HTTP server at http://localhost:8000/mcp ...")
+
+ # Run `uv run server.py` to start the Streamable HTTP server
+ process = subprocess.Popen(["uv", "run", server_file])
+ # Give it 3 seconds to start
+ time.sleep(3)
+
+ print("Streamable HTTP server started. Running example...\n\n")
+ except Exception as e:
+ print(f"Error starting Streamable HTTP server: {e}")
+ exit(1)
+
+ try:
+ asyncio.run(main())
+ finally:
+ if process:
+ process.terminate()
diff --git a/examples/mcp/streamablehttp_example/server.py b/examples/mcp/streamablehttp_example/server.py
new file mode 100644
index 000000000..d8f839652
--- /dev/null
+++ b/examples/mcp/streamablehttp_example/server.py
@@ -0,0 +1,33 @@
+import random
+
+import requests
+from mcp.server.fastmcp import FastMCP
+
+# Create server
+mcp = FastMCP("Echo Server")
+
+
+@mcp.tool()
+def add(a: int, b: int) -> int:
+ """Add two numbers"""
+ print(f"[debug-server] add({a}, {b})")
+ return a + b
+
+
+@mcp.tool()
+def get_secret_word() -> str:
+ print("[debug-server] get_secret_word()")
+ return random.choice(["apple", "banana", "cherry"])
+
+
+@mcp.tool()
+def get_current_weather(city: str) -> str:
+ print(f"[debug-server] get_current_weather({city})")
+
+ endpoint = "https://wttr.in"
+ response = requests.get(f"{endpoint}/{city}")
+ return response.text
+
+
+if __name__ == "__main__":
+ mcp.run(transport="streamable-http")
diff --git a/pyproject.toml b/pyproject.toml
index 22b028ae7..87a707d3d 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -13,7 +13,7 @@ dependencies = [
"typing-extensions>=4.12.2, <5",
"requests>=2.0, <3",
"types-requests>=2.0, <3",
- "mcp>=1.6.0, <2; python_version >= '3.10'",
+ "mcp>=1.8.0, <2; python_version >= '3.10'",
]
classifiers = [
"Typing :: Typed",
diff --git a/src/agents/mcp/__init__.py b/src/agents/mcp/__init__.py
index 1a72a89f0..d4eb8fa68 100644
--- a/src/agents/mcp/__init__.py
+++ b/src/agents/mcp/__init__.py
@@ -5,6 +5,8 @@
MCPServerSseParams,
MCPServerStdio,
MCPServerStdioParams,
+ MCPServerStreamableHttp,
+ MCPServerStreamableHttpParams,
)
except ImportError:
pass
@@ -17,5 +19,7 @@
"MCPServerSseParams",
"MCPServerStdio",
"MCPServerStdioParams",
+ "MCPServerStreamableHttp",
+ "MCPServerStreamableHttpParams",
"MCPUtil",
]
diff --git a/src/agents/mcp/server.py b/src/agents/mcp/server.py
index 9916c92b0..c5255ead7 100644
--- a/src/agents/mcp/server.py
+++ b/src/agents/mcp/server.py
@@ -10,7 +10,9 @@
from anyio.streams.memory import MemoryObjectReceiveStream, MemoryObjectSendStream
from mcp import ClientSession, StdioServerParameters, Tool as MCPTool, stdio_client
from mcp.client.sse import sse_client
-from mcp.types import CallToolResult, JSONRPCMessage
+from mcp.client.streamable_http import GetSessionIdCallback, streamablehttp_client
+from mcp.shared.message import SessionMessage
+from mcp.types import CallToolResult
from typing_extensions import NotRequired, TypedDict
from ..exceptions import UserError
@@ -83,8 +85,9 @@ def create_streams(
self,
) -> AbstractAsyncContextManager[
tuple[
- MemoryObjectReceiveStream[JSONRPCMessage | Exception],
- MemoryObjectSendStream[JSONRPCMessage],
+ MemoryObjectReceiveStream[SessionMessage | Exception],
+ MemoryObjectSendStream[SessionMessage],
+ GetSessionIdCallback | None
]
]:
"""Create the streams for the server."""
@@ -105,7 +108,11 @@ async def connect(self):
"""Connect to the server."""
try:
transport = await self.exit_stack.enter_async_context(self.create_streams())
- read, write = transport
+ # streamablehttp_client returns (read, write, get_session_id)
+ # sse_client returns (read, write)
+
+ read, write, *_ = transport
+
session = await self.exit_stack.enter_async_context(
ClientSession(
read,
@@ -232,8 +239,9 @@ def create_streams(
self,
) -> AbstractAsyncContextManager[
tuple[
- MemoryObjectReceiveStream[JSONRPCMessage | Exception],
- MemoryObjectSendStream[JSONRPCMessage],
+ MemoryObjectReceiveStream[SessionMessage | Exception],
+ MemoryObjectSendStream[SessionMessage],
+ GetSessionIdCallback | None
]
]:
"""Create the streams for the server."""
@@ -302,8 +310,9 @@ def create_streams(
self,
) -> AbstractAsyncContextManager[
tuple[
- MemoryObjectReceiveStream[JSONRPCMessage | Exception],
- MemoryObjectSendStream[JSONRPCMessage],
+ MemoryObjectReceiveStream[SessionMessage | Exception],
+ MemoryObjectSendStream[SessionMessage],
+ GetSessionIdCallback | None
]
]:
"""Create the streams for the server."""
@@ -318,3 +327,84 @@ def create_streams(
def name(self) -> str:
"""A readable name for the server."""
return self._name
+
+
+class MCPServerStreamableHttpParams(TypedDict):
+ """Mirrors the params in`mcp.client.streamable_http.streamablehttp_client`."""
+
+ url: str
+ """The URL of the server."""
+
+ headers: NotRequired[dict[str, str]]
+ """The headers to send to the server."""
+
+ timeout: NotRequired[timedelta]
+ """The timeout for the HTTP request. Defaults to 5 seconds."""
+
+ sse_read_timeout: NotRequired[timedelta]
+ """The timeout for the SSE connection, in seconds. Defaults to 5 minutes."""
+
+ terminate_on_close: NotRequired[bool]
+ """Terminate on close"""
+
+
+class MCPServerStreamableHttp(_MCPServerWithClientSession):
+ """MCP server implementation that uses the Streamable HTTP transport. See the [spec]
+ (https://modelcontextprotocol.io/specification/2025-03-26/basic/transports#streamable-http)
+ for details.
+ """
+
+ def __init__(
+ self,
+ params: MCPServerStreamableHttpParams,
+ cache_tools_list: bool = False,
+ name: str | None = None,
+ client_session_timeout_seconds: float | None = 5,
+ ):
+ """Create a new MCP server based on the Streamable HTTP transport.
+
+ Args:
+ params: The params that configure the server. This includes the URL of the server,
+ the headers to send to the server, the timeout for the HTTP request, and the
+ timeout for the Streamable HTTP connection and whether we need to
+ terminate on close.
+
+ cache_tools_list: Whether to cache the tools list. If `True`, the tools list will be
+ cached and only fetched from the server once. If `False`, the tools list will be
+ fetched from the server on each call to `list_tools()`. The cache can be
+ invalidated by calling `invalidate_tools_cache()`. You should set this to `True`
+ if you know the server will not change its tools list, because it can drastically
+ improve latency (by avoiding a round-trip to the server every time).
+
+ name: A readable name for the server. If not provided, we'll create one from the
+ URL.
+
+ client_session_timeout_seconds: the read timeout passed to the MCP ClientSession.
+ """
+ super().__init__(cache_tools_list, client_session_timeout_seconds)
+
+ self.params = params
+ self._name = name or f"streamable_http: {self.params['url']}"
+
+ def create_streams(
+ self,
+ ) -> AbstractAsyncContextManager[
+ tuple[
+ MemoryObjectReceiveStream[SessionMessage | Exception],
+ MemoryObjectSendStream[SessionMessage],
+ GetSessionIdCallback | None
+ ]
+ ]:
+ """Create the streams for the server."""
+ return streamablehttp_client(
+ url=self.params["url"],
+ headers=self.params.get("headers", None),
+ timeout=self.params.get("timeout", timedelta(seconds=30)),
+ sse_read_timeout=self.params.get("sse_read_timeout", timedelta(seconds=60 * 5)),
+ terminate_on_close=self.params.get("terminate_on_close", True)
+ )
+
+ @property
+ def name(self) -> str:
+ """A readable name for the server."""
+ return self._name
diff --git a/uv.lock b/uv.lock
index 87dd3cd2c..6ccc19966 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1047,7 +1047,7 @@ wheels = [
[[package]]
name = "mcp"
-version = "1.6.0"
+version = "1.8.1"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "anyio", marker = "python_full_version >= '3.10'" },
@@ -1055,13 +1055,14 @@ dependencies = [
{ name = "httpx-sse", marker = "python_full_version >= '3.10'" },
{ name = "pydantic", marker = "python_full_version >= '3.10'" },
{ name = "pydantic-settings", marker = "python_full_version >= '3.10'" },
+ { name = "python-multipart", marker = "python_full_version >= '3.10'" },
{ name = "sse-starlette", marker = "python_full_version >= '3.10'" },
{ name = "starlette", marker = "python_full_version >= '3.10'" },
- { name = "uvicorn", marker = "python_full_version >= '3.10'" },
+ { name = "uvicorn", marker = "python_full_version >= '3.10' and sys_platform != 'emscripten'" },
]
-sdist = { url = "https://files.pythonhosted.org/packages/95/d2/f587cb965a56e992634bebc8611c5b579af912b74e04eb9164bd49527d21/mcp-1.6.0.tar.gz", hash = "sha256:d9324876de2c5637369f43161cd71eebfd803df5a95e46225cab8d280e366723", size = 200031 }
+sdist = { url = "https://files.pythonhosted.org/packages/7c/13/16b712e8a3be6a736b411df2fc6b4e75eb1d3e99b1cd57a3a1decf17f612/mcp-1.8.1.tar.gz", hash = "sha256:ec0646271d93749f784d2316fb5fe6102fb0d1be788ec70a9e2517e8f2722c0e", size = 265605 }
wheels = [
- { url = "https://files.pythonhosted.org/packages/10/30/20a7f33b0b884a9d14dd3aa94ff1ac9da1479fe2ad66dd9e2736075d2506/mcp-1.6.0-py3-none-any.whl", hash = "sha256:7bd24c6ea042dbec44c754f100984d186620d8b841ec30f1b19eda9b93a634d0", size = 76077 },
+ { url = "https://files.pythonhosted.org/packages/1c/5d/91cf0d40e40ae9ecf8d4004e0f9611eea86085aa0b5505493e0ff53972da/mcp-1.8.1-py3-none-any.whl", hash = "sha256:948e03783859fa35abe05b9b6c0a1d5519be452fc079dc8d7f682549591c1770", size = 119761 },
]
[[package]]
@@ -1533,7 +1534,7 @@ requires-dist = [
{ name = "graphviz", marker = "extra == 'viz'", specifier = ">=0.17" },
{ name = "griffe", specifier = ">=1.5.6,<2" },
{ name = "litellm", marker = "extra == 'litellm'", specifier = ">=1.67.4.post1,<2" },
- { name = "mcp", marker = "python_full_version >= '3.10'", specifier = ">=1.6.0,<2" },
+ { name = "mcp", marker = "python_full_version >= '3.10'", specifier = ">=1.8.0,<2" },
{ name = "numpy", marker = "python_full_version >= '3.10' and extra == 'voice'", specifier = ">=2.2.0,<3" },
{ name = "openai", specifier = ">=1.76.0" },
{ name = "pydantic", specifier = ">=2.10,<3" },
@@ -2085,6 +2086,15 @@ wheels = [
{ url = "https://files.pythonhosted.org/packages/1e/18/98a99ad95133c6a6e2005fe89faedf294a748bd5dc803008059409ac9b1e/python_dotenv-1.1.0-py3-none-any.whl", hash = "sha256:d7c01d9e2293916c18baf562d95698754b0dbbb5e74d457c45d4f6561fb9d55d", size = 20256 },
]
+[[package]]
+name = "python-multipart"
+version = "0.0.20"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/f3/87/f44d7c9f274c7ee665a29b885ec97089ec5dc034c7f3fafa03da9e39a09e/python_multipart-0.0.20.tar.gz", hash = "sha256:8dd0cab45b8e23064ae09147625994d090fa46f5b0d1e13af944c331a7fa9d13", size = 37158 }
+wheels = [
+ { url = "https://files.pythonhosted.org/packages/45/58/38b5afbc1a800eeea951b9285d3912613f2603bdf897a4ab0f4bd7f405fc/python_multipart-0.0.20-py3-none-any.whl", hash = "sha256:8a62d3a8335e06589fe01f2a3e178cdcc632f3fbe0d492ad9ee0ec35aab1f104", size = 24546 },
+]
+
[[package]]
name = "python-xlib"
version = "0.33"
From 5fe096df67cf7ada53f0bd38954b7f12743b790b Mon Sep 17 00:00:00 2001
From: Rohan Mehta <rm@openai.com>
Date: Thu, 15 May 2025 18:41:00 -0400
Subject: [PATCH 05/68] v0.0.15 (#701)
---
pyproject.toml | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/pyproject.toml b/pyproject.toml
index 87a707d3d..672258c42 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
[project]
name = "openai-agents"
-version = "0.0.14"
+version = "0.0.15"
description = "OpenAI Agents SDK"
readme = "README.md"
requires-python = ">=3.9"
From c282324d9519b037ced8abe3678c86f7dd344a97 Mon Sep 17 00:00:00 2001
From: Dominik Kundel <dkundel@openai.com>
Date: Sun, 18 May 2025 10:24:24 -0700
Subject: [PATCH 06/68] Create AGENTS.md (#707)
Adding an AGENTS.md file for Codex use
---
AGENTS.md | 69 +++++++++++++++++++++++++++++++++++++++++++++++++++++++
1 file changed, 69 insertions(+)
create mode 100644 AGENTS.md
diff --git a/AGENTS.md b/AGENTS.md
new file mode 100644
index 000000000..ff37db326
--- /dev/null
+++ b/AGENTS.md
@@ -0,0 +1,69 @@
+Welcome to the OpenAI Agents SDK repository. This file contains the main points for new contributors.
+
+## Repository overview
+
+- **Source code**: `src/agents/` contains the implementation.
+- **Tests**: `tests/` with a short guide in `tests/README.md`.
+- **Examples**: under `examples/`.
+- **Documentation**: markdown pages live in `docs/` with `mkdocs.yml` controlling the site.
+- **Utilities**: developer commands are defined in the `Makefile`.
+- **PR template**: `.github/PULL_REQUEST_TEMPLATE/pull_request_template.md` describes the information every PR must include.
+
+## Local workflow
+
+1. Format, lint and type‑check your changes:
+
+ ```bash
+ make format
+ make lint
+ make mypy
+ ```
+
+2. Run the tests:
+
+ ```bash
+ make tests
+ ```
+
+ To run a single test, use `uv run pytest -s -k <test_name>`.
+
+3. Build the documentation (optional but recommended for docs changes):
+
+ ```bash
+ make build-docs
+ ```
+
+ Coverage can be generated with `make coverage`.
+
+## Snapshot tests
+
+Some tests rely on inline snapshots. See `tests/README.md` for details on updating them:
+
+```bash
+make snapshots-fix # update existing snapshots
+make snapshots-create # create new snapshots
+```
+
+Run `make tests` again after updating snapshots to ensure they pass.
+
+## Style notes
+
+- Write comments as full sentences and end them with a period.
+
+## Pull request expectations
+
+PRs should use the template located at `.github/PULL_REQUEST_TEMPLATE/pull_request_template.md`. Provide a summary, test plan and issue number if applicable, then check that:
+
+- New tests are added when needed.
+- Documentation is updated.
+- `make lint` and `make format` have been run.
+- The full test suite passes.
+
+Commit messages should be concise and written in the imperative mood. Small, focused commits are preferred.
+
+## What reviewers look for
+
+- Tests covering new behaviour.
+- Consistent style: code formatted with `ruff format`, imports sorted, and type hints passing `mypy`.
+- Clear documentation for any public API changes.
+- Clean history and a helpful PR description.
From 003cbfe5f5820cd73ad3adfbae56c054e3cb73ca Mon Sep 17 00:00:00 2001
From: Daniele Morotti <58258368+DanieleMorotti@users.noreply.github.com>
Date: Sun, 18 May 2025 19:25:08 +0200
Subject: [PATCH 07/68] Added mcp 'instructions' attribute to the server (#706)
Added the `instructions` attribute to the MCP servers to solve #704 .
Let me know if you want to add an example to the documentation.
---
src/agents/mcp/server.py | 6 ++++--
1 file changed, 4 insertions(+), 2 deletions(-)
diff --git a/src/agents/mcp/server.py b/src/agents/mcp/server.py
index c5255ead7..414b517ab 100644
--- a/src/agents/mcp/server.py
+++ b/src/agents/mcp/server.py
@@ -12,7 +12,7 @@
from mcp.client.sse import sse_client
from mcp.client.streamable_http import GetSessionIdCallback, streamablehttp_client
from mcp.shared.message import SessionMessage
-from mcp.types import CallToolResult
+from mcp.types import CallToolResult, InitializeResult
from typing_extensions import NotRequired, TypedDict
from ..exceptions import UserError
@@ -73,6 +73,7 @@ def __init__(self, cache_tools_list: bool, client_session_timeout_seconds: float
self.exit_stack: AsyncExitStack = AsyncExitStack()
self._cleanup_lock: asyncio.Lock = asyncio.Lock()
self.cache_tools_list = cache_tools_list
+ self.server_initialize_result: InitializeResult | None = None
self.client_session_timeout_seconds = client_session_timeout_seconds
@@ -122,7 +123,8 @@ async def connect(self):
else None,
)
)
- await session.initialize()
+ server_result = await session.initialize()
+ self.server_initialize_result = server_result
self.session = session
except Exception as e:
logger.error(f"Error initializing MCP server: {e}")
From 428c9a65bf0c17198d9a2a616159b9eb8badb2b6 Mon Sep 17 00:00:00 2001
From: franz101 <fkrekeler@gmail.com>
Date: Mon, 19 May 2025 21:41:11 +0200
Subject: [PATCH 08/68] Add Galileo to external tracing processors list (#662)
---
docs/tracing.md | 1 +
1 file changed, 1 insertion(+)
diff --git a/docs/tracing.md b/docs/tracing.md
index dd883c5aa..4a9c1bd90 100644
--- a/docs/tracing.md
+++ b/docs/tracing.md
@@ -115,3 +115,4 @@ To customize this default setup, to send traces to alternative or additional bac
- [Langfuse](https://langfuse.com/docs/integrations/openaiagentssdk/openai-agents)
- [Langtrace](https://docs.langtrace.ai/supported-integrations/llm-frameworks/openai-agents-sdk)
- [Okahu-Monocle](https://github.com/monocle2ai/monocle)
+- [Galileo](https://v2docs.galileo.ai/integrations/openai-agent-integration#openai-agent-integration)
From 466b44df180718a5d53c45293db2f57b6e719f95 Mon Sep 17 00:00:00 2001
From: WJPBProjects <76624567+WJPBProjects@users.noreply.github.com>
Date: Tue, 20 May 2025 18:23:56 +0100
Subject: [PATCH 09/68] Dev/add usage details to Usage class (#726)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
PR to enhance the `Usage` object and related logic, to support more
granular token accounting, matching the details available in the [OpenAI
Responses API](https://platform.openai.com/docs/api-reference/responses)
. Specifically, it:
- Adds `input_tokens_details` and `output_tokens_details` fields to the
`Usage` dataclass, storing detailed token breakdowns (e.g.,
`cached_tokens`, `reasoning_tokens`).
- Flows this change through
- Updates and extends tests to match
- Adds a test for the Usage.add method
### Motivation
- Aligns the SDK’s usage with the latest OpenAI responses API Usage
object
- Supports downstream use cases that require fine-grained token usage
data (e.g., billing, analytics, optimization) requested by startups
---------
Co-authored-by: Wulfie Bain <wulfie@openai.com>
---
src/agents/extensions/models/litellm_model.py | 11 ++++
src/agents/models/openai_chatcompletions.py | 15 +++++-
src/agents/models/openai_responses.py | 2 +
src/agents/run.py | 2 +
src/agents/usage.py | 22 +++++++-
.../test_litellm_chatcompletions_stream.py | 16 +++++-
tests/test_extra_headers.py | 20 ++++---
tests/test_openai_chatcompletions.py | 17 +++++-
tests/test_openai_chatcompletions_stream.py | 16 +++++-
tests/test_responses_tracing.py | 20 ++++++-
tests/test_usage.py | 52 +++++++++++++++++++
11 files changed, 178 insertions(+), 15 deletions(-)
create mode 100644 tests/test_usage.py
diff --git a/src/agents/extensions/models/litellm_model.py b/src/agents/extensions/models/litellm_model.py
index d3b25a198..ffb2c3c1c 100644
--- a/src/agents/extensions/models/litellm_model.py
+++ b/src/agents/extensions/models/litellm_model.py
@@ -6,6 +6,7 @@
from typing import Any, Literal, cast, overload
import litellm.types
+from openai.types.responses.response_usage import InputTokensDetails, OutputTokensDetails
from agents.exceptions import ModelBehaviorError
@@ -107,6 +108,16 @@ async def get_response(
input_tokens=response_usage.prompt_tokens,
output_tokens=response_usage.completion_tokens,
total_tokens=response_usage.total_tokens,
+ input_tokens_details=InputTokensDetails(
+ cached_tokens=getattr(
+ response_usage.prompt_tokens_details, "cached_tokens", 0
+ )
+ ),
+ output_tokens_details=OutputTokensDetails(
+ reasoning_tokens=getattr(
+ response_usage.completion_tokens_details, "reasoning_tokens", 0
+ )
+ ),
)
if response.usage
else Usage()
diff --git a/src/agents/models/openai_chatcompletions.py b/src/agents/models/openai_chatcompletions.py
index 89619f838..4465ff2fd 100644
--- a/src/agents/models/openai_chatcompletions.py
+++ b/src/agents/models/openai_chatcompletions.py
@@ -9,6 +9,7 @@
from openai.types import ChatModel
from openai.types.chat import ChatCompletion, ChatCompletionChunk
from openai.types.responses import Response
+from openai.types.responses.response_usage import InputTokensDetails, OutputTokensDetails
from .. import _debug
from ..agent_output import AgentOutputSchemaBase
@@ -83,6 +84,18 @@ async def get_response(
input_tokens=response.usage.prompt_tokens,
output_tokens=response.usage.completion_tokens,
total_tokens=response.usage.total_tokens,
+ input_tokens_details=InputTokensDetails(
+ cached_tokens=getattr(
+ response.usage.prompt_tokens_details, "cached_tokens", 0
+ )
+ or 0,
+ ),
+ output_tokens_details=OutputTokensDetails(
+ reasoning_tokens=getattr(
+ response.usage.completion_tokens_details, "reasoning_tokens", 0
+ )
+ or 0,
+ ),
)
if response.usage
else Usage()
@@ -252,7 +265,7 @@ async def _fetch_response(
stream_options=self._non_null_or_not_given(stream_options),
store=self._non_null_or_not_given(store),
reasoning_effort=self._non_null_or_not_given(reasoning_effort),
- extra_headers={ **HEADERS, **(model_settings.extra_headers or {}) },
+ extra_headers={**HEADERS, **(model_settings.extra_headers or {})},
extra_query=model_settings.extra_query,
extra_body=model_settings.extra_body,
metadata=self._non_null_or_not_given(model_settings.metadata),
diff --git a/src/agents/models/openai_responses.py b/src/agents/models/openai_responses.py
index c1ff85b98..6ec8f8f7b 100644
--- a/src/agents/models/openai_responses.py
+++ b/src/agents/models/openai_responses.py
@@ -98,6 +98,8 @@ async def get_response(
input_tokens=response.usage.input_tokens,
output_tokens=response.usage.output_tokens,
total_tokens=response.usage.total_tokens,
+ input_tokens_details=response.usage.input_tokens_details,
+ output_tokens_details=response.usage.output_tokens_details,
)
if response.usage
else Usage()
diff --git a/src/agents/run.py b/src/agents/run.py
index 849da7bfc..b196c3bf1 100644
--- a/src/agents/run.py
+++ b/src/agents/run.py
@@ -689,6 +689,8 @@ async def _run_single_turn_streamed(
input_tokens=event.response.usage.input_tokens,
output_tokens=event.response.usage.output_tokens,
total_tokens=event.response.usage.total_tokens,
+ input_tokens_details=event.response.usage.input_tokens_details,
+ output_tokens_details=event.response.usage.output_tokens_details,
)
if event.response.usage
else Usage()
diff --git a/src/agents/usage.py b/src/agents/usage.py
index 23d989b4b..843f62937 100644
--- a/src/agents/usage.py
+++ b/src/agents/usage.py
@@ -1,4 +1,6 @@
-from dataclasses import dataclass
+from dataclasses import dataclass, field
+
+from openai.types.responses.response_usage import InputTokensDetails, OutputTokensDetails
@dataclass
@@ -9,9 +11,18 @@ class Usage:
input_tokens: int = 0
"""Total input tokens sent, across all requests."""
+ input_tokens_details: InputTokensDetails = field(
+ default_factory=lambda: InputTokensDetails(cached_tokens=0)
+ )
+ """Details about the input tokens, matching responses API usage details."""
output_tokens: int = 0
"""Total output tokens received, across all requests."""
+ output_tokens_details: OutputTokensDetails = field(
+ default_factory=lambda: OutputTokensDetails(reasoning_tokens=0)
+ )
+ """Details about the output tokens, matching responses API usage details."""
+
total_tokens: int = 0
"""Total tokens sent and received, across all requests."""
@@ -20,3 +31,12 @@ def add(self, other: "Usage") -> None:
self.input_tokens += other.input_tokens if other.input_tokens else 0
self.output_tokens += other.output_tokens if other.output_tokens else 0
self.total_tokens += other.total_tokens if other.total_tokens else 0
+ self.input_tokens_details = InputTokensDetails(
+ cached_tokens=self.input_tokens_details.cached_tokens
+ + other.input_tokens_details.cached_tokens
+ )
+
+ self.output_tokens_details = OutputTokensDetails(
+ reasoning_tokens=self.output_tokens_details.reasoning_tokens
+ + other.output_tokens_details.reasoning_tokens
+ )
diff --git a/tests/models/test_litellm_chatcompletions_stream.py b/tests/models/test_litellm_chatcompletions_stream.py
index 80bd8ea22..06e46b39c 100644
--- a/tests/models/test_litellm_chatcompletions_stream.py
+++ b/tests/models/test_litellm_chatcompletions_stream.py
@@ -8,7 +8,11 @@
ChoiceDeltaToolCall,
ChoiceDeltaToolCallFunction,
)
-from openai.types.completion_usage import CompletionUsage
+from openai.types.completion_usage import (
+ CompletionTokensDetails,
+ CompletionUsage,
+ PromptTokensDetails,
+)
from openai.types.responses import (
Response,
ResponseFunctionToolCall,
@@ -46,7 +50,13 @@ async def test_stream_response_yields_events_for_text_content(monkeypatch) -> No
model="fake",
object="chat.completion.chunk",
choices=[Choice(index=0, delta=ChoiceDelta(content="llo"))],
- usage=CompletionUsage(completion_tokens=5, prompt_tokens=7, total_tokens=12),
+ usage=CompletionUsage(
+ completion_tokens=5,
+ prompt_tokens=7,
+ total_tokens=12,
+ completion_tokens_details=CompletionTokensDetails(reasoning_tokens=2),
+ prompt_tokens_details=PromptTokensDetails(cached_tokens=6),
+ ),
)
async def fake_stream() -> AsyncIterator[ChatCompletionChunk]:
@@ -112,6 +122,8 @@ async def patched_fetch_response(self, *args, **kwargs):
assert completed_resp.usage.input_tokens == 7
assert completed_resp.usage.output_tokens == 5
assert completed_resp.usage.total_tokens == 12
+ assert completed_resp.usage.input_tokens_details.cached_tokens == 6
+ assert completed_resp.usage.output_tokens_details.reasoning_tokens == 2
@pytest.mark.allow_call_model_methods
diff --git a/tests/test_extra_headers.py b/tests/test_extra_headers.py
index f29c25408..a6af30077 100644
--- a/tests/test_extra_headers.py
+++ b/tests/test_extra_headers.py
@@ -1,6 +1,7 @@
import pytest
from openai.types.chat.chat_completion import ChatCompletion, Choice
from openai.types.chat.chat_completion_message import ChatCompletionMessage
+from openai.types.responses.response_usage import InputTokensDetails, OutputTokensDetails
from agents import ModelSettings, ModelTracing, OpenAIChatCompletionsModel, OpenAIResponsesModel
@@ -17,21 +18,29 @@ class DummyResponses:
async def create(self, **kwargs):
nonlocal called_kwargs
called_kwargs = kwargs
+
class DummyResponse:
id = "dummy"
output = []
usage = type(
- "Usage", (), {"input_tokens": 0, "output_tokens": 0, "total_tokens": 0}
+ "Usage",
+ (),
+ {
+ "input_tokens": 0,
+ "output_tokens": 0,
+ "total_tokens": 0,
+ "input_tokens_details": InputTokensDetails(cached_tokens=0),
+ "output_tokens_details": OutputTokensDetails(reasoning_tokens=0),
+ },
)()
+
return DummyResponse()
class DummyClient:
def __init__(self):
self.responses = DummyResponses()
-
-
- model = OpenAIResponsesModel(model="gpt-4", openai_client=DummyClient()) # type: ignore
+ model = OpenAIResponsesModel(model="gpt-4", openai_client=DummyClient()) # type: ignore
extra_headers = {"X-Test-Header": "test-value"}
await model.get_response(
system_instructions=None,
@@ -47,7 +56,6 @@ def __init__(self):
assert called_kwargs["extra_headers"]["X-Test-Header"] == "test-value"
-
@pytest.mark.allow_call_model_methods
@pytest.mark.asyncio
async def test_extra_headers_passed_to_openai_client():
@@ -76,7 +84,7 @@ def __init__(self):
self.chat = type("_Chat", (), {"completions": DummyCompletions()})()
self.base_url = "https://api.openai.com"
- model = OpenAIChatCompletionsModel(model="gpt-4", openai_client=DummyClient()) # type: ignore
+ model = OpenAIChatCompletionsModel(model="gpt-4", openai_client=DummyClient()) # type: ignore
extra_headers = {"X-Test-Header": "test-value"}
await model.get_response(
system_instructions=None,
diff --git a/tests/test_openai_chatcompletions.py b/tests/test_openai_chatcompletions.py
index ba3ec68d0..ba4605d08 100644
--- a/tests/test_openai_chatcompletions.py
+++ b/tests/test_openai_chatcompletions.py
@@ -13,7 +13,10 @@
ChatCompletionMessageToolCall,
Function,
)
-from openai.types.completion_usage import CompletionUsage
+from openai.types.completion_usage import (
+ CompletionUsage,
+ PromptTokensDetails,
+)
from openai.types.responses import (
Response,
ResponseFunctionToolCall,
@@ -51,7 +54,13 @@ async def test_get_response_with_text_message(monkeypatch) -> None:
model="fake",
object="chat.completion",
choices=[choice],
- usage=CompletionUsage(completion_tokens=5, prompt_tokens=7, total_tokens=12),
+ usage=CompletionUsage(
+ completion_tokens=5,
+ prompt_tokens=7,
+ total_tokens=12,
+ # completion_tokens_details left blank to test default
+ prompt_tokens_details=PromptTokensDetails(cached_tokens=3),
+ ),
)
async def patched_fetch_response(self, *args, **kwargs):
@@ -81,6 +90,8 @@ async def patched_fetch_response(self, *args, **kwargs):
assert resp.usage.input_tokens == 7
assert resp.usage.output_tokens == 5
assert resp.usage.total_tokens == 12
+ assert resp.usage.input_tokens_details.cached_tokens == 3
+ assert resp.usage.output_tokens_details.reasoning_tokens == 0
assert resp.response_id is None
@@ -127,6 +138,8 @@ async def patched_fetch_response(self, *args, **kwargs):
assert resp.usage.requests == 0
assert resp.usage.input_tokens == 0
assert resp.usage.output_tokens == 0
+ assert resp.usage.input_tokens_details.cached_tokens == 0
+ assert resp.usage.output_tokens_details.reasoning_tokens == 0
@pytest.mark.allow_call_model_methods
diff --git a/tests/test_openai_chatcompletions_stream.py b/tests/test_openai_chatcompletions_stream.py
index b82f24303..5c8bb9e3a 100644
--- a/tests/test_openai_chatcompletions_stream.py
+++ b/tests/test_openai_chatcompletions_stream.py
@@ -8,7 +8,11 @@
ChoiceDeltaToolCall,
ChoiceDeltaToolCallFunction,
)
-from openai.types.completion_usage import CompletionUsage
+from openai.types.completion_usage import (
+ CompletionTokensDetails,
+ CompletionUsage,
+ PromptTokensDetails,
+)
from openai.types.responses import (
Response,
ResponseFunctionToolCall,
@@ -46,7 +50,13 @@ async def test_stream_response_yields_events_for_text_content(monkeypatch) -> No
model="fake",
object="chat.completion.chunk",
choices=[Choice(index=0, delta=ChoiceDelta(content="llo"))],
- usage=CompletionUsage(completion_tokens=5, prompt_tokens=7, total_tokens=12),
+ usage=CompletionUsage(
+ completion_tokens=5,
+ prompt_tokens=7,
+ total_tokens=12,
+ prompt_tokens_details=PromptTokensDetails(cached_tokens=2),
+ completion_tokens_details=CompletionTokensDetails(reasoning_tokens=3),
+ ),
)
async def fake_stream() -> AsyncIterator[ChatCompletionChunk]:
@@ -112,6 +122,8 @@ async def patched_fetch_response(self, *args, **kwargs):
assert completed_resp.usage.input_tokens == 7
assert completed_resp.usage.output_tokens == 5
assert completed_resp.usage.total_tokens == 12
+ assert completed_resp.usage.input_tokens_details.cached_tokens == 2
+ assert completed_resp.usage.output_tokens_details.reasoning_tokens == 3
@pytest.mark.allow_call_model_methods
diff --git a/tests/test_responses_tracing.py b/tests/test_responses_tracing.py
index 0bc97a953..dfac74bb9 100644
--- a/tests/test_responses_tracing.py
+++ b/tests/test_responses_tracing.py
@@ -1,7 +1,10 @@
+from typing import Optional
+
import pytest
from inline_snapshot import snapshot
from openai import AsyncOpenAI
from openai.types.responses import ResponseCompletedEvent
+from openai.types.responses.response_usage import InputTokensDetails, OutputTokensDetails
from agents import ModelSettings, ModelTracing, OpenAIResponsesModel, trace
from agents.tracing.span_data import ResponseSpanData
@@ -16,10 +19,25 @@ def is_disabled(self):
class DummyUsage:
- def __init__(self, input_tokens=1, output_tokens=1, total_tokens=2):
+ def __init__(
+ self,
+ input_tokens: int = 1,
+ input_tokens_details: Optional[InputTokensDetails] = None,
+ output_tokens: int = 1,
+ output_tokens_details: Optional[OutputTokensDetails] = None,
+ total_tokens: int = 2,
+ ):
self.input_tokens = input_tokens
self.output_tokens = output_tokens
self.total_tokens = total_tokens
+ self.input_tokens_details = (
+ input_tokens_details if input_tokens_details else InputTokensDetails(cached_tokens=0)
+ )
+ self.output_tokens_details = (
+ output_tokens_details
+ if output_tokens_details
+ else OutputTokensDetails(reasoning_tokens=0)
+ )
class DummyResponse:
diff --git a/tests/test_usage.py b/tests/test_usage.py
new file mode 100644
index 000000000..405f99ddf
--- /dev/null
+++ b/tests/test_usage.py
@@ -0,0 +1,52 @@
+from openai.types.responses.response_usage import InputTokensDetails, OutputTokensDetails
+
+from agents.usage import Usage
+
+
+def test_usage_add_aggregates_all_fields():
+ u1 = Usage(
+ requests=1,
+ input_tokens=10,
+ input_tokens_details=InputTokensDetails(cached_tokens=3),
+ output_tokens=20,
+ output_tokens_details=OutputTokensDetails(reasoning_tokens=5),
+ total_tokens=30,
+ )
+ u2 = Usage(
+ requests=2,
+ input_tokens=7,
+ input_tokens_details=InputTokensDetails(cached_tokens=4),
+ output_tokens=8,
+ output_tokens_details=OutputTokensDetails(reasoning_tokens=6),
+ total_tokens=15,
+ )
+
+ u1.add(u2)
+
+ assert u1.requests == 3
+ assert u1.input_tokens == 17
+ assert u1.output_tokens == 28
+ assert u1.total_tokens == 45
+ assert u1.input_tokens_details.cached_tokens == 7
+ assert u1.output_tokens_details.reasoning_tokens == 11
+
+
+def test_usage_add_aggregates_with_none_values():
+ u1 = Usage()
+ u2 = Usage(
+ requests=2,
+ input_tokens=7,
+ input_tokens_details=InputTokensDetails(cached_tokens=4),
+ output_tokens=8,
+ output_tokens_details=OutputTokensDetails(reasoning_tokens=6),
+ total_tokens=15,
+ )
+
+ u1.add(u2)
+
+ assert u1.requests == 2
+ assert u1.input_tokens == 7
+ assert u1.output_tokens == 8
+ assert u1.total_tokens == 15
+ assert u1.input_tokens_details.cached_tokens == 4
+ assert u1.output_tokens_details.reasoning_tokens == 6
From ce2e2a4571c2b176e8641c558fedaa7bc1692013 Mon Sep 17 00:00:00 2001
From: Rohan Mehta <rm@openai.com>
Date: Wed, 21 May 2025 15:17:58 -0400
Subject: [PATCH 10/68] Upgrade openAI sdk version (#730)
---
[//]: # (BEGIN SAPLING FOOTER)
* #732
* #731
* __->__ #730
---
pyproject.toml | 2 +-
src/agents/models/chatcmpl_stream_handler.py | 26 +++++++++++++++++++-
src/agents/models/openai_responses.py | 16 ++++--------
tests/fake_model.py | 1 +
tests/test_responses_tracing.py | 4 +++
tests/voice/test_workflow.py | 2 ++
uv.lock | 10 ++++----
7 files changed, 43 insertions(+), 18 deletions(-)
diff --git a/pyproject.toml b/pyproject.toml
index 672258c42..200ac2485 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -7,7 +7,7 @@ requires-python = ">=3.9"
license = "MIT"
authors = [{ name = "OpenAI", email = "support@openai.com" }]
dependencies = [
- "openai>=1.76.0",
+ "openai>=1.81.0",
"pydantic>=2.10, <3",
"griffe>=1.5.6, <2",
"typing-extensions>=4.12.2, <5",
diff --git a/src/agents/models/chatcmpl_stream_handler.py b/src/agents/models/chatcmpl_stream_handler.py
index c71adeb55..d18f5912a 100644
--- a/src/agents/models/chatcmpl_stream_handler.py
+++ b/src/agents/models/chatcmpl_stream_handler.py
@@ -38,6 +38,16 @@ class StreamingState:
function_calls: dict[int, ResponseFunctionToolCall] = field(default_factory=dict)
+class SequenceNumber:
+ def __init__(self):
+ self._sequence_number = 0
+
+ def get_and_increment(self) -> int:
+ num = self._sequence_number
+ self._sequence_number += 1
+ return num
+
+
class ChatCmplStreamHandler:
@classmethod
async def handle_stream(
@@ -47,13 +57,14 @@ async def handle_stream(
) -> AsyncIterator[TResponseStreamEvent]:
usage: CompletionUsage | None = None
state = StreamingState()
-
+ sequence_number = SequenceNumber()
async for chunk in stream:
if not state.started:
state.started = True
yield ResponseCreatedEvent(
response=response,
type="response.created",
+ sequence_number=sequence_number.get_and_increment(),
)
# This is always set by the OpenAI API, but not by others e.g. LiteLLM
@@ -89,6 +100,7 @@ async def handle_stream(
item=assistant_item,
output_index=0,
type="response.output_item.added",
+ sequence_number=sequence_number.get_and_increment(),
)
yield ResponseContentPartAddedEvent(
content_index=state.text_content_index_and_output[0],
@@ -100,6 +112,7 @@ async def handle_stream(
annotations=[],
),
type="response.content_part.added",
+ sequence_number=sequence_number.get_and_increment(),
)
# Emit the delta for this segment of content
yield ResponseTextDeltaEvent(
@@ -108,6 +121,7 @@ async def handle_stream(
item_id=FAKE_RESPONSES_ID,
output_index=0,
type="response.output_text.delta",
+ sequence_number=sequence_number.get_and_increment(),
)
# Accumulate the text into the response part
state.text_content_index_and_output[1].text += delta.content
@@ -134,6 +148,7 @@ async def handle_stream(
item=assistant_item,
output_index=0,
type="response.output_item.added",
+ sequence_number=sequence_number.get_and_increment(),
)
yield ResponseContentPartAddedEvent(
content_index=state.refusal_content_index_and_output[0],
@@ -145,6 +160,7 @@ async def handle_stream(
annotations=[],
),
type="response.content_part.added",
+ sequence_number=sequence_number.get_and_increment(),
)
# Emit the delta for this segment of refusal
yield ResponseRefusalDeltaEvent(
@@ -153,6 +169,7 @@ async def handle_stream(
item_id=FAKE_RESPONSES_ID,
output_index=0,
type="response.refusal.delta",
+ sequence_number=sequence_number.get_and_increment(),
)
# Accumulate the refusal string in the output part
state.refusal_content_index_and_output[1].refusal += delta.refusal
@@ -190,6 +207,7 @@ async def handle_stream(
output_index=0,
part=state.text_content_index_and_output[1],
type="response.content_part.done",
+ sequence_number=sequence_number.get_and_increment(),
)
if state.refusal_content_index_and_output:
@@ -201,6 +219,7 @@ async def handle_stream(
output_index=0,
part=state.refusal_content_index_and_output[1],
type="response.content_part.done",
+ sequence_number=sequence_number.get_and_increment(),
)
# Actually send events for the function calls
@@ -216,6 +235,7 @@ async def handle_stream(
),
output_index=function_call_starting_index,
type="response.output_item.added",
+ sequence_number=sequence_number.get_and_increment(),
)
# Then, yield the args
yield ResponseFunctionCallArgumentsDeltaEvent(
@@ -223,6 +243,7 @@ async def handle_stream(
item_id=FAKE_RESPONSES_ID,
output_index=function_call_starting_index,
type="response.function_call_arguments.delta",
+ sequence_number=sequence_number.get_and_increment(),
)
# Finally, the ResponseOutputItemDone
yield ResponseOutputItemDoneEvent(
@@ -235,6 +256,7 @@ async def handle_stream(
),
output_index=function_call_starting_index,
type="response.output_item.done",
+ sequence_number=sequence_number.get_and_increment(),
)
# Finally, send the Response completed event
@@ -258,6 +280,7 @@ async def handle_stream(
item=assistant_msg,
output_index=0,
type="response.output_item.done",
+ sequence_number=sequence_number.get_and_increment(),
)
for function_call in state.function_calls.values():
@@ -289,4 +312,5 @@ async def handle_stream(
yield ResponseCompletedEvent(
response=final_response,
type="response.completed",
+ sequence_number=sequence_number.get_and_increment(),
)
diff --git a/src/agents/models/openai_responses.py b/src/agents/models/openai_responses.py
index 6ec8f8f7b..cb6567909 100644
--- a/src/agents/models/openai_responses.py
+++ b/src/agents/models/openai_responses.py
@@ -10,6 +10,7 @@
from openai.types.responses import (
Response,
ResponseCompletedEvent,
+ ResponseIncludable,
ResponseStreamEvent,
ResponseTextConfigParam,
ToolParam,
@@ -36,13 +37,6 @@
_USER_AGENT = f"Agents/Python {__version__}"
_HEADERS = {"User-Agent": _USER_AGENT}
-# From the Responses API
-IncludeLiteral = Literal[
- "file_search_call.results",
- "message.input_image.image_url",
- "computer_call_output.output.image_url",
-]
-
class OpenAIResponsesModel(Model):
"""
@@ -273,7 +267,7 @@ def _get_client(self) -> AsyncOpenAI:
@dataclass
class ConvertedTools:
tools: list[ToolParam]
- includes: list[IncludeLiteral]
+ includes: list[ResponseIncludable]
class Converter:
@@ -330,7 +324,7 @@ def convert_tools(
handoffs: list[Handoff[Any]],
) -> ConvertedTools:
converted_tools: list[ToolParam] = []
- includes: list[IncludeLiteral] = []
+ includes: list[ResponseIncludable] = []
computer_tools = [tool for tool in tools if isinstance(tool, ComputerTool)]
if len(computer_tools) > 1:
@@ -348,7 +342,7 @@ def convert_tools(
return ConvertedTools(tools=converted_tools, includes=includes)
@classmethod
- def _convert_tool(cls, tool: Tool) -> tuple[ToolParam, IncludeLiteral | None]:
+ def _convert_tool(cls, tool: Tool) -> tuple[ToolParam, ResponseIncludable | None]:
"""Returns converted tool and includes"""
if isinstance(tool, FunctionTool):
@@ -359,7 +353,7 @@ def _convert_tool(cls, tool: Tool) -> tuple[ToolParam, IncludeLiteral | None]:
"type": "function",
"description": tool.description,
}
- includes: IncludeLiteral | None = None
+ includes: ResponseIncludable | None = None
elif isinstance(tool, WebSearchTool):
ws: WebSearchToolParam = {
"type": "web_search_preview",
diff --git a/tests/fake_model.py b/tests/fake_model.py
index 32f919ef1..9f0c83a2f 100644
--- a/tests/fake_model.py
+++ b/tests/fake_model.py
@@ -129,6 +129,7 @@ async def stream_response(
yield ResponseCompletedEvent(
type="response.completed",
response=get_response_obj(output, usage=self.hardcoded_usage),
+ sequence_number=0,
)
diff --git a/tests/test_responses_tracing.py b/tests/test_responses_tracing.py
index dfac74bb9..db24fe496 100644
--- a/tests/test_responses_tracing.py
+++ b/tests/test_responses_tracing.py
@@ -50,6 +50,7 @@ def __aiter__(self):
yield ResponseCompletedEvent(
type="response.completed",
response=fake_model.get_response_obj(self.output),
+ sequence_number=0,
)
@@ -201,6 +202,7 @@ async def __aiter__(self):
yield ResponseCompletedEvent(
type="response.completed",
response=fake_model.get_response_obj([], "dummy-id-123"),
+ sequence_number=0,
)
return DummyStream()
@@ -253,6 +255,7 @@ async def __aiter__(self):
yield ResponseCompletedEvent(
type="response.completed",
response=fake_model.get_response_obj([], "dummy-id-123"),
+ sequence_number=0,
)
return DummyStream()
@@ -304,6 +307,7 @@ async def __aiter__(self):
yield ResponseCompletedEvent(
type="response.completed",
response=fake_model.get_response_obj([], "dummy-id-123"),
+ sequence_number=0,
)
return DummyStream()
diff --git a/tests/voice/test_workflow.py b/tests/voice/test_workflow.py
index 2bdf2a657..035a05d56 100644
--- a/tests/voice/test_workflow.py
+++ b/tests/voice/test_workflow.py
@@ -81,11 +81,13 @@ async def stream_response(
type="response.output_text.delta",
output_index=0,
item_id=item.id,
+ sequence_number=0,
)
yield ResponseCompletedEvent(
type="response.completed",
response=get_response_obj(output),
+ sequence_number=1,
)
diff --git a/uv.lock b/uv.lock
index 6ccc19966..7a0cb1e6b 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1461,7 +1461,7 @@ wheels = [
[[package]]
name = "openai"
-version = "1.76.0"
+version = "1.81.0"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "anyio" },
@@ -1473,14 +1473,14 @@ dependencies = [
{ name = "tqdm" },
{ name = "typing-extensions" },
]
-sdist = { url = "https://files.pythonhosted.org/packages/84/51/817969ec969b73d8ddad085670ecd8a45ef1af1811d8c3b8a177ca4d1309/openai-1.76.0.tar.gz", hash = "sha256:fd2bfaf4608f48102d6b74f9e11c5ecaa058b60dad9c36e409c12477dfd91fb2", size = 434660 }
+sdist = { url = "https://files.pythonhosted.org/packages/1c/89/a1e4f3fa7ca4f7fec90dbf47d93b7cd5ff65924926733af15044e302a192/openai-1.81.0.tar.gz", hash = "sha256:349567a8607e0bcffd28e02f96b5c2397d0d25d06732d90ab3ecbf97abf030f9", size = 456861 }
wheels = [
- { url = "https://files.pythonhosted.org/packages/59/aa/84e02ab500ca871eb8f62784426963a1c7c17a72fea3c7f268af4bbaafa5/openai-1.76.0-py3-none-any.whl", hash = "sha256:a712b50e78cf78e6d7b2a8f69c4978243517c2c36999756673e07a14ce37dc0a", size = 661201 },
+ { url = "https://files.pythonhosted.org/packages/02/66/bcc7f9bf48e8610a33e3b5c96a5a644dad032d92404ea2a5e8b43ba067e8/openai-1.81.0-py3-none-any.whl", hash = "sha256:1c71572e22b43876c5d7d65ade0b7b516bb527c3d44ae94111267a09125f7bae", size = 717529 },
]
[[package]]
name = "openai-agents"
-version = "0.0.14"
+version = "0.0.15"
source = { editable = "." }
dependencies = [
{ name = "griffe" },
@@ -1536,7 +1536,7 @@ requires-dist = [
{ name = "litellm", marker = "extra == 'litellm'", specifier = ">=1.67.4.post1,<2" },
{ name = "mcp", marker = "python_full_version >= '3.10'", specifier = ">=1.8.0,<2" },
{ name = "numpy", marker = "python_full_version >= '3.10' and extra == 'voice'", specifier = ">=2.2.0,<3" },
- { name = "openai", specifier = ">=1.76.0" },
+ { name = "openai", specifier = ">=1.81.0" },
{ name = "pydantic", specifier = ">=2.10,<3" },
{ name = "requests", specifier = ">=2.0,<3" },
{ name = "types-requests", specifier = ">=2.0,<3" },
From 9fa5c39d69937a215a6f247883243fe38c5a39c2 Mon Sep 17 00:00:00 2001
From: Rohan Mehta <rm@openai.com>
Date: Wed, 21 May 2025 15:21:37 -0400
Subject: [PATCH 11/68] Hosted MCP support (#731)
---
[//]: # (BEGIN SAPLING FOOTER)
* #732
* __->__ #731
---
examples/hosted_mcp/__init__.py | 0
examples/hosted_mcp/approvals.py | 61 ++++++++++++++
examples/hosted_mcp/simple.py | 47 +++++++++++
src/agents/__init__.py | 8 ++
src/agents/_run_impl.py | 114 ++++++++++++++++++++++++--
src/agents/items.py | 41 ++++++++-
src/agents/models/openai_responses.py | 6 +-
src/agents/stream_events.py | 2 +
src/agents/tool.py | 64 ++++++++++++++-
9 files changed, 332 insertions(+), 11 deletions(-)
create mode 100644 examples/hosted_mcp/__init__.py
create mode 100644 examples/hosted_mcp/approvals.py
create mode 100644 examples/hosted_mcp/simple.py
diff --git a/examples/hosted_mcp/__init__.py b/examples/hosted_mcp/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/examples/hosted_mcp/approvals.py b/examples/hosted_mcp/approvals.py
new file mode 100644
index 000000000..2cabb3ee2
--- /dev/null
+++ b/examples/hosted_mcp/approvals.py
@@ -0,0 +1,61 @@
+import argparse
+import asyncio
+
+from agents import (
+ Agent,
+ HostedMCPTool,
+ MCPToolApprovalFunctionResult,
+ MCPToolApprovalRequest,
+ Runner,
+)
+
+"""This example demonstrates how to use the hosted MCP support in the OpenAI Responses API, with
+approval callbacks."""
+
+
+def approval_callback(request: MCPToolApprovalRequest) -> MCPToolApprovalFunctionResult:
+ answer = input(f"Approve running the tool `{request.data.name}`? (y/n) ")
+ result: MCPToolApprovalFunctionResult = {"approve": answer == "y"}
+ if not result["approve"]:
+ result["reason"] = "User denied"
+ return result
+
+
+async def main(verbose: bool, stream: bool):
+ agent = Agent(
+ name="Assistant",
+ tools=[
+ HostedMCPTool(
+ tool_config={
+ "type": "mcp",
+ "server_label": "gitmcp",
+ "server_url": "https://gitmcp.io/openai/codex",
+ "require_approval": "always",
+ },
+ on_approval_request=approval_callback,
+ )
+ ],
+ )
+
+ if stream:
+ result = Runner.run_streamed(agent, "Which language is this repo written in?")
+ async for event in result.stream_events():
+ if event.type == "run_item_stream_event":
+ print(f"Got event of type {event.item.__class__.__name__}")
+ print(f"Done streaming; final result: {result.final_output}")
+ else:
+ res = await Runner.run(agent, "Which language is this repo written in?")
+ print(res.final_output)
+
+ if verbose:
+ for item in result.new_items:
+ print(item)
+
+
+if __name__ == "__main__":
+ parser = argparse.ArgumentParser()
+ parser.add_argument("--verbose", action="store_true", default=False)
+ parser.add_argument("--stream", action="store_true", default=False)
+ args = parser.parse_args()
+
+ asyncio.run(main(args.verbose, args.stream))
diff --git a/examples/hosted_mcp/simple.py b/examples/hosted_mcp/simple.py
new file mode 100644
index 000000000..508c3a7ae
--- /dev/null
+++ b/examples/hosted_mcp/simple.py
@@ -0,0 +1,47 @@
+import argparse
+import asyncio
+
+from agents import Agent, HostedMCPTool, Runner
+
+"""This example demonstrates how to use the hosted MCP support in the OpenAI Responses API, with
+approvals not required for any tools. You should only use this for trusted MCP servers."""
+
+
+async def main(verbose: bool, stream: bool):
+ agent = Agent(
+ name="Assistant",
+ tools=[
+ HostedMCPTool(
+ tool_config={
+ "type": "mcp",
+ "server_label": "gitmcp",
+ "server_url": "https://gitmcp.io/openai/codex",
+ "require_approval": "never",
+ }
+ )
+ ],
+ )
+
+ if stream:
+ result = Runner.run_streamed(agent, "Which language is this repo written in?")
+ async for event in result.stream_events():
+ if event.type == "run_item_stream_event":
+ print(f"Got event of type {event.item.__class__.__name__}")
+ print(f"Done streaming; final result: {result.final_output}")
+ else:
+ res = await Runner.run(agent, "Which language is this repo written in?")
+ print(res.final_output)
+ # The repository is primarily written in multiple languages, including Rust and TypeScript...
+
+ if verbose:
+ for item in result.new_items:
+ print(item)
+
+
+if __name__ == "__main__":
+ parser = argparse.ArgumentParser()
+ parser.add_argument("--verbose", action="store_true", default=False)
+ parser.add_argument("--stream", action="store_true", default=False)
+ args = parser.parse_args()
+
+ asyncio.run(main(args.verbose, args.stream))
diff --git a/src/agents/__init__.py b/src/agents/__init__.py
index 6d7c90b4f..36c26b80d 100644
--- a/src/agents/__init__.py
+++ b/src/agents/__init__.py
@@ -58,6 +58,10 @@
FileSearchTool,
FunctionTool,
FunctionToolResult,
+ HostedMCPTool,
+ MCPToolApprovalFunction,
+ MCPToolApprovalFunctionResult,
+ MCPToolApprovalRequest,
Tool,
WebSearchTool,
default_tool_error_function,
@@ -208,6 +212,10 @@ def enable_verbose_stdout_logging():
"FileSearchTool",
"Tool",
"WebSearchTool",
+ "HostedMCPTool",
+ "MCPToolApprovalFunction",
+ "MCPToolApprovalRequest",
+ "MCPToolApprovalFunctionResult",
"function_tool",
"Usage",
"add_trace_processor",
diff --git a/src/agents/_run_impl.py b/src/agents/_run_impl.py
index b5a83685c..ab1e78797 100644
--- a/src/agents/_run_impl.py
+++ b/src/agents/_run_impl.py
@@ -25,7 +25,8 @@
ActionType,
ActionWait,
)
-from openai.types.responses.response_input_param import ComputerCallOutput
+from openai.types.responses.response_input_param import ComputerCallOutput, McpApprovalResponse
+from openai.types.responses.response_output_item import McpApprovalRequest, McpCall, McpListTools
from openai.types.responses.response_reasoning_item import ResponseReasoningItem
from .agent import Agent, ToolsToFinalOutputResult
@@ -38,6 +39,9 @@
HandoffCallItem,
HandoffOutputItem,
ItemHelpers,
+ MCPApprovalRequestItem,
+ MCPApprovalResponseItem,
+ MCPListToolsItem,
MessageOutputItem,
ModelResponse,
ReasoningItem,
@@ -52,7 +56,14 @@
from .models.interface import ModelTracing
from .run_context import RunContextWrapper, TContext
from .stream_events import RunItemStreamEvent, StreamEvent
-from .tool import ComputerTool, FunctionTool, FunctionToolResult, Tool
+from .tool import (
+ ComputerTool,
+ FunctionTool,
+ FunctionToolResult,
+ HostedMCPTool,
+ MCPToolApprovalRequest,
+ Tool,
+)
from .tracing import (
SpanError,
Trace,
@@ -112,6 +123,12 @@ class ToolRunComputerAction:
computer_tool: ComputerTool
+@dataclass
+class ToolRunMCPApprovalRequest:
+ request_item: McpApprovalRequest
+ mcp_tool: HostedMCPTool
+
+
@dataclass
class ProcessedResponse:
new_items: list[RunItem]
@@ -119,8 +136,9 @@ class ProcessedResponse:
functions: list[ToolRunFunction]
computer_actions: list[ToolRunComputerAction]
tools_used: list[str] # Names of all tools used, including hosted tools
+ mcp_approval_requests: list[ToolRunMCPApprovalRequest] # Only requests with callbacks
- def has_tools_to_run(self) -> bool:
+ def has_tools_or_approvals_to_run(self) -> bool:
# Handoffs, functions and computer actions need local processing
# Hosted tools have already run, so there's nothing to do.
return any(
@@ -128,6 +146,7 @@ def has_tools_to_run(self) -> bool:
self.handoffs,
self.functions,
self.computer_actions,
+ self.mcp_approval_requests,
]
)
@@ -226,7 +245,16 @@ async def execute_tools_and_side_effects(
new_step_items.extend([result.run_item for result in function_results])
new_step_items.extend(computer_results)
- # Second, check if there are any handoffs
+ # Next, run the MCP approval requests
+ if processed_response.mcp_approval_requests:
+ approval_results = await cls.execute_mcp_approval_requests(
+ agent=agent,
+ approval_requests=processed_response.mcp_approval_requests,
+ context_wrapper=context_wrapper,
+ )
+ new_step_items.extend(approval_results)
+
+ # Next, check if there are any handoffs
if run_handoffs := processed_response.handoffs:
return await cls.execute_handoffs(
agent=agent,
@@ -240,7 +268,7 @@ async def execute_tools_and_side_effects(
run_config=run_config,
)
- # Third, we'll check if the tool use should result in a final output
+ # Next, we'll check if the tool use should result in a final output
check_tool_use = await cls._check_for_final_output_from_tools(
agent=agent,
tool_results=function_results,
@@ -295,7 +323,7 @@ async def execute_tools_and_side_effects(
)
elif (
not output_schema or output_schema.is_plain_text()
- ) and not processed_response.has_tools_to_run():
+ ) and not processed_response.has_tools_or_approvals_to_run():
return await cls.execute_final_output(
agent=agent,
original_input=original_input,
@@ -343,10 +371,16 @@ def process_model_response(
run_handoffs = []
functions = []
computer_actions = []
+ mcp_approval_requests = []
tools_used: list[str] = []
handoff_map = {handoff.tool_name: handoff for handoff in handoffs}
function_map = {tool.name: tool for tool in all_tools if isinstance(tool, FunctionTool)}
computer_tool = next((tool for tool in all_tools if isinstance(tool, ComputerTool)), None)
+ hosted_mcp_server_map = {
+ tool.tool_config["server_label"]: tool
+ for tool in all_tools
+ if isinstance(tool, HostedMCPTool)
+ }
for output in response.output:
if isinstance(output, ResponseOutputMessage):
@@ -375,6 +409,34 @@ def process_model_response(
computer_actions.append(
ToolRunComputerAction(tool_call=output, computer_tool=computer_tool)
)
+ elif isinstance(output, McpApprovalRequest):
+ items.append(MCPApprovalRequestItem(raw_item=output, agent=agent))
+ if output.server_label not in hosted_mcp_server_map:
+ _error_tracing.attach_error_to_current_span(
+ SpanError(
+ message="MCP server label not found",
+ data={"server_label": output.server_label},
+ )
+ )
+ raise ModelBehaviorError(f"MCP server label {output.server_label} not found")
+ else:
+ server = hosted_mcp_server_map[output.server_label]
+ if server.on_approval_request:
+ mcp_approval_requests.append(
+ ToolRunMCPApprovalRequest(
+ request_item=output,
+ mcp_tool=server,
+ )
+ )
+ else:
+ logger.warning(
+ f"MCP server {output.server_label} has no on_approval_request hook"
+ )
+ elif isinstance(output, McpListTools):
+ items.append(MCPListToolsItem(raw_item=output, agent=agent))
+ elif isinstance(output, McpCall):
+ items.append(ToolCallItem(raw_item=output, agent=agent))
+ tools_used.append(output.name)
elif not isinstance(output, ResponseFunctionToolCall):
logger.warning(f"Unexpected output type, ignoring: {type(output)}")
continue
@@ -417,6 +479,7 @@ def process_model_response(
functions=functions,
computer_actions=computer_actions,
tools_used=tools_used,
+ mcp_approval_requests=mcp_approval_requests,
)
@classmethod
@@ -643,6 +706,40 @@ async def execute_handoffs(
next_step=NextStepHandoff(new_agent),
)
+ @classmethod
+ async def execute_mcp_approval_requests(
+ cls,
+ *,
+ agent: Agent[TContext],
+ approval_requests: list[ToolRunMCPApprovalRequest],
+ context_wrapper: RunContextWrapper[TContext],
+ ) -> list[RunItem]:
+ async def run_single_approval(approval_request: ToolRunMCPApprovalRequest) -> RunItem:
+ callback = approval_request.mcp_tool.on_approval_request
+ assert callback is not None, "Callback is required for MCP approval requests"
+ maybe_awaitable_result = callback(
+ MCPToolApprovalRequest(context_wrapper, approval_request.request_item)
+ )
+ if inspect.isawaitable(maybe_awaitable_result):
+ result = await maybe_awaitable_result
+ else:
+ result = maybe_awaitable_result
+ reason = result.get("reason", None)
+ raw_item: McpApprovalResponse = {
+ "approval_request_id": approval_request.request_item.id,
+ "approve": result["approve"],
+ "type": "mcp_approval_response",
+ }
+ if not result["approve"] and reason:
+ raw_item["reason"] = reason
+ return MCPApprovalResponseItem(
+ raw_item=raw_item,
+ agent=agent,
+ )
+
+ tasks = [run_single_approval(approval_request) for approval_request in approval_requests]
+ return await asyncio.gather(*tasks)
+
@classmethod
async def execute_final_output(
cls,
@@ -727,6 +824,11 @@ def stream_step_result_to_queue(
event = RunItemStreamEvent(item=item, name="tool_output")
elif isinstance(item, ReasoningItem):
event = RunItemStreamEvent(item=item, name="reasoning_item_created")
+ elif isinstance(item, MCPApprovalRequestItem):
+ event = RunItemStreamEvent(item=item, name="mcp_approval_requested")
+ elif isinstance(item, MCPListToolsItem):
+ event = RunItemStreamEvent(item=item, name="mcp_list_tools")
+
else:
logger.warning(f"Unexpected item type: {type(item)}")
event = None
diff --git a/src/agents/items.py b/src/agents/items.py
index 8fb2b52a3..65a911798 100644
--- a/src/agents/items.py
+++ b/src/agents/items.py
@@ -18,7 +18,12 @@
ResponseOutputText,
ResponseStreamEvent,
)
-from openai.types.responses.response_input_item_param import ComputerCallOutput, FunctionCallOutput
+from openai.types.responses.response_input_item_param import (
+ ComputerCallOutput,
+ FunctionCallOutput,
+ McpApprovalResponse,
+)
+from openai.types.responses.response_output_item import McpApprovalRequest, McpCall, McpListTools
from openai.types.responses.response_reasoning_item import ResponseReasoningItem
from pydantic import BaseModel
from typing_extensions import TypeAlias
@@ -108,6 +113,7 @@ class HandoffOutputItem(RunItemBase[TResponseInputItem]):
ResponseComputerToolCall,
ResponseFileSearchToolCall,
ResponseFunctionWebSearch,
+ McpCall,
]
"""A type that represents a tool call item."""
@@ -147,6 +153,36 @@ class ReasoningItem(RunItemBase[ResponseReasoningItem]):
type: Literal["reasoning_item"] = "reasoning_item"
+@dataclass
+class MCPListToolsItem(RunItemBase[McpListTools]):
+ """Represents a call to an MCP server to list tools."""
+
+ raw_item: McpListTools
+ """The raw MCP list tools call."""
+
+ type: Literal["mcp_list_tools_item"] = "mcp_list_tools_item"
+
+
+@dataclass
+class MCPApprovalRequestItem(RunItemBase[McpApprovalRequest]):
+ """Represents a request for MCP approval."""
+
+ raw_item: McpApprovalRequest
+ """The raw MCP approval request."""
+
+ type: Literal["mcp_approval_request_item"] = "mcp_approval_request_item"
+
+
+@dataclass
+class MCPApprovalResponseItem(RunItemBase[McpApprovalResponse]):
+ """Represents a response to an MCP approval request."""
+
+ raw_item: McpApprovalResponse
+ """The raw MCP approval response."""
+
+ type: Literal["mcp_approval_response_item"] = "mcp_approval_response_item"
+
+
RunItem: TypeAlias = Union[
MessageOutputItem,
HandoffCallItem,
@@ -154,6 +190,9 @@ class ReasoningItem(RunItemBase[ResponseReasoningItem]):
ToolCallItem,
ToolCallOutputItem,
ReasoningItem,
+ MCPListToolsItem,
+ MCPApprovalRequestItem,
+ MCPApprovalResponseItem,
]
"""An item generated by an agent."""
diff --git a/src/agents/models/openai_responses.py b/src/agents/models/openai_responses.py
index cb6567909..65a4f5caf 100644
--- a/src/agents/models/openai_responses.py
+++ b/src/agents/models/openai_responses.py
@@ -24,7 +24,7 @@
from ..handoffs import Handoff
from ..items import ItemHelpers, ModelResponse, TResponseInputItem
from ..logger import logger
-from ..tool import ComputerTool, FileSearchTool, FunctionTool, Tool, WebSearchTool
+from ..tool import ComputerTool, FileSearchTool, FunctionTool, HostedMCPTool, Tool, WebSearchTool
from ..tracing import SpanError, response_span
from ..usage import Usage
from ..version import __version__
@@ -383,7 +383,9 @@ def _convert_tool(cls, tool: Tool) -> tuple[ToolParam, ResponseIncludable | None
"display_height": tool.computer.dimensions[1],
}
includes = None
-
+ elif isinstance(tool, HostedMCPTool):
+ converted_tool = tool.tool_config
+ includes = None
else:
raise UserError(f"Unknown tool type: {type(tool)}, tool")
diff --git a/src/agents/stream_events.py b/src/agents/stream_events.py
index bd37d11f3..111d0b951 100644
--- a/src/agents/stream_events.py
+++ b/src/agents/stream_events.py
@@ -35,6 +35,8 @@ class RunItemStreamEvent:
"tool_called",
"tool_output",
"reasoning_item_created",
+ "mcp_approval_requested",
+ "mcp_list_tools",
]
"""The name of the event."""
diff --git a/src/agents/tool.py b/src/agents/tool.py
index c1c162423..3bcd57c2e 100644
--- a/src/agents/tool.py
+++ b/src/agents/tool.py
@@ -7,9 +7,11 @@
from typing import Any, Callable, Literal, Union, overload
from openai.types.responses.file_search_tool_param import Filters, RankingOptions
+from openai.types.responses.response_output_item import McpApprovalRequest
+from openai.types.responses.tool_param import Mcp
from openai.types.responses.web_search_tool_param import UserLocation
from pydantic import ValidationError
-from typing_extensions import Concatenate, ParamSpec
+from typing_extensions import Concatenate, NotRequired, ParamSpec, TypedDict
from . import _debug
from .computer import AsyncComputer, Computer
@@ -130,7 +132,55 @@ def name(self):
return "computer_use_preview"
-Tool = Union[FunctionTool, FileSearchTool, WebSearchTool, ComputerTool]
+@dataclass
+class MCPToolApprovalRequest:
+ """A request to approve a tool call."""
+
+ ctx_wrapper: RunContextWrapper[Any]
+ """The run context."""
+
+ data: McpApprovalRequest
+ """The data from the MCP tool approval request."""
+
+
+class MCPToolApprovalFunctionResult(TypedDict):
+ """The result of an MCP tool approval function."""
+
+ approve: bool
+ """Whether to approve the tool call."""
+
+ reason: NotRequired[str]
+ """An optional reason, if rejected."""
+
+
+MCPToolApprovalFunction = Callable[
+ [MCPToolApprovalRequest], MaybeAwaitable[MCPToolApprovalFunctionResult]
+]
+"""A function that approves or rejects a tool call."""
+
+
+@dataclass
+class HostedMCPTool:
+ """A tool that allows the LLM to use a remote MCP server. The LLM will automatically list and
+ call tools, without requiring a a round trip back to your code.
+ If you want to run MCP servers locally via stdio, in a VPC or other non-publicly-accessible
+ environment, or you just prefer to run tool calls locally, then you can instead use the servers
+ in `agents.mcp` and pass `Agent(mcp_servers=[...])` to the agent."""
+
+ tool_config: Mcp
+ """The MCP tool config, which includes the server URL and other settings."""
+
+ on_approval_request: MCPToolApprovalFunction | None = None
+ """An optional function that will be called if approval is requested for an MCP tool. If not
+ provided, you will need to manually add approvals/rejections to the input and call
+ `Runner.run(...)` again."""
+
+ @property
+ def name(self):
+ return "hosted_mcp"
+
+
+Tool = Union[FunctionTool, FileSearchTool, WebSearchTool, ComputerTool, HostedMCPTool]
"""A tool that can be used in an agent."""
@@ -308,3 +358,13 @@ def decorator(real_func: ToolFunction[...]) -> FunctionTool:
return _create_function_tool(real_func)
return decorator
+ return decorator
+ return decorator
+ return decorator
+ return decorator
+ return decorator
+ return decorator
+ return decorator
+ return decorator
+ return decorator
+ return decorator
From 079764f0ab463fda9ecf397b0a5d8e466e87a86c Mon Sep 17 00:00:00 2001
From: Rohan Mehta <rm@openai.com>
Date: Wed, 21 May 2025 15:26:22 -0400
Subject: [PATCH 12/68] Add support for local shell, image generator, code
interpreter tools (#732)
---
examples/tools/code_interpreter.py | 34 +++++++
examples/tools/image_generator.py | 54 +++++++++++
src/agents/__init__.py | 10 +++
src/agents/_run_impl.py | 124 +++++++++++++++++++++++++-
src/agents/items.py | 21 ++++-
src/agents/models/openai_responses.py | 35 +++++++-
src/agents/tool.py | 76 +++++++++++++---
7 files changed, 334 insertions(+), 20 deletions(-)
create mode 100644 examples/tools/code_interpreter.py
create mode 100644 examples/tools/image_generator.py
diff --git a/examples/tools/code_interpreter.py b/examples/tools/code_interpreter.py
new file mode 100644
index 000000000..a5843ce3f
--- /dev/null
+++ b/examples/tools/code_interpreter.py
@@ -0,0 +1,34 @@
+import asyncio
+
+from agents import Agent, CodeInterpreterTool, Runner, trace
+
+
+async def main():
+ agent = Agent(
+ name="Code interpreter",
+ instructions="You love doing math.",
+ tools=[
+ CodeInterpreterTool(
+ tool_config={"type": "code_interpreter", "container": {"type": "auto"}},
+ )
+ ],
+ )
+
+ with trace("Code interpreter example"):
+ print("Solving math problem...")
+ result = Runner.run_streamed(agent, "What is the square root of273 * 312821 plus 1782?")
+ async for event in result.stream_events():
+ if (
+ event.type == "run_item_stream_event"
+ and event.item.type == "tool_call_item"
+ and event.item.raw_item.type == "code_interpreter_call"
+ ):
+ print(f"Code interpreter code:\n```\n{event.item.raw_item.code}\n```\n")
+ elif event.type == "run_item_stream_event":
+ print(f"Other event: {event.item.type}")
+
+ print(f"Final output: {result.final_output}")
+
+
+if __name__ == "__main__":
+ asyncio.run(main())
diff --git a/examples/tools/image_generator.py b/examples/tools/image_generator.py
new file mode 100644
index 000000000..fd6fcc6ba
--- /dev/null
+++ b/examples/tools/image_generator.py
@@ -0,0 +1,54 @@
+import asyncio
+import base64
+import os
+import subprocess
+import sys
+import tempfile
+
+from agents import Agent, ImageGenerationTool, Runner, trace
+
+
+def open_file(path: str) -> None:
+ if sys.platform.startswith("darwin"):
+ subprocess.run(["open", path], check=False) # macOS
+ elif os.name == "nt": # Windows
+ os.astartfile(path) # type: ignore
+ elif os.name == "posix":
+ subprocess.run(["xdg-open", path], check=False) # Linux/Unix
+ else:
+ print(f"Don't know how to open files on this platform: {sys.platform}")
+
+
+async def main():
+ agent = Agent(
+ name="Image generator",
+ instructions="You are a helpful agent.",
+ tools=[
+ ImageGenerationTool(
+ tool_config={"type": "image_generation", "quality": "low"},
+ )
+ ],
+ )
+
+ with trace("Image generation example"):
+ print("Generating image, this may take a while...")
+ result = await Runner.run(
+ agent, "Create an image of a frog eating a pizza, comic book style."
+ )
+ print(result.final_output)
+ for item in result.new_items:
+ if (
+ item.type == "tool_call_item"
+ and item.raw_item.type == "image_generation_call"
+ and (img_result := item.raw_item.result)
+ ):
+ with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as tmp:
+ tmp.write(base64.b64decode(img_result))
+ temp_path = tmp.name
+
+ # Open the image
+ open_file(temp_path)
+
+
+if __name__ == "__main__":
+ asyncio.run(main())
diff --git a/src/agents/__init__.py b/src/agents/__init__.py
index 36c26b80d..58949157a 100644
--- a/src/agents/__init__.py
+++ b/src/agents/__init__.py
@@ -54,11 +54,16 @@
StreamEvent,
)
from .tool import (
+ CodeInterpreterTool,
ComputerTool,
FileSearchTool,
FunctionTool,
FunctionToolResult,
HostedMCPTool,
+ ImageGenerationTool,
+ LocalShellCommandRequest,
+ LocalShellExecutor,
+ LocalShellTool,
MCPToolApprovalFunction,
MCPToolApprovalFunctionResult,
MCPToolApprovalRequest,
@@ -210,6 +215,11 @@ def enable_verbose_stdout_logging():
"FunctionToolResult",
"ComputerTool",
"FileSearchTool",
+ "CodeInterpreterTool",
+ "ImageGenerationTool",
+ "LocalShellCommandRequest",
+ "LocalShellExecutor",
+ "LocalShellTool",
"Tool",
"WebSearchTool",
"HostedMCPTool",
diff --git a/src/agents/_run_impl.py b/src/agents/_run_impl.py
index ab1e78797..2cfa270e0 100644
--- a/src/agents/_run_impl.py
+++ b/src/agents/_run_impl.py
@@ -14,6 +14,9 @@
ResponseFunctionWebSearch,
ResponseOutputMessage,
)
+from openai.types.responses.response_code_interpreter_tool_call import (
+ ResponseCodeInterpreterToolCall,
+)
from openai.types.responses.response_computer_tool_call import (
ActionClick,
ActionDoubleClick,
@@ -26,7 +29,12 @@
ActionWait,
)
from openai.types.responses.response_input_param import ComputerCallOutput, McpApprovalResponse
-from openai.types.responses.response_output_item import McpApprovalRequest, McpCall, McpListTools
+from openai.types.responses.response_output_item import (
+ ImageGenerationCall,
+ LocalShellCall,
+ McpApprovalRequest,
+ McpListTools,
+)
from openai.types.responses.response_reasoning_item import ResponseReasoningItem
from .agent import Agent, ToolsToFinalOutputResult
@@ -61,6 +69,8 @@
FunctionTool,
FunctionToolResult,
HostedMCPTool,
+ LocalShellCommandRequest,
+ LocalShellTool,
MCPToolApprovalRequest,
Tool,
)
@@ -129,12 +139,19 @@ class ToolRunMCPApprovalRequest:
mcp_tool: HostedMCPTool
+@dataclass
+class ToolRunLocalShellCall:
+ tool_call: LocalShellCall
+ local_shell_tool: LocalShellTool
+
+
@dataclass
class ProcessedResponse:
new_items: list[RunItem]
handoffs: list[ToolRunHandoff]
functions: list[ToolRunFunction]
computer_actions: list[ToolRunComputerAction]
+ local_shell_calls: list[ToolRunLocalShellCall]
tools_used: list[str] # Names of all tools used, including hosted tools
mcp_approval_requests: list[ToolRunMCPApprovalRequest] # Only requests with callbacks
@@ -146,6 +163,7 @@ def has_tools_or_approvals_to_run(self) -> bool:
self.handoffs,
self.functions,
self.computer_actions,
+ self.local_shell_calls,
self.mcp_approval_requests,
]
)
@@ -371,11 +389,15 @@ def process_model_response(
run_handoffs = []
functions = []
computer_actions = []
+ local_shell_calls = []
mcp_approval_requests = []
tools_used: list[str] = []
handoff_map = {handoff.tool_name: handoff for handoff in handoffs}
function_map = {tool.name: tool for tool in all_tools if isinstance(tool, FunctionTool)}
computer_tool = next((tool for tool in all_tools if isinstance(tool, ComputerTool)), None)
+ local_shell_tool = next(
+ (tool for tool in all_tools if isinstance(tool, LocalShellTool)), None
+ )
hosted_mcp_server_map = {
tool.tool_config["server_label"]: tool
for tool in all_tools
@@ -434,9 +456,29 @@ def process_model_response(
)
elif isinstance(output, McpListTools):
items.append(MCPListToolsItem(raw_item=output, agent=agent))
- elif isinstance(output, McpCall):
+ elif isinstance(output, ImageGenerationCall):
+ items.append(ToolCallItem(raw_item=output, agent=agent))
+ tools_used.append("image_generation")
+ elif isinstance(output, ResponseCodeInterpreterToolCall):
items.append(ToolCallItem(raw_item=output, agent=agent))
- tools_used.append(output.name)
+ tools_used.append("code_interpreter")
+ elif isinstance(output, LocalShellCall):
+ items.append(ToolCallItem(raw_item=output, agent=agent))
+ tools_used.append("local_shell")
+ if not local_shell_tool:
+ _error_tracing.attach_error_to_current_span(
+ SpanError(
+ message="Local shell tool not found",
+ data={},
+ )
+ )
+ raise ModelBehaviorError(
+ "Model produced local shell call without a local shell tool."
+ )
+ local_shell_calls.append(
+ ToolRunLocalShellCall(tool_call=output, local_shell_tool=local_shell_tool)
+ )
+
elif not isinstance(output, ResponseFunctionToolCall):
logger.warning(f"Unexpected output type, ignoring: {type(output)}")
continue
@@ -478,6 +520,7 @@ def process_model_response(
handoffs=run_handoffs,
functions=functions,
computer_actions=computer_actions,
+ local_shell_calls=local_shell_calls,
tools_used=tools_used,
mcp_approval_requests=mcp_approval_requests,
)
@@ -552,6 +595,30 @@ async def run_single_tool(
for tool_run, result in zip(tool_runs, results)
]
+ @classmethod
+ async def execute_local_shell_calls(
+ cls,
+ *,
+ agent: Agent[TContext],
+ calls: list[ToolRunLocalShellCall],
+ context_wrapper: RunContextWrapper[TContext],
+ hooks: RunHooks[TContext],
+ config: RunConfig,
+ ) -> list[RunItem]:
+ results: list[RunItem] = []
+ # Need to run these serially, because each call can affect the local shell state
+ for call in calls:
+ results.append(
+ await LocalShellAction.execute(
+ agent=agent,
+ call=call,
+ hooks=hooks,
+ context_wrapper=context_wrapper,
+ config=config,
+ )
+ )
+ return results
+
@classmethod
async def execute_computer_actions(
cls,
@@ -1021,3 +1088,54 @@ async def _get_screenshot_async(
await computer.wait()
return await computer.screenshot()
+
+
+class LocalShellAction:
+ @classmethod
+ async def execute(
+ cls,
+ *,
+ agent: Agent[TContext],
+ call: ToolRunLocalShellCall,
+ hooks: RunHooks[TContext],
+ context_wrapper: RunContextWrapper[TContext],
+ config: RunConfig,
+ ) -> RunItem:
+ await asyncio.gather(
+ hooks.on_tool_start(context_wrapper, agent, call.local_shell_tool),
+ (
+ agent.hooks.on_tool_start(context_wrapper, agent, call.local_shell_tool)
+ if agent.hooks
+ else _coro.noop_coroutine()
+ ),
+ )
+
+ request = LocalShellCommandRequest(
+ ctx_wrapper=context_wrapper,
+ data=call.tool_call,
+ )
+ output = call.local_shell_tool.executor(request)
+ if inspect.isawaitable(output):
+ result = await output
+ else:
+ result = output
+
+ await asyncio.gather(
+ hooks.on_tool_end(context_wrapper, agent, call.local_shell_tool, result),
+ (
+ agent.hooks.on_tool_end(context_wrapper, agent, call.local_shell_tool, result)
+ if agent.hooks
+ else _coro.noop_coroutine()
+ ),
+ )
+
+ return ToolCallOutputItem(
+ agent=agent,
+ output=output,
+ raw_item={
+ "type": "local_shell_call_output",
+ "id": call.tool_call.call_id,
+ "output": result,
+ # "id": "out" + call.tool_call.id, # TODO remove this, it should be optional
+ },
+ )
diff --git a/src/agents/items.py b/src/agents/items.py
index 65a911798..64797ad22 100644
--- a/src/agents/items.py
+++ b/src/agents/items.py
@@ -18,12 +18,22 @@
ResponseOutputText,
ResponseStreamEvent,
)
+from openai.types.responses.response_code_interpreter_tool_call import (
+ ResponseCodeInterpreterToolCall,
+)
from openai.types.responses.response_input_item_param import (
ComputerCallOutput,
FunctionCallOutput,
+ LocalShellCallOutput,
McpApprovalResponse,
)
-from openai.types.responses.response_output_item import McpApprovalRequest, McpCall, McpListTools
+from openai.types.responses.response_output_item import (
+ ImageGenerationCall,
+ LocalShellCall,
+ McpApprovalRequest,
+ McpCall,
+ McpListTools,
+)
from openai.types.responses.response_reasoning_item import ResponseReasoningItem
from pydantic import BaseModel
from typing_extensions import TypeAlias
@@ -114,6 +124,9 @@ class HandoffOutputItem(RunItemBase[TResponseInputItem]):
ResponseFileSearchToolCall,
ResponseFunctionWebSearch,
McpCall,
+ ResponseCodeInterpreterToolCall,
+ ImageGenerationCall,
+ LocalShellCall,
]
"""A type that represents a tool call item."""
@@ -129,10 +142,12 @@ class ToolCallItem(RunItemBase[ToolCallItemTypes]):
@dataclass
-class ToolCallOutputItem(RunItemBase[Union[FunctionCallOutput, ComputerCallOutput]]):
+class ToolCallOutputItem(
+ RunItemBase[Union[FunctionCallOutput, ComputerCallOutput, LocalShellCallOutput]]
+):
"""Represents the output of a tool call."""
- raw_item: FunctionCallOutput | ComputerCallOutput
+ raw_item: FunctionCallOutput | ComputerCallOutput | LocalShellCallOutput
"""The raw item from the model."""
output: Any
diff --git a/src/agents/models/openai_responses.py b/src/agents/models/openai_responses.py
index 65a4f5caf..86c8e69cb 100644
--- a/src/agents/models/openai_responses.py
+++ b/src/agents/models/openai_responses.py
@@ -24,7 +24,17 @@
from ..handoffs import Handoff
from ..items import ItemHelpers, ModelResponse, TResponseInputItem
from ..logger import logger
-from ..tool import ComputerTool, FileSearchTool, FunctionTool, HostedMCPTool, Tool, WebSearchTool
+from ..tool import (
+ CodeInterpreterTool,
+ ComputerTool,
+ FileSearchTool,
+ FunctionTool,
+ HostedMCPTool,
+ ImageGenerationTool,
+ LocalShellTool,
+ Tool,
+ WebSearchTool,
+)
from ..tracing import SpanError, response_span
from ..usage import Usage
from ..version import __version__
@@ -295,6 +305,18 @@ def convert_tool_choice(
return {
"type": "computer_use_preview",
}
+ elif tool_choice == "image_generation":
+ return {
+ "type": "image_generation",
+ }
+ elif tool_choice == "code_interpreter":
+ return {
+ "type": "code_interpreter",
+ }
+ elif tool_choice == "mcp":
+ return {
+ "type": "mcp",
+ }
else:
return {
"type": "function",
@@ -386,6 +408,17 @@ def _convert_tool(cls, tool: Tool) -> tuple[ToolParam, ResponseIncludable | None
elif isinstance(tool, HostedMCPTool):
converted_tool = tool.tool_config
includes = None
+ elif isinstance(tool, ImageGenerationTool):
+ converted_tool = tool.tool_config
+ includes = None
+ elif isinstance(tool, CodeInterpreterTool):
+ converted_tool = tool.tool_config
+ includes = None
+ elif isinstance(tool, LocalShellTool):
+ converted_tool = {
+ "type": "local_shell",
+ }
+ includes = None
else:
raise UserError(f"Unknown tool type: {type(tool)}, tool")
diff --git a/src/agents/tool.py b/src/agents/tool.py
index 3bcd57c2e..fd5a21c89 100644
--- a/src/agents/tool.py
+++ b/src/agents/tool.py
@@ -7,8 +7,8 @@
from typing import Any, Callable, Literal, Union, overload
from openai.types.responses.file_search_tool_param import Filters, RankingOptions
-from openai.types.responses.response_output_item import McpApprovalRequest
-from openai.types.responses.tool_param import Mcp
+from openai.types.responses.response_output_item import LocalShellCall, McpApprovalRequest
+from openai.types.responses.tool_param import CodeInterpreter, ImageGeneration, Mcp
from openai.types.responses.web_search_tool_param import UserLocation
from pydantic import ValidationError
from typing_extensions import Concatenate, NotRequired, ParamSpec, TypedDict
@@ -180,7 +180,67 @@ def name(self):
return "hosted_mcp"
-Tool = Union[FunctionTool, FileSearchTool, WebSearchTool, ComputerTool, HostedMCPTool]
+@dataclass
+class CodeInterpreterTool:
+ """A tool that allows the LLM to execute code in a sandboxed environment."""
+
+ tool_config: CodeInterpreter
+ """The tool config, which includes the container and other settings."""
+
+ @property
+ def name(self):
+ return "code_interpreter"
+
+
+@dataclass
+class ImageGenerationTool:
+ """A tool that allows the LLM to generate images."""
+
+ tool_config: ImageGeneration
+ """The tool config, which image generation settings."""
+
+ @property
+ def name(self):
+ return "image_generation"
+
+
+@dataclass
+class LocalShellCommandRequest:
+ """A request to execute a command on a shell."""
+
+ ctx_wrapper: RunContextWrapper[Any]
+ """The run context."""
+
+ data: LocalShellCall
+ """The data from the local shell tool call."""
+
+
+LocalShellExecutor = Callable[[LocalShellCommandRequest], MaybeAwaitable[str]]
+"""A function that executes a command on a shell."""
+
+
+@dataclass
+class LocalShellTool:
+ """A tool that allows the LLM to execute commands on a shell."""
+
+ executor: LocalShellExecutor
+ """A function that executes a command on a shell."""
+
+ @property
+ def name(self):
+ return "local_shell"
+
+
+Tool = Union[
+ FunctionTool,
+ FileSearchTool,
+ WebSearchTool,
+ ComputerTool,
+ HostedMCPTool,
+ LocalShellTool,
+ ImageGenerationTool,
+ CodeInterpreterTool,
+]
"""A tool that can be used in an agent."""
@@ -358,13 +418,3 @@ def decorator(real_func: ToolFunction[...]) -> FunctionTool:
return _create_function_tool(real_func)
return decorator
- return decorator
- return decorator
- return decorator
- return decorator
- return decorator
- return decorator
- return decorator
- return decorator
- return decorator
- return decorator
From 1992be3e8d1746164f0f47f3e2001de4ab4059b9 Mon Sep 17 00:00:00 2001
From: Rohan Mehta <rm@openai.com>
Date: Wed, 21 May 2025 16:06:13 -0400
Subject: [PATCH 13/68] v0.0.16 (#733)
---
pyproject.toml | 2 +-
uv.lock | 2 +-
2 files changed, 2 insertions(+), 2 deletions(-)
diff --git a/pyproject.toml b/pyproject.toml
index 200ac2485..38a2f2b64 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
[project]
name = "openai-agents"
-version = "0.0.15"
+version = "0.0.16"
description = "OpenAI Agents SDK"
readme = "README.md"
requires-python = ">=3.9"
diff --git a/uv.lock b/uv.lock
index 7a0cb1e6b..6f2f3f843 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1480,7 +1480,7 @@ wheels = [
[[package]]
name = "openai-agents"
-version = "0.0.15"
+version = "0.0.16"
source = { editable = "." }
dependencies = [
{ name = "griffe" },
From 1364f4408e8e0d8bec1d6ac8337f68b3b888a4a7 Mon Sep 17 00:00:00 2001
From: Andrew Han <handrew11@gmail.com>
Date: Wed, 21 May 2025 14:59:47 -0700
Subject: [PATCH 14/68] fix Gemini token validation issue with LiteLLM (#735)
Fix for #734
---
src/agents/extensions/models/litellm_model.py | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
diff --git a/src/agents/extensions/models/litellm_model.py b/src/agents/extensions/models/litellm_model.py
index ffb2c3c1c..49e2d42d7 100644
--- a/src/agents/extensions/models/litellm_model.py
+++ b/src/agents/extensions/models/litellm_model.py
@@ -111,12 +111,12 @@ async def get_response(
input_tokens_details=InputTokensDetails(
cached_tokens=getattr(
response_usage.prompt_tokens_details, "cached_tokens", 0
- )
+ ) or 0
),
output_tokens_details=OutputTokensDetails(
reasoning_tokens=getattr(
response_usage.completion_tokens_details, "reasoning_tokens", 0
- )
+ ) or 0
),
)
if response.usage
From db462e32a30182d1e9fffe7328609e05c1bc347f Mon Sep 17 00:00:00 2001
From: Rohan Mehta <rm@openai.com>
Date: Fri, 23 May 2025 13:00:10 -0400
Subject: [PATCH 15/68] Fix visualization recursion with cycle detection (#737)
## Summary
- avoid infinite recursion in visualization by tracking visited agents
- test cycle detection in graph utility
## Testing
- `make mypy`
- `make tests`
Resolves #668
---
src/agents/extensions/visualization.py | 53 +++++++++++++++++---------
tests/test_visualization.py | 15 ++++++++
2 files changed, 50 insertions(+), 18 deletions(-)
diff --git a/src/agents/extensions/visualization.py b/src/agents/extensions/visualization.py
index 888e262c3..be762a330 100644
--- a/src/agents/extensions/visualization.py
+++ b/src/agents/extensions/visualization.py
@@ -1,4 +1,4 @@
-from typing import Optional
+from __future__ import annotations
import graphviz # type: ignore
@@ -31,7 +31,9 @@ def get_main_graph(agent: Agent) -> str:
return "".join(parts)
-def get_all_nodes(agent: Agent, parent: Optional[Agent] = None) -> str:
+def get_all_nodes(
+ agent: Agent, parent: Agent | None = None, visited: set[str] | None = None
+) -> str:
"""
Recursively generates the nodes for the given agent and its handoffs in DOT format.
@@ -41,17 +43,23 @@ def get_all_nodes(agent: Agent, parent: Optional[Agent] = None) -> str:
Returns:
str: The DOT format string representing the nodes.
"""
+ if visited is None:
+ visited = set()
+ if agent.name in visited:
+ return ""
+ visited.add(agent.name)
+
parts = []
# Start and end the graph
- parts.append(
- '"__start__" [label="__start__", shape=ellipse, style=filled, '
- "fillcolor=lightblue, width=0.5, height=0.3];"
- '"__end__" [label="__end__", shape=ellipse, style=filled, '
- "fillcolor=lightblue, width=0.5, height=0.3];"
- )
- # Ensure parent agent node is colored
if not parent:
+ parts.append(
+ '"__start__" [label="__start__", shape=ellipse, style=filled, '
+ "fillcolor=lightblue, width=0.5, height=0.3];"
+ '"__end__" [label="__end__", shape=ellipse, style=filled, '
+ "fillcolor=lightblue, width=0.5, height=0.3];"
+ )
+ # Ensure parent agent node is colored
parts.append(
f'"{agent.name}" [label="{agent.name}", shape=box, style=filled, '
"fillcolor=lightyellow, width=1.5, height=0.8];"
@@ -71,17 +79,20 @@ def get_all_nodes(agent: Agent, parent: Optional[Agent] = None) -> str:
f"fillcolor=lightyellow, width=1.5, height=0.8];"
)
if isinstance(handoff, Agent):
- parts.append(
- f'"{handoff.name}" [label="{handoff.name}", '
- f"shape=box, style=filled, style=rounded, "
- f"fillcolor=lightyellow, width=1.5, height=0.8];"
- )
- parts.append(get_all_nodes(handoff))
+ if handoff.name not in visited:
+ parts.append(
+ f'"{handoff.name}" [label="{handoff.name}", '
+ f"shape=box, style=filled, style=rounded, "
+ f"fillcolor=lightyellow, width=1.5, height=0.8];"
+ )
+ parts.append(get_all_nodes(handoff, agent, visited))
return "".join(parts)
-def get_all_edges(agent: Agent, parent: Optional[Agent] = None) -> str:
+def get_all_edges(
+ agent: Agent, parent: Agent | None = None, visited: set[str] | None = None
+) -> str:
"""
Recursively generates the edges for the given agent and its handoffs in DOT format.
@@ -92,6 +103,12 @@ def get_all_edges(agent: Agent, parent: Optional[Agent] = None) -> str:
Returns:
str: The DOT format string representing the edges.
"""
+ if visited is None:
+ visited = set()
+ if agent.name in visited:
+ return ""
+ visited.add(agent.name)
+
parts = []
if not parent:
@@ -109,7 +126,7 @@ def get_all_edges(agent: Agent, parent: Optional[Agent] = None) -> str:
if isinstance(handoff, Agent):
parts.append(f"""
"{agent.name}" -> "{handoff.name}";""")
- parts.append(get_all_edges(handoff, agent))
+ parts.append(get_all_edges(handoff, agent, visited))
if not agent.handoffs and not isinstance(agent, Tool): # type: ignore
parts.append(f'"{agent.name}" -> "__end__";')
@@ -117,7 +134,7 @@ def get_all_edges(agent: Agent, parent: Optional[Agent] = None) -> str:
return "".join(parts)
-def draw_graph(agent: Agent, filename: Optional[str] = None) -> graphviz.Source:
+def draw_graph(agent: Agent, filename: str | None = None) -> graphviz.Source:
"""
Draws the graph for the given agent and optionally saves it as a PNG file.
diff --git a/tests/test_visualization.py b/tests/test_visualization.py
index 6aa867743..8bce897e9 100644
--- a/tests/test_visualization.py
+++ b/tests/test_visualization.py
@@ -134,3 +134,18 @@ def test_draw_graph(mock_agent):
'"Handoff1" [label="Handoff1", shape=box, style=filled, style=rounded, '
"fillcolor=lightyellow, width=1.5, height=0.8];" in graph.source
)
+
+
+def test_cycle_detection():
+ agent_a = Agent(name="A")
+ agent_b = Agent(name="B")
+ agent_a.handoffs.append(agent_b)
+ agent_b.handoffs.append(agent_a)
+
+ nodes = get_all_nodes(agent_a)
+ edges = get_all_edges(agent_a)
+
+ assert nodes.count('"A" [label="A"') == 1
+ assert nodes.count('"B" [label="B"') == 1
+ assert '"A" -> "B"' in edges
+ assert '"B" -> "A"' in edges
From a96108e27915e55c133eaa66d155c19f043d7aca Mon Sep 17 00:00:00 2001
From: Rohan Mehta <rm@openai.com>
Date: Fri, 23 May 2025 13:00:21 -0400
Subject: [PATCH 16/68] Update MCP and tool docs (#736)
## Summary
- mention MCPServerStreamableHttp in MCP server docs
- document CodeInterpreterTool, HostedMCPTool, ImageGenerationTool and
LocalShellTool
- update Japanese translations
---
docs/ja/mcp.md | 9 +++++----
docs/ja/tools.md | 4 ++++
docs/mcp.md | 5 +++--
docs/tools.md | 4 ++++
4 files changed, 16 insertions(+), 6 deletions(-)
diff --git a/docs/ja/mcp.md b/docs/ja/mcp.md
index 7cdaa57ee..09804beb2 100644
--- a/docs/ja/mcp.md
+++ b/docs/ja/mcp.md
@@ -12,12 +12,13 @@ Agents SDK は MCP をサポートしており、これにより幅広い MCP
## MCP サーバー
-現在、MCP 仕様では使用するトランスポート方式に基づき 2 種類のサーバーが定義されています。
+現在、MCP 仕様では使用するトランスポート方式に基づき 3 種類のサーバーが定義されています。
-1. **stdio** サーバー: アプリケーションのサブプロセスとして実行されます。ローカルで動かすイメージです。
+1. **stdio** サーバー: アプリケーションのサブプロセスとして実行されます。ローカルで動かすイメージです。
2. **HTTP over SSE** サーバー: リモートで動作し、 URL 経由で接続します。
+3. **Streamable HTTP** サーバー: MCP 仕様に定義された Streamable HTTP トランスポートを使用してリモートで動作します。
-これらのサーバーへは [`MCPServerStdio`][agents.mcp.server.MCPServerStdio] と [`MCPServerSse`][agents.mcp.server.MCPServerSse] クラスを使用して接続できます。
+これらのサーバーへは [`MCPServerStdio`][agents.mcp.server.MCPServerStdio]、[`MCPServerSse`][agents.mcp.server.MCPServerSse]、[`MCPServerStreamableHttp`][agents.mcp.server.MCPServerStreamableHttp] クラスを使用して接続できます。
たとえば、[公式 MCP filesystem サーバー](https://www.npmjs.com/package/@modelcontextprotocol/server-filesystem)を利用する場合は次のようになります。
@@ -46,7 +47,7 @@ agent=Agent(
## キャッシュ
-エージェントが実行されるたびに、MCP サーバーへ `list_tools()` が呼び出されます。サーバーがリモートの場合は特にレイテンシが発生します。ツール一覧を自動でキャッシュしたい場合は、[`MCPServerStdio`][agents.mcp.server.MCPServerStdio] と [`MCPServerSse`][agents.mcp.server.MCPServerSse] の両方に `cache_tools_list=True` を渡してください。ツール一覧が変更されないと確信できる場合のみ使用してください。
+エージェントが実行されるたびに、MCP サーバーへ `list_tools()` が呼び出されます。サーバーがリモートの場合は特にレイテンシが発生します。ツール一覧を自動でキャッシュしたい場合は、[`MCPServerStdio`][agents.mcp.server.MCPServerStdio]、[`MCPServerSse`][agents.mcp.server.MCPServerSse]、[`MCPServerStreamableHttp`][agents.mcp.server.MCPServerStreamableHttp] の各クラスに `cache_tools_list=True` を渡してください。ツール一覧が変更されないと確信できる場合のみ使用してください。
キャッシュを無効化したい場合は、サーバーで `invalidate_tools_cache()` を呼び出します。
diff --git a/docs/ja/tools.md b/docs/ja/tools.md
index 7ab15e472..cd80092d5 100644
--- a/docs/ja/tools.md
+++ b/docs/ja/tools.md
@@ -17,6 +17,10 @@ OpenAI は [`OpenAIResponsesModel`][agents.models.openai_responses.OpenAIRespons
- [`WebSearchTool`][agents.tool.WebSearchTool] はエージェントに Web 検索を行わせます。
- [`FileSearchTool`][agents.tool.FileSearchTool] は OpenAI ベクトルストアから情報を取得します。
- [`ComputerTool`][agents.tool.ComputerTool] はコンピュータ操作タスクを自動化します。
+- [`CodeInterpreterTool`][agents.tool.CodeInterpreterTool] はサンドボックス環境でコードを実行します。
+- [`HostedMCPTool`][agents.tool.HostedMCPTool] はリモート MCP サーバーのツールをモデルから直接利用できるようにします。
+- [`ImageGenerationTool`][agents.tool.ImageGenerationTool] はプロンプトから画像を生成します。
+- [`LocalShellTool`][agents.tool.LocalShellTool] はローカルマシンでシェルコマンドを実行します。
```python
from agents import Agent, FileSearchTool, Runner, WebSearchTool
diff --git a/docs/mcp.md b/docs/mcp.md
index e279a25e0..2cd0aad9e 100644
--- a/docs/mcp.md
+++ b/docs/mcp.md
@@ -12,8 +12,9 @@ Currently, the MCP spec defines two kinds of servers, based on the transport mec
1. **stdio** servers run as a subprocess of your application. You can think of them as running "locally".
2. **HTTP over SSE** servers run remotely. You connect to them via a URL.
+3. **Streamable HTTP** servers run remotely using the Streamable HTTP transport defined in the MCP spec.
-You can use the [`MCPServerStdio`][agents.mcp.server.MCPServerStdio] and [`MCPServerSse`][agents.mcp.server.MCPServerSse] classes to connect to these servers.
+You can use the [`MCPServerStdio`][agents.mcp.server.MCPServerStdio], [`MCPServerSse`][agents.mcp.server.MCPServerSse], and [`MCPServerStreamableHttp`][agents.mcp.server.MCPServerStreamableHttp] classes to connect to these servers.
For example, this is how you'd use the [official MCP filesystem server](https://www.npmjs.com/package/@modelcontextprotocol/server-filesystem).
@@ -42,7 +43,7 @@ agent=Agent(
## Caching
-Every time an Agent runs, it calls `list_tools()` on the MCP server. This can be a latency hit, especially if the server is a remote server. To automatically cache the list of tools, you can pass `cache_tools_list=True` to both [`MCPServerStdio`][agents.mcp.server.MCPServerStdio] and [`MCPServerSse`][agents.mcp.server.MCPServerSse]. You should only do this if you're certain the tool list will not change.
+Every time an Agent runs, it calls `list_tools()` on the MCP server. This can be a latency hit, especially if the server is a remote server. To automatically cache the list of tools, you can pass `cache_tools_list=True` to [`MCPServerStdio`][agents.mcp.server.MCPServerStdio], [`MCPServerSse`][agents.mcp.server.MCPServerSse], and [`MCPServerStreamableHttp`][agents.mcp.server.MCPServerStreamableHttp]. You should only do this if you're certain the tool list will not change.
If you want to invalidate the cache, you can call `invalidate_tools_cache()` on the servers.
diff --git a/docs/tools.md b/docs/tools.md
index 5fe2ecedb..89e28d998 100644
--- a/docs/tools.md
+++ b/docs/tools.md
@@ -13,6 +13,10 @@ OpenAI offers a few built-in tools when using the [`OpenAIResponsesModel`][agent
- The [`WebSearchTool`][agents.tool.WebSearchTool] lets an agent search the web.
- The [`FileSearchTool`][agents.tool.FileSearchTool] allows retrieving information from your OpenAI Vector Stores.
- The [`ComputerTool`][agents.tool.ComputerTool] allows automating computer use tasks.
+- The [`CodeInterpreterTool`][agents.tool.CodeInterpreterTool] lets the LLM execute code in a sandboxed environment.
+- The [`HostedMCPTool`][agents.tool.HostedMCPTool] exposes a remote MCP server's tools to the model.
+- The [`ImageGenerationTool`][agents.tool.ImageGenerationTool] generates images from a prompt.
+- The [`LocalShellTool`][agents.tool.LocalShellTool] runs shell commands on your machine.
```python
from agents import Agent, FileSearchTool, Runner, WebSearchTool
From 6e078bf7a99badc5a36be961e4e6dd6dde4c3674 Mon Sep 17 00:00:00 2001
From: Rohan Mehta <rm@openai.com>
Date: Fri, 23 May 2025 13:00:30 -0400
Subject: [PATCH 17/68] Fix Gemini API content filter handling (#746)
## Summary
- avoid AttributeError when Gemini API returns `None` for chat message
- return empty output if message is filtered
- add regression test
## Testing
- `make format`
- `make lint`
- `make mypy`
- `make tests`
Towards #744
---
src/agents/models/openai_chatcompletions.py | 22 ++++++++++---
tests/test_openai_chatcompletions.py | 34 +++++++++++++++++++++
2 files changed, 51 insertions(+), 5 deletions(-)
diff --git a/src/agents/models/openai_chatcompletions.py b/src/agents/models/openai_chatcompletions.py
index 4465ff2fd..6b4045d21 100644
--- a/src/agents/models/openai_chatcompletions.py
+++ b/src/agents/models/openai_chatcompletions.py
@@ -71,12 +71,22 @@ async def get_response(
stream=False,
)
+ first_choice = response.choices[0]
+ message = first_choice.message
+
if _debug.DONT_LOG_MODEL_DATA:
logger.debug("Received model response")
else:
- logger.debug(
- f"LLM resp:\n{json.dumps(response.choices[0].message.model_dump(), indent=2)}\n"
- )
+ if message is not None:
+ logger.debug(
+ "LLM resp:\n%s\n",
+ json.dumps(message.model_dump(), indent=2),
+ )
+ else:
+ logger.debug(
+ "LLM resp had no message. finish_reason: %s",
+ first_choice.finish_reason,
+ )
usage = (
Usage(
@@ -101,13 +111,15 @@ async def get_response(
else Usage()
)
if tracing.include_data():
- span_generation.span_data.output = [response.choices[0].message.model_dump()]
+ span_generation.span_data.output = (
+ [message.model_dump()] if message is not None else []
+ )
span_generation.span_data.usage = {
"input_tokens": usage.input_tokens,
"output_tokens": usage.output_tokens,
}
- items = Converter.message_to_output_items(response.choices[0].message)
+ items = Converter.message_to_output_items(message) if message is not None else []
return ModelResponse(
output=items,
diff --git a/tests/test_openai_chatcompletions.py b/tests/test_openai_chatcompletions.py
index ba4605d08..9a85dcb7b 100644
--- a/tests/test_openai_chatcompletions.py
+++ b/tests/test_openai_chatcompletions.py
@@ -191,6 +191,40 @@ async def patched_fetch_response(self, *args, **kwargs):
assert fn_call_item.arguments == "{'x':1}"
+@pytest.mark.allow_call_model_methods
+@pytest.mark.asyncio
+async def test_get_response_with_no_message(monkeypatch) -> None:
+ """If the model returns no message, get_response should return an empty output."""
+ msg = ChatCompletionMessage(role="assistant", content="ignored")
+ choice = Choice(index=0, finish_reason="content_filter", message=msg)
+ choice.message = None # type: ignore[assignment]
+ chat = ChatCompletion(
+ id="resp-id",
+ created=0,
+ model="fake",
+ object="chat.completion",
+ choices=[choice],
+ usage=None,
+ )
+
+ async def patched_fetch_response(self, *args, **kwargs):
+ return chat
+
+ monkeypatch.setattr(OpenAIChatCompletionsModel, "_fetch_response", patched_fetch_response)
+ model = OpenAIProvider(use_responses=False).get_model("gpt-4")
+ resp: ModelResponse = await model.get_response(
+ system_instructions=None,
+ input="",
+ model_settings=ModelSettings(),
+ tools=[],
+ output_schema=None,
+ handoffs=[],
+ tracing=ModelTracing.DISABLED,
+ previous_response_id=None,
+ )
+ assert resp.output == []
+
+
@pytest.mark.asyncio
async def test_fetch_response_non_stream(monkeypatch) -> None:
"""
From d46e2ec35baeec3c84a873438eb341ed64a6eede Mon Sep 17 00:00:00 2001
From: siddharth Sambharia <siddharth.s@portkey.ai>
Date: Thu, 29 May 2025 21:13:25 +0530
Subject: [PATCH 18/68] Add Portkey AI as a tracing provider (#785)
This PR adds Portkey AI as a tracing provider. Portkey helps you take
your OpenAI agents from prototype to production.
Portkey turns your experimental OpenAI Agents into production-ready
systems by providing:
- Complete observability of every agent step, tool use, and interaction
- Built-in reliability with fallbacks, retries, and load balancing
- Cost tracking and optimization to manage your AI spend
- Access to 1600+ LLMs through a single integration
- Guardrails to keep agent behavior safe and compliant
- Version-controlled prompts for consistent agent performance
Towards #786
---
docs/ja/tracing.md | 3 ++-
docs/tracing.md | 1 +
2 files changed, 3 insertions(+), 1 deletion(-)
diff --git a/docs/ja/tracing.md b/docs/ja/tracing.md
index 0e0d0e77d..d67200ce4 100644
--- a/docs/ja/tracing.md
+++ b/docs/ja/tracing.md
@@ -119,4 +119,5 @@ async def main():
- [Comet Opik](https://www.comet.com/docs/opik/tracing/integrations/openai_agents)
- [Langfuse](https://langfuse.com/docs/integrations/openaiagentssdk/openai-agents)
- [Langtrace](https://docs.langtrace.ai/supported-integrations/llm-frameworks/openai-agents-sdk)
-- [Okahu‑Monocle](https://github.com/monocle2ai/monocle)
\ No newline at end of file
+- [Okahu‑Monocle](https://github.com/monocle2ai/monocle)
+- [Portkey AI](https://portkey.ai/docs/integrations/agents/openai-agents)
diff --git a/docs/tracing.md b/docs/tracing.md
index 4a9c1bd90..c7776ad7b 100644
--- a/docs/tracing.md
+++ b/docs/tracing.md
@@ -116,3 +116,4 @@ To customize this default setup, to send traces to alternative or additional bac
- [Langtrace](https://docs.langtrace.ai/supported-integrations/llm-frameworks/openai-agents-sdk)
- [Okahu-Monocle](https://github.com/monocle2ai/monocle)
- [Galileo](https://v2docs.galileo.ai/integrations/openai-agent-integration#openai-agent-integration)
+- [Portkey AI](https://portkey.ai/docs/integrations/agents/openai-agents)
From 71968625ccafe62f7015dc6ab5f8eaea81a95bd4 Mon Sep 17 00:00:00 2001
From: Daniele Morotti <58258368+DanieleMorotti@users.noreply.github.com>
Date: Thu, 29 May 2025 22:11:33 +0200
Subject: [PATCH 19/68] Added RunErrorDetails object for MaxTurnsExceeded
exception (#743)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
### Summary
Introduced the `RunErrorDetails` object to get partial results from a
run interrupted by `MaxTurnsExceeded` exception. In this proposal the
`RunErrorDetails` object contains all the fields from `RunResult` with
`final_output` set to `None` and `output_guardrail_results` set to an
empty list. We can decide to return less information.
@rm-openai At the moment the exception doesn't return the
`RunErrorDetails` object for the streaming mode. Do you have any
suggestions on how to deal with it? In the `_check_errors` function of
`agents/result.py` file.
### Test plan
I have not implemented any tests currently, but if needed I can
implement a basic test to retrieve partial data.
### Issue number
This PR is an attempt to solve issue #719
### Checks
- [✅ ] I've added new tests (if relevant)
- [ ] I've added/updated the relevant documentation
- [ ✅] I've run `make lint` and `make format`
- [ ✅] I've made sure tests pass
---
src/agents/__init__.py | 2 +
src/agents/exceptions.py | 41 ++++++++++++++++---
src/agents/result.py | 57 +++++++++++++++++++++------
src/agents/run.py | 30 +++++++++++++-
src/agents/util/_pretty_print.py | 12 ++++++
tests/test_run_error_details.py | 44 +++++++++++++++++++++
tests/test_tracing_errors_streamed.py | 4 --
7 files changed, 167 insertions(+), 23 deletions(-)
create mode 100644 tests/test_run_error_details.py
diff --git a/src/agents/__init__.py b/src/agents/__init__.py
index 58949157a..820616437 100644
--- a/src/agents/__init__.py
+++ b/src/agents/__init__.py
@@ -14,6 +14,7 @@
MaxTurnsExceeded,
ModelBehaviorError,
OutputGuardrailTripwireTriggered,
+ RunErrorDetails,
UserError,
)
from .guardrail import (
@@ -204,6 +205,7 @@ def enable_verbose_stdout_logging():
"AgentHooks",
"RunContextWrapper",
"TContext",
+ "RunErrorDetails",
"RunResult",
"RunResultStreaming",
"RunConfig",
diff --git a/src/agents/exceptions.py b/src/agents/exceptions.py
index 78898f017..4f6e2e768 100644
--- a/src/agents/exceptions.py
+++ b/src/agents/exceptions.py
@@ -1,11 +1,39 @@
-from typing import TYPE_CHECKING
+from __future__ import annotations
+
+from dataclasses import dataclass
+from typing import TYPE_CHECKING, Any
if TYPE_CHECKING:
+ from .agent import Agent
from .guardrail import InputGuardrailResult, OutputGuardrailResult
+ from .items import ModelResponse, RunItem, TResponseInputItem
+ from .run_context import RunContextWrapper
+
+from .util._pretty_print import pretty_print_run_error_details
+
+
+@dataclass
+class RunErrorDetails:
+ """Data collected from an agent run when an exception occurs."""
+ input: str | list[TResponseInputItem]
+ new_items: list[RunItem]
+ raw_responses: list[ModelResponse]
+ last_agent: Agent[Any]
+ context_wrapper: RunContextWrapper[Any]
+ input_guardrail_results: list[InputGuardrailResult]
+ output_guardrail_results: list[OutputGuardrailResult]
+
+ def __str__(self) -> str:
+ return pretty_print_run_error_details(self)
class AgentsException(Exception):
"""Base class for all exceptions in the Agents SDK."""
+ run_data: RunErrorDetails | None
+
+ def __init__(self, *args: object) -> None:
+ super().__init__(*args)
+ self.run_data = None
class MaxTurnsExceeded(AgentsException):
@@ -15,6 +43,7 @@ class MaxTurnsExceeded(AgentsException):
def __init__(self, message: str):
self.message = message
+ super().__init__(message)
class ModelBehaviorError(AgentsException):
@@ -26,6 +55,7 @@ class ModelBehaviorError(AgentsException):
def __init__(self, message: str):
self.message = message
+ super().__init__(message)
class UserError(AgentsException):
@@ -35,15 +65,16 @@ class UserError(AgentsException):
def __init__(self, message: str):
self.message = message
+ super().__init__(message)
class InputGuardrailTripwireTriggered(AgentsException):
"""Exception raised when a guardrail tripwire is triggered."""
- guardrail_result: "InputGuardrailResult"
+ guardrail_result: InputGuardrailResult
"""The result data of the guardrail that was triggered."""
- def __init__(self, guardrail_result: "InputGuardrailResult"):
+ def __init__(self, guardrail_result: InputGuardrailResult):
self.guardrail_result = guardrail_result
super().__init__(
f"Guardrail {guardrail_result.guardrail.__class__.__name__} triggered tripwire"
@@ -53,10 +84,10 @@ def __init__(self, guardrail_result: "InputGuardrailResult"):
class OutputGuardrailTripwireTriggered(AgentsException):
"""Exception raised when a guardrail tripwire is triggered."""
- guardrail_result: "OutputGuardrailResult"
+ guardrail_result: OutputGuardrailResult
"""The result data of the guardrail that was triggered."""
- def __init__(self, guardrail_result: "OutputGuardrailResult"):
+ def __init__(self, guardrail_result: OutputGuardrailResult):
self.guardrail_result = guardrail_result
super().__init__(
f"Guardrail {guardrail_result.guardrail.__class__.__name__} triggered tripwire"
diff --git a/src/agents/result.py b/src/agents/result.py
index 243db155c..764815246 100644
--- a/src/agents/result.py
+++ b/src/agents/result.py
@@ -11,14 +11,22 @@
from ._run_impl import QueueCompleteSentinel
from .agent import Agent
from .agent_output import AgentOutputSchemaBase
-from .exceptions import InputGuardrailTripwireTriggered, MaxTurnsExceeded
+from .exceptions import (
+ AgentsException,
+ InputGuardrailTripwireTriggered,
+ MaxTurnsExceeded,
+ RunErrorDetails,
+)
from .guardrail import InputGuardrailResult, OutputGuardrailResult
from .items import ItemHelpers, ModelResponse, RunItem, TResponseInputItem
from .logger import logger
from .run_context import RunContextWrapper
from .stream_events import StreamEvent
from .tracing import Trace
-from .util._pretty_print import pretty_print_result, pretty_print_run_result_streaming
+from .util._pretty_print import (
+ pretty_print_result,
+ pretty_print_run_result_streaming,
+)
if TYPE_CHECKING:
from ._run_impl import QueueCompleteSentinel
@@ -206,31 +214,53 @@ async def stream_events(self) -> AsyncIterator[StreamEvent]:
if self._stored_exception:
raise self._stored_exception
+ def _create_error_details(self) -> RunErrorDetails:
+ """Return a `RunErrorDetails` object considering the current attributes of the class."""
+ return RunErrorDetails(
+ input=self.input,
+ new_items=self.new_items,
+ raw_responses=self.raw_responses,
+ last_agent=self.current_agent,
+ context_wrapper=self.context_wrapper,
+ input_guardrail_results=self.input_guardrail_results,
+ output_guardrail_results=self.output_guardrail_results,
+ )
+
def _check_errors(self):
if self.current_turn > self.max_turns:
- self._stored_exception = MaxTurnsExceeded(f"Max turns ({self.max_turns}) exceeded")
+ max_turns_exc = MaxTurnsExceeded(f"Max turns ({self.max_turns}) exceeded")
+ max_turns_exc.run_data = self._create_error_details()
+ self._stored_exception = max_turns_exc
# Fetch all the completed guardrail results from the queue and raise if needed
while not self._input_guardrail_queue.empty():
guardrail_result = self._input_guardrail_queue.get_nowait()
if guardrail_result.output.tripwire_triggered:
- self._stored_exception = InputGuardrailTripwireTriggered(guardrail_result)
+ tripwire_exc = InputGuardrailTripwireTriggered(guardrail_result)
+ tripwire_exc.run_data = self._create_error_details()
+ self._stored_exception = tripwire_exc
# Check the tasks for any exceptions
if self._run_impl_task and self._run_impl_task.done():
- exc = self._run_impl_task.exception()
- if exc and isinstance(exc, Exception):
- self._stored_exception = exc
+ run_impl_exc = self._run_impl_task.exception()
+ if run_impl_exc and isinstance(run_impl_exc, Exception):
+ if isinstance(run_impl_exc, AgentsException) and run_impl_exc.run_data is None:
+ run_impl_exc.run_data = self._create_error_details()
+ self._stored_exception = run_impl_exc
if self._input_guardrails_task and self._input_guardrails_task.done():
- exc = self._input_guardrails_task.exception()
- if exc and isinstance(exc, Exception):
- self._stored_exception = exc
+ in_guard_exc = self._input_guardrails_task.exception()
+ if in_guard_exc and isinstance(in_guard_exc, Exception):
+ if isinstance(in_guard_exc, AgentsException) and in_guard_exc.run_data is None:
+ in_guard_exc.run_data = self._create_error_details()
+ self._stored_exception = in_guard_exc
if self._output_guardrails_task and self._output_guardrails_task.done():
- exc = self._output_guardrails_task.exception()
- if exc and isinstance(exc, Exception):
- self._stored_exception = exc
+ out_guard_exc = self._output_guardrails_task.exception()
+ if out_guard_exc and isinstance(out_guard_exc, Exception):
+ if isinstance(out_guard_exc, AgentsException) and out_guard_exc.run_data is None:
+ out_guard_exc.run_data = self._create_error_details()
+ self._stored_exception = out_guard_exc
def _cleanup_tasks(self):
if self._run_impl_task and not self._run_impl_task.done():
@@ -244,3 +274,4 @@ def _cleanup_tasks(self):
def __str__(self) -> str:
return pretty_print_run_result_streaming(self)
+
diff --git a/src/agents/run.py b/src/agents/run.py
index b196c3bf1..c67386495 100644
--- a/src/agents/run.py
+++ b/src/agents/run.py
@@ -1,3 +1,4 @@
+
from __future__ import annotations
import asyncio
@@ -26,6 +27,7 @@
MaxTurnsExceeded,
ModelBehaviorError,
OutputGuardrailTripwireTriggered,
+ RunErrorDetails,
)
from .guardrail import InputGuardrail, InputGuardrailResult, OutputGuardrail, OutputGuardrailResult
from .handoffs import Handoff, HandoffInputFilter, handoff
@@ -208,7 +210,9 @@ async def run(
data={"max_turns": max_turns},
),
)
- raise MaxTurnsExceeded(f"Max turns ({max_turns}) exceeded")
+ raise MaxTurnsExceeded(
+ f"Max turns ({max_turns}) exceeded"
+ )
logger.debug(
f"Running agent {current_agent.name} (turn {current_turn})",
@@ -283,6 +287,17 @@ async def run(
raise AgentsException(
f"Unknown next step type: {type(turn_result.next_step)}"
)
+ except AgentsException as exc:
+ exc.run_data = RunErrorDetails(
+ input=original_input,
+ new_items=generated_items,
+ raw_responses=model_responses,
+ last_agent=current_agent,
+ context_wrapper=context_wrapper,
+ input_guardrail_results=input_guardrail_results,
+ output_guardrail_results=[]
+ )
+ raise
finally:
if current_span:
current_span.finish(reset_current=True)
@@ -609,6 +624,19 @@ async def _run_streamed_impl(
streamed_result._event_queue.put_nowait(QueueCompleteSentinel())
elif isinstance(turn_result.next_step, NextStepRunAgain):
pass
+ except AgentsException as exc:
+ streamed_result.is_complete = True
+ streamed_result._event_queue.put_nowait(QueueCompleteSentinel())
+ exc.run_data = RunErrorDetails(
+ input=streamed_result.input,
+ new_items=streamed_result.new_items,
+ raw_responses=streamed_result.raw_responses,
+ last_agent=current_agent,
+ context_wrapper=context_wrapper,
+ input_guardrail_results=streamed_result.input_guardrail_results,
+ output_guardrail_results=streamed_result.output_guardrail_results,
+ )
+ raise
except Exception as e:
if current_span:
_error_tracing.attach_error_to_span(
diff --git a/src/agents/util/_pretty_print.py b/src/agents/util/_pretty_print.py
index afd3e2b1b..29df3562e 100644
--- a/src/agents/util/_pretty_print.py
+++ b/src/agents/util/_pretty_print.py
@@ -3,6 +3,7 @@
from pydantic import BaseModel
if TYPE_CHECKING:
+ from ..exceptions import RunErrorDetails
from ..result import RunResult, RunResultBase, RunResultStreaming
@@ -38,6 +39,17 @@ def pretty_print_result(result: "RunResult") -> str:
return output
+def pretty_print_run_error_details(result: "RunErrorDetails") -> str:
+ output = "RunErrorDetails:"
+ output += f'\n- Last agent: Agent(name="{result.last_agent.name}", ...)'
+ output += f"\n- {len(result.new_items)} new item(s)"
+ output += f"\n- {len(result.raw_responses)} raw response(s)"
+ output += f"\n- {len(result.input_guardrail_results)} input guardrail result(s)"
+ output += "\n(See `RunErrorDetails` for more details)"
+
+ return output
+
+
def pretty_print_run_result_streaming(result: "RunResultStreaming") -> str:
output = "RunResultStreaming:"
output += f'\n- Current agent: Agent(name="{result.current_agent.name}", ...)'
diff --git a/tests/test_run_error_details.py b/tests/test_run_error_details.py
new file mode 100644
index 000000000..2268b3780
--- /dev/null
+++ b/tests/test_run_error_details.py
@@ -0,0 +1,44 @@
+import json
+
+import pytest
+
+from agents import Agent, MaxTurnsExceeded, RunErrorDetails, Runner
+
+from .fake_model import FakeModel
+from .test_responses import get_function_tool, get_function_tool_call, get_text_message
+
+
+@pytest.mark.asyncio
+async def test_run_error_includes_data():
+ model = FakeModel()
+ agent = Agent(name="test", model=model, tools=[get_function_tool("foo", "res")])
+ model.add_multiple_turn_outputs([
+ [get_text_message("1"), get_function_tool_call("foo", json.dumps({"a": "b"}))],
+ [get_text_message("done")],
+ ])
+ with pytest.raises(MaxTurnsExceeded) as exc:
+ await Runner.run(agent, input="hello", max_turns=1)
+ data = exc.value.run_data
+ assert isinstance(data, RunErrorDetails)
+ assert data.last_agent == agent
+ assert len(data.raw_responses) == 1
+ assert len(data.new_items) > 0
+
+
+@pytest.mark.asyncio
+async def test_streamed_run_error_includes_data():
+ model = FakeModel()
+ agent = Agent(name="test", model=model, tools=[get_function_tool("foo", "res")])
+ model.add_multiple_turn_outputs([
+ [get_text_message("1"), get_function_tool_call("foo", json.dumps({"a": "b"}))],
+ [get_text_message("done")],
+ ])
+ result = Runner.run_streamed(agent, input="hello", max_turns=1)
+ with pytest.raises(MaxTurnsExceeded) as exc:
+ async for _ in result.stream_events():
+ pass
+ data = exc.value.run_data
+ assert isinstance(data, RunErrorDetails)
+ assert data.last_agent == agent
+ assert len(data.raw_responses) == 1
+ assert len(data.new_items) > 0
diff --git a/tests/test_tracing_errors_streamed.py b/tests/test_tracing_errors_streamed.py
index 416793e70..40efef3fa 100644
--- a/tests/test_tracing_errors_streamed.py
+++ b/tests/test_tracing_errors_streamed.py
@@ -168,10 +168,6 @@ async def test_tool_call_error():
"children": [
{
"type": "agent",
- "error": {
- "message": "Error in agent run",
- "data": {"error": "Invalid JSON input for tool foo: bad_json"},
- },
"data": {
"name": "test_agent",
"handoffs": [],
From 47fa8e87b1b1553f1733dd1909b784cedbc98872 Mon Sep 17 00:00:00 2001
From: Sarmad Gulzar <sarmadgulzar@icloud.com>
Date: Fri, 30 May 2025 02:24:31 +0500
Subject: [PATCH 20/68] Fixed Python syntax (#665)
---
docs/tools.md | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/docs/tools.md b/docs/tools.md
index 89e28d998..4e9a20d32 100644
--- a/docs/tools.md
+++ b/docs/tools.md
@@ -270,7 +270,7 @@ The `agent.as_tool` function is a convenience method to make it easy to turn an
```python
@function_tool
async def run_my_agent() -> str:
- """A tool that runs the agent with custom configs".
+ """A tool that runs the agent with custom configs"""
agent = Agent(name="My agent", instructions="...")
From b699d9a5332da6024a31279be2c33f602cf0dba2 Mon Sep 17 00:00:00 2001
From: rob-openai <roberttinn@openai.com>
Date: Fri, 30 May 2025 07:32:25 -0700
Subject: [PATCH 21/68] Small fix for litellm model (#789)
Small fix:
Removing `import litellm.types` as its outside the try except block for
importing litellm so the import error message isn't displayed, and the
line actually isn't needed. I was reproducing a GitHub issue and came
across this in the process.
---
src/agents/extensions/models/litellm_model.py | 1 -
1 file changed, 1 deletion(-)
diff --git a/src/agents/extensions/models/litellm_model.py b/src/agents/extensions/models/litellm_model.py
index 49e2d42d7..14130c5e3 100644
--- a/src/agents/extensions/models/litellm_model.py
+++ b/src/agents/extensions/models/litellm_model.py
@@ -5,7 +5,6 @@
from collections.abc import AsyncIterator
from typing import Any, Literal, cast, overload
-import litellm.types
from openai.types.responses.response_usage import InputTokensDetails, OutputTokensDetails
from agents.exceptions import ModelBehaviorError
From 16fb29c1f040bd9807c3d353c918ccb6a407f550 Mon Sep 17 00:00:00 2001
From: Rehan Ul Haq <mmrhaq@gmail.com>
Date: Fri, 30 May 2025 20:53:15 +0500
Subject: [PATCH 22/68] Fix typo in assertion message for handoff function
(#780)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
### Overview
This PR fixes a typo in the assert statement within the `handoff`
function in `handoffs.py`, changing `'on_input'` to `'on_handoff`' for
accuracy and clarity.
### Changes
- Corrected the word “on_input” to “on_handoff” in the docstring.
### Motivation
Clear and correct documentation improves code readability and reduces
confusion for users and contributors.
### Checklist
- [x] I have reviewed the docstring after making the change.
- [x] No functionality is affected.
- [x] The change follows the repository’s contribution guidelines.
---
src/agents/handoffs.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/src/agents/handoffs.py b/src/agents/handoffs.py
index 686191f3d..50dd417a2 100644
--- a/src/agents/handoffs.py
+++ b/src/agents/handoffs.py
@@ -168,7 +168,7 @@ def handoff(
input_filter: a function that filters the inputs that are passed to the next agent.
"""
assert (on_handoff and input_type) or not (on_handoff and input_type), (
- "You must provide either both on_input and input_type, or neither"
+ "You must provide either both on_handoff and input_type, or neither"
)
type_adapter: TypeAdapter[Any] | None
if input_type is not None:
From 0a28d71ccaa0591dd8cb724b5a6c64e84d67ef95 Mon Sep 17 00:00:00 2001
From: Chang Luo <33987852+luochang212@users.noreply.github.com>
Date: Sat, 31 May 2025 00:11:10 +0800
Subject: [PATCH 23/68] Fix typo: Replace 'two' with 'three' in /docs/mcp.md
(#757)
The documentation in `docs/mcp.md` listed three server types (stdio,
HTTP over SSE, Streamable HTTP) but incorrectly stated "two kinds of
servers" in the heading. This PR fixes the numerical discrepancy.
**Changes:**
- Modified from "two kinds of servers" to "three kinds of servers".
- File: `docs/mcp.md` (line 11).
---
docs/mcp.md | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/docs/mcp.md b/docs/mcp.md
index 2cd0aad9e..76d142029 100644
--- a/docs/mcp.md
+++ b/docs/mcp.md
@@ -8,7 +8,7 @@ The Agents SDK has support for MCP. This enables you to use a wide range of MCP
## MCP servers
-Currently, the MCP spec defines two kinds of servers, based on the transport mechanism they use:
+Currently, the MCP spec defines three kinds of servers, based on the transport mechanism they use:
1. **stdio** servers run as a subprocess of your application. You can think of them as running "locally".
2. **HTTP over SSE** servers run remotely. You connect to them via a URL.
From ad80f788b9a9c37ab76018824073103b88f154d7 Mon Sep 17 00:00:00 2001
From: Venkat Naveen <56882317+venkatnaveen7@users.noreply.github.com>
Date: Fri, 30 May 2025 20:13:57 +0400
Subject: [PATCH 24/68] Update input_guardrails.py (#774)
Changed the function comment as input_guardrails only deals with input
messages
---
examples/agent_patterns/input_guardrails.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/examples/agent_patterns/input_guardrails.py b/examples/agent_patterns/input_guardrails.py
index 154535511..18ab9d2a7 100644
--- a/examples/agent_patterns/input_guardrails.py
+++ b/examples/agent_patterns/input_guardrails.py
@@ -20,7 +20,7 @@
Guardrails are checks that run in parallel to the agent's execution.
They can be used to do things like:
- Check if input messages are off-topic
-- Check that output messages don't violate any policies
+- Check that input messages don't violate any policies
- Take over control of the agent's execution if an unexpected input is detected
In this example, we'll setup an input guardrail that trips if the user is asking to do math homework.
From 64383502dd45ea4f44ee9a014f8f21e5fd88c1cd Mon Sep 17 00:00:00 2001
From: Rehan Ul Haq <mmrhaq@gmail.com>
Date: Fri, 30 May 2025 21:14:10 +0500
Subject: [PATCH 25/68] docs: fix typo in docstring for is_strict_json_schema
method (#775)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
### Overview
This PR fixes a small typo in the docstring of the
`is_strict_json_schema` abstract method of the `AgentOutputSchemaBase`
class in `agent_output.py`.
### Changes
- Corrected the word “valis” to “valid” in the docstring.
### Motivation
Clear and correct documentation improves code readability and reduces
confusion for users and contributors.
### Checklist
- [x] I have reviewed the docstring after making the change.
- [x] No functionality is affected.
- [x] The change follows the repository’s contribution guidelines.
---
src/agents/agent_output.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/src/agents/agent_output.py b/src/agents/agent_output.py
index 066bbd835..ee14956e3 100644
--- a/src/agents/agent_output.py
+++ b/src/agents/agent_output.py
@@ -38,7 +38,7 @@ def json_schema(self) -> dict[str, Any]:
@abc.abstractmethod
def is_strict_json_schema(self) -> bool:
"""Whether the JSON schema is in strict mode. Strict mode constrains the JSON schema
- features, but guarantees valis JSON. See here for details:
+ features, but guarantees valid JSON. See here for details:
https://platform.openai.com/docs/guides/structured-outputs#supported-schemas
"""
pass
From cfe9099f3f30607c92e3e7fd62d59990c0642e70 Mon Sep 17 00:00:00 2001
From: Rohan Mehta <rm@openai.com>
Date: Fri, 30 May 2025 14:41:54 -0400
Subject: [PATCH 26/68] Add comment to handoff_occured misspelling (#792)
People keep trying to fix this, but its a breaking change.
---
src/agents/stream_events.py | 1 +
1 file changed, 1 insertion(+)
diff --git a/src/agents/stream_events.py b/src/agents/stream_events.py
index 111d0b951..a271e8acd 100644
--- a/src/agents/stream_events.py
+++ b/src/agents/stream_events.py
@@ -31,6 +31,7 @@ class RunItemStreamEvent:
name: Literal[
"message_output_created",
"handoff_requested",
+ # This is misspelled, but we can't change it because that would be a breaking change
"handoff_occured",
"tool_called",
"tool_output",
From 3e7b2863e9486146586cd382d383013a7e93c40e Mon Sep 17 00:00:00 2001
From: Kazuhiro Sera <seratch@openai.com>
Date: Tue, 3 Jun 2025 00:10:07 +0900
Subject: [PATCH 27/68] Fix #777 by handling MCPCall events in RunImpl (#799)
This pull request resolves #777; If you think we should introduce a new
item type for MCP call output, please let me know. As other hosted tools
use this event, I believe using the same should be good to go tho.
---
examples/hosted_mcp/approvals.py | 2 +-
examples/hosted_mcp/simple.py | 2 +-
src/agents/_run_impl.py | 4 ++++
3 files changed, 6 insertions(+), 2 deletions(-)
diff --git a/examples/hosted_mcp/approvals.py b/examples/hosted_mcp/approvals.py
index 2cabb3ee2..3080a1d63 100644
--- a/examples/hosted_mcp/approvals.py
+++ b/examples/hosted_mcp/approvals.py
@@ -48,7 +48,7 @@ async def main(verbose: bool, stream: bool):
print(res.final_output)
if verbose:
- for item in result.new_items:
+ for item in res.new_items:
print(item)
diff --git a/examples/hosted_mcp/simple.py b/examples/hosted_mcp/simple.py
index 508c3a7ae..895fdfbe0 100644
--- a/examples/hosted_mcp/simple.py
+++ b/examples/hosted_mcp/simple.py
@@ -34,7 +34,7 @@ async def main(verbose: bool, stream: bool):
# The repository is primarily written in multiple languages, including Rust and TypeScript...
if verbose:
- for item in result.new_items:
+ for item in res.new_items:
print(item)
diff --git a/src/agents/_run_impl.py b/src/agents/_run_impl.py
index 2cfa270e0..e98010555 100644
--- a/src/agents/_run_impl.py
+++ b/src/agents/_run_impl.py
@@ -33,6 +33,7 @@
ImageGenerationCall,
LocalShellCall,
McpApprovalRequest,
+ McpCall,
McpListTools,
)
from openai.types.responses.response_reasoning_item import ResponseReasoningItem
@@ -456,6 +457,9 @@ def process_model_response(
)
elif isinstance(output, McpListTools):
items.append(MCPListToolsItem(raw_item=output, agent=agent))
+ elif isinstance(output, McpCall):
+ items.append(ToolCallItem(raw_item=output, agent=agent))
+ tools_used.append("mcp")
elif isinstance(output, ImageGenerationCall):
items.append(ToolCallItem(raw_item=output, agent=agent))
tools_used.append("image_generation")
From 775d3e237efd4686bb98aca11ac96c0488ac1fd8 Mon Sep 17 00:00:00 2001
From: westhood <westhoods@gmail.com>
Date: Mon, 2 Jun 2025 23:10:21 +0800
Subject: [PATCH 28/68] Ensure item.model_dump only contains JSON serializable
types (#801)
The EmbeddedResource from MCP tool call contains a field with type
AnyUrl that is not JSON-serializable. To avoid this exception, use
item.model_dump(mode="json") to ensure a JSON-serializable return value.
---
src/agents/mcp/util.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/src/agents/mcp/util.py b/src/agents/mcp/util.py
index bbfe1885c..5a963bc01 100644
--- a/src/agents/mcp/util.py
+++ b/src/agents/mcp/util.py
@@ -116,7 +116,7 @@ async def invoke_mcp_tool(
if len(result.content) == 1:
tool_output = result.content[0].model_dump_json()
elif len(result.content) > 1:
- tool_output = json.dumps([item.model_dump() for item in result.content])
+ tool_output = json.dumps([item.model_dump(mode="json") for item in result.content])
else:
logger.error(f"Errored MCP tool result: {result}")
tool_output = "Error running tool."
From d4c7a23e1dc49d5f060276e6afcd815418266ffd Mon Sep 17 00:00:00 2001
From: Rohan Mehta <rm@openai.com>
Date: Mon, 2 Jun 2025 14:49:16 -0400
Subject: [PATCH 29/68] Don't cache agent tools during a run (#803)
### Summary:
Towards #767. We were caching the list of tools for an agent, so if you
did `agent.tools.append(...)` from a tool call, the next call to the
model wouldn't include the new tool. THis is a bug.
### Test Plan:
Unit tests. Note that now MCP tools are listed each time the agent runs
(users can still cache the `list_tools` however).
---
src/agents/exceptions.py | 2 +
src/agents/extensions/models/litellm_model.py | 6 +-
src/agents/mcp/server.py | 10 ++--
src/agents/result.py | 1 -
src/agents/run.py | 15 ++---
src/agents/voice/model.py | 2 +
tests/mcp/test_mcp_tracing.py | 60 ++++++++++++-------
tests/models/test_litellm_extra_body.py | 3 +-
tests/test_agent_runner.py | 35 +++++++++++
tests/test_agent_runner_streamed.py | 37 ++++++++++++
tests/test_run_error_details.py | 20 ++++---
11 files changed, 143 insertions(+), 48 deletions(-)
diff --git a/src/agents/exceptions.py b/src/agents/exceptions.py
index 4f6e2e768..c00024c2e 100644
--- a/src/agents/exceptions.py
+++ b/src/agents/exceptions.py
@@ -15,6 +15,7 @@
@dataclass
class RunErrorDetails:
"""Data collected from an agent run when an exception occurs."""
+
input: str | list[TResponseInputItem]
new_items: list[RunItem]
raw_responses: list[ModelResponse]
@@ -29,6 +30,7 @@ def __str__(self) -> str:
class AgentsException(Exception):
"""Base class for all exceptions in the Agents SDK."""
+
run_data: RunErrorDetails | None
def __init__(self, *args: object) -> None:
diff --git a/src/agents/extensions/models/litellm_model.py b/src/agents/extensions/models/litellm_model.py
index 14130c5e3..7cf7a2de5 100644
--- a/src/agents/extensions/models/litellm_model.py
+++ b/src/agents/extensions/models/litellm_model.py
@@ -110,12 +110,14 @@ async def get_response(
input_tokens_details=InputTokensDetails(
cached_tokens=getattr(
response_usage.prompt_tokens_details, "cached_tokens", 0
- ) or 0
+ )
+ or 0
),
output_tokens_details=OutputTokensDetails(
reasoning_tokens=getattr(
response_usage.completion_tokens_details, "reasoning_tokens", 0
- ) or 0
+ )
+ or 0
),
)
if response.usage
diff --git a/src/agents/mcp/server.py b/src/agents/mcp/server.py
index 414b517ab..b012a0968 100644
--- a/src/agents/mcp/server.py
+++ b/src/agents/mcp/server.py
@@ -88,7 +88,7 @@ def create_streams(
tuple[
MemoryObjectReceiveStream[SessionMessage | Exception],
MemoryObjectSendStream[SessionMessage],
- GetSessionIdCallback | None
+ GetSessionIdCallback | None,
]
]:
"""Create the streams for the server."""
@@ -243,7 +243,7 @@ def create_streams(
tuple[
MemoryObjectReceiveStream[SessionMessage | Exception],
MemoryObjectSendStream[SessionMessage],
- GetSessionIdCallback | None
+ GetSessionIdCallback | None,
]
]:
"""Create the streams for the server."""
@@ -314,7 +314,7 @@ def create_streams(
tuple[
MemoryObjectReceiveStream[SessionMessage | Exception],
MemoryObjectSendStream[SessionMessage],
- GetSessionIdCallback | None
+ GetSessionIdCallback | None,
]
]:
"""Create the streams for the server."""
@@ -394,7 +394,7 @@ def create_streams(
tuple[
MemoryObjectReceiveStream[SessionMessage | Exception],
MemoryObjectSendStream[SessionMessage],
- GetSessionIdCallback | None
+ GetSessionIdCallback | None,
]
]:
"""Create the streams for the server."""
@@ -403,7 +403,7 @@ def create_streams(
headers=self.params.get("headers", None),
timeout=self.params.get("timeout", timedelta(seconds=30)),
sse_read_timeout=self.params.get("sse_read_timeout", timedelta(seconds=60 * 5)),
- terminate_on_close=self.params.get("terminate_on_close", True)
+ terminate_on_close=self.params.get("terminate_on_close", True),
)
@property
diff --git a/src/agents/result.py b/src/agents/result.py
index 764815246..5cf0e74c8 100644
--- a/src/agents/result.py
+++ b/src/agents/result.py
@@ -274,4 +274,3 @@ def _cleanup_tasks(self):
def __str__(self) -> str:
return pretty_print_run_result_streaming(self)
-
diff --git a/src/agents/run.py b/src/agents/run.py
index c67386495..bfbdacd45 100644
--- a/src/agents/run.py
+++ b/src/agents/run.py
@@ -1,4 +1,3 @@
-
from __future__ import annotations
import asyncio
@@ -182,6 +181,8 @@ async def run(
try:
while True:
+ all_tools = await cls._get_all_tools(current_agent)
+
# Start an agent span if we don't have one. This span is ended if the current
# agent changes, or if the agent loop ends.
if current_span is None:
@@ -197,8 +198,6 @@ async def run(
output_type=output_type_name,
)
current_span.start(mark_as_current=True)
-
- all_tools = await cls._get_all_tools(current_agent)
current_span.span_data.tools = [t.name for t in all_tools]
current_turn += 1
@@ -210,9 +209,7 @@ async def run(
data={"max_turns": max_turns},
),
)
- raise MaxTurnsExceeded(
- f"Max turns ({max_turns}) exceeded"
- )
+ raise MaxTurnsExceeded(f"Max turns ({max_turns}) exceeded")
logger.debug(
f"Running agent {current_agent.name} (turn {current_turn})",
@@ -295,7 +292,7 @@ async def run(
last_agent=current_agent,
context_wrapper=context_wrapper,
input_guardrail_results=input_guardrail_results,
- output_guardrail_results=[]
+ output_guardrail_results=[],
)
raise
finally:
@@ -528,6 +525,8 @@ async def _run_streamed_impl(
if streamed_result.is_complete:
break
+ all_tools = await cls._get_all_tools(current_agent)
+
# Start an agent span if we don't have one. This span is ended if the current
# agent changes, or if the agent loop ends.
if current_span is None:
@@ -543,8 +542,6 @@ async def _run_streamed_impl(
output_type=output_type_name,
)
current_span.start(mark_as_current=True)
-
- all_tools = await cls._get_all_tools(current_agent)
tool_names = [t.name for t in all_tools]
current_span.span_data.tools = tool_names
current_turn += 1
diff --git a/src/agents/voice/model.py b/src/agents/voice/model.py
index c36a4de76..b048a452d 100644
--- a/src/agents/voice/model.py
+++ b/src/agents/voice/model.py
@@ -17,9 +17,11 @@
TTSVoice = Literal["alloy", "ash", "coral", "echo", "fable", "onyx", "nova", "sage", "shimmer"]
"""Exportable type for the TTSModelSettings voice enum"""
+
@dataclass
class TTSModelSettings:
"""Settings for a TTS model."""
+
voice: TTSVoice | None = None
"""
The voice to use for the TTS model. If not provided, the default voice for the respective model
diff --git a/tests/mcp/test_mcp_tracing.py b/tests/mcp/test_mcp_tracing.py
index b71954b5b..54575dcb5 100644
--- a/tests/mcp/test_mcp_tracing.py
+++ b/tests/mcp/test_mcp_tracing.py
@@ -44,6 +44,10 @@ async def test_mcp_tracing():
{
"workflow_name": "Agent workflow",
"children": [
+ {
+ "type": "mcp_tools",
+ "data": {"server": "fake_mcp_server", "result": ["test_tool_1"]},
+ },
{
"type": "agent",
"data": {
@@ -53,10 +57,6 @@ async def test_mcp_tracing():
"output_type": "str",
},
"children": [
- {
- "type": "mcp_tools",
- "data": {"server": "fake_mcp_server", "result": ["test_tool_1"]},
- },
{
"type": "function",
"data": {
@@ -66,8 +66,12 @@ async def test_mcp_tracing():
"mcp_data": {"server": "fake_mcp_server"},
},
},
+ {
+ "type": "mcp_tools",
+ "data": {"server": "fake_mcp_server", "result": ["test_tool_1"]},
+ },
],
- }
+ },
],
}
]
@@ -100,6 +104,13 @@ async def test_mcp_tracing():
{
"workflow_name": "Agent workflow",
"children": [
+ {
+ "type": "mcp_tools",
+ "data": {
+ "server": "fake_mcp_server",
+ "result": ["test_tool_1", "test_tool_2"],
+ },
+ },
{
"type": "agent",
"data": {
@@ -109,13 +120,6 @@ async def test_mcp_tracing():
"output_type": "str",
},
"children": [
- {
- "type": "mcp_tools",
- "data": {
- "server": "fake_mcp_server",
- "result": ["test_tool_1", "test_tool_2"],
- },
- },
{
"type": "function",
"data": {
@@ -133,8 +137,15 @@ async def test_mcp_tracing():
"mcp_data": {"server": "fake_mcp_server"},
},
},
+ {
+ "type": "mcp_tools",
+ "data": {
+ "server": "fake_mcp_server",
+ "result": ["test_tool_1", "test_tool_2"],
+ },
+ },
],
- }
+ },
],
}
]
@@ -165,6 +176,13 @@ async def test_mcp_tracing():
{
"workflow_name": "Agent workflow",
"children": [
+ {
+ "type": "mcp_tools",
+ "data": {
+ "server": "fake_mcp_server",
+ "result": ["test_tool_1", "test_tool_2", "test_tool_3"],
+ },
+ },
{
"type": "agent",
"data": {
@@ -174,13 +192,6 @@ async def test_mcp_tracing():
"output_type": "str",
},
"children": [
- {
- "type": "mcp_tools",
- "data": {
- "server": "fake_mcp_server",
- "result": ["test_tool_1", "test_tool_2", "test_tool_3"],
- },
- },
{
"type": "function",
"data": {
@@ -190,8 +201,15 @@ async def test_mcp_tracing():
"mcp_data": {"server": "fake_mcp_server"},
},
},
+ {
+ "type": "mcp_tools",
+ "data": {
+ "server": "fake_mcp_server",
+ "result": ["test_tool_1", "test_tool_2", "test_tool_3"],
+ },
+ },
],
- }
+ },
],
}
]
diff --git a/tests/models/test_litellm_extra_body.py b/tests/models/test_litellm_extra_body.py
index ac56c25cf..3c83b0607 100644
--- a/tests/models/test_litellm_extra_body.py
+++ b/tests/models/test_litellm_extra_body.py
@@ -26,8 +26,7 @@ async def fake_acompletion(model, messages=None, **kwargs):
monkeypatch.setattr(litellm, "acompletion", fake_acompletion)
settings = ModelSettings(
- temperature=0.1,
- extra_body={"cached_content": "some_cache", "foo": 123}
+ temperature=0.1, extra_body={"cached_content": "some_cache", "foo": 123}
)
model = LitellmModel(model="test-model")
diff --git a/tests/test_agent_runner.py b/tests/test_agent_runner.py
index 14a278a90..77eb8019e 100644
--- a/tests/test_agent_runner.py
+++ b/tests/test_agent_runner.py
@@ -745,3 +745,38 @@ async def test_previous_response_id_passed_between_runs_streamed_multi_turn():
pass
assert model.last_turn_args.get("previous_response_id") == "resp-stream-test"
+
+
+@pytest.mark.asyncio
+async def test_dynamic_tool_addition_run() -> None:
+ """Test that tools can be added to an agent during a run."""
+ model = FakeModel()
+
+ executed: dict[str, bool] = {"called": False}
+
+ agent = Agent(name="test", model=model, tool_use_behavior="run_llm_again")
+
+ @function_tool(name_override="tool2")
+ def tool2() -> str:
+ executed["called"] = True
+ return "result2"
+
+ @function_tool(name_override="add_tool")
+ async def add_tool() -> str:
+ agent.tools.append(tool2)
+ return "added"
+
+ agent.tools.append(add_tool)
+
+ model.add_multiple_turn_outputs(
+ [
+ [get_function_tool_call("add_tool", json.dumps({}))],
+ [get_function_tool_call("tool2", json.dumps({}))],
+ [get_text_message("done")],
+ ]
+ )
+
+ result = await Runner.run(agent, input="start")
+
+ assert executed["called"] is True
+ assert result.final_output == "done"
diff --git a/tests/test_agent_runner_streamed.py b/tests/test_agent_runner_streamed.py
index 87a76a706..31fe2979b 100644
--- a/tests/test_agent_runner_streamed.py
+++ b/tests/test_agent_runner_streamed.py
@@ -18,6 +18,7 @@
RunContextWrapper,
Runner,
UserError,
+ function_tool,
handoff,
)
from agents.items import RunItem
@@ -684,3 +685,39 @@ async def test_streaming_events():
assert len(agent_data) == 2, "should have 2 agent updated events"
assert agent_data[0].new_agent == agent_2, "should have started with agent_2"
assert agent_data[1].new_agent == agent_1, "should have handed off to agent_1"
+
+
+@pytest.mark.asyncio
+async def test_dynamic_tool_addition_run_streamed() -> None:
+ model = FakeModel()
+
+ executed: dict[str, bool] = {"called": False}
+
+ agent = Agent(name="test", model=model, tool_use_behavior="run_llm_again")
+
+ @function_tool(name_override="tool2")
+ def tool2() -> str:
+ executed["called"] = True
+ return "result2"
+
+ @function_tool(name_override="add_tool")
+ async def add_tool() -> str:
+ agent.tools.append(tool2)
+ return "added"
+
+ agent.tools.append(add_tool)
+
+ model.add_multiple_turn_outputs(
+ [
+ [get_function_tool_call("add_tool", json.dumps({}))],
+ [get_function_tool_call("tool2", json.dumps({}))],
+ [get_text_message("done")],
+ ]
+ )
+
+ result = Runner.run_streamed(agent, input="start")
+ async for _ in result.stream_events():
+ pass
+
+ assert executed["called"] is True
+ assert result.final_output == "done"
diff --git a/tests/test_run_error_details.py b/tests/test_run_error_details.py
index 2268b3780..104b248fc 100644
--- a/tests/test_run_error_details.py
+++ b/tests/test_run_error_details.py
@@ -12,10 +12,12 @@
async def test_run_error_includes_data():
model = FakeModel()
agent = Agent(name="test", model=model, tools=[get_function_tool("foo", "res")])
- model.add_multiple_turn_outputs([
- [get_text_message("1"), get_function_tool_call("foo", json.dumps({"a": "b"}))],
- [get_text_message("done")],
- ])
+ model.add_multiple_turn_outputs(
+ [
+ [get_text_message("1"), get_function_tool_call("foo", json.dumps({"a": "b"}))],
+ [get_text_message("done")],
+ ]
+ )
with pytest.raises(MaxTurnsExceeded) as exc:
await Runner.run(agent, input="hello", max_turns=1)
data = exc.value.run_data
@@ -29,10 +31,12 @@ async def test_run_error_includes_data():
async def test_streamed_run_error_includes_data():
model = FakeModel()
agent = Agent(name="test", model=model, tools=[get_function_tool("foo", "res")])
- model.add_multiple_turn_outputs([
- [get_text_message("1"), get_function_tool_call("foo", json.dumps({"a": "b"}))],
- [get_text_message("done")],
- ])
+ model.add_multiple_turn_outputs(
+ [
+ [get_text_message("1"), get_function_tool_call("foo", json.dumps({"a": "b"}))],
+ [get_text_message("done")],
+ ]
+ )
result = Runner.run_streamed(agent, input="hello", max_turns=1)
with pytest.raises(MaxTurnsExceeded) as exc:
async for _ in result.stream_events():
From 995af4d83e0b0e086ad8f2b11f194fa29d1e27e1 Mon Sep 17 00:00:00 2001
From: Rohan Mehta <rm@openai.com>
Date: Mon, 2 Jun 2025 15:32:02 -0400
Subject: [PATCH 30/68] Only start tracing worker thread on first span/trace
(#804)
Closes #796. Shouldn't start a busy waiting thread if there aren't any
traces.
Test plan
```
import threading
assert threading.active_count() == 1
import agents
assert threading.active_count() == 1
```
---
src/agents/tracing/processors.py | 32 +++++++++++++++++++++++++++++---
1 file changed, 29 insertions(+), 3 deletions(-)
diff --git a/src/agents/tracing/processors.py b/src/agents/tracing/processors.py
index 2913b11a4..73f733125 100644
--- a/src/agents/tracing/processors.py
+++ b/src/agents/tracing/processors.py
@@ -188,10 +188,27 @@ def __init__(
# Track when we next *must* perform a scheduled export
self._next_export_time = time.time() + self._schedule_delay
- self._worker_thread = threading.Thread(target=self._run, daemon=True)
- self._worker_thread.start()
+ # We lazily start the background worker thread the first time a span/trace is queued.
+ self._worker_thread: threading.Thread | None = None
+ self._thread_start_lock = threading.Lock()
+
+ def _ensure_thread_started(self) -> None:
+ # Fast path without holding the lock
+ if self._worker_thread and self._worker_thread.is_alive():
+ return
+
+ # Double-checked locking to avoid starting multiple threads
+ with self._thread_start_lock:
+ if self._worker_thread and self._worker_thread.is_alive():
+ return
+
+ self._worker_thread = threading.Thread(target=self._run, daemon=True)
+ self._worker_thread.start()
def on_trace_start(self, trace: Trace) -> None:
+ # Ensure the background worker is running before we enqueue anything.
+ self._ensure_thread_started()
+
try:
self._queue.put_nowait(trace)
except queue.Full:
@@ -206,6 +223,9 @@ def on_span_start(self, span: Span[Any]) -> None:
pass
def on_span_end(self, span: Span[Any]) -> None:
+ # Ensure the background worker is running before we enqueue anything.
+ self._ensure_thread_started()
+
try:
self._queue.put_nowait(span)
except queue.Full:
@@ -216,7 +236,13 @@ def shutdown(self, timeout: float | None = None):
Called when the application stops. We signal our thread to stop, then join it.
"""
self._shutdown_event.set()
- self._worker_thread.join(timeout=timeout)
+
+ # Only join if we ever started the background thread; otherwise flush synchronously.
+ if self._worker_thread and self._worker_thread.is_alive():
+ self._worker_thread.join(timeout=timeout)
+ else:
+ # No background thread: process any remaining items synchronously.
+ self._export_batches(force=True)
def force_flush(self):
"""
From 4046fcb3fab3d1e298e6a3b3515585b13b384975 Mon Sep 17 00:00:00 2001
From: Rohan Mehta <rm@openai.com>
Date: Tue, 3 Jun 2025 13:44:16 -0400
Subject: [PATCH 31/68] Add is_enabled to FunctionTool (#808)
### Summary:
Allows a user to do `function_tool(is_enabled=<some_callable>)`; the
callable is called when the agent runs.
This allows you to dynamically enable/disable a tool based on the
context/env.
The meta-goal is to allow `Agent` to be effectively immutable. That
enables some nice things down the line, and this allows you to
dynamically modify the tools list without mutating the agent.
### Test Plan:
Unit tests
---
src/agents/agent.py | 22 +++++++++++++---
src/agents/run.py | 10 ++++---
src/agents/tool.py | 17 +++++++++++-
tests/test_function_tool.py | 43 ++++++++++++++++++++++++++++++-
tests/test_run_step_execution.py | 2 +-
tests/test_run_step_processing.py | 32 +++++++++++++----------
6 files changed, 102 insertions(+), 24 deletions(-)
diff --git a/src/agents/agent.py b/src/agents/agent.py
index e22f579fa..6adccedd5 100644
--- a/src/agents/agent.py
+++ b/src/agents/agent.py
@@ -1,5 +1,6 @@
from __future__ import annotations
+import asyncio
import dataclasses
import inspect
from collections.abc import Awaitable
@@ -17,7 +18,7 @@
from .model_settings import ModelSettings
from .models.interface import Model
from .run_context import RunContextWrapper, TContext
-from .tool import FunctionToolResult, Tool, function_tool
+from .tool import FunctionTool, FunctionToolResult, Tool, function_tool
from .util import _transforms
from .util._types import MaybeAwaitable
@@ -246,7 +247,22 @@ async def get_mcp_tools(self) -> list[Tool]:
convert_schemas_to_strict = self.mcp_config.get("convert_schemas_to_strict", False)
return await MCPUtil.get_all_function_tools(self.mcp_servers, convert_schemas_to_strict)
- async def get_all_tools(self) -> list[Tool]:
+ async def get_all_tools(self, run_context: RunContextWrapper[Any]) -> list[Tool]:
"""All agent tools, including MCP tools and function tools."""
mcp_tools = await self.get_mcp_tools()
- return mcp_tools + self.tools
+
+ async def _check_tool_enabled(tool: Tool) -> bool:
+ if not isinstance(tool, FunctionTool):
+ return True
+
+ attr = tool.is_enabled
+ if isinstance(attr, bool):
+ return attr
+ res = attr(run_context, self)
+ if inspect.isawaitable(res):
+ return bool(await res)
+ return bool(res)
+
+ results = await asyncio.gather(*(_check_tool_enabled(t) for t in self.tools))
+ enabled: list[Tool] = [t for t, ok in zip(self.tools, results) if ok]
+ return [*mcp_tools, *enabled]
diff --git a/src/agents/run.py b/src/agents/run.py
index bfbdacd45..f375a0b89 100644
--- a/src/agents/run.py
+++ b/src/agents/run.py
@@ -181,7 +181,7 @@ async def run(
try:
while True:
- all_tools = await cls._get_all_tools(current_agent)
+ all_tools = await cls._get_all_tools(current_agent, context_wrapper)
# Start an agent span if we don't have one. This span is ended if the current
# agent changes, or if the agent loop ends.
@@ -525,7 +525,7 @@ async def _run_streamed_impl(
if streamed_result.is_complete:
break
- all_tools = await cls._get_all_tools(current_agent)
+ all_tools = await cls._get_all_tools(current_agent, context_wrapper)
# Start an agent span if we don't have one. This span is ended if the current
# agent changes, or if the agent loop ends.
@@ -980,8 +980,10 @@ def _get_handoffs(cls, agent: Agent[Any]) -> list[Handoff]:
return handoffs
@classmethod
- async def _get_all_tools(cls, agent: Agent[Any]) -> list[Tool]:
- return await agent.get_all_tools()
+ async def _get_all_tools(
+ cls, agent: Agent[Any], context_wrapper: RunContextWrapper[Any]
+ ) -> list[Tool]:
+ return await agent.get_all_tools(context_wrapper)
@classmethod
def _get_model(cls, agent: Agent[Any], run_config: RunConfig) -> Model:
diff --git a/src/agents/tool.py b/src/agents/tool.py
index fd5a21c89..57272f9f4 100644
--- a/src/agents/tool.py
+++ b/src/agents/tool.py
@@ -4,7 +4,7 @@
import json
from collections.abc import Awaitable
from dataclasses import dataclass
-from typing import Any, Callable, Literal, Union, overload
+from typing import TYPE_CHECKING, Any, Callable, Literal, Union, overload
from openai.types.responses.file_search_tool_param import Filters, RankingOptions
from openai.types.responses.response_output_item import LocalShellCall, McpApprovalRequest
@@ -24,6 +24,9 @@
from .util import _error_tracing
from .util._types import MaybeAwaitable
+if TYPE_CHECKING:
+ from .agent import Agent
+
ToolParams = ParamSpec("ToolParams")
ToolFunctionWithoutContext = Callable[ToolParams, Any]
@@ -74,6 +77,11 @@ class FunctionTool:
"""Whether the JSON schema is in strict mode. We **strongly** recommend setting this to True,
as it increases the likelihood of correct JSON input."""
+ is_enabled: bool | Callable[[RunContextWrapper[Any], Agent[Any]], MaybeAwaitable[bool]] = True
+ """Whether the tool is enabled. Either a bool or a Callable that takes the run context and agent
+ and returns whether the tool is enabled. You can use this to dynamically enable/disable a tool
+ based on your context/state."""
+
@dataclass
class FileSearchTool:
@@ -262,6 +270,7 @@ def function_tool(
use_docstring_info: bool = True,
failure_error_function: ToolErrorFunction | None = None,
strict_mode: bool = True,
+ is_enabled: bool | Callable[[RunContextWrapper[Any], Agent[Any]], MaybeAwaitable[bool]] = True,
) -> FunctionTool:
"""Overload for usage as @function_tool (no parentheses)."""
...
@@ -276,6 +285,7 @@ def function_tool(
use_docstring_info: bool = True,
failure_error_function: ToolErrorFunction | None = None,
strict_mode: bool = True,
+ is_enabled: bool | Callable[[RunContextWrapper[Any], Agent[Any]], MaybeAwaitable[bool]] = True,
) -> Callable[[ToolFunction[...]], FunctionTool]:
"""Overload for usage as @function_tool(...)."""
...
@@ -290,6 +300,7 @@ def function_tool(
use_docstring_info: bool = True,
failure_error_function: ToolErrorFunction | None = default_tool_error_function,
strict_mode: bool = True,
+ is_enabled: bool | Callable[[RunContextWrapper[Any], Agent[Any]], MaybeAwaitable[bool]] = True,
) -> FunctionTool | Callable[[ToolFunction[...]], FunctionTool]:
"""
Decorator to create a FunctionTool from a function. By default, we will:
@@ -318,6 +329,9 @@ def function_tool(
If False, it allows non-strict JSON schemas. For example, if a parameter has a default
value, it will be optional, additional properties are allowed, etc. See here for more:
https://platform.openai.com/docs/guides/structured-outputs?api-mode=responses#supported-schemas
+ is_enabled: Whether the tool is enabled. Can be a bool or a callable that takes the run
+ context and agent and returns whether the tool is enabled. Disabled tools are hidden
+ from the LLM at runtime.
"""
def _create_function_tool(the_func: ToolFunction[...]) -> FunctionTool:
@@ -407,6 +421,7 @@ async def _on_invoke_tool(ctx: RunContextWrapper[Any], input: str) -> Any:
params_json_schema=schema.params_json_schema,
on_invoke_tool=_on_invoke_tool,
strict_json_schema=strict_mode,
+ is_enabled=is_enabled,
)
# If func is actually a callable, we were used as @function_tool with no parentheses
diff --git a/tests/test_function_tool.py b/tests/test_function_tool.py
index 0a57aea87..c5d7da649 100644
--- a/tests/test_function_tool.py
+++ b/tests/test_function_tool.py
@@ -5,7 +5,7 @@
from pydantic import BaseModel
from typing_extensions import TypedDict
-from agents import FunctionTool, ModelBehaviorError, RunContextWrapper, function_tool
+from agents import Agent, FunctionTool, ModelBehaviorError, RunContextWrapper, function_tool
from agents.tool import default_tool_error_function
@@ -255,3 +255,44 @@ def custom_sync_error_function(ctx: RunContextWrapper[Any], error: Exception) ->
result = await tool.on_invoke_tool(ctx, '{"a": 1, "b": 2}')
assert result == "error_ValueError"
+
+
+class BoolCtx(BaseModel):
+ enable_tools: bool
+
+
+@pytest.mark.asyncio
+async def test_is_enabled_bool_and_callable():
+ @function_tool(is_enabled=False)
+ def disabled_tool():
+ return "nope"
+
+ async def cond_enabled(ctx: RunContextWrapper[BoolCtx], agent: Agent[Any]) -> bool:
+ return ctx.context.enable_tools
+
+ @function_tool(is_enabled=cond_enabled)
+ def another_tool():
+ return "hi"
+
+ async def third_tool_on_invoke_tool(ctx: RunContextWrapper[Any], args: str) -> str:
+ return "third"
+
+ third_tool = FunctionTool(
+ name="third_tool",
+ description="third tool",
+ on_invoke_tool=third_tool_on_invoke_tool,
+ is_enabled=lambda ctx, agent: ctx.context.enable_tools,
+ params_json_schema={},
+ )
+
+ agent = Agent(name="t", tools=[disabled_tool, another_tool, third_tool])
+ context_1 = RunContextWrapper(BoolCtx(enable_tools=False))
+ context_2 = RunContextWrapper(BoolCtx(enable_tools=True))
+
+ tools_with_ctx = await agent.get_all_tools(context_1)
+ assert tools_with_ctx == []
+
+ tools_with_ctx = await agent.get_all_tools(context_2)
+ assert len(tools_with_ctx) == 2
+ assert tools_with_ctx[0].name == "another_tool"
+ assert tools_with_ctx[1].name == "third_tool"
diff --git a/tests/test_run_step_execution.py b/tests/test_run_step_execution.py
index 6ae25fbd5..b4c83d015 100644
--- a/tests/test_run_step_execution.py
+++ b/tests/test_run_step_execution.py
@@ -290,7 +290,7 @@ async def get_execute_result(
processed_response = RunImpl.process_model_response(
agent=agent,
- all_tools=await agent.get_all_tools(),
+ all_tools=await agent.get_all_tools(context_wrapper or RunContextWrapper(None)),
response=response,
output_schema=output_schema,
handoffs=handoffs,
diff --git a/tests/test_run_step_processing.py b/tests/test_run_step_processing.py
index 2ea98f06a..3cc1231c1 100644
--- a/tests/test_run_step_processing.py
+++ b/tests/test_run_step_processing.py
@@ -34,6 +34,10 @@
)
+def _dummy_ctx() -> RunContextWrapper[None]:
+ return RunContextWrapper(context=None)
+
+
def test_empty_response():
agent = Agent(name="test")
response = ModelResponse(
@@ -83,7 +87,7 @@ async def test_single_tool_call():
response=response,
output_schema=None,
handoffs=[],
- all_tools=await agent.get_all_tools(),
+ all_tools=await agent.get_all_tools(_dummy_ctx()),
)
assert not result.handoffs
assert result.functions and len(result.functions) == 1
@@ -111,7 +115,7 @@ async def test_missing_tool_call_raises_error():
response=response,
output_schema=None,
handoffs=[],
- all_tools=await agent.get_all_tools(),
+ all_tools=await agent.get_all_tools(_dummy_ctx()),
)
@@ -140,7 +144,7 @@ async def test_multiple_tool_calls():
response=response,
output_schema=None,
handoffs=[],
- all_tools=await agent.get_all_tools(),
+ all_tools=await agent.get_all_tools(_dummy_ctx()),
)
assert not result.handoffs
assert result.functions and len(result.functions) == 2
@@ -169,7 +173,7 @@ async def test_handoffs_parsed_correctly():
response=response,
output_schema=None,
handoffs=[],
- all_tools=await agent_3.get_all_tools(),
+ all_tools=await agent_3.get_all_tools(_dummy_ctx()),
)
assert not result.handoffs, "Shouldn't have a handoff here"
@@ -183,7 +187,7 @@ async def test_handoffs_parsed_correctly():
response=response,
output_schema=None,
handoffs=Runner._get_handoffs(agent_3),
- all_tools=await agent_3.get_all_tools(),
+ all_tools=await agent_3.get_all_tools(_dummy_ctx()),
)
assert len(result.handoffs) == 1, "Should have a handoff here"
handoff = result.handoffs[0]
@@ -213,7 +217,7 @@ async def test_missing_handoff_fails():
response=response,
output_schema=None,
handoffs=Runner._get_handoffs(agent_3),
- all_tools=await agent_3.get_all_tools(),
+ all_tools=await agent_3.get_all_tools(_dummy_ctx()),
)
@@ -236,7 +240,7 @@ async def test_multiple_handoffs_doesnt_error():
response=response,
output_schema=None,
handoffs=Runner._get_handoffs(agent_3),
- all_tools=await agent_3.get_all_tools(),
+ all_tools=await agent_3.get_all_tools(_dummy_ctx()),
)
assert len(result.handoffs) == 2, "Should have multiple handoffs here"
@@ -262,7 +266,7 @@ async def test_final_output_parsed_correctly():
response=response,
output_schema=Runner._get_output_schema(agent),
handoffs=[],
- all_tools=await agent.get_all_tools(),
+ all_tools=await agent.get_all_tools(_dummy_ctx()),
)
@@ -288,7 +292,7 @@ async def test_file_search_tool_call_parsed_correctly():
response=response,
output_schema=None,
handoffs=[],
- all_tools=await agent.get_all_tools(),
+ all_tools=await agent.get_all_tools(_dummy_ctx()),
)
# The final item should be a ToolCallItem for the file search call
assert any(
@@ -313,7 +317,7 @@ async def test_function_web_search_tool_call_parsed_correctly():
response=response,
output_schema=None,
handoffs=[],
- all_tools=await agent.get_all_tools(),
+ all_tools=await agent.get_all_tools(_dummy_ctx()),
)
assert any(
isinstance(item, ToolCallItem) and item.raw_item is web_search_call
@@ -340,7 +344,7 @@ async def test_reasoning_item_parsed_correctly():
response=response,
output_schema=None,
handoffs=[],
- all_tools=await Agent(name="test").get_all_tools(),
+ all_tools=await Agent(name="test").get_all_tools(_dummy_ctx()),
)
assert any(
isinstance(item, ReasoningItem) and item.raw_item is reasoning for item in result.new_items
@@ -409,7 +413,7 @@ async def test_computer_tool_call_without_computer_tool_raises_error():
response=response,
output_schema=None,
handoffs=[],
- all_tools=await Agent(name="test").get_all_tools(),
+ all_tools=await Agent(name="test").get_all_tools(_dummy_ctx()),
)
@@ -437,7 +441,7 @@ async def test_computer_tool_call_with_computer_tool_parsed_correctly():
response=response,
output_schema=None,
handoffs=[],
- all_tools=await agent.get_all_tools(),
+ all_tools=await agent.get_all_tools(_dummy_ctx()),
)
assert any(
isinstance(item, ToolCallItem) and item.raw_item is computer_call
@@ -468,7 +472,7 @@ async def test_tool_and_handoff_parsed_correctly():
response=response,
output_schema=None,
handoffs=Runner._get_handoffs(agent_3),
- all_tools=await agent_3.get_all_tools(),
+ all_tools=await agent_3.get_all_tools(_dummy_ctx()),
)
assert result.functions and len(result.functions) == 1
assert len(result.handoffs) == 1, "Should have a handoff here"
From 204bec1b8b183d6164381f22803171349b2edef0 Mon Sep 17 00:00:00 2001
From: Rohan Mehta <rm@openai.com>
Date: Tue, 3 Jun 2025 22:36:51 -0400
Subject: [PATCH 32/68] v0.0.17 (#809)
bump version
---
pyproject.toml | 2 +-
uv.lock | 2 +-
2 files changed, 2 insertions(+), 2 deletions(-)
diff --git a/pyproject.toml b/pyproject.toml
index 38a2f2b64..b59073ed8 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
[project]
name = "openai-agents"
-version = "0.0.16"
+version = "0.0.17"
description = "OpenAI Agents SDK"
readme = "README.md"
requires-python = ">=3.9"
diff --git a/uv.lock b/uv.lock
index 6f2f3f843..1779b8637 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1480,7 +1480,7 @@ wheels = [
[[package]]
name = "openai-agents"
-version = "0.0.16"
+version = "0.0.17"
source = { editable = "." }
dependencies = [
{ name = "griffe" },
From 4a529e6c167ce2f25d7d19f18edc6dfcef59aca8 Mon Sep 17 00:00:00 2001
From: Rohan Mehta <rm@openai.com>
Date: Wed, 4 Jun 2025 11:53:17 -0400
Subject: [PATCH 33/68] Add REPL run_demo_loop helper (#811)
---
docs/ja/repl.md | 22 ++++++++++++++
docs/ref/repl.md | 6 ++++
docs/repl.md | 19 ++++++++++++
mkdocs.yml | 3 ++
src/agents/__init__.py | 2 ++
src/agents/repl.py | 65 ++++++++++++++++++++++++++++++++++++++++++
tests/test_repl.py | 28 ++++++++++++++++++
7 files changed, 145 insertions(+)
create mode 100644 docs/ja/repl.md
create mode 100644 docs/ref/repl.md
create mode 100644 docs/repl.md
create mode 100644 src/agents/repl.py
create mode 100644 tests/test_repl.py
diff --git a/docs/ja/repl.md b/docs/ja/repl.md
new file mode 100644
index 000000000..108c12b90
--- /dev/null
+++ b/docs/ja/repl.md
@@ -0,0 +1,22 @@
+---
+search:
+ exclude: true
+---
+# REPL ユーティリティ
+
+`run_demo_loop` を使うと、ターミナルから手軽にエージェントを試せます。
+
+```python
+import asyncio
+from agents import Agent, run_demo_loop
+
+async def main() -> None:
+ agent = Agent(name="Assistant", instructions="あなたは親切なアシスタントです")
+ await run_demo_loop(agent)
+
+if __name__ == "__main__":
+ asyncio.run(main())
+```
+
+`run_demo_loop` は入力を繰り返し受け取り、会話履歴を保持したままエージェントを実行します。既定ではストリーミング出力を表示します。
+`quit` または `exit` と入力するか `Ctrl-D` を押すと終了します。
diff --git a/docs/ref/repl.md b/docs/ref/repl.md
new file mode 100644
index 000000000..a064a9bff
--- /dev/null
+++ b/docs/ref/repl.md
@@ -0,0 +1,6 @@
+# `repl`
+
+::: agents.repl
+ options:
+ members:
+ - run_demo_loop
diff --git a/docs/repl.md b/docs/repl.md
new file mode 100644
index 000000000..073b87f51
--- /dev/null
+++ b/docs/repl.md
@@ -0,0 +1,19 @@
+# REPL utility
+
+The SDK provides `run_demo_loop` for quick interactive testing.
+
+```python
+import asyncio
+from agents import Agent, run_demo_loop
+
+async def main() -> None:
+ agent = Agent(name="Assistant", instructions="You are a helpful assistant.")
+ await run_demo_loop(agent)
+
+if __name__ == "__main__":
+ asyncio.run(main())
+```
+
+`run_demo_loop` prompts for user input in a loop, keeping the conversation
+history between turns. By default it streams model output as it is produced.
+Type `quit` or `exit` (or press `Ctrl-D`) to leave the loop.
diff --git a/mkdocs.yml b/mkdocs.yml
index ad719670c..a58258a93 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -59,6 +59,7 @@ plugins:
- running_agents.md
- results.md
- streaming.md
+ - repl.md
- tools.md
- mcp.md
- handoffs.md
@@ -80,6 +81,7 @@ plugins:
- ref/index.md
- ref/agent.md
- ref/run.md
+ - ref/repl.md
- ref/tool.md
- ref/result.md
- ref/stream_events.md
@@ -139,6 +141,7 @@ plugins:
- running_agents.md
- results.md
- streaming.md
+ - repl.md
- tools.md
- mcp.md
- handoffs.md
diff --git a/src/agents/__init__.py b/src/agents/__init__.py
index 820616437..ee2f2aa16 100644
--- a/src/agents/__init__.py
+++ b/src/agents/__init__.py
@@ -45,6 +45,7 @@
from .models.openai_chatcompletions import OpenAIChatCompletionsModel
from .models.openai_provider import OpenAIProvider
from .models.openai_responses import OpenAIResponsesModel
+from .repl import run_demo_loop
from .result import RunResult, RunResultStreaming
from .run import RunConfig, Runner
from .run_context import RunContextWrapper, TContext
@@ -160,6 +161,7 @@ def enable_verbose_stdout_logging():
"ToolsToFinalOutputFunction",
"ToolsToFinalOutputResult",
"Runner",
+ "run_demo_loop",
"Model",
"ModelProvider",
"ModelTracing",
diff --git a/src/agents/repl.py b/src/agents/repl.py
new file mode 100644
index 000000000..9a4f30759
--- /dev/null
+++ b/src/agents/repl.py
@@ -0,0 +1,65 @@
+from __future__ import annotations
+
+from typing import Any
+
+from openai.types.responses.response_text_delta_event import ResponseTextDeltaEvent
+
+from .agent import Agent
+from .items import ItemHelpers, TResponseInputItem
+from .result import RunResultBase
+from .run import Runner
+from .stream_events import AgentUpdatedStreamEvent, RawResponsesStreamEvent, RunItemStreamEvent
+
+
+async def run_demo_loop(agent: Agent[Any], *, stream: bool = True) -> None:
+ """Run a simple REPL loop with the given agent.
+
+ This utility allows quick manual testing and debugging of an agent from the
+ command line. Conversation state is preserved across turns. Enter ``exit``
+ or ``quit`` to stop the loop.
+
+ Args:
+ agent: The starting agent to run.
+ stream: Whether to stream the agent output.
+ """
+
+ current_agent = agent
+ input_items: list[TResponseInputItem] = []
+ while True:
+ try:
+ user_input = input(" > ")
+ except (EOFError, KeyboardInterrupt):
+ print()
+ break
+ if user_input.strip().lower() in {"exit", "quit"}:
+ break
+ if not user_input:
+ continue
+
+ input_items.append({"role": "user", "content": user_input})
+
+ result: RunResultBase
+ if stream:
+ result = Runner.run_streamed(current_agent, input=input_items)
+ async for event in result.stream_events():
+ if isinstance(event, RawResponsesStreamEvent):
+ if isinstance(event.data, ResponseTextDeltaEvent):
+ print(event.data.delta, end="", flush=True)
+ elif isinstance(event, RunItemStreamEvent):
+ if event.item.type == "tool_call_item":
+ print("\n[tool called]", flush=True)
+ elif event.item.type == "tool_call_output_item":
+ print(f"\n[tool output: {event.item.output}]", flush=True)
+ elif event.item.type == "message_output_item":
+ message = ItemHelpers.text_message_output(event.item)
+ print(message, end="", flush=True)
+ elif isinstance(event, AgentUpdatedStreamEvent):
+ print(f"\n[Agent updated: {event.new_agent.name}]", flush=True)
+ print()
+ else:
+ result = await Runner.run(current_agent, input_items)
+ if result.final_output is not None:
+ print(result.final_output)
+
+ current_agent = result.last_agent
+ input_items = result.to_input_list()
diff --git a/tests/test_repl.py b/tests/test_repl.py
new file mode 100644
index 000000000..7ba2011be
--- /dev/null
+++ b/tests/test_repl.py
@@ -0,0 +1,28 @@
+import pytest
+
+from agents import Agent, run_demo_loop
+
+from .fake_model import FakeModel
+from .test_responses import get_text_input_item, get_text_message
+
+
+@pytest.mark.asyncio
+async def test_run_demo_loop_conversation(monkeypatch, capsys):
+ model = FakeModel()
+ model.add_multiple_turn_outputs([[get_text_message("hello")], [get_text_message("good")]])
+
+ agent = Agent(name="test", model=model)
+
+ inputs = iter(["Hi", "How are you?", "quit"])
+ monkeypatch.setattr("builtins.input", lambda _=" > ": next(inputs))
+
+ await run_demo_loop(agent, stream=False)
+
+ output = capsys.readouterr().out
+ assert "hello" in output
+ assert "good" in output
+ assert model.last_turn_args["input"] == [
+ get_text_input_item("Hi"),
+ get_text_message("hello").model_dump(exclude_unset=True),
+ get_text_input_item("How are you?"),
+ ]
From 05db7a68cd779ff0af0a91e190b6b9010b24f6a6 Mon Sep 17 00:00:00 2001
From: Rohan Mehta <rm@openai.com>
Date: Wed, 4 Jun 2025 15:37:09 -0400
Subject: [PATCH 34/68] Crosslink to js/ts (#815)
---
README.md | 3 +++
1 file changed, 3 insertions(+)
diff --git a/README.md b/README.md
index 7dcd97b33..785177916 100644
--- a/README.md
+++ b/README.md
@@ -4,6 +4,9 @@ The OpenAI Agents SDK is a lightweight yet powerful framework for building multi
<img src="https://cdn.openai.com/API/docs/images/orchestration.png" alt="Image of the Agents Tracing UI" style="max-height: 803px;">
+> [!NOTE]
+> Looking for the JavaScript/TypeScript version? Check out [Agents SDK JS/TS](https://github.com/openai/openai-agents-js).
+
### Core concepts:
1. [**Agents**](https://openai.github.io/openai-agents-python/agents): LLMs configured with instructions, tools, guardrails, and handoffs
From 5c7c678aeffbaf33c5114460fb481a5584e58d20 Mon Sep 17 00:00:00 2001
From: Rohan Mehta <rm@openai.com>
Date: Wed, 4 Jun 2025 16:57:19 -0400
Subject: [PATCH 35/68] Add release documentation (#814)
## Summary
- describe semantic versioning and release steps
- add release page to documentation nav
## Testing
- `make format`
- `make lint`
- `make mypy`
- `make tests`
- `make build-docs`
------
https://chatgpt.com/codex/tasks/task_i_68409d25afdc83218ad362d10c8a80a1
---
docs/release.md | 18 ++++++++++++++++++
mkdocs.yml | 1 +
2 files changed, 19 insertions(+)
create mode 100644 docs/release.md
diff --git a/docs/release.md b/docs/release.md
new file mode 100644
index 000000000..3bfc6e9b8
--- /dev/null
+++ b/docs/release.md
@@ -0,0 +1,18 @@
+# Release process
+
+The project follows a slightly modified version of semantic versioning using the form `0.Y.Z`. The leading `0` indicates the SDK is still evolving rapidly. Increment the components as follows:
+
+## Minor (`Y`) versions
+
+We will increase minor versions `Y` for **breaking changes** to any public interfaces that are not marked as beta. For example, going from `0.0.x` to `0.1.x` might include breaking changes.
+
+If you don't want breaking changes, we recommend pinning to `0.0.x` versions in your project.
+
+## Patch (`Z`) versions
+
+We will increment `Z` for non-breaking changes:
+
+- Bug fixes
+- New features
+- Changes to private interfaces
+- Updates to beta features
diff --git a/mkdocs.yml b/mkdocs.yml
index a58258a93..b79e6454f 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -72,6 +72,7 @@ plugins:
- models/litellm.md
- config.md
- visualization.md
+ - release.md
- Voice agents:
- voice/quickstart.md
- voice/pipeline.md
From c98e234845949865a90e3a0338580e49e9b4b75b Mon Sep 17 00:00:00 2001
From: James Hills <70035505+jhills20@users.noreply.github.com>
Date: Mon, 9 Jun 2025 07:13:43 -0700
Subject: [PATCH 36/68] Fix handoff transfer message JSON (#818)
## Summary
- ensure `Handoff.get_transfer_message` emits valid JSON
- test transfer message validity
## Testing
- `make format`
- `make lint`
- `make mypy`
- `make tests`
------
https://chatgpt.com/codex/tasks/task_i_68432f925b048324a16878d28e850841
---
src/agents/handoffs.py | 4 ++--
tests/test_handoff_tool.py | 8 ++++++++
2 files changed, 10 insertions(+), 2 deletions(-)
diff --git a/src/agents/handoffs.py b/src/agents/handoffs.py
index 50dd417a2..76c93a298 100644
--- a/src/agents/handoffs.py
+++ b/src/agents/handoffs.py
@@ -1,6 +1,7 @@
from __future__ import annotations
import inspect
+import json
from collections.abc import Awaitable
from dataclasses import dataclass
from typing import TYPE_CHECKING, Any, Callable, Generic, cast, overload
@@ -99,8 +100,7 @@ class Handoff(Generic[TContext]):
"""
def get_transfer_message(self, agent: Agent[Any]) -> str:
- base = f"{{'assistant': '{agent.name}'}}"
- return base
+ return json.dumps({"assistant": agent.name})
@classmethod
def default_tool_name(cls, agent: Agent[Any]) -> str:
diff --git a/tests/test_handoff_tool.py b/tests/test_handoff_tool.py
index a2a06208f..0a8f064f1 100644
--- a/tests/test_handoff_tool.py
+++ b/tests/test_handoff_tool.py
@@ -1,3 +1,4 @@
+import json
from typing import Any
import pytest
@@ -276,3 +277,10 @@ def test_handoff_input_schema_is_strict():
"additionalProperties" in obj.input_json_schema
and not obj.input_json_schema["additionalProperties"]
), "Input schema should be strict and have additionalProperties=False"
+
+
+def test_get_transfer_message_is_valid_json() -> None:
+ agent = Agent(name="foo")
+ obj = handoff(agent)
+ transfer = obj.get_transfer_message(agent)
+ assert json.loads(transfer) == {"assistant": agent.name}
From dcb88e69cd8a0a82894d212dd5ebee118f99057b Mon Sep 17 00:00:00 2001
From: Javier Leguina <92868166+jleguina@users.noreply.github.com>
Date: Mon, 9 Jun 2025 15:24:51 +0100
Subject: [PATCH 37/68] docs: custom output extraction (#817)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
In deep agent workflows, each sub‐agent automatically performs an LLM
step to summarize its tool calls before returning to its parent. This
leads to:
1. Excessive latency: every nested agent invokes the LLM, compounding
delays.
2. Loss of raw tool data: summaries may strip out details the top‐level
agent needs.
We discovered that `Agent.as_tool(...)` already accepts an
(undocumented) `custom_output_extractor` parameter. By providing a
callback, a parent agent can override what the sub‐agent returns e.g.
hand back raw tool outputs or a custom slice so that only the final
agent does summarization.
---
This PR adds a “Custom output extraction” section to the Markdown docs
under “Agents as tools,” with a minimal code example.
---
docs/tools.md | 27 +++++++++++++++++++++++++++
1 file changed, 27 insertions(+)
diff --git a/docs/tools.md b/docs/tools.md
index 4e9a20d32..6dba1a853 100644
--- a/docs/tools.md
+++ b/docs/tools.md
@@ -284,6 +284,33 @@ async def run_my_agent() -> str:
return str(result.final_output)
```
+### Custom output extraction
+
+In certain cases, you might want to modify the output of the tool-agents before returning it to the central agent. This may be useful if you want to:
+
+- Extract a specific piece of information (e.g., a JSON payload) from the sub-agent's chat history.
+- Convert or reformat the agent’s final answer (e.g., transform Markdown into plain text or CSV).
+- Validate the output or provide a fallback value when the agent’s response is missing or malformed.
+
+You can do this by supplying the `custom_output_extractor` argument to the `as_tool` method:
+
+```python
+async def extract_json_payload(run_result: RunResult) -> str:
+ # Scan the agent’s outputs in reverse order until we find a JSON-like message from a tool call.
+ for item in reversed(run_result.new_items):
+ if isinstance(item, ToolCallOutputItem) and item.output.strip().startswith("{"):
+ return item.output.strip()
+ # Fallback to an empty JSON object if nothing was found
+ return "{}"
+
+
+json_tool = data_agent.as_tool(
+ tool_name="get_data_json",
+ tool_description="Run the data agent and return only its JSON payload",
+ custom_output_extractor=extract_json_payload,
+)
+```
+
## Handling errors in function tools
When you create a function tool via `@function_tool`, you can pass a `failure_error_function`. This is a function that provides an error response to the LLM in case the tool call crashes.
From 8dfd6ff35c1b73bc5d2e6a14c0246b03aa2f9f98 Mon Sep 17 00:00:00 2001
From: Niv Hertz <46317590+niv-hertz@users.noreply.github.com>
Date: Mon, 9 Jun 2025 18:08:50 +0300
Subject: [PATCH 38/68] Added support for passing tool_call_id via the
RunContextWrapper (#766)
This PR fixes issue:
https://github.com/openai/openai-agents-python/issues/559
By adding the tool_call_id to the RunContextWrapper prior to calling
tools. This gives the ability to access the tool_call_id in the
implementation of the tool.
---
src/agents/_run_impl.py | 12 +++++----
src/agents/function_schema.py | 9 ++++---
src/agents/tool.py | 14 +++++++---
src/agents/tool_context.py | 28 +++++++++++++++++++
tests/test_function_tool.py | 33 ++++++++++++-----------
tests/test_function_tool_decorator.py | 9 ++++---
tests/test_responses.py | 6 +++--
tests/test_run_step_execution.py | 39 +++++++++++++++++++++++++++
8 files changed, 115 insertions(+), 35 deletions(-)
create mode 100644 src/agents/tool_context.py
diff --git a/src/agents/_run_impl.py b/src/agents/_run_impl.py
index e98010555..a75c5e825 100644
--- a/src/agents/_run_impl.py
+++ b/src/agents/_run_impl.py
@@ -75,6 +75,7 @@
MCPToolApprovalRequest,
Tool,
)
+from .tool_context import ToolContext
from .tracing import (
SpanError,
Trace,
@@ -543,23 +544,24 @@ async def run_single_tool(
func_tool: FunctionTool, tool_call: ResponseFunctionToolCall
) -> Any:
with function_span(func_tool.name) as span_fn:
+ tool_context = ToolContext.from_agent_context(context_wrapper, tool_call.call_id)
if config.trace_include_sensitive_data:
span_fn.span_data.input = tool_call.arguments
try:
_, _, result = await asyncio.gather(
- hooks.on_tool_start(context_wrapper, agent, func_tool),
+ hooks.on_tool_start(tool_context, agent, func_tool),
(
- agent.hooks.on_tool_start(context_wrapper, agent, func_tool)
+ agent.hooks.on_tool_start(tool_context, agent, func_tool)
if agent.hooks
else _coro.noop_coroutine()
),
- func_tool.on_invoke_tool(context_wrapper, tool_call.arguments),
+ func_tool.on_invoke_tool(tool_context, tool_call.arguments),
)
await asyncio.gather(
- hooks.on_tool_end(context_wrapper, agent, func_tool, result),
+ hooks.on_tool_end(tool_context, agent, func_tool, result),
(
- agent.hooks.on_tool_end(context_wrapper, agent, func_tool, result)
+ agent.hooks.on_tool_end(tool_context, agent, func_tool, result)
if agent.hooks
else _coro.noop_coroutine()
),
diff --git a/src/agents/function_schema.py b/src/agents/function_schema.py
index 0e5868965..188566970 100644
--- a/src/agents/function_schema.py
+++ b/src/agents/function_schema.py
@@ -13,6 +13,7 @@
from .exceptions import UserError
from .run_context import RunContextWrapper
from .strict_schema import ensure_strict_json_schema
+from .tool_context import ToolContext
@dataclass
@@ -237,21 +238,21 @@ def function_schema(
ann = type_hints.get(first_name, first_param.annotation)
if ann != inspect._empty:
origin = get_origin(ann) or ann
- if origin is RunContextWrapper:
+ if origin is RunContextWrapper or origin is ToolContext:
takes_context = True # Mark that the function takes context
else:
filtered_params.append((first_name, first_param))
else:
filtered_params.append((first_name, first_param))
- # For parameters other than the first, raise error if any use RunContextWrapper.
+ # For parameters other than the first, raise error if any use RunContextWrapper or ToolContext.
for name, param in params[1:]:
ann = type_hints.get(name, param.annotation)
if ann != inspect._empty:
origin = get_origin(ann) or ann
- if origin is RunContextWrapper:
+ if origin is RunContextWrapper or origin is ToolContext:
raise UserError(
- f"RunContextWrapper param found at non-first position in function"
+ f"RunContextWrapper/ToolContext param found at non-first position in function"
f" {func.__name__}"
)
filtered_params.append((name, param))
diff --git a/src/agents/tool.py b/src/agents/tool.py
index 57272f9f4..ce66a53ba 100644
--- a/src/agents/tool.py
+++ b/src/agents/tool.py
@@ -20,6 +20,7 @@
from .items import RunItem
from .logger import logger
from .run_context import RunContextWrapper
+from .tool_context import ToolContext
from .tracing import SpanError
from .util import _error_tracing
from .util._types import MaybeAwaitable
@@ -31,8 +32,13 @@
ToolFunctionWithoutContext = Callable[ToolParams, Any]
ToolFunctionWithContext = Callable[Concatenate[RunContextWrapper[Any], ToolParams], Any]
+ToolFunctionWithToolContext = Callable[Concatenate[ToolContext, ToolParams], Any]
-ToolFunction = Union[ToolFunctionWithoutContext[ToolParams], ToolFunctionWithContext[ToolParams]]
+ToolFunction = Union[
+ ToolFunctionWithoutContext[ToolParams],
+ ToolFunctionWithContext[ToolParams],
+ ToolFunctionWithToolContext[ToolParams],
+]
@dataclass
@@ -62,7 +68,7 @@ class FunctionTool:
params_json_schema: dict[str, Any]
"""The JSON schema for the tool's parameters."""
- on_invoke_tool: Callable[[RunContextWrapper[Any], str], Awaitable[Any]]
+ on_invoke_tool: Callable[[ToolContext[Any], str], Awaitable[Any]]
"""A function that invokes the tool with the given context and parameters. The params passed
are:
1. The tool run context.
@@ -344,7 +350,7 @@ def _create_function_tool(the_func: ToolFunction[...]) -> FunctionTool:
strict_json_schema=strict_mode,
)
- async def _on_invoke_tool_impl(ctx: RunContextWrapper[Any], input: str) -> Any:
+ async def _on_invoke_tool_impl(ctx: ToolContext[Any], input: str) -> Any:
try:
json_data: dict[str, Any] = json.loads(input) if input else {}
except Exception as e:
@@ -393,7 +399,7 @@ async def _on_invoke_tool_impl(ctx: RunContextWrapper[Any], input: str) -> Any:
return result
- async def _on_invoke_tool(ctx: RunContextWrapper[Any], input: str) -> Any:
+ async def _on_invoke_tool(ctx: ToolContext[Any], input: str) -> Any:
try:
return await _on_invoke_tool_impl(ctx, input)
except Exception as e:
diff --git a/src/agents/tool_context.py b/src/agents/tool_context.py
new file mode 100644
index 000000000..17b595f06
--- /dev/null
+++ b/src/agents/tool_context.py
@@ -0,0 +1,28 @@
+from dataclasses import dataclass, field, fields
+from typing import Any
+
+from .run_context import RunContextWrapper, TContext
+
+
+def _assert_must_pass_tool_call_id() -> str:
+ raise ValueError("tool_call_id must be passed to ToolContext")
+
+@dataclass
+class ToolContext(RunContextWrapper[TContext]):
+ """The context of a tool call."""
+
+ tool_call_id: str = field(default_factory=_assert_must_pass_tool_call_id)
+ """The ID of the tool call."""
+
+ @classmethod
+ def from_agent_context(
+ cls, context: RunContextWrapper[TContext], tool_call_id: str
+ ) -> "ToolContext":
+ """
+ Create a ToolContext from a RunContextWrapper.
+ """
+ # Grab the names of the RunContextWrapper's init=True fields
+ base_values: dict[str, Any] = {
+ f.name: getattr(context, f.name) for f in fields(RunContextWrapper) if f.init
+ }
+ return cls(tool_call_id=tool_call_id, **base_values)
diff --git a/tests/test_function_tool.py b/tests/test_function_tool.py
index c5d7da649..b232bf75e 100644
--- a/tests/test_function_tool.py
+++ b/tests/test_function_tool.py
@@ -7,6 +7,7 @@
from agents import Agent, FunctionTool, ModelBehaviorError, RunContextWrapper, function_tool
from agents.tool import default_tool_error_function
+from agents.tool_context import ToolContext
def argless_function() -> str:
@@ -18,11 +19,11 @@ async def test_argless_function():
tool = function_tool(argless_function)
assert tool.name == "argless_function"
- result = await tool.on_invoke_tool(RunContextWrapper(None), "")
+ result = await tool.on_invoke_tool(ToolContext(context=None, tool_call_id="1"), "")
assert result == "ok"
-def argless_with_context(ctx: RunContextWrapper[str]) -> str:
+def argless_with_context(ctx: ToolContext[str]) -> str:
return "ok"
@@ -31,11 +32,11 @@ async def test_argless_with_context():
tool = function_tool(argless_with_context)
assert tool.name == "argless_with_context"
- result = await tool.on_invoke_tool(RunContextWrapper(None), "")
+ result = await tool.on_invoke_tool(ToolContext(None, tool_call_id="1"), "")
assert result == "ok"
# Extra JSON should not raise an error
- result = await tool.on_invoke_tool(RunContextWrapper(None), '{"a": 1}')
+ result = await tool.on_invoke_tool(ToolContext(None, tool_call_id="1"), '{"a": 1}')
assert result == "ok"
@@ -48,15 +49,15 @@ async def test_simple_function():
tool = function_tool(simple_function, failure_error_function=None)
assert tool.name == "simple_function"
- result = await tool.on_invoke_tool(RunContextWrapper(None), '{"a": 1}')
+ result = await tool.on_invoke_tool(ToolContext(None, tool_call_id="1"), '{"a": 1}')
assert result == 6
- result = await tool.on_invoke_tool(RunContextWrapper(None), '{"a": 1, "b": 2}')
+ result = await tool.on_invoke_tool(ToolContext(None, tool_call_id="1"), '{"a": 1, "b": 2}')
assert result == 3
# Missing required argument should raise an error
with pytest.raises(ModelBehaviorError):
- await tool.on_invoke_tool(RunContextWrapper(None), "")
+ await tool.on_invoke_tool(ToolContext(None, tool_call_id="1"), "")
class Foo(BaseModel):
@@ -84,7 +85,7 @@ async def test_complex_args_function():
"bar": Bar(x="hello", y=10),
}
)
- result = await tool.on_invoke_tool(RunContextWrapper(None), valid_json)
+ result = await tool.on_invoke_tool(ToolContext(None, tool_call_id="1"), valid_json)
assert result == "6 hello10 hello"
valid_json = json.dumps(
@@ -93,7 +94,7 @@ async def test_complex_args_function():
"bar": Bar(x="hello", y=10),
}
)
- result = await tool.on_invoke_tool(RunContextWrapper(None), valid_json)
+ result = await tool.on_invoke_tool(ToolContext(None, tool_call_id="1"), valid_json)
assert result == "3 hello10 hello"
valid_json = json.dumps(
@@ -103,12 +104,12 @@ async def test_complex_args_function():
"baz": "world",
}
)
- result = await tool.on_invoke_tool(RunContextWrapper(None), valid_json)
+ result = await tool.on_invoke_tool(ToolContext(None, tool_call_id="1"), valid_json)
assert result == "3 hello10 world"
# Missing required argument should raise an error
with pytest.raises(ModelBehaviorError):
- await tool.on_invoke_tool(RunContextWrapper(None), '{"foo": {"a": 1}}')
+ await tool.on_invoke_tool(ToolContext(None, tool_call_id="1"), '{"foo": {"a": 1}}')
def test_function_config_overrides():
@@ -168,7 +169,7 @@ async def run_function(ctx: RunContextWrapper[Any], args: str) -> str:
assert tool.params_json_schema[key] == value
assert tool.strict_json_schema
- result = await tool.on_invoke_tool(RunContextWrapper(None), '{"data": "hello"}')
+ result = await tool.on_invoke_tool(ToolContext(None, tool_call_id="1"), '{"data": "hello"}')
assert result == "hello_done"
tool_not_strict = FunctionTool(
@@ -183,7 +184,7 @@ async def run_function(ctx: RunContextWrapper[Any], args: str) -> str:
assert "additionalProperties" not in tool_not_strict.params_json_schema
result = await tool_not_strict.on_invoke_tool(
- RunContextWrapper(None), '{"data": "hello", "bar": "baz"}'
+ ToolContext(None, tool_call_id="1"), '{"data": "hello", "bar": "baz"}'
)
assert result == "hello_done"
@@ -194,7 +195,7 @@ def my_func(a: int, b: int = 5):
raise ValueError("test")
tool = function_tool(my_func)
- ctx = RunContextWrapper(None)
+ ctx = ToolContext(None, tool_call_id="1")
result = await tool.on_invoke_tool(ctx, "")
assert "Invalid JSON" in str(result)
@@ -218,7 +219,7 @@ def custom_sync_error_function(ctx: RunContextWrapper[Any], error: Exception) ->
return f"error_{error.__class__.__name__}"
tool = function_tool(my_func, failure_error_function=custom_sync_error_function)
- ctx = RunContextWrapper(None)
+ ctx = ToolContext(None, tool_call_id="1")
result = await tool.on_invoke_tool(ctx, "")
assert result == "error_ModelBehaviorError"
@@ -242,7 +243,7 @@ def custom_sync_error_function(ctx: RunContextWrapper[Any], error: Exception) ->
return f"error_{error.__class__.__name__}"
tool = function_tool(my_func, failure_error_function=custom_sync_error_function)
- ctx = RunContextWrapper(None)
+ ctx = ToolContext(None, tool_call_id="1")
result = await tool.on_invoke_tool(ctx, "")
assert result == "error_ModelBehaviorError"
diff --git a/tests/test_function_tool_decorator.py b/tests/test_function_tool_decorator.py
index 3b52788fb..d334d8f84 100644
--- a/tests/test_function_tool_decorator.py
+++ b/tests/test_function_tool_decorator.py
@@ -7,6 +7,7 @@
from agents import function_tool
from agents.run_context import RunContextWrapper
+from agents.tool_context import ToolContext
class DummyContext:
@@ -14,8 +15,8 @@ def __init__(self):
self.data = "something"
-def ctx_wrapper() -> RunContextWrapper[DummyContext]:
- return RunContextWrapper(DummyContext())
+def ctx_wrapper() -> ToolContext[DummyContext]:
+ return ToolContext(context=DummyContext(), tool_call_id="1")
@function_tool
@@ -44,7 +45,7 @@ async def test_sync_no_context_with_args_invocation():
@function_tool
-def sync_with_context(ctx: RunContextWrapper[DummyContext], name: str) -> str:
+def sync_with_context(ctx: ToolContext[DummyContext], name: str) -> str:
return f"{name}_{ctx.context.data}"
@@ -71,7 +72,7 @@ async def test_async_no_context_invocation():
@function_tool
-async def async_with_context(ctx: RunContextWrapper[DummyContext], prefix: str, num: int) -> str:
+async def async_with_context(ctx: ToolContext[DummyContext], prefix: str, num: int) -> str:
await asyncio.sleep(0)
return f"{prefix}-{num}-{ctx.context.data}"
diff --git a/tests/test_responses.py b/tests/test_responses.py
index 6b91bf8c6..74212f61b 100644
--- a/tests/test_responses.py
+++ b/tests/test_responses.py
@@ -49,10 +49,12 @@ def _foo() -> str:
)
-def get_function_tool_call(name: str, arguments: str | None = None) -> ResponseOutputItem:
+def get_function_tool_call(
+ name: str, arguments: str | None = None, call_id: str | None = None
+) -> ResponseOutputItem:
return ResponseFunctionToolCall(
id="1",
- call_id="2",
+ call_id=call_id or "2",
type="function_call",
name=name,
arguments=arguments or "",
diff --git a/tests/test_run_step_execution.py b/tests/test_run_step_execution.py
index b4c83d015..6f446649a 100644
--- a/tests/test_run_step_execution.py
+++ b/tests/test_run_step_execution.py
@@ -1,5 +1,6 @@
from __future__ import annotations
+import json
from typing import Any
import pytest
@@ -26,6 +27,8 @@
RunImpl,
SingleStepResult,
)
+from agents.tool import function_tool
+from agents.tool_context import ToolContext
from .test_responses import (
get_final_output_message,
@@ -158,6 +161,42 @@ async def test_multiple_tool_calls():
assert isinstance(result.next_step, NextStepRunAgain)
+@pytest.mark.asyncio
+async def test_multiple_tool_calls_with_tool_context():
+ async def _fake_tool(context: ToolContext[str], value: str) -> str:
+ return f"{value}-{context.tool_call_id}"
+
+ tool = function_tool(_fake_tool, name_override="fake_tool", failure_error_function=None)
+
+ agent = Agent(
+ name="test",
+ tools=[tool],
+ )
+ response = ModelResponse(
+ output=[
+ get_function_tool_call("fake_tool", json.dumps({"value": "123"}), call_id="1"),
+ get_function_tool_call("fake_tool", json.dumps({"value": "456"}), call_id="2"),
+ ],
+ usage=Usage(),
+ response_id=None,
+ )
+
+ result = await get_execute_result(agent, response)
+ assert result.original_input == "hello"
+
+ # 4 items: new message, 2 tool calls, 2 tool call outputs
+ assert len(result.generated_items) == 4
+ assert isinstance(result.next_step, NextStepRunAgain)
+
+ items = result.generated_items
+ assert_item_is_function_tool_call(items[0], "fake_tool", json.dumps({"value": "123"}))
+ assert_item_is_function_tool_call(items[1], "fake_tool", json.dumps({"value": "456"}))
+ assert_item_is_function_tool_call_output(items[2], "123-1")
+ assert_item_is_function_tool_call_output(items[3], "456-2")
+
+ assert isinstance(result.next_step, NextStepRunAgain)
+
+
@pytest.mark.asyncio
async def test_handoff_output_leads_to_handoff_next_step():
agent_1 = Agent(name="test_1")
From 0eee6b8305e52aa4de7cae74db4c22633019522a Mon Sep 17 00:00:00 2001
From: Rohan Mehta <rm@openai.com>
Date: Tue, 10 Jun 2025 18:14:34 -0400
Subject: [PATCH 39/68] Allow arbitrary kwargs in model (#842)
Sometimes users want to provide parameters specific to a model provider.
This is an escape hatch.
---
src/agents/extensions/models/litellm_model.py | 4 +
src/agents/model_settings.py | 15 ++
src/agents/models/openai_chatcompletions.py | 1 +
src/agents/models/openai_responses.py | 1 +
tests/model_settings/test_serialization.py | 74 ++++++++
tests/models/test_kwargs_functionality.py | 177 ++++++++++++++++++
6 files changed, 272 insertions(+)
create mode 100644 tests/models/test_kwargs_functionality.py
diff --git a/src/agents/extensions/models/litellm_model.py b/src/agents/extensions/models/litellm_model.py
index 7cf7a2de5..3ded80be2 100644
--- a/src/agents/extensions/models/litellm_model.py
+++ b/src/agents/extensions/models/litellm_model.py
@@ -284,6 +284,10 @@ async def _fetch_response(
if model_settings.extra_body and isinstance(model_settings.extra_body, dict):
extra_kwargs.update(model_settings.extra_body)
+ # Add kwargs from model_settings.extra_args, filtering out None values
+ if model_settings.extra_args:
+ extra_kwargs.update(model_settings.extra_args)
+
ret = await litellm.acompletion(
model=self.model,
messages=converted_messages,
diff --git a/src/agents/model_settings.py b/src/agents/model_settings.py
index 7b016c98f..881390279 100644
--- a/src/agents/model_settings.py
+++ b/src/agents/model_settings.py
@@ -73,6 +73,11 @@ class ModelSettings:
"""Additional headers to provide with the request.
Defaults to None if not provided."""
+ extra_args: dict[str, Any] | None = None
+ """Arbitrary keyword arguments to pass to the model API call.
+ These will be passed directly to the underlying model provider's API.
+ Use with caution as not all models support all parameters."""
+
def resolve(self, override: ModelSettings | None) -> ModelSettings:
"""Produce a new ModelSettings by overlaying any non-None values from the
override on top of this instance."""
@@ -84,6 +89,16 @@ def resolve(self, override: ModelSettings | None) -> ModelSettings:
for field in fields(self)
if getattr(override, field.name) is not None
}
+
+ # Handle extra_args merging specially - merge dictionaries instead of replacing
+ if self.extra_args is not None or override.extra_args is not None:
+ merged_args = {}
+ if self.extra_args:
+ merged_args.update(self.extra_args)
+ if override.extra_args:
+ merged_args.update(override.extra_args)
+ changes["extra_args"] = merged_args if merged_args else None
+
return replace(self, **changes)
def to_json_dict(self) -> dict[str, Any]:
diff --git a/src/agents/models/openai_chatcompletions.py b/src/agents/models/openai_chatcompletions.py
index 6b4045d21..4dad976bd 100644
--- a/src/agents/models/openai_chatcompletions.py
+++ b/src/agents/models/openai_chatcompletions.py
@@ -281,6 +281,7 @@ async def _fetch_response(
extra_query=model_settings.extra_query,
extra_body=model_settings.extra_body,
metadata=self._non_null_or_not_given(model_settings.metadata),
+ **(model_settings.extra_args or {}),
)
if isinstance(ret, ChatCompletion):
diff --git a/src/agents/models/openai_responses.py b/src/agents/models/openai_responses.py
index 86c8e69cb..fdc391c6a 100644
--- a/src/agents/models/openai_responses.py
+++ b/src/agents/models/openai_responses.py
@@ -266,6 +266,7 @@ async def _fetch_response(
store=self._non_null_or_not_given(model_settings.store),
reasoning=self._non_null_or_not_given(model_settings.reasoning),
metadata=self._non_null_or_not_given(model_settings.metadata),
+ **(model_settings.extra_args or {}),
)
def _get_client(self) -> AsyncOpenAI:
diff --git a/tests/model_settings/test_serialization.py b/tests/model_settings/test_serialization.py
index d76a58d17..ad4db4019 100644
--- a/tests/model_settings/test_serialization.py
+++ b/tests/model_settings/test_serialization.py
@@ -47,6 +47,7 @@ def test_all_fields_serialization() -> None:
extra_query={"foo": "bar"},
extra_body={"foo": "bar"},
extra_headers={"foo": "bar"},
+ extra_args={"custom_param": "value", "another_param": 42},
)
# Verify that every single field is set to a non-None value
@@ -57,3 +58,76 @@ def test_all_fields_serialization() -> None:
# Now, lets serialize the ModelSettings instance to a JSON string
verify_serialization(model_settings)
+
+
+def test_extra_args_serialization() -> None:
+ """Test that extra_args are properly serialized."""
+ model_settings = ModelSettings(
+ temperature=0.5,
+ extra_args={"custom_param": "value", "another_param": 42, "nested": {"key": "value"}},
+ )
+
+ json_dict = model_settings.to_json_dict()
+ assert json_dict["extra_args"] == {
+ "custom_param": "value",
+ "another_param": 42,
+ "nested": {"key": "value"},
+ }
+
+ # Verify serialization works
+ verify_serialization(model_settings)
+
+
+def test_extra_args_resolve() -> None:
+ """Test that extra_args are properly merged in the resolve method."""
+ base_settings = ModelSettings(
+ temperature=0.5, extra_args={"param1": "base_value", "param2": "base_only"}
+ )
+
+ override_settings = ModelSettings(
+ top_p=0.9, extra_args={"param1": "override_value", "param3": "override_only"}
+ )
+
+ resolved = base_settings.resolve(override_settings)
+
+ # Check that regular fields are properly resolved
+ assert resolved.temperature == 0.5 # from base
+ assert resolved.top_p == 0.9 # from override
+
+ # Check that extra_args are properly merged
+ expected_extra_args = {
+ "param1": "override_value", # override wins
+ "param2": "base_only", # from base
+ "param3": "override_only", # from override
+ }
+ assert resolved.extra_args == expected_extra_args
+
+
+def test_extra_args_resolve_with_none() -> None:
+ """Test that resolve works properly when one side has None extra_args."""
+ # Base with extra_args, override with None
+ base_settings = ModelSettings(extra_args={"param1": "value1"})
+ override_settings = ModelSettings(temperature=0.8)
+
+ resolved = base_settings.resolve(override_settings)
+ assert resolved.extra_args == {"param1": "value1"}
+ assert resolved.temperature == 0.8
+
+ # Base with None, override with extra_args
+ base_settings = ModelSettings(temperature=0.5)
+ override_settings = ModelSettings(extra_args={"param2": "value2"})
+
+ resolved = base_settings.resolve(override_settings)
+ assert resolved.extra_args == {"param2": "value2"}
+ assert resolved.temperature == 0.5
+
+
+def test_extra_args_resolve_both_none() -> None:
+ """Test that resolve works when both sides have None extra_args."""
+ base_settings = ModelSettings(temperature=0.5)
+ override_settings = ModelSettings(top_p=0.9)
+
+ resolved = base_settings.resolve(override_settings)
+ assert resolved.extra_args is None
+ assert resolved.temperature == 0.5
+ assert resolved.top_p == 0.9
diff --git a/tests/models/test_kwargs_functionality.py b/tests/models/test_kwargs_functionality.py
new file mode 100644
index 000000000..210610a02
--- /dev/null
+++ b/tests/models/test_kwargs_functionality.py
@@ -0,0 +1,177 @@
+import litellm
+import pytest
+from litellm.types.utils import Choices, Message, ModelResponse, Usage
+from openai.types.chat.chat_completion import ChatCompletion, Choice
+from openai.types.chat.chat_completion_message import ChatCompletionMessage
+from openai.types.completion_usage import CompletionUsage
+
+from agents.extensions.models.litellm_model import LitellmModel
+from agents.model_settings import ModelSettings
+from agents.models.interface import ModelTracing
+from agents.models.openai_chatcompletions import OpenAIChatCompletionsModel
+
+
+@pytest.mark.allow_call_model_methods
+@pytest.mark.asyncio
+async def test_litellm_kwargs_forwarded(monkeypatch):
+ """
+ Test that kwargs from ModelSettings are forwarded to litellm.acompletion.
+ """
+ captured: dict[str, object] = {}
+
+ async def fake_acompletion(model, messages=None, **kwargs):
+ captured.update(kwargs)
+ msg = Message(role="assistant", content="test response")
+ choice = Choices(index=0, message=msg)
+ return ModelResponse(choices=[choice], usage=Usage(0, 0, 0))
+
+ monkeypatch.setattr(litellm, "acompletion", fake_acompletion)
+
+ settings = ModelSettings(
+ temperature=0.5,
+ extra_args={
+ "custom_param": "custom_value",
+ "seed": 42,
+ "stop": ["END"],
+ "logit_bias": {123: -100},
+ },
+ )
+ model = LitellmModel(model="test-model")
+
+ await model.get_response(
+ system_instructions=None,
+ input="test input",
+ model_settings=settings,
+ tools=[],
+ output_schema=None,
+ handoffs=[],
+ tracing=ModelTracing.DISABLED,
+ previous_response_id=None,
+ )
+
+ # Verify that all kwargs were passed through
+ assert captured["custom_param"] == "custom_value"
+ assert captured["seed"] == 42
+ assert captured["stop"] == ["END"]
+ assert captured["logit_bias"] == {123: -100}
+
+ # Verify regular parameters are still passed
+ assert captured["temperature"] == 0.5
+
+
+@pytest.mark.allow_call_model_methods
+@pytest.mark.asyncio
+async def test_openai_chatcompletions_kwargs_forwarded(monkeypatch):
+ """
+ Test that kwargs from ModelSettings are forwarded to OpenAI chat completions API.
+ """
+ captured: dict[str, object] = {}
+
+ class MockChatCompletions:
+ async def create(self, **kwargs):
+ captured.update(kwargs)
+ msg = ChatCompletionMessage(role="assistant", content="test response")
+ choice = Choice(index=0, message=msg, finish_reason="stop")
+ return ChatCompletion(
+ id="test-id",
+ created=0,
+ model="gpt-4",
+ object="chat.completion",
+ choices=[choice],
+ usage=CompletionUsage(completion_tokens=5, prompt_tokens=10, total_tokens=15),
+ )
+
+ class MockChat:
+ def __init__(self):
+ self.completions = MockChatCompletions()
+
+ class MockClient:
+ def __init__(self):
+ self.chat = MockChat()
+ self.base_url = "https://api.openai.com/v1"
+
+ settings = ModelSettings(
+ temperature=0.7,
+ extra_args={
+ "seed": 123,
+ "logit_bias": {456: 10},
+ "stop": ["STOP", "END"],
+ "user": "test-user",
+ },
+ )
+
+ mock_client = MockClient()
+ model = OpenAIChatCompletionsModel(model="gpt-4", openai_client=mock_client) # type: ignore
+
+ await model.get_response(
+ system_instructions="Test system",
+ input="test input",
+ model_settings=settings,
+ tools=[],
+ output_schema=None,
+ handoffs=[],
+ tracing=ModelTracing.DISABLED,
+ previous_response_id=None,
+ )
+
+ # Verify that all kwargs were passed through
+ assert captured["seed"] == 123
+ assert captured["logit_bias"] == {456: 10}
+ assert captured["stop"] == ["STOP", "END"]
+ assert captured["user"] == "test-user"
+
+ # Verify regular parameters are still passed
+ assert captured["temperature"] == 0.7
+
+
+@pytest.mark.allow_call_model_methods
+@pytest.mark.asyncio
+async def test_empty_kwargs_handling(monkeypatch):
+ """
+ Test that empty or None kwargs are handled gracefully.
+ """
+ captured: dict[str, object] = {}
+
+ async def fake_acompletion(model, messages=None, **kwargs):
+ captured.update(kwargs)
+ msg = Message(role="assistant", content="test response")
+ choice = Choices(index=0, message=msg)
+ return ModelResponse(choices=[choice], usage=Usage(0, 0, 0))
+
+ monkeypatch.setattr(litellm, "acompletion", fake_acompletion)
+
+ # Test with None kwargs
+ settings_none = ModelSettings(temperature=0.5, extra_args=None)
+ model = LitellmModel(model="test-model")
+
+ await model.get_response(
+ system_instructions=None,
+ input="test input",
+ model_settings=settings_none,
+ tools=[],
+ output_schema=None,
+ handoffs=[],
+ tracing=ModelTracing.DISABLED,
+ previous_response_id=None,
+ )
+
+ # Should work without error and include regular parameters
+ assert captured["temperature"] == 0.5
+
+ # Test with empty dict
+ captured.clear()
+ settings_empty = ModelSettings(temperature=0.3, extra_args={})
+
+ await model.get_response(
+ system_instructions=None,
+ input="test input",
+ model_settings=settings_empty,
+ tools=[],
+ output_schema=None,
+ handoffs=[],
+ tracing=ModelTracing.DISABLED,
+ previous_response_id=None,
+ )
+
+ # Should work without error and include regular parameters
+ assert captured["temperature"] == 0.3
From 6d2806f10c59df6753a23000709ad807ba62aca1 Mon Sep 17 00:00:00 2001
From: Rohan Mehta <rm@openai.com>
Date: Mon, 16 Jun 2025 10:50:20 -0400
Subject: [PATCH 40/68] Fix function_schema name override bug (#872)
## Summary
- ensure `name_override` is always used in `function_schema`
- test name override when docstring info is disabled
## Testing
- `make format`
- `make lint`
- `make mypy`
- `make tests`
Resolves #860
------
https://chatgpt.com/codex/tasks/task_i_684f1cf885b08321b4dd3f4294e24ca2
---
src/agents/function_schema.py | 3 ++-
tests/test_function_schema.py | 12 ++++++++++++
2 files changed, 14 insertions(+), 1 deletion(-)
diff --git a/src/agents/function_schema.py b/src/agents/function_schema.py
index 188566970..dd1db1fee 100644
--- a/src/agents/function_schema.py
+++ b/src/agents/function_schema.py
@@ -223,7 +223,8 @@ def function_schema(
doc_info = None
param_descs = {}
- func_name = name_override or doc_info.name if doc_info else func.__name__
+ # Ensure name_override takes precedence even if docstring info is disabled.
+ func_name = name_override or (doc_info.name if doc_info else func.__name__)
# 2. Inspect function signature and get type hints
sig = inspect.signature(func)
diff --git a/tests/test_function_schema.py b/tests/test_function_schema.py
index 5618d8ae9..54e7e2f9e 100644
--- a/tests/test_function_schema.py
+++ b/tests/test_function_schema.py
@@ -439,3 +439,15 @@ def func_with_mapping(test_one: Mapping[str, int]) -> str:
with pytest.raises(UserError):
function_schema(func_with_mapping)
+
+
+def test_name_override_without_docstring() -> None:
+ """name_override should be used even when not parsing docstrings."""
+
+ def foo(x: int) -> int:
+ return x
+
+ fs = function_schema(foo, use_docstring_info=False, name_override="custom")
+
+ assert fs.name == "custom"
+ assert fs.params_json_schema.get("title") == "custom_args"
From 281a7b2bb61cb20346e75234fbfaa2bf4ab808cc Mon Sep 17 00:00:00 2001
From: Daniele Morotti <58258368+DanieleMorotti@users.noreply.github.com>
Date: Mon, 16 Jun 2025 17:35:09 +0200
Subject: [PATCH 41/68] adopted float instead of timedelta for timeout
parameters (#874)
I replaced the `timedelta` parameters for MCP timeouts with `float`
values, addressing issue #845 .
Given that the MCP official repository has incorporated these changes in
[this PR](https://github.com/modelcontextprotocol/python-sdk/pull/941),
updating the MCP version in openai-agents and specifying the timeouts as
floats should be enough.
---
pyproject.toml | 2 +-
src/agents/mcp/server.py | 8 ++++----
uv.lock | 8 ++++----
3 files changed, 9 insertions(+), 9 deletions(-)
diff --git a/pyproject.toml b/pyproject.toml
index b59073ed8..a674dac96 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -13,7 +13,7 @@ dependencies = [
"typing-extensions>=4.12.2, <5",
"requests>=2.0, <3",
"types-requests>=2.0, <3",
- "mcp>=1.8.0, <2; python_version >= '3.10'",
+ "mcp>=1.9.4, <2; python_version >= '3.10'",
]
classifiers = [
"Typing :: Typed",
diff --git a/src/agents/mcp/server.py b/src/agents/mcp/server.py
index b012a0968..3d1e17790 100644
--- a/src/agents/mcp/server.py
+++ b/src/agents/mcp/server.py
@@ -340,10 +340,10 @@ class MCPServerStreamableHttpParams(TypedDict):
headers: NotRequired[dict[str, str]]
"""The headers to send to the server."""
- timeout: NotRequired[timedelta]
+ timeout: NotRequired[timedelta | float]
"""The timeout for the HTTP request. Defaults to 5 seconds."""
- sse_read_timeout: NotRequired[timedelta]
+ sse_read_timeout: NotRequired[timedelta | float]
"""The timeout for the SSE connection, in seconds. Defaults to 5 minutes."""
terminate_on_close: NotRequired[bool]
@@ -401,8 +401,8 @@ def create_streams(
return streamablehttp_client(
url=self.params["url"],
headers=self.params.get("headers", None),
- timeout=self.params.get("timeout", timedelta(seconds=30)),
- sse_read_timeout=self.params.get("sse_read_timeout", timedelta(seconds=60 * 5)),
+ timeout=self.params.get("timeout", 5),
+ sse_read_timeout=self.params.get("sse_read_timeout", 60 * 5),
terminate_on_close=self.params.get("terminate_on_close", True),
)
diff --git a/uv.lock b/uv.lock
index 1779b8637..56f56f413 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1047,7 +1047,7 @@ wheels = [
[[package]]
name = "mcp"
-version = "1.8.1"
+version = "1.9.4"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "anyio", marker = "python_full_version >= '3.10'" },
@@ -1060,9 +1060,9 @@ dependencies = [
{ name = "starlette", marker = "python_full_version >= '3.10'" },
{ name = "uvicorn", marker = "python_full_version >= '3.10' and sys_platform != 'emscripten'" },
]
-sdist = { url = "https://files.pythonhosted.org/packages/7c/13/16b712e8a3be6a736b411df2fc6b4e75eb1d3e99b1cd57a3a1decf17f612/mcp-1.8.1.tar.gz", hash = "sha256:ec0646271d93749f784d2316fb5fe6102fb0d1be788ec70a9e2517e8f2722c0e", size = 265605 }
+sdist = { url = "https://files.pythonhosted.org/packages/06/f2/dc2450e566eeccf92d89a00c3e813234ad58e2ba1e31d11467a09ac4f3b9/mcp-1.9.4.tar.gz", hash = "sha256:cfb0bcd1a9535b42edaef89947b9e18a8feb49362e1cc059d6e7fc636f2cb09f", size = 333294 }
wheels = [
- { url = "https://files.pythonhosted.org/packages/1c/5d/91cf0d40e40ae9ecf8d4004e0f9611eea86085aa0b5505493e0ff53972da/mcp-1.8.1-py3-none-any.whl", hash = "sha256:948e03783859fa35abe05b9b6c0a1d5519be452fc079dc8d7f682549591c1770", size = 119761 },
+ { url = "https://files.pythonhosted.org/packages/97/fc/80e655c955137393c443842ffcc4feccab5b12fa7cb8de9ced90f90e6998/mcp-1.9.4-py3-none-any.whl", hash = "sha256:7fcf36b62936adb8e63f89346bccca1268eeca9bf6dfb562ee10b1dfbda9dac0", size = 130232 },
]
[[package]]
@@ -1534,7 +1534,7 @@ requires-dist = [
{ name = "graphviz", marker = "extra == 'viz'", specifier = ">=0.17" },
{ name = "griffe", specifier = ">=1.5.6,<2" },
{ name = "litellm", marker = "extra == 'litellm'", specifier = ">=1.67.4.post1,<2" },
- { name = "mcp", marker = "python_full_version >= '3.10'", specifier = ">=1.8.0,<2" },
+ { name = "mcp", marker = "python_full_version >= '3.10'", specifier = ">=1.9.4,<2" },
{ name = "numpy", marker = "python_full_version >= '3.10' and extra == 'voice'", specifier = ">=2.2.0,<3" },
{ name = "openai", specifier = ">=1.81.0" },
{ name = "pydantic", specifier = ">=2.10,<3" },
From 2b9b8f7e7363490c2d38d319cd1acaa288595f9a Mon Sep 17 00:00:00 2001
From: Rohan Mehta <rm@openai.com>
Date: Mon, 16 Jun 2025 15:47:48 -0400
Subject: [PATCH 42/68] Prompts support (#876)
Add support for the new openai prompts feature.
---
examples/basic/prompt_template.py | 79 +++++++++++++++
pyproject.toml | 2 +-
src/agents/__init__.py | 4 +
src/agents/agent.py | 14 +++
src/agents/extensions/models/litellm_model.py | 8 +-
src/agents/models/interface.py | 6 ++
src/agents/models/openai_chatcompletions.py | 9 +-
src/agents/models/openai_responses.py | 9 ++
src/agents/prompts.py | 76 +++++++++++++++
src/agents/run.py | 17 +++-
src/agents/tool_context.py | 1 +
tests/fake_model.py | 2 +
.../test_litellm_chatcompletions_stream.py | 3 +
tests/test_agent_prompt.py | 97 +++++++++++++++++++
tests/test_openai_chatcompletions.py | 4 +
tests/test_openai_chatcompletions_stream.py | 3 +
tests/test_responses_tracing.py | 6 ++
tests/voice/test_workflow.py | 3 +
uv.lock | 8 +-
19 files changed, 342 insertions(+), 9 deletions(-)
create mode 100644 examples/basic/prompt_template.py
create mode 100644 src/agents/prompts.py
create mode 100644 tests/test_agent_prompt.py
diff --git a/examples/basic/prompt_template.py b/examples/basic/prompt_template.py
new file mode 100644
index 000000000..59251935e
--- /dev/null
+++ b/examples/basic/prompt_template.py
@@ -0,0 +1,79 @@
+import argparse
+import asyncio
+import random
+
+from agents import Agent, GenerateDynamicPromptData, Runner
+
+"""
+NOTE: This example will not work out of the box, because the default prompt ID will not be available
+in your project.
+
+To use it, please:
+1. Go to https://platform.openai.com/playground/prompts
+2. Create a new prompt variable, `poem_style`.
+3. Create a system prompt with the content:
+```
+Write a poem in {{poem_style}}
+```
+4. Run the example with the `--prompt-id` flag.
+"""
+
+DEFAULT_PROMPT_ID = "pmpt_6850729e8ba481939fd439e058c69ee004afaa19c520b78b"
+
+
+class DynamicContext:
+ def __init__(self, prompt_id: str):
+ self.prompt_id = prompt_id
+ self.poem_style = random.choice(["limerick", "haiku", "ballad"])
+ print(f"[debug] DynamicContext initialized with poem_style: {self.poem_style}")
+
+
+async def _get_dynamic_prompt(data: GenerateDynamicPromptData):
+ ctx: DynamicContext = data.context.context
+ return {
+ "id": ctx.prompt_id,
+ "version": "1",
+ "variables": {
+ "poem_style": ctx.poem_style,
+ },
+ }
+
+
+async def dynamic_prompt(prompt_id: str):
+ context = DynamicContext(prompt_id)
+
+ agent = Agent(
+ name="Assistant",
+ prompt=_get_dynamic_prompt,
+ )
+
+ result = await Runner.run(agent, "Tell me about recursion in programming.", context=context)
+ print(result.final_output)
+
+
+async def static_prompt(prompt_id: str):
+ agent = Agent(
+ name="Assistant",
+ prompt={
+ "id": prompt_id,
+ "version": "1",
+ "variables": {
+ "poem_style": "limerick",
+ },
+ },
+ )
+
+ result = await Runner.run(agent, "Tell me about recursion in programming.")
+ print(result.final_output)
+
+
+if __name__ == "__main__":
+ parser = argparse.ArgumentParser()
+ parser.add_argument("--dynamic", action="store_true")
+ parser.add_argument("--prompt-id", type=str, default=DEFAULT_PROMPT_ID)
+ args = parser.parse_args()
+
+ if args.dynamic:
+ asyncio.run(dynamic_prompt(args.prompt_id))
+ else:
+ asyncio.run(static_prompt(args.prompt_id))
diff --git a/pyproject.toml b/pyproject.toml
index a674dac96..e6d1d7746 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -7,7 +7,7 @@ requires-python = ">=3.9"
license = "MIT"
authors = [{ name = "OpenAI", email = "support@openai.com" }]
dependencies = [
- "openai>=1.81.0",
+ "openai>=1.87.0",
"pydantic>=2.10, <3",
"griffe>=1.5.6, <2",
"typing-extensions>=4.12.2, <5",
diff --git a/src/agents/__init__.py b/src/agents/__init__.py
index ee2f2aa16..a52347605 100644
--- a/src/agents/__init__.py
+++ b/src/agents/__init__.py
@@ -45,6 +45,7 @@
from .models.openai_chatcompletions import OpenAIChatCompletionsModel
from .models.openai_provider import OpenAIProvider
from .models.openai_responses import OpenAIResponsesModel
+from .prompts import DynamicPromptFunction, GenerateDynamicPromptData, Prompt
from .repl import run_demo_loop
from .result import RunResult, RunResultStreaming
from .run import RunConfig, Runner
@@ -178,6 +179,9 @@ def enable_verbose_stdout_logging():
"AgentsException",
"InputGuardrailTripwireTriggered",
"OutputGuardrailTripwireTriggered",
+ "DynamicPromptFunction",
+ "GenerateDynamicPromptData",
+ "Prompt",
"MaxTurnsExceeded",
"ModelBehaviorError",
"UserError",
diff --git a/src/agents/agent.py b/src/agents/agent.py
index 6adccedd5..61a9abe0c 100644
--- a/src/agents/agent.py
+++ b/src/agents/agent.py
@@ -7,6 +7,7 @@
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, Callable, Generic, Literal, cast
+from openai.types.responses.response_prompt_param import ResponsePromptParam
from typing_extensions import NotRequired, TypeAlias, TypedDict
from .agent_output import AgentOutputSchemaBase
@@ -17,6 +18,7 @@
from .mcp import MCPUtil
from .model_settings import ModelSettings
from .models.interface import Model
+from .prompts import DynamicPromptFunction, Prompt, PromptUtil
from .run_context import RunContextWrapper, TContext
from .tool import FunctionTool, FunctionToolResult, Tool, function_tool
from .util import _transforms
@@ -95,6 +97,12 @@ class Agent(Generic[TContext]):
return a string.
"""
+ prompt: Prompt | DynamicPromptFunction | None = None
+ """A prompt object (or a function that returns a Prompt). Prompts allow you to dynamically
+ configure the instructions, tools and other config for an agent outside of your code. Only
+ usable with OpenAI models, using the Responses API.
+ """
+
handoff_description: str | None = None
"""A description of the agent. This is used when the agent is used as a handoff, so that an
LLM knows what it does and when to invoke it.
@@ -242,6 +250,12 @@ async def get_system_prompt(self, run_context: RunContextWrapper[TContext]) -> s
return None
+ async def get_prompt(
+ self, run_context: RunContextWrapper[TContext]
+ ) -> ResponsePromptParam | None:
+ """Get the prompt for the agent."""
+ return await PromptUtil.to_model_input(self.prompt, run_context, self)
+
async def get_mcp_tools(self) -> list[Tool]:
"""Fetches the available tools from the MCP servers."""
convert_schemas_to_strict = self.mcp_config.get("convert_schemas_to_strict", False)
diff --git a/src/agents/extensions/models/litellm_model.py b/src/agents/extensions/models/litellm_model.py
index 3ded80be2..c58a52dae 100644
--- a/src/agents/extensions/models/litellm_model.py
+++ b/src/agents/extensions/models/litellm_model.py
@@ -71,6 +71,7 @@ async def get_response(
handoffs: list[Handoff],
tracing: ModelTracing,
previous_response_id: str | None,
+ prompt: Any | None = None,
) -> ModelResponse:
with generation_span(
model=str(self.model),
@@ -88,6 +89,7 @@ async def get_response(
span_generation,
tracing,
stream=False,
+ prompt=prompt,
)
assert isinstance(response.choices[0], litellm.types.utils.Choices)
@@ -153,8 +155,8 @@ async def stream_response(
output_schema: AgentOutputSchemaBase | None,
handoffs: list[Handoff],
tracing: ModelTracing,
- *,
previous_response_id: str | None,
+ prompt: Any | None = None,
) -> AsyncIterator[TResponseStreamEvent]:
with generation_span(
model=str(self.model),
@@ -172,6 +174,7 @@ async def stream_response(
span_generation,
tracing,
stream=True,
+ prompt=prompt,
)
final_response: Response | None = None
@@ -202,6 +205,7 @@ async def _fetch_response(
span: Span[GenerationSpanData],
tracing: ModelTracing,
stream: Literal[True],
+ prompt: Any | None = None,
) -> tuple[Response, AsyncStream[ChatCompletionChunk]]: ...
@overload
@@ -216,6 +220,7 @@ async def _fetch_response(
span: Span[GenerationSpanData],
tracing: ModelTracing,
stream: Literal[False],
+ prompt: Any | None = None,
) -> litellm.types.utils.ModelResponse: ...
async def _fetch_response(
@@ -229,6 +234,7 @@ async def _fetch_response(
span: Span[GenerationSpanData],
tracing: ModelTracing,
stream: bool = False,
+ prompt: Any | None = None,
) -> litellm.types.utils.ModelResponse | tuple[Response, AsyncStream[ChatCompletionChunk]]:
converted_messages = Converter.items_to_messages(input)
diff --git a/src/agents/models/interface.py b/src/agents/models/interface.py
index 3a79e5640..5a185806c 100644
--- a/src/agents/models/interface.py
+++ b/src/agents/models/interface.py
@@ -5,6 +5,8 @@
from collections.abc import AsyncIterator
from typing import TYPE_CHECKING
+from openai.types.responses.response_prompt_param import ResponsePromptParam
+
from ..agent_output import AgentOutputSchemaBase
from ..handoffs import Handoff
from ..items import ModelResponse, TResponseInputItem, TResponseStreamEvent
@@ -46,6 +48,7 @@ async def get_response(
tracing: ModelTracing,
*,
previous_response_id: str | None,
+ prompt: ResponsePromptParam | None,
) -> ModelResponse:
"""Get a response from the model.
@@ -59,6 +62,7 @@ async def get_response(
tracing: Tracing configuration.
previous_response_id: the ID of the previous response. Generally not used by the model,
except for the OpenAI Responses API.
+ prompt: The prompt config to use for the model.
Returns:
The full model response.
@@ -77,6 +81,7 @@ def stream_response(
tracing: ModelTracing,
*,
previous_response_id: str | None,
+ prompt: ResponsePromptParam | None,
) -> AsyncIterator[TResponseStreamEvent]:
"""Stream a response from the model.
@@ -90,6 +95,7 @@ def stream_response(
tracing: Tracing configuration.
previous_response_id: the ID of the previous response. Generally not used by the model,
except for the OpenAI Responses API.
+ prompt: The prompt config to use for the model.
Returns:
An iterator of response stream events, in OpenAI Responses format.
diff --git a/src/agents/models/openai_chatcompletions.py b/src/agents/models/openai_chatcompletions.py
index 4dad976bd..08803d8c0 100644
--- a/src/agents/models/openai_chatcompletions.py
+++ b/src/agents/models/openai_chatcompletions.py
@@ -9,6 +9,7 @@
from openai.types import ChatModel
from openai.types.chat import ChatCompletion, ChatCompletionChunk
from openai.types.responses import Response
+from openai.types.responses.response_prompt_param import ResponsePromptParam
from openai.types.responses.response_usage import InputTokensDetails, OutputTokensDetails
from .. import _debug
@@ -53,6 +54,7 @@ async def get_response(
handoffs: list[Handoff],
tracing: ModelTracing,
previous_response_id: str | None,
+ prompt: ResponsePromptParam | None = None,
) -> ModelResponse:
with generation_span(
model=str(self.model),
@@ -69,6 +71,7 @@ async def get_response(
span_generation,
tracing,
stream=False,
+ prompt=prompt,
)
first_choice = response.choices[0]
@@ -136,8 +139,8 @@ async def stream_response(
output_schema: AgentOutputSchemaBase | None,
handoffs: list[Handoff],
tracing: ModelTracing,
- *,
previous_response_id: str | None,
+ prompt: ResponsePromptParam | None = None,
) -> AsyncIterator[TResponseStreamEvent]:
"""
Yields a partial message as it is generated, as well as the usage information.
@@ -157,6 +160,7 @@ async def stream_response(
span_generation,
tracing,
stream=True,
+ prompt=prompt,
)
final_response: Response | None = None
@@ -187,6 +191,7 @@ async def _fetch_response(
span: Span[GenerationSpanData],
tracing: ModelTracing,
stream: Literal[True],
+ prompt: ResponsePromptParam | None = None,
) -> tuple[Response, AsyncStream[ChatCompletionChunk]]: ...
@overload
@@ -201,6 +206,7 @@ async def _fetch_response(
span: Span[GenerationSpanData],
tracing: ModelTracing,
stream: Literal[False],
+ prompt: ResponsePromptParam | None = None,
) -> ChatCompletion: ...
async def _fetch_response(
@@ -214,6 +220,7 @@ async def _fetch_response(
span: Span[GenerationSpanData],
tracing: ModelTracing,
stream: bool = False,
+ prompt: ResponsePromptParam | None = None,
) -> ChatCompletion | tuple[Response, AsyncStream[ChatCompletionChunk]]:
converted_messages = Converter.items_to_messages(input)
diff --git a/src/agents/models/openai_responses.py b/src/agents/models/openai_responses.py
index fdc391c6a..961f690b0 100644
--- a/src/agents/models/openai_responses.py
+++ b/src/agents/models/openai_responses.py
@@ -17,6 +17,7 @@
WebSearchToolParam,
response_create_params,
)
+from openai.types.responses.response_prompt_param import ResponsePromptParam
from .. import _debug
from ..agent_output import AgentOutputSchemaBase
@@ -74,6 +75,7 @@ async def get_response(
handoffs: list[Handoff],
tracing: ModelTracing,
previous_response_id: str | None,
+ prompt: ResponsePromptParam | None = None,
) -> ModelResponse:
with response_span(disabled=tracing.is_disabled()) as span_response:
try:
@@ -86,6 +88,7 @@ async def get_response(
handoffs,
previous_response_id,
stream=False,
+ prompt=prompt,
)
if _debug.DONT_LOG_MODEL_DATA:
@@ -141,6 +144,7 @@ async def stream_response(
handoffs: list[Handoff],
tracing: ModelTracing,
previous_response_id: str | None,
+ prompt: ResponsePromptParam | None = None,
) -> AsyncIterator[ResponseStreamEvent]:
"""
Yields a partial message as it is generated, as well as the usage information.
@@ -156,6 +160,7 @@ async def stream_response(
handoffs,
previous_response_id,
stream=True,
+ prompt=prompt,
)
final_response: Response | None = None
@@ -192,6 +197,7 @@ async def _fetch_response(
handoffs: list[Handoff],
previous_response_id: str | None,
stream: Literal[True],
+ prompt: ResponsePromptParam | None = None,
) -> AsyncStream[ResponseStreamEvent]: ...
@overload
@@ -205,6 +211,7 @@ async def _fetch_response(
handoffs: list[Handoff],
previous_response_id: str | None,
stream: Literal[False],
+ prompt: ResponsePromptParam | None = None,
) -> Response: ...
async def _fetch_response(
@@ -217,6 +224,7 @@ async def _fetch_response(
handoffs: list[Handoff],
previous_response_id: str | None,
stream: Literal[True] | Literal[False] = False,
+ prompt: ResponsePromptParam | None = None,
) -> Response | AsyncStream[ResponseStreamEvent]:
list_input = ItemHelpers.input_to_new_input_list(input)
@@ -252,6 +260,7 @@ async def _fetch_response(
input=list_input,
include=converted_tools.includes,
tools=converted_tools.tools,
+ prompt=self._non_null_or_not_given(prompt),
temperature=self._non_null_or_not_given(model_settings.temperature),
top_p=self._non_null_or_not_given(model_settings.top_p),
truncation=self._non_null_or_not_given(model_settings.truncation),
diff --git a/src/agents/prompts.py b/src/agents/prompts.py
new file mode 100644
index 000000000..aa627d033
--- /dev/null
+++ b/src/agents/prompts.py
@@ -0,0 +1,76 @@
+from __future__ import annotations
+
+import inspect
+from dataclasses import dataclass
+from typing import TYPE_CHECKING, Any, Callable
+
+from openai.types.responses.response_prompt_param import (
+ ResponsePromptParam,
+ Variables as ResponsesPromptVariables,
+)
+from typing_extensions import NotRequired, TypedDict
+
+from agents.util._types import MaybeAwaitable
+
+from .exceptions import UserError
+from .run_context import RunContextWrapper
+
+if TYPE_CHECKING:
+ from .agent import Agent
+
+
+class Prompt(TypedDict):
+ """Prompt configuration to use for interacting with an OpenAI model."""
+
+ id: str
+ """The unique ID of the prompt."""
+
+ version: NotRequired[str]
+ """Optional version of the prompt."""
+
+ variables: NotRequired[dict[str, ResponsesPromptVariables]]
+ """Optional variables to substitute into the prompt."""
+
+
+@dataclass
+class GenerateDynamicPromptData:
+ """Inputs to a function that allows you to dynamically generate a prompt."""
+
+ context: RunContextWrapper[Any]
+ """The run context."""
+
+ agent: Agent[Any]
+ """The agent for which the prompt is being generated."""
+
+
+DynamicPromptFunction = Callable[[GenerateDynamicPromptData], MaybeAwaitable[Prompt]]
+"""A function that dynamically generates a prompt."""
+
+
+class PromptUtil:
+ @staticmethod
+ async def to_model_input(
+ prompt: Prompt | DynamicPromptFunction | None,
+ context: RunContextWrapper[Any],
+ agent: Agent[Any],
+ ) -> ResponsePromptParam | None:
+ if prompt is None:
+ return None
+
+ resolved_prompt: Prompt
+ if isinstance(prompt, dict):
+ resolved_prompt = prompt
+ else:
+ func_result = prompt(GenerateDynamicPromptData(context=context, agent=agent))
+ if inspect.isawaitable(func_result):
+ resolved_prompt = await func_result
+ else:
+ resolved_prompt = func_result
+ if not isinstance(resolved_prompt, dict):
+ raise UserError("Dynamic prompt function must return a Prompt")
+
+ return {
+ "id": resolved_prompt["id"],
+ "version": resolved_prompt.get("version"),
+ "variables": resolved_prompt.get("variables"),
+ }
diff --git a/src/agents/run.py b/src/agents/run.py
index f375a0b89..10148a323 100644
--- a/src/agents/run.py
+++ b/src/agents/run.py
@@ -6,6 +6,9 @@
from typing import Any, cast
from openai.types.responses import ResponseCompletedEvent
+from openai.types.responses.response_prompt_param import (
+ ResponsePromptParam,
+)
from ._run_impl import (
AgentToolUseTracker,
@@ -682,7 +685,10 @@ async def _run_single_turn_streamed(
streamed_result.current_agent = agent
streamed_result._current_agent_output_schema = output_schema
- system_prompt = await agent.get_system_prompt(context_wrapper)
+ system_prompt, prompt_config = await asyncio.gather(
+ agent.get_system_prompt(context_wrapper),
+ agent.get_prompt(context_wrapper),
+ )
handoffs = cls._get_handoffs(agent)
model = cls._get_model(agent, run_config)
@@ -706,6 +712,7 @@ async def _run_single_turn_streamed(
run_config.tracing_disabled, run_config.trace_include_sensitive_data
),
previous_response_id=previous_response_id,
+ prompt=prompt_config,
):
if isinstance(event, ResponseCompletedEvent):
usage = (
@@ -777,7 +784,10 @@ async def _run_single_turn(
),
)
- system_prompt = await agent.get_system_prompt(context_wrapper)
+ system_prompt, prompt_config = await asyncio.gather(
+ agent.get_system_prompt(context_wrapper),
+ agent.get_prompt(context_wrapper),
+ )
output_schema = cls._get_output_schema(agent)
handoffs = cls._get_handoffs(agent)
@@ -795,6 +805,7 @@ async def _run_single_turn(
run_config,
tool_use_tracker,
previous_response_id,
+ prompt_config,
)
return await cls._get_single_step_result_from_response(
@@ -938,6 +949,7 @@ async def _get_new_response(
run_config: RunConfig,
tool_use_tracker: AgentToolUseTracker,
previous_response_id: str | None,
+ prompt_config: ResponsePromptParam | None,
) -> ModelResponse:
model = cls._get_model(agent, run_config)
model_settings = agent.model_settings.resolve(run_config.model_settings)
@@ -954,6 +966,7 @@ async def _get_new_response(
run_config.tracing_disabled, run_config.trace_include_sensitive_data
),
previous_response_id=previous_response_id,
+ prompt=prompt_config,
)
context_wrapper.usage.add(new_response.usage)
diff --git a/src/agents/tool_context.py b/src/agents/tool_context.py
index 17b595f06..c4329b8af 100644
--- a/src/agents/tool_context.py
+++ b/src/agents/tool_context.py
@@ -7,6 +7,7 @@
def _assert_must_pass_tool_call_id() -> str:
raise ValueError("tool_call_id must be passed to ToolContext")
+
@dataclass
class ToolContext(RunContextWrapper[TContext]):
"""The context of a tool call."""
diff --git a/tests/fake_model.py b/tests/fake_model.py
index 9f0c83a2f..6c1377e6d 100644
--- a/tests/fake_model.py
+++ b/tests/fake_model.py
@@ -61,6 +61,7 @@ async def get_response(
tracing: ModelTracing,
*,
previous_response_id: str | None,
+ prompt: Any | None,
) -> ModelResponse:
self.last_turn_args = {
"system_instructions": system_instructions,
@@ -103,6 +104,7 @@ async def stream_response(
tracing: ModelTracing,
*,
previous_response_id: str | None,
+ prompt: Any | None,
) -> AsyncIterator[TResponseStreamEvent]:
self.last_turn_args = {
"system_instructions": system_instructions,
diff --git a/tests/models/test_litellm_chatcompletions_stream.py b/tests/models/test_litellm_chatcompletions_stream.py
index 06e46b39c..cd342e444 100644
--- a/tests/models/test_litellm_chatcompletions_stream.py
+++ b/tests/models/test_litellm_chatcompletions_stream.py
@@ -90,6 +90,7 @@ async def patched_fetch_response(self, *args, **kwargs):
handoffs=[],
tracing=ModelTracing.DISABLED,
previous_response_id=None,
+ prompt=None,
):
output_events.append(event)
# We expect a response.created, then a response.output_item.added, content part added,
@@ -182,6 +183,7 @@ async def patched_fetch_response(self, *args, **kwargs):
handoffs=[],
tracing=ModelTracing.DISABLED,
previous_response_id=None,
+ prompt=None,
):
output_events.append(event)
# Expect sequence similar to text: created, output_item.added, content part added,
@@ -270,6 +272,7 @@ async def patched_fetch_response(self, *args, **kwargs):
handoffs=[],
tracing=ModelTracing.DISABLED,
previous_response_id=None,
+ prompt=None,
):
output_events.append(event)
# Sequence should be: response.created, then after loop we expect function call-related events:
diff --git a/tests/test_agent_prompt.py b/tests/test_agent_prompt.py
new file mode 100644
index 000000000..010717d66
--- /dev/null
+++ b/tests/test_agent_prompt.py
@@ -0,0 +1,97 @@
+import pytest
+
+from agents import Agent, Prompt, RunContextWrapper, Runner
+
+from .fake_model import FakeModel
+from .test_responses import get_text_message
+
+
+class PromptCaptureFakeModel(FakeModel):
+ """Subclass of FakeModel that records the prompt passed to the model."""
+
+ def __init__(self):
+ super().__init__()
+ self.last_prompt = None
+
+ async def get_response(
+ self,
+ system_instructions,
+ input,
+ model_settings,
+ tools,
+ output_schema,
+ handoffs,
+ tracing,
+ *,
+ previous_response_id,
+ prompt,
+ ):
+ # Record the prompt that the agent resolved and passed in.
+ self.last_prompt = prompt
+ return await super().get_response(
+ system_instructions,
+ input,
+ model_settings,
+ tools,
+ output_schema,
+ handoffs,
+ tracing,
+ previous_response_id=previous_response_id,
+ prompt=prompt,
+ )
+
+
+@pytest.mark.asyncio
+async def test_static_prompt_is_resolved_correctly():
+ static_prompt: Prompt = {
+ "id": "my_prompt",
+ "version": "1",
+ "variables": {"some_var": "some_value"},
+ }
+
+ agent = Agent(name="test", prompt=static_prompt)
+ context_wrapper = RunContextWrapper(context=None)
+
+ resolved = await agent.get_prompt(context_wrapper)
+
+ assert resolved == {
+ "id": "my_prompt",
+ "version": "1",
+ "variables": {"some_var": "some_value"},
+ }
+
+
+@pytest.mark.asyncio
+async def test_dynamic_prompt_is_resolved_correctly():
+ dynamic_prompt_value: Prompt = {"id": "dyn_prompt", "version": "2"}
+
+ def dynamic_prompt_fn(_data):
+ return dynamic_prompt_value
+
+ agent = Agent(name="test", prompt=dynamic_prompt_fn)
+ context_wrapper = RunContextWrapper(context=None)
+
+ resolved = await agent.get_prompt(context_wrapper)
+
+ assert resolved == {"id": "dyn_prompt", "version": "2", "variables": None}
+
+
+@pytest.mark.asyncio
+async def test_prompt_is_passed_to_model():
+ static_prompt: Prompt = {"id": "model_prompt"}
+
+ model = PromptCaptureFakeModel()
+ agent = Agent(name="test", model=model, prompt=static_prompt)
+
+ # Ensure the model returns a simple message so the run completes in one turn.
+ model.set_next_output([get_text_message("done")])
+
+ await Runner.run(agent, input="hello")
+
+ # The model should have received the prompt resolved by the agent.
+ expected_prompt = {
+ "id": "model_prompt",
+ "version": None,
+ "variables": None,
+ }
+ assert model.last_prompt == expected_prompt
diff --git a/tests/test_openai_chatcompletions.py b/tests/test_openai_chatcompletions.py
index 9a85dcb7b..a6909b195 100644
--- a/tests/test_openai_chatcompletions.py
+++ b/tests/test_openai_chatcompletions.py
@@ -77,6 +77,7 @@ async def patched_fetch_response(self, *args, **kwargs):
handoffs=[],
tracing=ModelTracing.DISABLED,
previous_response_id=None,
+ prompt=None,
)
# Should have produced exactly one output message with one text part
assert isinstance(resp, ModelResponse)
@@ -128,6 +129,7 @@ async def patched_fetch_response(self, *args, **kwargs):
handoffs=[],
tracing=ModelTracing.DISABLED,
previous_response_id=None,
+ prompt=None,
)
assert len(resp.output) == 1
assert isinstance(resp.output[0], ResponseOutputMessage)
@@ -180,6 +182,7 @@ async def patched_fetch_response(self, *args, **kwargs):
handoffs=[],
tracing=ModelTracing.DISABLED,
previous_response_id=None,
+ prompt=None,
)
# Expect a message item followed by a function tool call item.
assert len(resp.output) == 2
@@ -221,6 +224,7 @@ async def patched_fetch_response(self, *args, **kwargs):
handoffs=[],
tracing=ModelTracing.DISABLED,
previous_response_id=None,
+ prompt=None,
)
assert resp.output == []
diff --git a/tests/test_openai_chatcompletions_stream.py b/tests/test_openai_chatcompletions_stream.py
index 5c8bb9e3a..49e7bc2f4 100644
--- a/tests/test_openai_chatcompletions_stream.py
+++ b/tests/test_openai_chatcompletions_stream.py
@@ -90,6 +90,7 @@ async def patched_fetch_response(self, *args, **kwargs):
handoffs=[],
tracing=ModelTracing.DISABLED,
previous_response_id=None,
+ prompt=None,
):
output_events.append(event)
# We expect a response.created, then a response.output_item.added, content part added,
@@ -182,6 +183,7 @@ async def patched_fetch_response(self, *args, **kwargs):
handoffs=[],
tracing=ModelTracing.DISABLED,
previous_response_id=None,
+ prompt=None,
):
output_events.append(event)
# Expect sequence similar to text: created, output_item.added, content part added,
@@ -270,6 +272,7 @@ async def patched_fetch_response(self, *args, **kwargs):
handoffs=[],
tracing=ModelTracing.DISABLED,
previous_response_id=None,
+ prompt=None,
):
output_events.append(event)
# Sequence should be: response.created, then after loop we expect function call-related events:
diff --git a/tests/test_responses_tracing.py b/tests/test_responses_tracing.py
index db24fe496..fe63e8ecb 100644
--- a/tests/test_responses_tracing.py
+++ b/tests/test_responses_tracing.py
@@ -71,6 +71,7 @@ async def dummy_fetch_response(
handoffs,
prev_response_id,
stream,
+ prompt,
):
return DummyResponse()
@@ -115,6 +116,7 @@ async def dummy_fetch_response(
handoffs,
prev_response_id,
stream,
+ prompt,
):
return DummyResponse()
@@ -157,6 +159,7 @@ async def dummy_fetch_response(
handoffs,
prev_response_id,
stream,
+ prompt,
):
return DummyResponse()
@@ -196,6 +199,7 @@ async def dummy_fetch_response(
handoffs,
prev_response_id,
stream,
+ prompt,
):
class DummyStream:
async def __aiter__(self):
@@ -249,6 +253,7 @@ async def dummy_fetch_response(
handoffs,
prev_response_id,
stream,
+ prompt,
):
class DummyStream:
async def __aiter__(self):
@@ -301,6 +306,7 @@ async def dummy_fetch_response(
handoffs,
prev_response_id,
stream,
+ prompt,
):
class DummyStream:
async def __aiter__(self):
diff --git a/tests/voice/test_workflow.py b/tests/voice/test_workflow.py
index 035a05d56..cfbb95011 100644
--- a/tests/voice/test_workflow.py
+++ b/tests/voice/test_workflow.py
@@ -2,6 +2,7 @@
import json
from collections.abc import AsyncIterator
+from typing import Any
import pytest
from inline_snapshot import snapshot
@@ -53,6 +54,7 @@ async def get_response(
tracing: ModelTracing,
*,
previous_response_id: str | None,
+ prompt: Any | None,
) -> ModelResponse:
raise NotImplementedError("Not implemented")
@@ -67,6 +69,7 @@ async def stream_response(
tracing: ModelTracing,
*,
previous_response_id: str | None,
+ prompt: Any | None,
) -> AsyncIterator[TResponseStreamEvent]:
output = self.get_next_output()
for item in output:
diff --git a/uv.lock b/uv.lock
index 56f56f413..cd26d45f6 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1461,7 +1461,7 @@ wheels = [
[[package]]
name = "openai"
-version = "1.81.0"
+version = "1.87.0"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "anyio" },
@@ -1473,9 +1473,9 @@ dependencies = [
{ name = "tqdm" },
{ name = "typing-extensions" },
]
-sdist = { url = "https://files.pythonhosted.org/packages/1c/89/a1e4f3fa7ca4f7fec90dbf47d93b7cd5ff65924926733af15044e302a192/openai-1.81.0.tar.gz", hash = "sha256:349567a8607e0bcffd28e02f96b5c2397d0d25d06732d90ab3ecbf97abf030f9", size = 456861 }
+sdist = { url = "https://files.pythonhosted.org/packages/47/ed/2b3f6c7e950784e9442115ab8ebeff514d543fb33da10607b39364645a75/openai-1.87.0.tar.gz", hash = "sha256:5c69764171e0db9ef993e7a4d8a01fd8ff1026b66f8bdd005b9461782b6e7dfc", size = 470880 }
wheels = [
- { url = "https://files.pythonhosted.org/packages/02/66/bcc7f9bf48e8610a33e3b5c96a5a644dad032d92404ea2a5e8b43ba067e8/openai-1.81.0-py3-none-any.whl", hash = "sha256:1c71572e22b43876c5d7d65ade0b7b516bb527c3d44ae94111267a09125f7bae", size = 717529 },
+ { url = "https://files.pythonhosted.org/packages/36/ac/313ded47ce1d5bc2ec02ed5dd5506bf5718678a4655ac20f337231d9aae3/openai-1.87.0-py3-none-any.whl", hash = "sha256:f9bcae02ac4fff6522276eee85d33047335cfb692b863bd8261353ce4ada5692", size = 734368 },
]
[[package]]
@@ -1536,7 +1536,7 @@ requires-dist = [
{ name = "litellm", marker = "extra == 'litellm'", specifier = ">=1.67.4.post1,<2" },
{ name = "mcp", marker = "python_full_version >= '3.10'", specifier = ">=1.9.4,<2" },
{ name = "numpy", marker = "python_full_version >= '3.10' and extra == 'voice'", specifier = ">=2.2.0,<3" },
- { name = "openai", specifier = ">=1.81.0" },
+ { name = "openai", specifier = ">=1.87.0" },
{ name = "pydantic", specifier = ">=2.10,<3" },
{ name = "requests", specifier = ">=2.0,<3" },
{ name = "types-requests", specifier = ">=2.0,<3" },
From 901d2ac57c21b5d4fc56fc5d083a8e6c473b7363 Mon Sep 17 00:00:00 2001
From: Rohan Mehta <rm@openai.com>
Date: Mon, 16 Jun 2025 15:49:36 -0400
Subject: [PATCH 43/68] v0.0.18 (#878)
---
pyproject.toml | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/pyproject.toml b/pyproject.toml
index e6d1d7746..6cdf337ee 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
[project]
name = "openai-agents"
-version = "0.0.17"
+version = "0.0.18"
description = "OpenAI Agents SDK"
readme = "README.md"
requires-python = ">=3.9"
From 0cf503e1c2234ba8405166c7f12b29c5c5aac1e5 Mon Sep 17 00:00:00 2001
From: pakrym-oai <pakrym@openai.com>
Date: Tue, 17 Jun 2025 17:41:10 -0700
Subject: [PATCH 44/68] Allow replacing AgentRunner and TraceProvider (#720)
---
src/agents/__init__.py | 2 +
src/agents/run.py | 301 ++-
src/agents/tracing/__init__.py | 16 +-
src/agents/tracing/create.py | 32 +-
src/agents/tracing/provider.py | 294 +++
src/agents/tracing/setup.py | 219 +-
src/agents/tracing/util.py | 19 +-
tests/conftest.py | 10 +-
tests/models/test_map.py | 9 +-
tests/test_agent_config.py | 11 +-
tests/test_handoff_tool.py | 10 +-
tests/test_output_tool.py | 16 +-
tests/test_run.py | 26 +
tests/test_run_config.py | 2 +-
tests/test_run_step_execution.py | 6 +-
tests/test_run_step_processing.py | 12 +-
tests/voice/test_workflow.py | 5 +-
uv.lock | 3374 ++++++++++++++---------------
18 files changed, 2309 insertions(+), 2055 deletions(-)
create mode 100644 src/agents/tracing/provider.py
create mode 100644 tests/test_run.py
diff --git a/src/agents/__init__.py b/src/agents/__init__.py
index a52347605..3eecaead0 100644
--- a/src/agents/__init__.py
+++ b/src/agents/__init__.py
@@ -104,6 +104,7 @@
handoff_span,
mcp_tools_span,
set_trace_processors,
+ set_trace_provider,
set_tracing_disabled,
set_tracing_export_api_key,
speech_group_span,
@@ -246,6 +247,7 @@ def enable_verbose_stdout_logging():
"guardrail_span",
"handoff_span",
"set_trace_processors",
+ "set_trace_provider",
"set_tracing_disabled",
"speech_group_span",
"transcription_span",
diff --git a/src/agents/run.py b/src/agents/run.py
index 10148a323..8a44a0e54 100644
--- a/src/agents/run.py
+++ b/src/agents/run.py
@@ -3,12 +3,13 @@
import asyncio
import copy
from dataclasses import dataclass, field
-from typing import Any, cast
+from typing import Any, Generic, cast
from openai.types.responses import ResponseCompletedEvent
from openai.types.responses.response_prompt_param import (
ResponsePromptParam,
)
+from typing_extensions import NotRequired, TypedDict, Unpack
from ._run_impl import (
AgentToolUseTracker,
@@ -31,7 +32,12 @@
OutputGuardrailTripwireTriggered,
RunErrorDetails,
)
-from .guardrail import InputGuardrail, InputGuardrailResult, OutputGuardrail, OutputGuardrailResult
+from .guardrail import (
+ InputGuardrail,
+ InputGuardrailResult,
+ OutputGuardrail,
+ OutputGuardrailResult,
+)
from .handoffs import Handoff, HandoffInputFilter, handoff
from .items import ItemHelpers, ModelResponse, RunItem, TResponseInputItem
from .lifecycle import RunHooks
@@ -50,6 +56,27 @@
DEFAULT_MAX_TURNS = 10
+DEFAULT_AGENT_RUNNER: AgentRunner = None # type: ignore
+# the value is set at the end of the module
+
+
+def set_default_agent_runner(runner: AgentRunner | None) -> None:
+ """
+ WARNING: this class is experimental and not part of the public API
+ It should not be used directly.
+ """
+ global DEFAULT_AGENT_RUNNER
+ DEFAULT_AGENT_RUNNER = runner or AgentRunner()
+
+
+def get_default_agent_runner() -> AgentRunner:
+ """
+ WARNING: this class is experimental and not part of the public API
+ It should not be used directly.
+ """
+ global DEFAULT_AGENT_RUNNER
+ return DEFAULT_AGENT_RUNNER
+
@dataclass
class RunConfig:
@@ -110,6 +137,25 @@ class RunConfig:
"""
+class RunOptions(TypedDict, Generic[TContext]):
+ """Arguments for ``AgentRunner`` methods."""
+
+ context: NotRequired[TContext | None]
+ """The context for the run."""
+
+ max_turns: NotRequired[int]
+ """The maximum number of turns to run for."""
+
+ hooks: NotRequired[RunHooks[TContext] | None]
+ """Lifecycle hooks for the run."""
+
+ run_config: NotRequired[RunConfig | None]
+ """Run configuration."""
+
+ previous_response_id: NotRequired[str | None]
+ """The ID of the previous response, if any."""
+
+
class Runner:
@classmethod
async def run(
@@ -130,13 +176,10 @@ async def run(
`agent.output_type`, the loop terminates.
3. If there's a handoff, we run the loop again, with the new agent.
4. Else, we run tool calls (if any), and re-run the loop.
-
In two cases, the agent may raise an exception:
1. If the max_turns is exceeded, a MaxTurnsExceeded exception is raised.
2. If a guardrail tripwire is triggered, a GuardrailTripwireTriggered exception is raised.
-
Note that only the first agent's input guardrails are run.
-
Args:
starting_agent: The starting agent to run.
input: The initial input to the agent. You can pass a single string for a user message,
@@ -148,11 +191,139 @@ async def run(
run_config: Global settings for the entire agent run.
previous_response_id: The ID of the previous response, if using OpenAI models via the
Responses API, this allows you to skip passing in input from the previous turn.
+ Returns:
+ A run result containing all the inputs, guardrail results and the output of the last
+ agent. Agents may perform handoffs, so we don't know the specific type of the output.
+ """
+ runner = DEFAULT_AGENT_RUNNER
+ return await runner.run(
+ starting_agent,
+ input,
+ context=context,
+ max_turns=max_turns,
+ hooks=hooks,
+ run_config=run_config,
+ previous_response_id=previous_response_id,
+ )
+ @classmethod
+ def run_sync(
+ cls,
+ starting_agent: Agent[TContext],
+ input: str | list[TResponseInputItem],
+ *,
+ context: TContext | None = None,
+ max_turns: int = DEFAULT_MAX_TURNS,
+ hooks: RunHooks[TContext] | None = None,
+ run_config: RunConfig | None = None,
+ previous_response_id: str | None = None,
+ ) -> RunResult:
+ """Run a workflow synchronously, starting at the given agent. Note that this just wraps the
+ `run` method, so it will not work if there's already an event loop (e.g. inside an async
+ function, or in a Jupyter notebook or async context like FastAPI). For those cases, use
+ the `run` method instead.
+ The agent will run in a loop until a final output is generated. The loop runs like so:
+ 1. The agent is invoked with the given input.
+ 2. If there is a final output (i.e. the agent produces something of type
+ `agent.output_type`, the loop terminates.
+ 3. If there's a handoff, we run the loop again, with the new agent.
+ 4. Else, we run tool calls (if any), and re-run the loop.
+ In two cases, the agent may raise an exception:
+ 1. If the max_turns is exceeded, a MaxTurnsExceeded exception is raised.
+ 2. If a guardrail tripwire is triggered, a GuardrailTripwireTriggered exception is raised.
+ Note that only the first agent's input guardrails are run.
+ Args:
+ starting_agent: The starting agent to run.
+ input: The initial input to the agent. You can pass a single string for a user message,
+ or a list of input items.
+ context: The context to run the agent with.
+ max_turns: The maximum number of turns to run the agent for. A turn is defined as one
+ AI invocation (including any tool calls that might occur).
+ hooks: An object that receives callbacks on various lifecycle events.
+ run_config: Global settings for the entire agent run.
+ previous_response_id: The ID of the previous response, if using OpenAI models via the
+ Responses API, this allows you to skip passing in input from the previous turn.
Returns:
A run result containing all the inputs, guardrail results and the output of the last
agent. Agents may perform handoffs, so we don't know the specific type of the output.
"""
+ runner = DEFAULT_AGENT_RUNNER
+ return runner.run_sync(
+ starting_agent,
+ input,
+ context=context,
+ max_turns=max_turns,
+ hooks=hooks,
+ run_config=run_config,
+ previous_response_id=previous_response_id,
+ )
+
+ @classmethod
+ def run_streamed(
+ cls,
+ starting_agent: Agent[TContext],
+ input: str | list[TResponseInputItem],
+ context: TContext | None = None,
+ max_turns: int = DEFAULT_MAX_TURNS,
+ hooks: RunHooks[TContext] | None = None,
+ run_config: RunConfig | None = None,
+ previous_response_id: str | None = None,
+ ) -> RunResultStreaming:
+ """Run a workflow starting at the given agent in streaming mode. The returned result object
+ contains a method you can use to stream semantic events as they are generated.
+ The agent will run in a loop until a final output is generated. The loop runs like so:
+ 1. The agent is invoked with the given input.
+ 2. If there is a final output (i.e. the agent produces something of type
+ `agent.output_type`, the loop terminates.
+ 3. If there's a handoff, we run the loop again, with the new agent.
+ 4. Else, we run tool calls (if any), and re-run the loop.
+ In two cases, the agent may raise an exception:
+ 1. If the max_turns is exceeded, a MaxTurnsExceeded exception is raised.
+ 2. If a guardrail tripwire is triggered, a GuardrailTripwireTriggered exception is raised.
+ Note that only the first agent's input guardrails are run.
+ Args:
+ starting_agent: The starting agent to run.
+ input: The initial input to the agent. You can pass a single string for a user message,
+ or a list of input items.
+ context: The context to run the agent with.
+ max_turns: The maximum number of turns to run the agent for. A turn is defined as one
+ AI invocation (including any tool calls that might occur).
+ hooks: An object that receives callbacks on various lifecycle events.
+ run_config: Global settings for the entire agent run.
+ previous_response_id: The ID of the previous response, if using OpenAI models via the
+ Responses API, this allows you to skip passing in input from the previous turn.
+ Returns:
+ A result object that contains data about the run, as well as a method to stream events.
+ """
+ runner = DEFAULT_AGENT_RUNNER
+ return runner.run_streamed(
+ starting_agent,
+ input,
+ context=context,
+ max_turns=max_turns,
+ hooks=hooks,
+ run_config=run_config,
+ previous_response_id=previous_response_id,
+ )
+
+
+class AgentRunner:
+ """
+ WARNING: this class is experimental and not part of the public API
+ It should not be used directly or subclassed.
+ """
+
+ async def run(
+ self,
+ starting_agent: Agent[TContext],
+ input: str | list[TResponseInputItem],
+ **kwargs: Unpack[RunOptions[TContext]],
+ ) -> RunResult:
+ context = kwargs.get("context")
+ max_turns = kwargs.get("max_turns", DEFAULT_MAX_TURNS)
+ hooks = kwargs.get("hooks")
+ run_config = kwargs.get("run_config")
+ previous_response_id = kwargs.get("previous_response_id")
if hooks is None:
hooks = RunHooks[Any]()
if run_config is None:
@@ -184,13 +355,15 @@ async def run(
try:
while True:
- all_tools = await cls._get_all_tools(current_agent, context_wrapper)
+ all_tools = await AgentRunner._get_all_tools(current_agent, context_wrapper)
# Start an agent span if we don't have one. This span is ended if the current
# agent changes, or if the agent loop ends.
if current_span is None:
- handoff_names = [h.agent_name for h in cls._get_handoffs(current_agent)]
- if output_schema := cls._get_output_schema(current_agent):
+ handoff_names = [
+ h.agent_name for h in AgentRunner._get_handoffs(current_agent)
+ ]
+ if output_schema := AgentRunner._get_output_schema(current_agent):
output_type_name = output_schema.name()
else:
output_type_name = "str"
@@ -220,14 +393,14 @@ async def run(
if current_turn == 1:
input_guardrail_results, turn_result = await asyncio.gather(
- cls._run_input_guardrails(
+ self._run_input_guardrails(
starting_agent,
starting_agent.input_guardrails
+ (run_config.input_guardrails or []),
copy.deepcopy(input),
context_wrapper,
),
- cls._run_single_turn(
+ self._run_single_turn(
agent=current_agent,
all_tools=all_tools,
original_input=original_input,
@@ -241,7 +414,7 @@ async def run(
),
)
else:
- turn_result = await cls._run_single_turn(
+ turn_result = await self._run_single_turn(
agent=current_agent,
all_tools=all_tools,
original_input=original_input,
@@ -260,7 +433,7 @@ async def run(
generated_items = turn_result.generated_items
if isinstance(turn_result.next_step, NextStepFinalOutput):
- output_guardrail_results = await cls._run_output_guardrails(
+ output_guardrail_results = await self._run_output_guardrails(
current_agent.output_guardrails + (run_config.output_guardrails or []),
current_agent,
turn_result.next_step.output,
@@ -302,54 +475,19 @@ async def run(
if current_span:
current_span.finish(reset_current=True)
- @classmethod
def run_sync(
- cls,
+ self,
starting_agent: Agent[TContext],
input: str | list[TResponseInputItem],
- *,
- context: TContext | None = None,
- max_turns: int = DEFAULT_MAX_TURNS,
- hooks: RunHooks[TContext] | None = None,
- run_config: RunConfig | None = None,
- previous_response_id: str | None = None,
+ **kwargs: Unpack[RunOptions[TContext]],
) -> RunResult:
- """Run a workflow synchronously, starting at the given agent. Note that this just wraps the
- `run` method, so it will not work if there's already an event loop (e.g. inside an async
- function, or in a Jupyter notebook or async context like FastAPI). For those cases, use
- the `run` method instead.
-
- The agent will run in a loop until a final output is generated. The loop runs like so:
- 1. The agent is invoked with the given input.
- 2. If there is a final output (i.e. the agent produces something of type
- `agent.output_type`, the loop terminates.
- 3. If there's a handoff, we run the loop again, with the new agent.
- 4. Else, we run tool calls (if any), and re-run the loop.
-
- In two cases, the agent may raise an exception:
- 1. If the max_turns is exceeded, a MaxTurnsExceeded exception is raised.
- 2. If a guardrail tripwire is triggered, a GuardrailTripwireTriggered exception is raised.
-
- Note that only the first agent's input guardrails are run.
-
- Args:
- starting_agent: The starting agent to run.
- input: The initial input to the agent. You can pass a single string for a user message,
- or a list of input items.
- context: The context to run the agent with.
- max_turns: The maximum number of turns to run the agent for. A turn is defined as one
- AI invocation (including any tool calls that might occur).
- hooks: An object that receives callbacks on various lifecycle events.
- run_config: Global settings for the entire agent run.
- previous_response_id: The ID of the previous response, if using OpenAI models via the
- Responses API, this allows you to skip passing in input from the previous turn.
-
- Returns:
- A run result containing all the inputs, guardrail results and the output of the last
- agent. Agents may perform handoffs, so we don't know the specific type of the output.
- """
+ context = kwargs.get("context")
+ max_turns = kwargs.get("max_turns", DEFAULT_MAX_TURNS)
+ hooks = kwargs.get("hooks")
+ run_config = kwargs.get("run_config")
+ previous_response_id = kwargs.get("previous_response_id")
return asyncio.get_event_loop().run_until_complete(
- cls.run(
+ self.run(
starting_agent,
input,
context=context,
@@ -360,47 +498,17 @@ def run_sync(
)
)
- @classmethod
def run_streamed(
- cls,
+ self,
starting_agent: Agent[TContext],
input: str | list[TResponseInputItem],
- context: TContext | None = None,
- max_turns: int = DEFAULT_MAX_TURNS,
- hooks: RunHooks[TContext] | None = None,
- run_config: RunConfig | None = None,
- previous_response_id: str | None = None,
+ **kwargs: Unpack[RunOptions[TContext]],
) -> RunResultStreaming:
- """Run a workflow starting at the given agent in streaming mode. The returned result object
- contains a method you can use to stream semantic events as they are generated.
-
- The agent will run in a loop until a final output is generated. The loop runs like so:
- 1. The agent is invoked with the given input.
- 2. If there is a final output (i.e. the agent produces something of type
- `agent.output_type`, the loop terminates.
- 3. If there's a handoff, we run the loop again, with the new agent.
- 4. Else, we run tool calls (if any), and re-run the loop.
-
- In two cases, the agent may raise an exception:
- 1. If the max_turns is exceeded, a MaxTurnsExceeded exception is raised.
- 2. If a guardrail tripwire is triggered, a GuardrailTripwireTriggered exception is raised.
-
- Note that only the first agent's input guardrails are run.
-
- Args:
- starting_agent: The starting agent to run.
- input: The initial input to the agent. You can pass a single string for a user message,
- or a list of input items.
- context: The context to run the agent with.
- max_turns: The maximum number of turns to run the agent for. A turn is defined as one
- AI invocation (including any tool calls that might occur).
- hooks: An object that receives callbacks on various lifecycle events.
- run_config: Global settings for the entire agent run.
- previous_response_id: The ID of the previous response, if using OpenAI models via the
- Responses API, this allows you to skip passing in input from the previous turn.
- Returns:
- A result object that contains data about the run, as well as a method to stream events.
- """
+ context = kwargs.get("context")
+ max_turns = kwargs.get("max_turns", DEFAULT_MAX_TURNS)
+ hooks = kwargs.get("hooks")
+ run_config = kwargs.get("run_config")
+ previous_response_id = kwargs.get("previous_response_id")
if hooks is None:
hooks = RunHooks[Any]()
if run_config is None:
@@ -421,7 +529,7 @@ def run_streamed(
)
)
- output_schema = cls._get_output_schema(starting_agent)
+ output_schema = AgentRunner._get_output_schema(starting_agent)
context_wrapper: RunContextWrapper[TContext] = RunContextWrapper(
context=context # type: ignore
)
@@ -444,7 +552,7 @@ def run_streamed(
# Kick off the actual agent loop in the background and return the streamed result object.
streamed_result._run_impl_task = asyncio.create_task(
- cls._run_streamed_impl(
+ self._start_streaming(
starting_input=input,
streamed_result=streamed_result,
starting_agent=starting_agent,
@@ -501,7 +609,7 @@ async def _run_input_guardrails_with_queue(
streamed_result.input_guardrail_results = guardrail_results
@classmethod
- async def _run_streamed_impl(
+ async def _start_streaming(
cls,
starting_input: str | list[TResponseInputItem],
streamed_result: RunResultStreaming,
@@ -1008,3 +1116,6 @@ def _get_model(cls, agent: Agent[Any], run_config: RunConfig) -> Model:
return agent.model
return run_config.model_provider.get_model(agent.model)
+
+
+DEFAULT_AGENT_RUNNER = AgentRunner()
diff --git a/src/agents/tracing/__init__.py b/src/agents/tracing/__init__.py
index 9df944263..64b0bd71f 100644
--- a/src/agents/tracing/__init__.py
+++ b/src/agents/tracing/__init__.py
@@ -1,5 +1,7 @@
import atexit
+from agents.tracing.provider import DefaultTraceProvider, TraceProvider
+
from .create import (
agent_span,
custom_span,
@@ -18,7 +20,7 @@
)
from .processor_interface import TracingProcessor
from .processors import default_exporter, default_processor
-from .setup import GLOBAL_TRACE_PROVIDER
+from .setup import get_trace_provider, set_trace_provider
from .span_data import (
AgentSpanData,
CustomSpanData,
@@ -45,10 +47,12 @@
"generation_span",
"get_current_span",
"get_current_trace",
+ "get_trace_provider",
"guardrail_span",
"handoff_span",
"response_span",
"set_trace_processors",
+ "set_trace_provider",
"set_tracing_disabled",
"trace",
"Trace",
@@ -67,6 +71,7 @@
"SpeechSpanData",
"TranscriptionSpanData",
"TracingProcessor",
+ "TraceProvider",
"gen_trace_id",
"gen_span_id",
"speech_group_span",
@@ -80,21 +85,21 @@ def add_trace_processor(span_processor: TracingProcessor) -> None:
"""
Adds a new trace processor. This processor will receive all traces/spans.
"""
- GLOBAL_TRACE_PROVIDER.register_processor(span_processor)
+ get_trace_provider().register_processor(span_processor)
def set_trace_processors(processors: list[TracingProcessor]) -> None:
"""
Set the list of trace processors. This will replace the current list of processors.
"""
- GLOBAL_TRACE_PROVIDER.set_processors(processors)
+ get_trace_provider().set_processors(processors)
def set_tracing_disabled(disabled: bool) -> None:
"""
Set whether tracing is globally disabled.
"""
- GLOBAL_TRACE_PROVIDER.set_disabled(disabled)
+ get_trace_provider().set_disabled(disabled)
def set_tracing_export_api_key(api_key: str) -> None:
@@ -104,10 +109,11 @@ def set_tracing_export_api_key(api_key: str) -> None:
default_exporter().set_api_key(api_key)
+set_trace_provider(DefaultTraceProvider())
# Add the default processor, which exports traces and spans to the backend in batches. You can
# change the default behavior by either:
# 1. calling add_trace_processor(), which adds additional processors, or
# 2. calling set_trace_processors(), which replaces the default processor.
add_trace_processor(default_processor())
-atexit.register(GLOBAL_TRACE_PROVIDER.shutdown)
+atexit.register(get_trace_provider().shutdown)
diff --git a/src/agents/tracing/create.py b/src/agents/tracing/create.py
index b6fe46104..ac451abf5 100644
--- a/src/agents/tracing/create.py
+++ b/src/agents/tracing/create.py
@@ -4,7 +4,7 @@
from typing import TYPE_CHECKING, Any
from ..logger import logger
-from .setup import GLOBAL_TRACE_PROVIDER
+from .setup import get_trace_provider
from .span_data import (
AgentSpanData,
CustomSpanData,
@@ -56,13 +56,13 @@ def trace(
Returns:
The newly created trace object.
"""
- current_trace = GLOBAL_TRACE_PROVIDER.get_current_trace()
+ current_trace = get_trace_provider().get_current_trace()
if current_trace:
logger.warning(
"Trace already exists. Creating a new trace, but this is probably a mistake."
)
- return GLOBAL_TRACE_PROVIDER.create_trace(
+ return get_trace_provider().create_trace(
name=workflow_name,
trace_id=trace_id,
group_id=group_id,
@@ -73,12 +73,12 @@ def trace(
def get_current_trace() -> Trace | None:
"""Returns the currently active trace, if present."""
- return GLOBAL_TRACE_PROVIDER.get_current_trace()
+ return get_trace_provider().get_current_trace()
def get_current_span() -> Span[Any] | None:
"""Returns the currently active span, if present."""
- return GLOBAL_TRACE_PROVIDER.get_current_span()
+ return get_trace_provider().get_current_span()
def agent_span(
@@ -108,7 +108,7 @@ def agent_span(
Returns:
The newly created agent span.
"""
- return GLOBAL_TRACE_PROVIDER.create_span(
+ return get_trace_provider().create_span(
span_data=AgentSpanData(name=name, handoffs=handoffs, tools=tools, output_type=output_type),
span_id=span_id,
parent=parent,
@@ -141,7 +141,7 @@ def function_span(
Returns:
The newly created function span.
"""
- return GLOBAL_TRACE_PROVIDER.create_span(
+ return get_trace_provider().create_span(
span_data=FunctionSpanData(name=name, input=input, output=output),
span_id=span_id,
parent=parent,
@@ -183,7 +183,7 @@ def generation_span(
Returns:
The newly created generation span.
"""
- return GLOBAL_TRACE_PROVIDER.create_span(
+ return get_trace_provider().create_span(
span_data=GenerationSpanData(
input=input,
output=output,
@@ -215,7 +215,7 @@ def response_span(
trace/span as the parent.
disabled: If True, we will return a Span but the Span will not be recorded.
"""
- return GLOBAL_TRACE_PROVIDER.create_span(
+ return get_trace_provider().create_span(
span_data=ResponseSpanData(response=response),
span_id=span_id,
parent=parent,
@@ -246,7 +246,7 @@ def handoff_span(
Returns:
The newly created handoff span.
"""
- return GLOBAL_TRACE_PROVIDER.create_span(
+ return get_trace_provider().create_span(
span_data=HandoffSpanData(from_agent=from_agent, to_agent=to_agent),
span_id=span_id,
parent=parent,
@@ -278,7 +278,7 @@ def custom_span(
Returns:
The newly created custom span.
"""
- return GLOBAL_TRACE_PROVIDER.create_span(
+ return get_trace_provider().create_span(
span_data=CustomSpanData(name=name, data=data or {}),
span_id=span_id,
parent=parent,
@@ -306,7 +306,7 @@ def guardrail_span(
trace/span as the parent.
disabled: If True, we will return a Span but the Span will not be recorded.
"""
- return GLOBAL_TRACE_PROVIDER.create_span(
+ return get_trace_provider().create_span(
span_data=GuardrailSpanData(name=name, triggered=triggered),
span_id=span_id,
parent=parent,
@@ -344,7 +344,7 @@ def transcription_span(
Returns:
The newly created speech-to-text span.
"""
- return GLOBAL_TRACE_PROVIDER.create_span(
+ return get_trace_provider().create_span(
span_data=TranscriptionSpanData(
input=input,
input_format=input_format,
@@ -386,7 +386,7 @@ def speech_span(
trace/span as the parent.
disabled: If True, we will return a Span but the Span will not be recorded.
"""
- return GLOBAL_TRACE_PROVIDER.create_span(
+ return get_trace_provider().create_span(
span_data=SpeechSpanData(
model=model,
input=input,
@@ -419,7 +419,7 @@ def speech_group_span(
trace/span as the parent.
disabled: If True, we will return a Span but the Span will not be recorded.
"""
- return GLOBAL_TRACE_PROVIDER.create_span(
+ return get_trace_provider().create_span(
span_data=SpeechGroupSpanData(input=input),
span_id=span_id,
parent=parent,
@@ -447,7 +447,7 @@ def mcp_tools_span(
trace/span as the parent.
disabled: If True, we will return a Span but the Span will not be recorded.
"""
- return GLOBAL_TRACE_PROVIDER.create_span(
+ return get_trace_provider().create_span(
span_data=MCPListToolsSpanData(server=server, result=result),
span_id=span_id,
parent=parent,
diff --git a/src/agents/tracing/provider.py b/src/agents/tracing/provider.py
new file mode 100644
index 000000000..38d3b7ab3
--- /dev/null
+++ b/src/agents/tracing/provider.py
@@ -0,0 +1,294 @@
+from __future__ import annotations
+
+import os
+import threading
+import uuid
+from abc import ABC, abstractmethod
+from datetime import datetime, timezone
+from typing import Any
+
+from ..logger import logger
+from .processor_interface import TracingProcessor
+from .scope import Scope
+from .spans import NoOpSpan, Span, SpanImpl, TSpanData
+from .traces import NoOpTrace, Trace, TraceImpl
+
+
+class SynchronousMultiTracingProcessor(TracingProcessor):
+ """
+ Forwards all calls to a list of TracingProcessors, in order of registration.
+ """
+
+ def __init__(self):
+ # Using a tuple to avoid race conditions when iterating over processors
+ self._processors: tuple[TracingProcessor, ...] = ()
+ self._lock = threading.Lock()
+
+ def add_tracing_processor(self, tracing_processor: TracingProcessor):
+ """
+ Add a processor to the list of processors. Each processor will receive all traces/spans.
+ """
+ with self._lock:
+ self._processors += (tracing_processor,)
+
+ def set_processors(self, processors: list[TracingProcessor]):
+ """
+ Set the list of processors. This will replace the current list of processors.
+ """
+ with self._lock:
+ self._processors = tuple(processors)
+
+ def on_trace_start(self, trace: Trace) -> None:
+ """
+ Called when a trace is started.
+ """
+ for processor in self._processors:
+ processor.on_trace_start(trace)
+
+ def on_trace_end(self, trace: Trace) -> None:
+ """
+ Called when a trace is finished.
+ """
+ for processor in self._processors:
+ processor.on_trace_end(trace)
+
+ def on_span_start(self, span: Span[Any]) -> None:
+ """
+ Called when a span is started.
+ """
+ for processor in self._processors:
+ processor.on_span_start(span)
+
+ def on_span_end(self, span: Span[Any]) -> None:
+ """
+ Called when a span is finished.
+ """
+ for processor in self._processors:
+ processor.on_span_end(span)
+
+ def shutdown(self) -> None:
+ """
+ Called when the application stops.
+ """
+ for processor in self._processors:
+ logger.debug(f"Shutting down trace processor {processor}")
+ processor.shutdown()
+
+ def force_flush(self):
+ """
+ Force the processors to flush their buffers.
+ """
+ for processor in self._processors:
+ processor.force_flush()
+
+
+class TraceProvider(ABC):
+ """Interface for creating traces and spans."""
+
+ @abstractmethod
+ def register_processor(self, processor: TracingProcessor) -> None:
+ """Add a processor that will receive all traces and spans."""
+
+ @abstractmethod
+ def set_processors(self, processors: list[TracingProcessor]) -> None:
+ """Replace the list of processors with ``processors``."""
+
+ @abstractmethod
+ def get_current_trace(self) -> Trace | None:
+ """Return the currently active trace, if any."""
+
+ @abstractmethod
+ def get_current_span(self) -> Span[Any] | None:
+ """Return the currently active span, if any."""
+
+ @abstractmethod
+ def set_disabled(self, disabled: bool) -> None:
+ """Enable or disable tracing globally."""
+
+ @abstractmethod
+ def time_iso(self) -> str:
+ """Return the current time in ISO 8601 format."""
+
+ @abstractmethod
+ def gen_trace_id(self) -> str:
+ """Generate a new trace identifier."""
+
+ @abstractmethod
+ def gen_span_id(self) -> str:
+ """Generate a new span identifier."""
+
+ @abstractmethod
+ def gen_group_id(self) -> str:
+ """Generate a new group identifier."""
+
+ @abstractmethod
+ def create_trace(
+ self,
+ name: str,
+ trace_id: str | None = None,
+ group_id: str | None = None,
+ metadata: dict[str, Any] | None = None,
+ disabled: bool = False,
+ ) -> Trace:
+ """Create a new trace."""
+
+ @abstractmethod
+ def create_span(
+ self,
+ span_data: TSpanData,
+ span_id: str | None = None,
+ parent: Trace | Span[Any] | None = None,
+ disabled: bool = False,
+ ) -> Span[TSpanData]:
+ """Create a new span."""
+
+ @abstractmethod
+ def shutdown(self) -> None:
+ """Clean up any resources used by the provider."""
+
+
+class DefaultTraceProvider(TraceProvider):
+ def __init__(self) -> None:
+ self._multi_processor = SynchronousMultiTracingProcessor()
+ self._disabled = os.environ.get("OPENAI_AGENTS_DISABLE_TRACING", "false").lower() in (
+ "true",
+ "1",
+ )
+
+ def register_processor(self, processor: TracingProcessor):
+ """
+ Add a processor to the list of processors. Each processor will receive all traces/spans.
+ """
+ self._multi_processor.add_tracing_processor(processor)
+
+ def set_processors(self, processors: list[TracingProcessor]):
+ """
+ Set the list of processors. This will replace the current list of processors.
+ """
+ self._multi_processor.set_processors(processors)
+
+ def get_current_trace(self) -> Trace | None:
+ """
+ Returns the currently active trace, if any.
+ """
+ return Scope.get_current_trace()
+
+ def get_current_span(self) -> Span[Any] | None:
+ """
+ Returns the currently active span, if any.
+ """
+ return Scope.get_current_span()
+
+ def set_disabled(self, disabled: bool) -> None:
+ """
+ Set whether tracing is disabled.
+ """
+ self._disabled = disabled
+
+ def time_iso(self) -> str:
+ """Return the current time in ISO 8601 format."""
+ return datetime.now(timezone.utc).isoformat()
+
+ def gen_trace_id(self) -> str:
+ """Generate a new trace ID."""
+ return f"trace_{uuid.uuid4().hex}"
+
+ def gen_span_id(self) -> str:
+ """Generate a new span ID."""
+ return f"span_{uuid.uuid4().hex[:24]}"
+
+ def gen_group_id(self) -> str:
+ """Generate a new group ID."""
+ return f"group_{uuid.uuid4().hex[:24]}"
+
+ def create_trace(
+ self,
+ name: str,
+ trace_id: str | None = None,
+ group_id: str | None = None,
+ metadata: dict[str, Any] | None = None,
+ disabled: bool = False,
+ ) -> Trace:
+ """
+ Create a new trace.
+ """
+ if self._disabled or disabled:
+ logger.debug(f"Tracing is disabled. Not creating trace {name}")
+ return NoOpTrace()
+
+ trace_id = trace_id or self.gen_trace_id()
+
+ logger.debug(f"Creating trace {name} with id {trace_id}")
+
+ return TraceImpl(
+ name=name,
+ trace_id=trace_id,
+ group_id=group_id,
+ metadata=metadata,
+ processor=self._multi_processor,
+ )
+
+ def create_span(
+ self,
+ span_data: TSpanData,
+ span_id: str | None = None,
+ parent: Trace | Span[Any] | None = None,
+ disabled: bool = False,
+ ) -> Span[TSpanData]:
+ """
+ Create a new span.
+ """
+ if self._disabled or disabled:
+ logger.debug(f"Tracing is disabled. Not creating span {span_data}")
+ return NoOpSpan(span_data)
+
+ if not parent:
+ current_span = Scope.get_current_span()
+ current_trace = Scope.get_current_trace()
+ if current_trace is None:
+ logger.error(
+ "No active trace. Make sure to start a trace with `trace()` first"
+ "Returning NoOpSpan."
+ )
+ return NoOpSpan(span_data)
+ elif isinstance(current_trace, NoOpTrace) or isinstance(current_span, NoOpSpan):
+ logger.debug(
+ f"Parent {current_span} or {current_trace} is no-op, returning NoOpSpan"
+ )
+ return NoOpSpan(span_data)
+
+ parent_id = current_span.span_id if current_span else None
+ trace_id = current_trace.trace_id
+
+ elif isinstance(parent, Trace):
+ if isinstance(parent, NoOpTrace):
+ logger.debug(f"Parent {parent} is no-op, returning NoOpSpan")
+ return NoOpSpan(span_data)
+ trace_id = parent.trace_id
+ parent_id = None
+ elif isinstance(parent, Span):
+ if isinstance(parent, NoOpSpan):
+ logger.debug(f"Parent {parent} is no-op, returning NoOpSpan")
+ return NoOpSpan(span_data)
+ parent_id = parent.span_id
+ trace_id = parent.trace_id
+
+ logger.debug(f"Creating span {span_data} with id {span_id}")
+
+ return SpanImpl(
+ trace_id=trace_id,
+ span_id=span_id or self.gen_span_id(),
+ parent_id=parent_id,
+ processor=self._multi_processor,
+ span_data=span_data,
+ )
+
+ def shutdown(self) -> None:
+ if self._disabled:
+ return
+
+ try:
+ logger.debug("Shutting down trace provider")
+ self._multi_processor.shutdown()
+ except Exception as e:
+ logger.error(f"Error shutting down trace provider: {e}")
diff --git a/src/agents/tracing/setup.py b/src/agents/tracing/setup.py
index 9e27d210b..3a56b728f 100644
--- a/src/agents/tracing/setup.py
+++ b/src/agents/tracing/setup.py
@@ -1,214 +1,21 @@
from __future__ import annotations
-import os
-import threading
-from typing import Any
+from typing import TYPE_CHECKING
-from ..logger import logger
-from . import util
-from .processor_interface import TracingProcessor
-from .scope import Scope
-from .spans import NoOpSpan, Span, SpanImpl, TSpanData
-from .traces import NoOpTrace, Trace, TraceImpl
+if TYPE_CHECKING:
+ from .provider import TraceProvider
+GLOBAL_TRACE_PROVIDER: TraceProvider | None = None
-class SynchronousMultiTracingProcessor(TracingProcessor):
- """
- Forwards all calls to a list of TracingProcessors, in order of registration.
- """
- def __init__(self):
- # Using a tuple to avoid race conditions when iterating over processors
- self._processors: tuple[TracingProcessor, ...] = ()
- self._lock = threading.Lock()
+def set_trace_provider(provider: TraceProvider) -> None:
+ """Set the global trace provider used by tracing utilities."""
+ global GLOBAL_TRACE_PROVIDER
+ GLOBAL_TRACE_PROVIDER = provider
- def add_tracing_processor(self, tracing_processor: TracingProcessor):
- """
- Add a processor to the list of processors. Each processor will receive all traces/spans.
- """
- with self._lock:
- self._processors += (tracing_processor,)
- def set_processors(self, processors: list[TracingProcessor]):
- """
- Set the list of processors. This will replace the current list of processors.
- """
- with self._lock:
- self._processors = tuple(processors)
-
- def on_trace_start(self, trace: Trace) -> None:
- """
- Called when a trace is started.
- """
- for processor in self._processors:
- processor.on_trace_start(trace)
-
- def on_trace_end(self, trace: Trace) -> None:
- """
- Called when a trace is finished.
- """
- for processor in self._processors:
- processor.on_trace_end(trace)
-
- def on_span_start(self, span: Span[Any]) -> None:
- """
- Called when a span is started.
- """
- for processor in self._processors:
- processor.on_span_start(span)
-
- def on_span_end(self, span: Span[Any]) -> None:
- """
- Called when a span is finished.
- """
- for processor in self._processors:
- processor.on_span_end(span)
-
- def shutdown(self) -> None:
- """
- Called when the application stops.
- """
- for processor in self._processors:
- logger.debug(f"Shutting down trace processor {processor}")
- processor.shutdown()
-
- def force_flush(self):
- """
- Force the processors to flush their buffers.
- """
- for processor in self._processors:
- processor.force_flush()
-
-
-class TraceProvider:
- def __init__(self):
- self._multi_processor = SynchronousMultiTracingProcessor()
- self._disabled = os.environ.get("OPENAI_AGENTS_DISABLE_TRACING", "false").lower() in (
- "true",
- "1",
- )
-
- def register_processor(self, processor: TracingProcessor):
- """
- Add a processor to the list of processors. Each processor will receive all traces/spans.
- """
- self._multi_processor.add_tracing_processor(processor)
-
- def set_processors(self, processors: list[TracingProcessor]):
- """
- Set the list of processors. This will replace the current list of processors.
- """
- self._multi_processor.set_processors(processors)
-
- def get_current_trace(self) -> Trace | None:
- """
- Returns the currently active trace, if any.
- """
- return Scope.get_current_trace()
-
- def get_current_span(self) -> Span[Any] | None:
- """
- Returns the currently active span, if any.
- """
- return Scope.get_current_span()
-
- def set_disabled(self, disabled: bool) -> None:
- """
- Set whether tracing is disabled.
- """
- self._disabled = disabled
-
- def create_trace(
- self,
- name: str,
- trace_id: str | None = None,
- group_id: str | None = None,
- metadata: dict[str, Any] | None = None,
- disabled: bool = False,
- ) -> Trace:
- """
- Create a new trace.
- """
- if self._disabled or disabled:
- logger.debug(f"Tracing is disabled. Not creating trace {name}")
- return NoOpTrace()
-
- trace_id = trace_id or util.gen_trace_id()
-
- logger.debug(f"Creating trace {name} with id {trace_id}")
-
- return TraceImpl(
- name=name,
- trace_id=trace_id,
- group_id=group_id,
- metadata=metadata,
- processor=self._multi_processor,
- )
-
- def create_span(
- self,
- span_data: TSpanData,
- span_id: str | None = None,
- parent: Trace | Span[Any] | None = None,
- disabled: bool = False,
- ) -> Span[TSpanData]:
- """
- Create a new span.
- """
- if self._disabled or disabled:
- logger.debug(f"Tracing is disabled. Not creating span {span_data}")
- return NoOpSpan(span_data)
-
- if not parent:
- current_span = Scope.get_current_span()
- current_trace = Scope.get_current_trace()
- if current_trace is None:
- logger.error(
- "No active trace. Make sure to start a trace with `trace()` first"
- "Returning NoOpSpan."
- )
- return NoOpSpan(span_data)
- elif isinstance(current_trace, NoOpTrace) or isinstance(current_span, NoOpSpan):
- logger.debug(
- f"Parent {current_span} or {current_trace} is no-op, returning NoOpSpan"
- )
- return NoOpSpan(span_data)
-
- parent_id = current_span.span_id if current_span else None
- trace_id = current_trace.trace_id
-
- elif isinstance(parent, Trace):
- if isinstance(parent, NoOpTrace):
- logger.debug(f"Parent {parent} is no-op, returning NoOpSpan")
- return NoOpSpan(span_data)
- trace_id = parent.trace_id
- parent_id = None
- elif isinstance(parent, Span):
- if isinstance(parent, NoOpSpan):
- logger.debug(f"Parent {parent} is no-op, returning NoOpSpan")
- return NoOpSpan(span_data)
- parent_id = parent.span_id
- trace_id = parent.trace_id
-
- logger.debug(f"Creating span {span_data} with id {span_id}")
-
- return SpanImpl(
- trace_id=trace_id,
- span_id=span_id,
- parent_id=parent_id,
- processor=self._multi_processor,
- span_data=span_data,
- )
-
- def shutdown(self) -> None:
- if self._disabled:
- return
-
- try:
- logger.debug("Shutting down trace provider")
- self._multi_processor.shutdown()
- except Exception as e:
- logger.error(f"Error shutting down trace provider: {e}")
-
-
-GLOBAL_TRACE_PROVIDER = TraceProvider()
+def get_trace_provider() -> TraceProvider:
+ """Get the global trace provider used by tracing utilities."""
+ if GLOBAL_TRACE_PROVIDER is None:
+ raise RuntimeError("Trace provider not set")
+ return GLOBAL_TRACE_PROVIDER
diff --git a/src/agents/tracing/util.py b/src/agents/tracing/util.py
index f546b4e50..7f436d019 100644
--- a/src/agents/tracing/util.py
+++ b/src/agents/tracing/util.py
@@ -1,22 +1,21 @@
-import uuid
-from datetime import datetime, timezone
+from .setup import get_trace_provider
def time_iso() -> str:
- """Returns the current time in ISO 8601 format."""
- return datetime.now(timezone.utc).isoformat()
+ """Return the current time in ISO 8601 format."""
+ return get_trace_provider().time_iso()
def gen_trace_id() -> str:
- """Generates a new trace ID."""
- return f"trace_{uuid.uuid4().hex}"
+ """Generate a new trace ID."""
+ return get_trace_provider().gen_trace_id()
def gen_span_id() -> str:
- """Generates a new span ID."""
- return f"span_{uuid.uuid4().hex[:24]}"
+ """Generate a new span ID."""
+ return get_trace_provider().gen_span_id()
def gen_group_id() -> str:
- """Generates a new group ID."""
- return f"group_{uuid.uuid4().hex[:24]}"
+ """Generate a new group ID."""
+ return get_trace_provider().gen_group_id()
diff --git a/tests/conftest.py b/tests/conftest.py
index ba0d88221..b73d734d1 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -5,8 +5,9 @@
from agents.models import _openai_shared
from agents.models.openai_chatcompletions import OpenAIChatCompletionsModel
from agents.models.openai_responses import OpenAIResponsesModel
+from agents.run import set_default_agent_runner
from agents.tracing import set_trace_processors
-from agents.tracing.setup import GLOBAL_TRACE_PROVIDER
+from agents.tracing.setup import get_trace_provider
from .testing_processor import SPAN_PROCESSOR_TESTING
@@ -33,11 +34,16 @@ def clear_openai_settings():
_openai_shared._use_responses_by_default = True
+@pytest.fixture(autouse=True)
+def clear_default_runner():
+ set_default_agent_runner(None)
+
+
# This fixture will run after all tests end
@pytest.fixture(autouse=True, scope="session")
def shutdown_trace_provider():
yield
- GLOBAL_TRACE_PROVIDER.shutdown()
+ get_trace_provider().shutdown()
@pytest.fixture(autouse=True)
diff --git a/tests/models/test_map.py b/tests/models/test_map.py
index 6b65fc094..b1a129667 100644
--- a/tests/models/test_map.py
+++ b/tests/models/test_map.py
@@ -1,20 +1,21 @@
-from agents import Agent, OpenAIResponsesModel, RunConfig, Runner
+from agents import Agent, OpenAIResponsesModel, RunConfig
from agents.extensions.models.litellm_model import LitellmModel
+from agents.run import AgentRunner
def test_no_prefix_is_openai():
agent = Agent(model="gpt-4o", instructions="", name="test")
- model = Runner._get_model(agent, RunConfig())
+ model = AgentRunner._get_model(agent, RunConfig())
assert isinstance(model, OpenAIResponsesModel)
def openai_prefix_is_openai():
agent = Agent(model="openai/gpt-4o", instructions="", name="test")
- model = Runner._get_model(agent, RunConfig())
+ model = AgentRunner._get_model(agent, RunConfig())
assert isinstance(model, OpenAIResponsesModel)
def test_litellm_prefix_is_litellm():
agent = Agent(model="litellm/foo/bar", instructions="", name="test")
- model = Runner._get_model(agent, RunConfig())
+ model = AgentRunner._get_model(agent, RunConfig())
assert isinstance(model, LitellmModel)
diff --git a/tests/test_agent_config.py b/tests/test_agent_config.py
index f79c0cf8a..f9423619d 100644
--- a/tests/test_agent_config.py
+++ b/tests/test_agent_config.py
@@ -1,7 +1,8 @@
import pytest
from pydantic import BaseModel
-from agents import Agent, AgentOutputSchema, Handoff, RunContextWrapper, Runner, handoff
+from agents import Agent, AgentOutputSchema, Handoff, RunContextWrapper, handoff
+from agents.run import AgentRunner
@pytest.mark.asyncio
@@ -42,7 +43,7 @@ async def test_handoff_with_agents():
handoffs=[agent_1, agent_2],
)
- handoffs = Runner._get_handoffs(agent_3)
+ handoffs = AgentRunner._get_handoffs(agent_3)
assert len(handoffs) == 2
assert handoffs[0].agent_name == "agent_1"
@@ -77,7 +78,7 @@ async def test_handoff_with_handoff_obj():
],
)
- handoffs = Runner._get_handoffs(agent_3)
+ handoffs = AgentRunner._get_handoffs(agent_3)
assert len(handoffs) == 2
assert handoffs[0].agent_name == "agent_1"
@@ -111,7 +112,7 @@ async def test_handoff_with_handoff_obj_and_agent():
handoffs=[handoff(agent_1), agent_2],
)
- handoffs = Runner._get_handoffs(agent_3)
+ handoffs = AgentRunner._get_handoffs(agent_3)
assert len(handoffs) == 2
assert handoffs[0].agent_name == "agent_1"
@@ -159,7 +160,7 @@ async def test_agent_final_output():
output_type=Foo,
)
- schema = Runner._get_output_schema(agent)
+ schema = AgentRunner._get_output_schema(agent)
assert isinstance(schema, AgentOutputSchema)
assert schema is not None
assert schema.output_type == Foo
diff --git a/tests/test_handoff_tool.py b/tests/test_handoff_tool.py
index 0a8f064f1..a1b5b80ba 100644
--- a/tests/test_handoff_tool.py
+++ b/tests/test_handoff_tool.py
@@ -12,10 +12,10 @@
MessageOutputItem,
ModelBehaviorError,
RunContextWrapper,
- Runner,
UserError,
handoff,
)
+from agents.run import AgentRunner
def message_item(content: str, agent: Agent[Any]) -> MessageOutputItem:
@@ -45,9 +45,9 @@ def test_single_handoff_setup():
assert not agent_1.handoffs
assert agent_2.handoffs == [agent_1]
- assert not Runner._get_handoffs(agent_1)
+ assert not AgentRunner._get_handoffs(agent_1)
- handoff_objects = Runner._get_handoffs(agent_2)
+ handoff_objects = AgentRunner._get_handoffs(agent_2)
assert len(handoff_objects) == 1
obj = handoff_objects[0]
assert obj.tool_name == Handoff.default_tool_name(agent_1)
@@ -64,7 +64,7 @@ def test_multiple_handoffs_setup():
assert not agent_1.handoffs
assert not agent_2.handoffs
- handoff_objects = Runner._get_handoffs(agent_3)
+ handoff_objects = AgentRunner._get_handoffs(agent_3)
assert len(handoff_objects) == 2
assert handoff_objects[0].tool_name == Handoff.default_tool_name(agent_1)
assert handoff_objects[1].tool_name == Handoff.default_tool_name(agent_2)
@@ -95,7 +95,7 @@ def test_custom_handoff_setup():
assert not agent_1.handoffs
assert not agent_2.handoffs
- handoff_objects = Runner._get_handoffs(agent_3)
+ handoff_objects = AgentRunner._get_handoffs(agent_3)
assert len(handoff_objects) == 2
first_handoff = handoff_objects[0]
diff --git a/tests/test_output_tool.py b/tests/test_output_tool.py
index 37c1b1b67..e98fd3c55 100644
--- a/tests/test_output_tool.py
+++ b/tests/test_output_tool.py
@@ -10,16 +10,16 @@
AgentOutputSchema,
AgentOutputSchemaBase,
ModelBehaviorError,
- Runner,
UserError,
)
from agents.agent_output import _WRAPPER_DICT_KEY
+from agents.run import AgentRunner
from agents.util import _json
def test_plain_text_output():
agent = Agent(name="test")
- output_schema = Runner._get_output_schema(agent)
+ output_schema = AgentRunner._get_output_schema(agent)
assert not output_schema, "Shouldn't have an output tool config without an output type"
agent = Agent(name="test", output_type=str)
@@ -32,7 +32,7 @@ class Foo(BaseModel):
def test_structured_output_pydantic():
agent = Agent(name="test", output_type=Foo)
- output_schema = Runner._get_output_schema(agent)
+ output_schema = AgentRunner._get_output_schema(agent)
assert output_schema, "Should have an output tool config with a structured output type"
assert isinstance(output_schema, AgentOutputSchema)
@@ -52,7 +52,7 @@ class Bar(TypedDict):
def test_structured_output_typed_dict():
agent = Agent(name="test", output_type=Bar)
- output_schema = Runner._get_output_schema(agent)
+ output_schema = AgentRunner._get_output_schema(agent)
assert output_schema, "Should have an output tool config with a structured output type"
assert isinstance(output_schema, AgentOutputSchema)
assert output_schema.output_type == Bar, "Should have the correct output type"
@@ -65,7 +65,7 @@ def test_structured_output_typed_dict():
def test_structured_output_list():
agent = Agent(name="test", output_type=list[str])
- output_schema = Runner._get_output_schema(agent)
+ output_schema = AgentRunner._get_output_schema(agent)
assert output_schema, "Should have an output tool config with a structured output type"
assert isinstance(output_schema, AgentOutputSchema)
assert output_schema.output_type == list[str], "Should have the correct output type"
@@ -79,14 +79,14 @@ def test_structured_output_list():
def test_bad_json_raises_error(mocker):
agent = Agent(name="test", output_type=Foo)
- output_schema = Runner._get_output_schema(agent)
+ output_schema = AgentRunner._get_output_schema(agent)
assert output_schema, "Should have an output tool config with a structured output type"
with pytest.raises(ModelBehaviorError):
output_schema.validate_json("not valid json")
agent = Agent(name="test", output_type=list[str])
- output_schema = Runner._get_output_schema(agent)
+ output_schema = AgentRunner._get_output_schema(agent)
assert output_schema, "Should have an output tool config with a structured output type"
mock_validate_json = mocker.patch.object(_json, "validate_json")
@@ -155,7 +155,7 @@ def validate_json(self, json_str: str) -> Any:
def test_custom_output_schema():
custom_output_schema = CustomOutputSchema()
agent = Agent(name="test", output_type=custom_output_schema)
- output_schema = Runner._get_output_schema(agent)
+ output_schema = AgentRunner._get_output_schema(agent)
assert output_schema, "Should have an output tool config with a structured output type"
assert isinstance(output_schema, CustomOutputSchema)
diff --git a/tests/test_run.py b/tests/test_run.py
new file mode 100644
index 000000000..66cfee1f1
--- /dev/null
+++ b/tests/test_run.py
@@ -0,0 +1,26 @@
+from __future__ import annotations
+
+from unittest import mock
+
+import pytest
+
+from agents import Agent, Runner
+from agents.run import AgentRunner, set_default_agent_runner
+
+from .fake_model import FakeModel
+
+
+@pytest.mark.asyncio
+async def test_static_run_methods_call_into_default_runner() -> None:
+ runner = mock.Mock(spec=AgentRunner)
+ set_default_agent_runner(runner)
+
+ agent = Agent(name="test", model=FakeModel())
+ await Runner.run(agent, input="test")
+ runner.run.assert_called_once()
+
+ Runner.run_streamed(agent, input="test")
+ runner.run_streamed.assert_called_once()
+
+ Runner.run_sync(agent, input="test")
+ runner.run_sync.assert_called_once()
diff --git a/tests/test_run_config.py b/tests/test_run_config.py
index 51835ab66..e19899006 100644
--- a/tests/test_run_config.py
+++ b/tests/test_run_config.py
@@ -60,7 +60,7 @@ async def test_run_config_model_name_override_takes_precedence() -> None:
async def test_run_config_model_override_object_takes_precedence() -> None:
"""
When a concrete Model instance is set on the RunConfig, then that instance should be
- returned by Runner._get_model regardless of the agent's model.
+ returned by AgentRunner._get_model regardless of the agent's model.
"""
fake_model = FakeModel(initial_output=[get_text_message("override-object")])
agent = Agent(name="test", model="agent-model")
diff --git a/tests/test_run_step_execution.py b/tests/test_run_step_execution.py
index 6f446649a..2454a4462 100644
--- a/tests/test_run_step_execution.py
+++ b/tests/test_run_step_execution.py
@@ -14,7 +14,6 @@
RunContextWrapper,
RunHooks,
RunItem,
- Runner,
ToolCallItem,
ToolCallOutputItem,
TResponseInputItem,
@@ -27,6 +26,7 @@
RunImpl,
SingleStepResult,
)
+from agents.run import AgentRunner
from agents.tool import function_tool
from agents.tool_context import ToolContext
@@ -324,8 +324,8 @@ async def get_execute_result(
context_wrapper: RunContextWrapper[Any] | None = None,
run_config: RunConfig | None = None,
) -> SingleStepResult:
- output_schema = Runner._get_output_schema(agent)
- handoffs = Runner._get_handoffs(agent)
+ output_schema = AgentRunner._get_output_schema(agent)
+ handoffs = AgentRunner._get_handoffs(agent)
processed_response = RunImpl.process_model_response(
agent=agent,
diff --git a/tests/test_run_step_processing.py b/tests/test_run_step_processing.py
index 3cc1231c1..5a75ec837 100644
--- a/tests/test_run_step_processing.py
+++ b/tests/test_run_step_processing.py
@@ -19,11 +19,11 @@
ModelResponse,
ReasoningItem,
RunContextWrapper,
- Runner,
ToolCallItem,
Usage,
)
from agents._run_impl import RunImpl
+from agents.run import AgentRunner
from .test_responses import (
get_final_output_message,
@@ -186,7 +186,7 @@ async def test_handoffs_parsed_correctly():
agent=agent_3,
response=response,
output_schema=None,
- handoffs=Runner._get_handoffs(agent_3),
+ handoffs=AgentRunner._get_handoffs(agent_3),
all_tools=await agent_3.get_all_tools(_dummy_ctx()),
)
assert len(result.handoffs) == 1, "Should have a handoff here"
@@ -216,7 +216,7 @@ async def test_missing_handoff_fails():
agent=agent_3,
response=response,
output_schema=None,
- handoffs=Runner._get_handoffs(agent_3),
+ handoffs=AgentRunner._get_handoffs(agent_3),
all_tools=await agent_3.get_all_tools(_dummy_ctx()),
)
@@ -239,7 +239,7 @@ async def test_multiple_handoffs_doesnt_error():
agent=agent_3,
response=response,
output_schema=None,
- handoffs=Runner._get_handoffs(agent_3),
+ handoffs=AgentRunner._get_handoffs(agent_3),
all_tools=await agent_3.get_all_tools(_dummy_ctx()),
)
assert len(result.handoffs) == 2, "Should have multiple handoffs here"
@@ -264,7 +264,7 @@ async def test_final_output_parsed_correctly():
RunImpl.process_model_response(
agent=agent,
response=response,
- output_schema=Runner._get_output_schema(agent),
+ output_schema=AgentRunner._get_output_schema(agent),
handoffs=[],
all_tools=await agent.get_all_tools(_dummy_ctx()),
)
@@ -471,7 +471,7 @@ async def test_tool_and_handoff_parsed_correctly():
agent=agent_3,
response=response,
output_schema=None,
- handoffs=Runner._get_handoffs(agent_3),
+ handoffs=AgentRunner._get_handoffs(agent_3),
all_tools=await agent_3.get_all_tools(_dummy_ctx()),
)
assert result.functions and len(result.functions) == 1
diff --git a/tests/voice/test_workflow.py b/tests/voice/test_workflow.py
index cfbb95011..e99810be1 100644
--- a/tests/voice/test_workflow.py
+++ b/tests/voice/test_workflow.py
@@ -19,11 +19,12 @@
TResponseStreamEvent,
)
+from ..fake_model import get_response_obj
+from ..test_responses import get_function_tool, get_function_tool_call, get_text_message
+
try:
from agents.voice import SingleAgentVoiceWorkflow
- from ..fake_model import get_response_obj
- from ..test_responses import get_function_tool, get_function_tool_call, get_text_message
except ImportError:
pass
diff --git a/uv.lock b/uv.lock
index cd26d45f6..dca27bdf7 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,5 +1,5 @@
version = 1
-revision = 1
+revision = 2
requires-python = ">=3.9"
resolution-markers = [
"python_full_version >= '3.10'",
@@ -10,9 +10,9 @@ resolution-markers = [
name = "aiohappyeyeballs"
version = "2.6.1"
source = { registry = "https://pypi.org/simple" }
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+sdist = { url = "https://files.pythonhosted.org/packages/26/30/f84a107a9c4331c14b2b586036f40965c128aa4fee4dda5d3d51cb14ad54/aiohappyeyeballs-2.6.1.tar.gz", hash = "sha256:c3f9d0113123803ccadfdf3f0faa505bc78e6a72d1cc4806cbd719826e943558", size = 22760, upload-time = "2025-03-12T01:42:48.764Z" }
wheels = [
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]
[[package]]
@@ -29,88 +29,88 @@ dependencies = [
{ name = "propcache" },
{ name = "yarl" },
]
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From 91c62c1dea97d02ad4974947e572d634d42496d1 Mon Sep 17 00:00:00 2001
From: pakrym-oai <pakrym@openai.com>
Date: Tue, 17 Jun 2025 17:47:26 -0700
Subject: [PATCH 45/68] Prepare 0.0.19 release (#895)
---
pyproject.toml | 2 +-
uv.lock | 2 +-
2 files changed, 2 insertions(+), 2 deletions(-)
diff --git a/pyproject.toml b/pyproject.toml
index 6cdf337ee..75e714768 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
[project]
name = "openai-agents"
-version = "0.0.18"
+version = "0.0.19"
description = "OpenAI Agents SDK"
readme = "README.md"
requires-python = ">=3.9"
diff --git a/uv.lock b/uv.lock
index dca27bdf7..679d8d2c1 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1480,7 +1480,7 @@ wheels = [
[[package]]
name = "openai-agents"
-version = "0.0.18"
+version = "0.0.19"
source = { editable = "." }
dependencies = [
{ name = "griffe" },
From c1466c62167edbb6a10e4cb6381ff47a00708436 Mon Sep 17 00:00:00 2001
From: Rohan Mehta <rm@openai.com>
Date: Tue, 24 Jun 2025 10:53:33 -0400
Subject: [PATCH 46/68] Add is_enabled to handoffs (#925)
Was added to function tools before, now handoffs. Towards #918
---
src/agents/handoffs.py | 14 +++++
src/agents/run.py | 31 +++++++--
tests/test_agent_config.py | 6 +-
tests/test_handoff_tool.py | 100 +++++++++++++++++++++++++++---
tests/test_run_step_execution.py | 2 +-
tests/test_run_step_processing.py | 8 +--
6 files changed, 140 insertions(+), 21 deletions(-)
diff --git a/src/agents/handoffs.py b/src/agents/handoffs.py
index 76c93a298..cb2752e4f 100644
--- a/src/agents/handoffs.py
+++ b/src/agents/handoffs.py
@@ -15,6 +15,7 @@
from .strict_schema import ensure_strict_json_schema
from .tracing.spans import SpanError
from .util import _error_tracing, _json, _transforms
+from .util._types import MaybeAwaitable
if TYPE_CHECKING:
from .agent import Agent
@@ -99,6 +100,11 @@ class Handoff(Generic[TContext]):
True, as it increases the likelihood of correct JSON input.
"""
+ is_enabled: bool | Callable[[RunContextWrapper[Any], Agent[Any]], MaybeAwaitable[bool]] = True
+ """Whether the handoff is enabled. Either a bool or a Callable that takes the run context and
+ agent and returns whether the handoff is enabled. You can use this to dynamically enable/disable
+ a handoff based on your context/state."""
+
def get_transfer_message(self, agent: Agent[Any]) -> str:
return json.dumps({"assistant": agent.name})
@@ -121,6 +127,7 @@ def handoff(
tool_name_override: str | None = None,
tool_description_override: str | None = None,
input_filter: Callable[[HandoffInputData], HandoffInputData] | None = None,
+ is_enabled: bool | Callable[[RunContextWrapper[Any], Agent[Any]], MaybeAwaitable[bool]] = True,
) -> Handoff[TContext]: ...
@@ -133,6 +140,7 @@ def handoff(
tool_description_override: str | None = None,
tool_name_override: str | None = None,
input_filter: Callable[[HandoffInputData], HandoffInputData] | None = None,
+ is_enabled: bool | Callable[[RunContextWrapper[Any], Agent[Any]], MaybeAwaitable[bool]] = True,
) -> Handoff[TContext]: ...
@@ -144,6 +152,7 @@ def handoff(
tool_description_override: str | None = None,
tool_name_override: str | None = None,
input_filter: Callable[[HandoffInputData], HandoffInputData] | None = None,
+ is_enabled: bool | Callable[[RunContextWrapper[Any], Agent[Any]], MaybeAwaitable[bool]] = True,
) -> Handoff[TContext]: ...
@@ -154,6 +163,7 @@ def handoff(
on_handoff: OnHandoffWithInput[THandoffInput] | OnHandoffWithoutInput | None = None,
input_type: type[THandoffInput] | None = None,
input_filter: Callable[[HandoffInputData], HandoffInputData] | None = None,
+ is_enabled: bool | Callable[[RunContextWrapper[Any], Agent[Any]], MaybeAwaitable[bool]] = True,
) -> Handoff[TContext]:
"""Create a handoff from an agent.
@@ -166,6 +176,9 @@ def handoff(
input_type: the type of the input to the handoff. If provided, the input will be validated
against this type. Only relevant if you pass a function that takes an input.
input_filter: a function that filters the inputs that are passed to the next agent.
+ is_enabled: Whether the handoff is enabled. Can be a bool or a callable that takes the run
+ context and agent and returns whether the handoff is enabled. Disabled handoffs are
+ hidden from the LLM at runtime.
"""
assert (on_handoff and input_type) or not (on_handoff and input_type), (
"You must provide either both on_handoff and input_type, or neither"
@@ -233,4 +246,5 @@ async def _invoke_handoff(
on_invoke_handoff=_invoke_handoff,
input_filter=input_filter,
agent_name=agent.name,
+ is_enabled=is_enabled,
)
diff --git a/src/agents/run.py b/src/agents/run.py
index 8a44a0e54..e5f9378ec 100644
--- a/src/agents/run.py
+++ b/src/agents/run.py
@@ -2,6 +2,7 @@
import asyncio
import copy
+import inspect
from dataclasses import dataclass, field
from typing import Any, Generic, cast
@@ -361,7 +362,8 @@ async def run(
# agent changes, or if the agent loop ends.
if current_span is None:
handoff_names = [
- h.agent_name for h in AgentRunner._get_handoffs(current_agent)
+ h.agent_name
+ for h in await AgentRunner._get_handoffs(current_agent, context_wrapper)
]
if output_schema := AgentRunner._get_output_schema(current_agent):
output_type_name = output_schema.name()
@@ -641,7 +643,10 @@ async def _start_streaming(
# Start an agent span if we don't have one. This span is ended if the current
# agent changes, or if the agent loop ends.
if current_span is None:
- handoff_names = [h.agent_name for h in cls._get_handoffs(current_agent)]
+ handoff_names = [
+ h.agent_name
+ for h in await cls._get_handoffs(current_agent, context_wrapper)
+ ]
if output_schema := cls._get_output_schema(current_agent):
output_type_name = output_schema.name()
else:
@@ -798,7 +803,7 @@ async def _run_single_turn_streamed(
agent.get_prompt(context_wrapper),
)
- handoffs = cls._get_handoffs(agent)
+ handoffs = await cls._get_handoffs(agent, context_wrapper)
model = cls._get_model(agent, run_config)
model_settings = agent.model_settings.resolve(run_config.model_settings)
model_settings = RunImpl.maybe_reset_tool_choice(agent, tool_use_tracker, model_settings)
@@ -898,7 +903,7 @@ async def _run_single_turn(
)
output_schema = cls._get_output_schema(agent)
- handoffs = cls._get_handoffs(agent)
+ handoffs = await cls._get_handoffs(agent, context_wrapper)
input = ItemHelpers.input_to_new_input_list(original_input)
input.extend([generated_item.to_input_item() for generated_item in generated_items])
@@ -1091,14 +1096,28 @@ def _get_output_schema(cls, agent: Agent[Any]) -> AgentOutputSchemaBase | None:
return AgentOutputSchema(agent.output_type)
@classmethod
- def _get_handoffs(cls, agent: Agent[Any]) -> list[Handoff]:
+ async def _get_handoffs(
+ cls, agent: Agent[Any], context_wrapper: RunContextWrapper[Any]
+ ) -> list[Handoff]:
handoffs = []
for handoff_item in agent.handoffs:
if isinstance(handoff_item, Handoff):
handoffs.append(handoff_item)
elif isinstance(handoff_item, Agent):
handoffs.append(handoff(handoff_item))
- return handoffs
+
+ async def _check_handoff_enabled(handoff_obj: Handoff) -> bool:
+ attr = handoff_obj.is_enabled
+ if isinstance(attr, bool):
+ return attr
+ res = attr(context_wrapper, agent)
+ if inspect.isawaitable(res):
+ return bool(await res)
+ return bool(res)
+
+ results = await asyncio.gather(*(_check_handoff_enabled(h) for h in handoffs))
+ enabled: list[Handoff] = [h for h, ok in zip(handoffs, results) if ok]
+ return enabled
@classmethod
async def _get_all_tools(
diff --git a/tests/test_agent_config.py b/tests/test_agent_config.py
index f9423619d..a985fd60d 100644
--- a/tests/test_agent_config.py
+++ b/tests/test_agent_config.py
@@ -43,7 +43,7 @@ async def test_handoff_with_agents():
handoffs=[agent_1, agent_2],
)
- handoffs = AgentRunner._get_handoffs(agent_3)
+ handoffs = await AgentRunner._get_handoffs(agent_3, RunContextWrapper(None))
assert len(handoffs) == 2
assert handoffs[0].agent_name == "agent_1"
@@ -78,7 +78,7 @@ async def test_handoff_with_handoff_obj():
],
)
- handoffs = AgentRunner._get_handoffs(agent_3)
+ handoffs = await AgentRunner._get_handoffs(agent_3, RunContextWrapper(None))
assert len(handoffs) == 2
assert handoffs[0].agent_name == "agent_1"
@@ -112,7 +112,7 @@ async def test_handoff_with_handoff_obj_and_agent():
handoffs=[handoff(agent_1), agent_2],
)
- handoffs = AgentRunner._get_handoffs(agent_3)
+ handoffs = await AgentRunner._get_handoffs(agent_3, RunContextWrapper(None))
assert len(handoffs) == 2
assert handoffs[0].agent_name == "agent_1"
diff --git a/tests/test_handoff_tool.py b/tests/test_handoff_tool.py
index a1b5b80ba..0f7fc2166 100644
--- a/tests/test_handoff_tool.py
+++ b/tests/test_handoff_tool.py
@@ -38,16 +38,17 @@ def get_len(data: HandoffInputData) -> int:
return input_len + pre_handoff_len + new_items_len
-def test_single_handoff_setup():
+@pytest.mark.asyncio
+async def test_single_handoff_setup():
agent_1 = Agent(name="test_1")
agent_2 = Agent(name="test_2", handoffs=[agent_1])
assert not agent_1.handoffs
assert agent_2.handoffs == [agent_1]
- assert not AgentRunner._get_handoffs(agent_1)
+ assert not (await AgentRunner._get_handoffs(agent_1, RunContextWrapper(agent_1)))
- handoff_objects = AgentRunner._get_handoffs(agent_2)
+ handoff_objects = await AgentRunner._get_handoffs(agent_2, RunContextWrapper(agent_2))
assert len(handoff_objects) == 1
obj = handoff_objects[0]
assert obj.tool_name == Handoff.default_tool_name(agent_1)
@@ -55,7 +56,8 @@ def test_single_handoff_setup():
assert obj.agent_name == agent_1.name
-def test_multiple_handoffs_setup():
+@pytest.mark.asyncio
+async def test_multiple_handoffs_setup():
agent_1 = Agent(name="test_1")
agent_2 = Agent(name="test_2")
agent_3 = Agent(name="test_3", handoffs=[agent_1, agent_2])
@@ -64,7 +66,7 @@ def test_multiple_handoffs_setup():
assert not agent_1.handoffs
assert not agent_2.handoffs
- handoff_objects = AgentRunner._get_handoffs(agent_3)
+ handoff_objects = await AgentRunner._get_handoffs(agent_3, RunContextWrapper(agent_3))
assert len(handoff_objects) == 2
assert handoff_objects[0].tool_name == Handoff.default_tool_name(agent_1)
assert handoff_objects[1].tool_name == Handoff.default_tool_name(agent_2)
@@ -76,7 +78,8 @@ def test_multiple_handoffs_setup():
assert handoff_objects[1].agent_name == agent_2.name
-def test_custom_handoff_setup():
+@pytest.mark.asyncio
+async def test_custom_handoff_setup():
agent_1 = Agent(name="test_1")
agent_2 = Agent(name="test_2")
agent_3 = Agent(
@@ -95,7 +98,7 @@ def test_custom_handoff_setup():
assert not agent_1.handoffs
assert not agent_2.handoffs
- handoff_objects = AgentRunner._get_handoffs(agent_3)
+ handoff_objects = await AgentRunner._get_handoffs(agent_3, RunContextWrapper(agent_3))
assert len(handoff_objects) == 2
first_handoff = handoff_objects[0]
@@ -284,3 +287,86 @@ def test_get_transfer_message_is_valid_json() -> None:
obj = handoff(agent)
transfer = obj.get_transfer_message(agent)
assert json.loads(transfer) == {"assistant": agent.name}
+
+
+def test_handoff_is_enabled_bool():
+ """Test that handoff respects is_enabled boolean parameter."""
+ agent = Agent(name="test")
+
+ # Test enabled handoff (default)
+ handoff_enabled = handoff(agent)
+ assert handoff_enabled.is_enabled is True
+
+ # Test explicitly enabled handoff
+ handoff_explicit_enabled = handoff(agent, is_enabled=True)
+ assert handoff_explicit_enabled.is_enabled is True
+
+ # Test disabled handoff
+ handoff_disabled = handoff(agent, is_enabled=False)
+ assert handoff_disabled.is_enabled is False
+
+
+@pytest.mark.asyncio
+async def test_handoff_is_enabled_callable():
+ """Test that handoff respects is_enabled callable parameter."""
+ agent = Agent(name="test")
+
+ # Test callable that returns True
+ def always_enabled(ctx: RunContextWrapper[Any], agent: Agent[Any]) -> bool:
+ return True
+
+ handoff_callable_enabled = handoff(agent, is_enabled=always_enabled)
+ assert callable(handoff_callable_enabled.is_enabled)
+ result = handoff_callable_enabled.is_enabled(RunContextWrapper(agent), agent)
+ assert result is True
+
+ # Test callable that returns False
+ def always_disabled(ctx: RunContextWrapper[Any], agent: Agent[Any]) -> bool:
+ return False
+
+ handoff_callable_disabled = handoff(agent, is_enabled=always_disabled)
+ assert callable(handoff_callable_disabled.is_enabled)
+ result = handoff_callable_disabled.is_enabled(RunContextWrapper(agent), agent)
+ assert result is False
+
+ # Test async callable
+ async def async_enabled(ctx: RunContextWrapper[Any], agent: Agent[Any]) -> bool:
+ return True
+
+ handoff_async_enabled = handoff(agent, is_enabled=async_enabled)
+ assert callable(handoff_async_enabled.is_enabled)
+ result = await handoff_async_enabled.is_enabled(RunContextWrapper(agent), agent) # type: ignore
+ assert result is True
+
+
+@pytest.mark.asyncio
+async def test_handoff_is_enabled_filtering_integration():
+ """Integration test that disabled handoffs are filtered out by the runner."""
+
+ # Set up agents
+ agent_1 = Agent(name="agent_1")
+ agent_2 = Agent(name="agent_2")
+ agent_3 = Agent(name="agent_3")
+
+ # Create main agent with mixed enabled/disabled handoffs
+ main_agent = Agent(
+ name="main_agent",
+ handoffs=[
+ handoff(agent_1, is_enabled=True), # enabled
+ handoff(agent_2, is_enabled=False), # disabled
+ handoff(agent_3, is_enabled=lambda ctx, agent: True), # enabled callable
+ ],
+ )
+
+ context_wrapper = RunContextWrapper(main_agent)
+
+ # Get filtered handoffs using the runner's method
+ filtered_handoffs = await AgentRunner._get_handoffs(main_agent, context_wrapper)
+
+ # Should only have 2 handoffs (agent_1 and agent_3), agent_2 should be filtered out
+ assert len(filtered_handoffs) == 2
+
+ # Check that the correct agents are present
+ agent_names = {h.agent_name for h in filtered_handoffs}
+ assert agent_names == {"agent_1", "agent_3"}
+ assert "agent_2" not in agent_names
diff --git a/tests/test_run_step_execution.py b/tests/test_run_step_execution.py
index 2454a4462..4cf9ae832 100644
--- a/tests/test_run_step_execution.py
+++ b/tests/test_run_step_execution.py
@@ -325,7 +325,7 @@ async def get_execute_result(
run_config: RunConfig | None = None,
) -> SingleStepResult:
output_schema = AgentRunner._get_output_schema(agent)
- handoffs = AgentRunner._get_handoffs(agent)
+ handoffs = await AgentRunner._get_handoffs(agent, context_wrapper or RunContextWrapper(None))
processed_response = RunImpl.process_model_response(
agent=agent,
diff --git a/tests/test_run_step_processing.py b/tests/test_run_step_processing.py
index 5a75ec837..6a2904791 100644
--- a/tests/test_run_step_processing.py
+++ b/tests/test_run_step_processing.py
@@ -186,7 +186,7 @@ async def test_handoffs_parsed_correctly():
agent=agent_3,
response=response,
output_schema=None,
- handoffs=AgentRunner._get_handoffs(agent_3),
+ handoffs=await AgentRunner._get_handoffs(agent_3, _dummy_ctx()),
all_tools=await agent_3.get_all_tools(_dummy_ctx()),
)
assert len(result.handoffs) == 1, "Should have a handoff here"
@@ -216,7 +216,7 @@ async def test_missing_handoff_fails():
agent=agent_3,
response=response,
output_schema=None,
- handoffs=AgentRunner._get_handoffs(agent_3),
+ handoffs=await AgentRunner._get_handoffs(agent_3, _dummy_ctx()),
all_tools=await agent_3.get_all_tools(_dummy_ctx()),
)
@@ -239,7 +239,7 @@ async def test_multiple_handoffs_doesnt_error():
agent=agent_3,
response=response,
output_schema=None,
- handoffs=AgentRunner._get_handoffs(agent_3),
+ handoffs=await AgentRunner._get_handoffs(agent_3, _dummy_ctx()),
all_tools=await agent_3.get_all_tools(_dummy_ctx()),
)
assert len(result.handoffs) == 2, "Should have multiple handoffs here"
@@ -471,7 +471,7 @@ async def test_tool_and_handoff_parsed_correctly():
agent=agent_3,
response=response,
output_schema=None,
- handoffs=AgentRunner._get_handoffs(agent_3),
+ handoffs=await AgentRunner._get_handoffs(agent_3, _dummy_ctx()),
all_tools=await agent_3.get_all_tools(_dummy_ctx()),
)
assert result.functions and len(result.functions) == 1
From 0f21c8aedb0251c6269934f9543021ee10e9489e Mon Sep 17 00:00:00 2001
From: Daniele Morotti <58258368+DanieleMorotti@users.noreply.github.com>
Date: Tue, 24 Jun 2025 16:56:24 +0200
Subject: [PATCH 47/68] Removed lines to avoid duplicate output in REPL utility
(#928)
In the REPL utility, the final output was printed after the streaming,
causing a duplication issue.
I only removed the lines within the stream mode that printed the final
output. It should not affect any other use case of the utility.
It solves a comment done in #784 .
---
src/agents/repl.py | 5 +----
1 file changed, 1 insertion(+), 4 deletions(-)
diff --git a/src/agents/repl.py b/src/agents/repl.py
index 9a4f30759..f7142555f 100644
--- a/src/agents/repl.py
+++ b/src/agents/repl.py
@@ -5,7 +5,7 @@
from openai.types.responses.response_text_delta_event import ResponseTextDeltaEvent
from .agent import Agent
-from .items import ItemHelpers, TResponseInputItem
+from .items import TResponseInputItem
from .result import RunResultBase
from .run import Runner
from .stream_events import AgentUpdatedStreamEvent, RawResponsesStreamEvent, RunItemStreamEvent
@@ -50,9 +50,6 @@ async def run_demo_loop(agent: Agent[Any], *, stream: bool = True) -> None:
print("\n[tool called]", flush=True)
elif event.item.type == "tool_call_output_item":
print(f"\n[tool output: {event.item.output}]", flush=True)
- elif event.item.type == "message_output_item":
- message = ItemHelpers.text_message_output(event.item)
- print(message, end="", flush=True)
elif isinstance(event, AgentUpdatedStreamEvent):
print(f"\n[Agent updated: {event.new_agent.name}]", flush=True)
print()
From d88bf14360920a5b8a2576a610a5d04519f1857b Mon Sep 17 00:00:00 2001
From: Niv Hertz <46317590+niv-hertz@users.noreply.github.com>
Date: Tue, 24 Jun 2025 18:14:19 +0300
Subject: [PATCH 48/68] Bugfix | Fixed a bug when calling reasoning models with
`store=False` (#920)
resolves https://github.com/openai/openai-agents-python/issues/919
---
src/agents/model_settings.py | 5 +++++
src/agents/models/openai_responses.py | 6 +++++-
tests/model_settings/test_serialization.py | 1 +
3 files changed, 11 insertions(+), 1 deletion(-)
diff --git a/src/agents/model_settings.py b/src/agents/model_settings.py
index 881390279..f844eb87c 100644
--- a/src/agents/model_settings.py
+++ b/src/agents/model_settings.py
@@ -5,6 +5,7 @@
from typing import Any, Literal
from openai._types import Body, Headers, Query
+from openai.types.responses import ResponseIncludable
from openai.types.shared import Reasoning
from pydantic import BaseModel
@@ -61,6 +62,10 @@ class ModelSettings:
"""Whether to include usage chunk.
Defaults to True if not provided."""
+ response_include: list[ResponseIncludable] | None = None
+ """Additional output data to include in the model response.
+ [include parameter](https://platform.openai.com/docs/api-reference/responses/create#responses-create-include)"""
+
extra_query: Query | None = None
"""Additional query fields to provide with the request.
Defaults to None if not provided."""
diff --git a/src/agents/models/openai_responses.py b/src/agents/models/openai_responses.py
index 961f690b0..637adaccd 100644
--- a/src/agents/models/openai_responses.py
+++ b/src/agents/models/openai_responses.py
@@ -240,6 +240,10 @@ async def _fetch_response(
converted_tools = Converter.convert_tools(tools, handoffs)
response_format = Converter.get_response_format(output_schema)
+ include: list[ResponseIncludable] = converted_tools.includes
+ if model_settings.response_include is not None:
+ include = list({*include, *model_settings.response_include})
+
if _debug.DONT_LOG_MODEL_DATA:
logger.debug("Calling LLM")
else:
@@ -258,7 +262,7 @@ async def _fetch_response(
instructions=self._non_null_or_not_given(system_instructions),
model=self.model,
input=list_input,
- include=converted_tools.includes,
+ include=include,
tools=converted_tools.tools,
prompt=self._non_null_or_not_given(prompt),
temperature=self._non_null_or_not_given(model_settings.temperature),
diff --git a/tests/model_settings/test_serialization.py b/tests/model_settings/test_serialization.py
index ad4db4019..2bbc7ce2c 100644
--- a/tests/model_settings/test_serialization.py
+++ b/tests/model_settings/test_serialization.py
@@ -44,6 +44,7 @@ def test_all_fields_serialization() -> None:
metadata={"foo": "bar"},
store=False,
include_usage=False,
+ response_include=["reasoning.encrypted_content"],
extra_query={"foo": "bar"},
extra_body={"foo": "bar"},
extra_headers={"foo": "bar"},
From 3e5f3c03e539607b65a586ec200f2df8ab1f58d0 Mon Sep 17 00:00:00 2001
From: Rohan Mehta <rm@openai.com>
Date: Tue, 24 Jun 2025 12:16:02 -0400
Subject: [PATCH 49/68] Point CLAUDE.md to AGENTS.md (#930)
People soemtimes use claude code to send PRs, this allows the agents.md
to be shared for that
---
AGENTS.md | 4 +++-
CLAUDE.md | 1 +
2 files changed, 4 insertions(+), 1 deletion(-)
create mode 100644 CLAUDE.md
diff --git a/AGENTS.md b/AGENTS.md
index ff37db326..291c31837 100644
--- a/AGENTS.md
+++ b/AGENTS.md
@@ -35,6 +35,8 @@ Welcome to the OpenAI Agents SDK repository. This file contains the main points
Coverage can be generated with `make coverage`.
+All python commands should be run via `uv run python ...`
+
## Snapshot tests
Some tests rely on inline snapshots. See `tests/README.md` for details on updating them:
@@ -64,6 +66,6 @@ Commit messages should be concise and written in the imperative mood. Small, foc
## What reviewers look for
- Tests covering new behaviour.
-- Consistent style: code formatted with `ruff format`, imports sorted, and type hints passing `mypy`.
+- Consistent style: code formatted with `uv run ruff format`, imports sorted, and type hints passing `uv run mypy .`.
- Clear documentation for any public API changes.
- Clean history and a helpful PR description.
diff --git a/CLAUDE.md b/CLAUDE.md
new file mode 100644
index 000000000..5e01a1c3d
--- /dev/null
+++ b/CLAUDE.md
@@ -0,0 +1 @@
+Read the AGENTS.md file for instructions.
\ No newline at end of file
From 421693ab84ad7a4ac864e0f331340dba0eaf5908 Mon Sep 17 00:00:00 2001
From: Kazuhiro Sera <seratch@openai.com>
Date: Wed, 25 Jun 2025 02:46:21 +0900
Subject: [PATCH 50/68] Fix #890 by adjusting the guardrail document page
(#903)
This pull request resolves #890 and enables the translation script to
accept a file to work on.
---
docs/guardrails.md | 2 +-
docs/ja/guardrails.md | 44 ++++++++++++-------------
docs/scripts/translate_docs.py | 59 +++++++++++++++++++++++-----------
3 files changed, 64 insertions(+), 41 deletions(-)
diff --git a/docs/guardrails.md b/docs/guardrails.md
index 2f0be0f2a..8df904a4c 100644
--- a/docs/guardrails.md
+++ b/docs/guardrails.md
@@ -23,7 +23,7 @@ Input guardrails run in 3 steps:
Output guardrails run in 3 steps:
-1. First, the guardrail receives the same input passed to the agent.
+1. First, the guardrail receives the output produced by the agent.
2. Next, the guardrail function runs to produce a [`GuardrailFunctionOutput`][agents.guardrail.GuardrailFunctionOutput], which is then wrapped in an [`OutputGuardrailResult`][agents.guardrail.OutputGuardrailResult]
3. Finally, we check if [`.tripwire_triggered`][agents.guardrail.GuardrailFunctionOutput.tripwire_triggered] is true. If true, an [`OutputGuardrailTripwireTriggered`][agents.exceptions.OutputGuardrailTripwireTriggered] exception is raised, so you can appropriately respond to the user or handle the exception.
diff --git a/docs/ja/guardrails.md b/docs/ja/guardrails.md
index e7b02a6ed..b67bb8bad 100644
--- a/docs/ja/guardrails.md
+++ b/docs/ja/guardrails.md
@@ -4,44 +4,44 @@ search:
---
# ガードレール
-ガードレールは エージェント と _並列_ に実行され、 ユーザー入力 のチェックとバリデーションを行います。たとえば、顧客からのリクエストを支援するために非常に賢い (そのため遅く / 高価な) モデルを使うエージェントがあるとします。悪意のある ユーザー がモデルに数学の宿題を手伝わせようとするのは避けたいですよね。その場合、 高速 / 低コスト のモデルでガードレールを実行できます。ガードレールが悪意のある利用を検知した場合、即座にエラーを送出して高価なモデルの実行を停止し、時間と費用を節約できます。
+ガードレールは エージェント と _並行して_ 実行され、ユーザー入力のチェックとバリデーションを行えます。例えば、とても賢い（つまり遅く/高価な）モデルを使用してカスタマーリクエストを処理するエージェントがあるとします。悪意のある ユーザー がモデルに数学の宿題を手伝わせようとするのは避けたいでしょう。そこで、速く/安価なモデルで動くガードレールを実行できます。ガードレールが悪意のある利用を検知すると、直ちにエラーを送出して高価なモデルの実行を停止し、時間とコストを節約できます。
-ガードレールには 2 種類あります。
+ガードレールには 2 種類あります:
-1. Input ガードレールは最初の ユーザー入力 に対して実行されます
-2. Output ガードレールは最終的なエージェント出力に対して実行されます
+1. 入力ガードレール は初期 ユーザー 入力に対して実行されます
+2. 出力ガードレール は最終的なエージェント出力に対して実行されます
-## Input ガードレール
+## 入力ガードレール
-Input ガードレールは 3 つのステップで実行されます。
+入力ガードレールは 3 ステップで実行されます:
1. まず、ガードレールはエージェントに渡されたものと同じ入力を受け取ります。
-2. 次に、ガードレール関数が実行され [`GuardrailFunctionOutput`][agents.guardrail.GuardrailFunctionOutput] を生成し、それが [`InputGuardrailResult`][agents.guardrail.InputGuardrailResult] でラップされます。
-3. 最後に [`.tripwire_triggered`][agents.guardrail.GuardrailFunctionOutput.tripwire_triggered] が true かどうかを確認します。true の場合、[`InputGuardrailTripwireTriggered`][agents.exceptions.InputGuardrailTripwireTriggered] 例外が送出されるので、 ユーザー への適切な応答や例外処理を行えます。
+2. 次に、ガードレール関数が実行され [`GuardrailFunctionOutput`][agents.guardrail.GuardrailFunctionOutput] を生成し、それが [`InputGuardrailResult`][agents.guardrail.InputGuardrailResult] にラップされます。
+3. 最後に [.tripwire_triggered][agents.guardrail.GuardrailFunctionOutput.tripwire_triggered] が true かどうかを確認します。true の場合、[`InputGuardrailTripwireTriggered`][agents.exceptions.InputGuardrailTripwireTriggered] 例外が送出されるので、適切に ユーザー に応答したり例外を処理できます。
!!! Note
- Input ガードレールは ユーザー入力 に対して実行されることを想定しているため、エージェントのガードレールが実行されるのはそのエージェントが *最初* のエージェントである場合だけです。「なぜ `guardrails` プロパティがエージェントにあり、 `Runner.run` に渡さないのか？」と思うかもしれません。ガードレールは実際の エージェント に密接に関連する場合が多く、エージェントごとに異なるガードレールを実行するため、コードを同じ場所に置くことで可読性が向上するからです。
+ 入力ガードレールは ユーザー 入力に対して実行されることを意図しているため、ガードレールは *最初* のエージェントでのみ実行されます。「なぜ `guardrails` プロパティがエージェントにあり、`Runner.run` に渡さないのか」と疑問に思うかもしれません。これは、ガードレールが実際の エージェント と密接に関連していることが多いからです。異なるエージェントには異なるガードレールを実行するため、コードを同じ場所に置くことで可読性が向上します。
-## Output ガードレール
+## 出力ガードレール
-Output ガードレールは 3 つのステップで実行されます。
+出力ガードレールは 3 ステップで実行されます:
-1. まず、ガードレールはエージェントに渡されたものと同じ入力を受け取ります。
-2. 次に、ガードレール関数が実行され [`GuardrailFunctionOutput`][agents.guardrail.GuardrailFunctionOutput] を生成し、それが [`OutputGuardrailResult`][agents.guardrail.OutputGuardrailResult] でラップされます。
-3. 最後に [`.tripwire_triggered`][agents.guardrail.GuardrailFunctionOutput.tripwire_triggered] が true かどうかを確認します。true の場合、[`OutputGuardrailTripwireTriggered`][agents.exceptions.OutputGuardrailTripwireTriggered] 例外が送出されるので、 ユーザー への適切な応答や例外処理を行えます。
+1. まず、ガードレールはエージェントが生成した出力を受け取ります。
+2. 次に、ガードレール関数が実行され [`GuardrailFunctionOutput`][agents.guardrail.GuardrailFunctionOutput] を生成し、それが [`OutputGuardrailResult`][agents.guardrail.OutputGuardrailResult] にラップされます。
+3. 最後に [.tripwire_triggered][agents.guardrail.GuardrailFunctionOutput.tripwire_triggered] が true かどうかを確認します。true の場合、[`OutputGuardrailTripwireTriggered`][agents.exceptions.OutputGuardrailTripwireTriggered] 例外が送出されるので、適切に ユーザー に応答したり例外を処理できます。
!!! Note
- Output ガードレールは最終的なエージェント出力に対して実行されることを想定しているため、エージェントのガードレールが実行されるのはそのエージェントが *最後* のエージェントである場合だけです。Input ガードレール同様、ガードレールは実際の エージェント に密接に関連するため、コードを同じ場所に置くことで可読性が向上します。
+ 出力ガードレールは最終的なエージェント出力に対して実行されることを意図しているため、ガードレールは *最後* のエージェントでのみ実行されます。入力ガードレールの場合と同様、ガードレールが実際の エージェント と密接に関連していることが多いため、コードを同じ場所に置くことで可読性が向上します。
-## トリップワイヤ
+## トリップワイヤー
-入力または出力がガードレールに失敗した場合、ガードレールはトリップワイヤを用いてそれを通知できます。ガードレールがトリップワイヤを発火したことを検知すると、ただちに `{Input,Output}GuardrailTripwireTriggered` 例外を送出してエージェントの実行を停止します。
+入力または出力がガードレールを通過できなかった場合、ガードレールはトリップワイヤーでそれを示すことができます。トリップワイヤーがトリガーされたガードレールを検知した時点で、直ちに `{Input,Output}GuardrailTripwireTriggered` 例外を送出し、エージェントの実行を停止します。
## ガードレールの実装
-入力を受け取り、[`GuardrailFunctionOutput`][agents.guardrail.GuardrailFunctionOutput] を返す関数を用意する必要があります。次の例では、内部で エージェント を実行してこれを行います。
+入力を受け取り、[`GuardrailFunctionOutput`][agents.guardrail.GuardrailFunctionOutput] を返す関数を提供する必要があります。この例では、内部で エージェント を実行してこれを行います。
```python
from pydantic import BaseModel
@@ -94,12 +94,12 @@ async def main():
print("Math homework guardrail tripped")
```
-1. この エージェント をガードレール関数内で使用します。
-2. これはエージェントの入力 / コンテキストを受け取り、結果を返すガードレール関数です。
+1. このエージェントをガードレール関数内で使用します。
+2. これはエージェントの入力/コンテキストを受け取り、結果を返すガードレール関数です。
3. ガードレール結果に追加情報を含めることができます。
4. これはワークフローを定義する実際のエージェントです。
-Output ガードレールも同様です。
+出力ガードレールも同様です。
```python
from pydantic import BaseModel
@@ -155,4 +155,4 @@ async def main():
1. これは実際のエージェントの出力型です。
2. これはガードレールの出力型です。
3. これはエージェントの出力を受け取り、結果を返すガードレール関数です。
-4. これはワークフローを定義する実際のエージェントです。
\ No newline at end of file
+4. これはワークフローを定義する実際のエージェントです。
\ No newline at end of file
diff --git a/docs/scripts/translate_docs.py b/docs/scripts/translate_docs.py
index b2e8b44fc..5dada2681 100644
--- a/docs/scripts/translate_docs.py
+++ b/docs/scripts/translate_docs.py
@@ -1,5 +1,7 @@
# ruff: noqa
import os
+import sys
+import argparse
from openai import OpenAI
from concurrent.futures import ThreadPoolExecutor
@@ -263,24 +265,45 @@ def translate_single_source_file(file_path: str) -> None:
def main():
- # Traverse the source directory
- for root, _, file_names in os.walk(source_dir):
- # Skip the target directories
- if any(lang in root for lang in languages):
- continue
- # Increasing this will make the translation faster; you can decide considering the model's capacity
- concurrency = 6
- with ThreadPoolExecutor(max_workers=concurrency) as executor:
- futures = []
- for file_name in file_names:
- filepath = os.path.join(root, file_name)
- futures.append(executor.submit(translate_single_source_file, filepath))
- if len(futures) >= concurrency:
- for future in futures:
- future.result()
- futures.clear()
-
- print("Translation completed.")
+ parser = argparse.ArgumentParser(description="Translate documentation files")
+ parser.add_argument("--file", type=str, help="Specific file to translate (relative to docs directory)")
+ args = parser.parse_args()
+
+ if args.file:
+ # Translate a single file
+ # Handle both "foo.md" and "docs/foo.md" formats
+ if args.file.startswith("docs/"):
+ # Remove "docs/" prefix if present
+ relative_file = args.file[5:]
+ else:
+ relative_file = args.file
+
+ file_path = os.path.join(source_dir, relative_file)
+ if os.path.exists(file_path):
+ translate_single_source_file(file_path)
+ print(f"Translation completed for {relative_file}")
+ else:
+ print(f"Error: File {file_path} does not exist")
+ sys.exit(1)
+ else:
+ # Traverse the source directory (original behavior)
+ for root, _, file_names in os.walk(source_dir):
+ # Skip the target directories
+ if any(lang in root for lang in languages):
+ continue
+ # Increasing this will make the translation faster; you can decide considering the model's capacity
+ concurrency = 6
+ with ThreadPoolExecutor(max_workers=concurrency) as executor:
+ futures = []
+ for file_name in file_names:
+ filepath = os.path.join(root, file_name)
+ futures.append(executor.submit(translate_single_source_file, filepath))
+ if len(futures) >= concurrency:
+ for future in futures:
+ future.result()
+ futures.clear()
+
+ print("Translation completed.")
if __name__ == "__main__":
From 7665dd1acc03ddecc2e8f70f907ee9941060b76f Mon Sep 17 00:00:00 2001
From: Kazuhiro Sera <seratch@openai.com>
Date: Thu, 26 Jun 2025 00:18:18 +0900
Subject: [PATCH 51/68] Add exempt-issue-labels to the issue triage GH Action
job (#936)
Like I did for the TypeScript SDK project (see
https://github.com/openai/openai-agents-js/pull/97), we may want to have
the labels to exclude the issues from auto-closing. Some of the issues
that have been open for a while could just need time.
---
.github/workflows/issues.yml | 1 +
1 file changed, 1 insertion(+)
diff --git a/.github/workflows/issues.yml b/.github/workflows/issues.yml
index 6447f83ef..dca717752 100644
--- a/.github/workflows/issues.yml
+++ b/.github/workflows/issues.yml
@@ -21,6 +21,7 @@ jobs:
days-before-pr-stale: 10
days-before-pr-close: 7
stale-pr-label: "stale"
+ exempt-issue-labels: "skip-stale"
stale-pr-message: "This PR is stale because it has been open for 10 days with no activity."
close-pr-message: "This PR was closed because it has been inactive for 7 days since being marked as stale."
repo-token: ${{ secrets.GITHUB_TOKEN }}
From c2005f8273a899ffd32e4b77c06701f347f8ec92 Mon Sep 17 00:00:00 2001
From: Easonshi <oldcitystal@gmail.com>
Date: Wed, 25 Jun 2025 23:32:20 +0800
Subject: [PATCH 52/68] Remove duplicate entry from `__init__.py` (#897)
### Summary
This PR fixes a duplicated line in `__init__.py`
### Checks
- [x] I've added/updated the relevant documentation
- [x] I've run `make lint` and `make format`
Co-authored-by: easonsshi <easonsshi@tencent.com>
---
src/agents/__init__.py | 1 -
1 file changed, 1 deletion(-)
diff --git a/src/agents/__init__.py b/src/agents/__init__.py
index 3eecaead0..1296b72be 100644
--- a/src/agents/__init__.py
+++ b/src/agents/__init__.py
@@ -206,7 +206,6 @@ def enable_verbose_stdout_logging():
"ToolCallItem",
"ToolCallOutputItem",
"ReasoningItem",
- "ModelResponse",
"ItemHelpers",
"RunHooks",
"AgentHooks",
From 94f80353d9f60d3005f330cd37eea8a7d0ac78a1 Mon Sep 17 00:00:00 2001
From: Kazuhiro Sera <seratch@openai.com>
Date: Thu, 26 Jun 2025 08:28:10 +0900
Subject: [PATCH 53/68] Fix #604 Chat Completion model raises runtime error
when response.choices is empty (#935)
This pull request resolves #604; just checking the existence of the data and avoiding the runtime exception should make sense.
---
src/agents/models/openai_chatcompletions.py | 16 +++++++++-------
1 file changed, 9 insertions(+), 7 deletions(-)
diff --git a/src/agents/models/openai_chatcompletions.py b/src/agents/models/openai_chatcompletions.py
index 08803d8c0..120d726db 100644
--- a/src/agents/models/openai_chatcompletions.py
+++ b/src/agents/models/openai_chatcompletions.py
@@ -7,7 +7,8 @@
from openai import NOT_GIVEN, AsyncOpenAI, AsyncStream
from openai.types import ChatModel
-from openai.types.chat import ChatCompletion, ChatCompletionChunk
+from openai.types.chat import ChatCompletion, ChatCompletionChunk, ChatCompletionMessage
+from openai.types.chat.chat_completion import Choice
from openai.types.responses import Response
from openai.types.responses.response_prompt_param import ResponsePromptParam
from openai.types.responses.response_usage import InputTokensDetails, OutputTokensDetails
@@ -74,8 +75,11 @@ async def get_response(
prompt=prompt,
)
- first_choice = response.choices[0]
- message = first_choice.message
+ message: ChatCompletionMessage | None = None
+ first_choice: Choice | None = None
+ if response.choices and len(response.choices) > 0:
+ first_choice = response.choices[0]
+ message = first_choice.message
if _debug.DONT_LOG_MODEL_DATA:
logger.debug("Received model response")
@@ -86,10 +90,8 @@ async def get_response(
json.dumps(message.model_dump(), indent=2),
)
else:
- logger.debug(
- "LLM resp had no message. finish_reason: %s",
- first_choice.finish_reason,
- )
+ finish_reason = first_choice.finish_reason if first_choice else "-"
+ logger.debug(f"LLM resp had no message. finish_reason: {finish_reason}")
usage = (
Usage(
From 653abc5f598204250193cef4664e8bf183436ddb Mon Sep 17 00:00:00 2001
From: Abbas Asad <168946441+Abbas-Asad@users.noreply.github.com>
Date: Thu, 26 Jun 2025 04:40:22 +0500
Subject: [PATCH 54/68] Fix #892 by adding proper tool description in
context.md (#937)
### Summary
This pull request fixes [issue
#892](https://github.com/openai/openai-agents-python/issues/892) by
adding a missing docstring to the `fetch_user_age` tool function in
`docs/context.md`.
### Problem
Many non-OpenAI LLMs (such as Claude, Gemini, Mistral, etc.) are unable
to use the `fetch_user_age` function because it lacks a docstring. As a
result, they return responses like:
> "I cannot determine the user's age because the available tools lack
the ability to fetch user-specific information."
### Changes Made
- Added a one-line docstring to the `fetch_user_age` function
- Improved return statement to match expected tool output
```python
@function_tool
async def fetch_user_age(wrapper: RunContextWrapper[UserInfo]) -> str:
"""Fetch the age of the user. Call this function to get user's age information."""
return f"The user {wrapper.context.name} is 47 years old"
---
docs/context.md | 3 ++-
1 file changed, 2 insertions(+), 1 deletion(-)
diff --git a/docs/context.md b/docs/context.md
index 4176ec51f..6e54565e0 100644
--- a/docs/context.md
+++ b/docs/context.md
@@ -38,7 +38,8 @@ class UserInfo: # (1)!
@function_tool
async def fetch_user_age(wrapper: RunContextWrapper[UserInfo]) -> str: # (2)!
- return f"User {wrapper.context.name} is 47 years old"
+ """Fetch the age of the user. Call this function to get user's age information."""
+ return f"The user {wrapper.context.name} is 47 years old"
async def main():
user_info = UserInfo(name="John", uid=123)
From c1cb7ce5384329272b6b3cd379bd5c70f9655236 Mon Sep 17 00:00:00 2001
From: Daniel Hashmi <151331476+DanielHashmi@users.noreply.github.com>
Date: Fri, 27 Jun 2025 11:55:13 +0500
Subject: [PATCH 55/68] Duplicate Classifier in pyproject.toml (#951)
"Intended Audience :: Developers" appears twice in the classifiers list
---
pyproject.toml | 1 -
1 file changed, 1 deletion(-)
diff --git a/pyproject.toml b/pyproject.toml
index 75e714768..6c0bbe9f1 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -23,7 +23,6 @@ classifiers = [
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
- "Intended Audience :: Developers",
"Operating System :: OS Independent",
"Topic :: Software Development :: Libraries :: Python Modules",
"License :: OSI Approved :: MIT License",
From a6580a5090399d1558b219018fa8a3a8aa622654 Mon Sep 17 00:00:00 2001
From: Kat <74958594+KatHaruto@users.noreply.github.com>
Date: Fri, 27 Jun 2025 23:31:22 +0900
Subject: [PATCH 56/68] fix: add ensure_ascii=False to json.dumps for correct
Unicode output (#639)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
Set `ensure_ascii=False` in `json.dumps(...)` to allow proper Unicode
character output (e.g., Japanese).
Without this, non-ASCII characters are escaped (e.g., 日本語 →
\u65e5\u672c\u8a9e), which makes logs or exports harder to read.
---
src/agents/extensions/models/litellm_model.py | 10 +++++++---
src/agents/models/openai_chatcompletions.py | 6 +++---
src/agents/models/openai_responses.py | 12 +++++++++---
3 files changed, 19 insertions(+), 9 deletions(-)
diff --git a/src/agents/extensions/models/litellm_model.py b/src/agents/extensions/models/litellm_model.py
index c58a52dae..a06c61dc3 100644
--- a/src/agents/extensions/models/litellm_model.py
+++ b/src/agents/extensions/models/litellm_model.py
@@ -98,7 +98,11 @@ async def get_response(
logger.debug("Received model response")
else:
logger.debug(
- f"LLM resp:\n{json.dumps(response.choices[0].message.model_dump(), indent=2)}\n"
+ f"""LLM resp:\n{
+ json.dumps(
+ response.choices[0].message.model_dump(), indent=2, ensure_ascii=False
+ )
+ }\n"""
)
if hasattr(response, "usage"):
@@ -269,8 +273,8 @@ async def _fetch_response(
else:
logger.debug(
f"Calling Litellm model: {self.model}\n"
- f"{json.dumps(converted_messages, indent=2)}\n"
- f"Tools:\n{json.dumps(converted_tools, indent=2)}\n"
+ f"{json.dumps(converted_messages, indent=2, ensure_ascii=False)}\n"
+ f"Tools:\n{json.dumps(converted_tools, indent=2, ensure_ascii=False)}\n"
f"Stream: {stream}\n"
f"Tool choice: {tool_choice}\n"
f"Response format: {response_format}\n"
diff --git a/src/agents/models/openai_chatcompletions.py b/src/agents/models/openai_chatcompletions.py
index 120d726db..6de431b4d 100644
--- a/src/agents/models/openai_chatcompletions.py
+++ b/src/agents/models/openai_chatcompletions.py
@@ -87,7 +87,7 @@ async def get_response(
if message is not None:
logger.debug(
"LLM resp:\n%s\n",
- json.dumps(message.model_dump(), indent=2),
+ json.dumps(message.model_dump(), indent=2, ensure_ascii=False),
)
else:
finish_reason = first_choice.finish_reason if first_choice else "-"
@@ -256,8 +256,8 @@ async def _fetch_response(
logger.debug("Calling LLM")
else:
logger.debug(
- f"{json.dumps(converted_messages, indent=2)}\n"
- f"Tools:\n{json.dumps(converted_tools, indent=2)}\n"
+ f"{json.dumps(converted_messages, indent=2, ensure_ascii=False)}\n"
+ f"Tools:\n{json.dumps(converted_tools, indent=2, ensure_ascii=False)}\n"
f"Stream: {stream}\n"
f"Tool choice: {tool_choice}\n"
f"Response format: {response_format}\n"
diff --git a/src/agents/models/openai_responses.py b/src/agents/models/openai_responses.py
index 637adaccd..a7ce62983 100644
--- a/src/agents/models/openai_responses.py
+++ b/src/agents/models/openai_responses.py
@@ -96,7 +96,13 @@ async def get_response(
else:
logger.debug(
"LLM resp:\n"
- f"{json.dumps([x.model_dump() for x in response.output], indent=2)}\n"
+ f"""{
+ json.dumps(
+ [x.model_dump() for x in response.output],
+ indent=2,
+ ensure_ascii=False,
+ )
+ }\n"""
)
usage = (
@@ -249,8 +255,8 @@ async def _fetch_response(
else:
logger.debug(
f"Calling LLM {self.model} with input:\n"
- f"{json.dumps(list_input, indent=2)}\n"
- f"Tools:\n{json.dumps(converted_tools.tools, indent=2)}\n"
+ f"{json.dumps(list_input, indent=2, ensure_ascii=False)}\n"
+ f"Tools:\n{json.dumps(converted_tools.tools, indent=2, ensure_ascii=False)}\n"
f"Stream: {stream}\n"
f"Tool choice: {tool_choice}\n"
f"Response format: {response_format}\n"
From 271a1a4b9722016c1baf4d27a0b898fbf1dbf89d Mon Sep 17 00:00:00 2001
From: Richard <164130786@qq.com>
Date: Fri, 27 Jun 2025 22:33:08 +0800
Subject: [PATCH 57/68] Add uv as an alternative Python environment setup
option for issue #884 (#909)
- Add Option A (venv) and Option B (uv) in Get started section
- Mark uv as recommended to align with development workflow
- Include Windows activation commands for both options
- Resolves #884
---
README.md | 13 ++++++++++---
1 file changed, 10 insertions(+), 3 deletions(-)
diff --git a/README.md b/README.md
index 785177916..b334bc20b 100644
--- a/README.md
+++ b/README.md
@@ -20,14 +20,21 @@ Explore the [examples](examples) directory to see the SDK in action, and read ou
1. Set up your Python environment
-```
+- Option A: Using venv (traditional method)
+```bash
python -m venv env
-source env/bin/activate
+source env/bin/activate # On Windows: env\Scripts\activate
+```
+
+- Option B: Using uv (recommended)
+```bash
+uv venv
+source .venv/bin/activate # On Windows: .venv\Scripts\activate
```
2. Install Agents SDK
-```
+```bash
pip install openai-agents
```
From 816b7702bc78fed6aae7678f98ac827f03e4e4df Mon Sep 17 00:00:00 2001
From: Rehan Ul Haq <mmrhaq@gmail.com>
Date: Fri, 27 Jun 2025 19:37:57 +0500
Subject: [PATCH 58/68] Fix and Document `parallel_tool_calls` Attribute in
ModelSettings (#763)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
Closes #762
**Description**
This PR updates the docstring for the `parallel_tool_calls` attribute in
the `ModelSettings` dataclass to accurately reflect its default
behavior.. The previous docstring incorrectly stated that the default of
`False`, while the actual behavior is dependent on the underlying model
provider's default.
As noted in OpenAI's (here refers as model provider) [Function
Calling](https://platform.openai.com/docs/guides/function-calling?api-mode=responses#parallel-function-calling)
documentation, "The model may choose to call multiple functions in a
single turn. You can prevent this by setting parallel_tool_calls to
false, which ensures exactly zero or one tool is called."
Therefore, when the `parallel_tool_calls` attribute in the
`ModelSettings` dataclass is set to `None` (i.e., `parallel_tool_calls:
bool | None = None`), and this value is passed directly to the API
without modification, it defers to the model provider's default behavior
for parallel tool calls. This is typically `True` for most current
providers, but it's important to acknowledge that this isn't a fixed
default within our codebase.
The new docstring is formatted for automatic documentation generation
and provides clear, accurate information for users and developers.
**Key changes:**
* **Clarified the default behavior of `parallel_tool_calls`:** Instead
of stating a fixed default, the docstring now accurately reflects that
the behavior defaults to whatever the model provider does when the
attribute is `None`.
* Improved the docstring format for compatibility with documentation
tools.
* Clarified the purpose and usage of the `parallel_tool_calls`
attribute.
**Testing:**
* Explicitly set `parallel_tool_calls=False` in both the `run_config` of
the `Runner.run` method and in the agent’s `model_settings` attribute.
* Example for `Runner.run`:
```python
Runner.run(agent, input, run_config=RunConfig(model_settings=ModelSettings(parallel_tool_calls=False)))
```
* Example for agent initialization:
```python
agent = Agent(..., model_settings=ModelSettings(parallel_tool_calls=False))
```
* Verified that when `parallel_tool_calls=False`, tools are called
sequentially.
* Confirmed that by default (without setting the attribute), tools are
called in parallel (Tested with openai models).
* Checked that the updated docstring renders correctly in the generated
documentation.
* Ensured the default value in code matches the documentation.
**Why this is important:**
* Prevents confusion for users and developers regarding the default
behavior of `parallel_tool_calls`.
* Ensures that generated documentation is accurate and up-to-date.
* Improves overall code quality and maintainability.
---
src/agents/model_settings.py | 9 +++++++--
1 file changed, 7 insertions(+), 2 deletions(-)
diff --git a/src/agents/model_settings.py b/src/agents/model_settings.py
index f844eb87c..709046b7a 100644
--- a/src/agents/model_settings.py
+++ b/src/agents/model_settings.py
@@ -37,8 +37,13 @@ class ModelSettings:
"""The tool choice to use when calling the model."""
parallel_tool_calls: bool | None = None
- """Whether to use parallel tool calls when calling the model.
- Defaults to False if not provided."""
+ """Controls whether the model can make multiple parallel tool calls in a single turn.
+ If not provided (i.e., set to None), this behavior defers to the underlying
+ model provider's default. For most current providers (e.g., OpenAI), this typically
+ means parallel tool calls are enabled (True).
+ Set to True to explicitly enable parallel tool calls, or False to restrict the
+ model to at most one tool call per turn.
+ """
truncation: Literal["auto", "disabled"] | None = None
"""The truncation strategy to use when calling the model."""
From 0475450d59daec1f1610f17fc549cc3d3dc0f04d Mon Sep 17 00:00:00 2001
From: CCM <ccmien@gmail.com>
Date: Fri, 27 Jun 2025 22:39:49 +0800
Subject: [PATCH 59/68] replace .py file with .ipynb for Jupyter example (#262)
Co-authored-by: chenchaomin <chenchaomin@guazi.com>
---
README.md | 2 +-
examples/basic/hello_world_jupyter.ipynb | 45 ++++++++++++++++++++++++
examples/basic/hello_world_jupyter.py | 11 ------
3 files changed, 46 insertions(+), 12 deletions(-)
create mode 100644 examples/basic/hello_world_jupyter.ipynb
delete mode 100644 examples/basic/hello_world_jupyter.py
diff --git a/README.md b/README.md
index b334bc20b..079aebb06 100644
--- a/README.md
+++ b/README.md
@@ -57,7 +57,7 @@ print(result.final_output)
(_If running this, ensure you set the `OPENAI_API_KEY` environment variable_)
-(_For Jupyter notebook users, see [hello_world_jupyter.py](examples/basic/hello_world_jupyter.py)_)
+(_For Jupyter notebook users, see [hello_world_jupyter.ipynb](examples/basic/hello_world_jupyter.ipynb)_)
## Handoffs example
diff --git a/examples/basic/hello_world_jupyter.ipynb b/examples/basic/hello_world_jupyter.ipynb
new file mode 100644
index 000000000..42ee8e6a2
--- /dev/null
+++ b/examples/basic/hello_world_jupyter.ipynb
@@ -0,0 +1,45 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "8a77ee2e-22f2-409c-837d-b994978b0aa2",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "A function calls self, \n",
+ "Unraveling layers deep, \n",
+ "Base case ends the quest. \n",
+ "\n",
+ "Infinite loops lurk, \n",
+ "Mind the base condition well, \n",
+ "Or it will not work. \n",
+ "\n",
+ "Trees and lists unfold, \n",
+ "Elegant solutions bloom, \n",
+ "Recursion's art told.\n"
+ ]
+ }
+ ],
+ "source": [
+ "from agents import Agent, Runner\n",
+ "\n",
+ "agent = Agent(name=\"Assistant\", instructions=\"You are a helpful assistant\")\n",
+ "\n",
+ "# Intended for Jupyter notebooks where there's an existing event loop\n",
+ "result = await Runner.run(agent, \"Write a haiku about recursion in programming.\") # type: ignore[top-level-await] # noqa: F704\n",
+ "print(result.final_output)"
+ ]
+ }
+ ],
+ "metadata": {
+ "language_info": {
+ "name": "python"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/examples/basic/hello_world_jupyter.py b/examples/basic/hello_world_jupyter.py
deleted file mode 100644
index c929a7c68..000000000
--- a/examples/basic/hello_world_jupyter.py
+++ /dev/null
@@ -1,11 +0,0 @@
-from agents import Agent, Runner
-
-agent = Agent(name="Assistant", instructions="You are a helpful assistant")
-
-# Intended for Jupyter notebooks where there's an existing event loop
-result = await Runner.run(agent, "Write a haiku about recursion in programming.") # type: ignore[top-level-await] # noqa: F704
-print(result.final_output)
-
-# Code within code loops,
-# Infinite mirrors reflect—
-# Logic folds on self.
From 445033946bfa5996985c99a9bff5c26705179703 Mon Sep 17 00:00:00 2001
From: devtalker <ycwen1119@gmail.com>
Date: Fri, 27 Jun 2025 23:22:03 +0800
Subject: [PATCH 60/68] feat: add MCP tool filtering support (#861)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
## Add MCP Tool Filtering Support
This PR implements tool filtering capabilities for MCP servers,
addressing multiple community requests for this feature.
### Problem
Currently, Agent SDK automatically fetches all available tools from MCP
servers without the ability to select specific tools. This creates
several issues:
- Unwanted tools occupy LLM context and affect tool selection accuracy
- Security concerns when limiting tool access scope
- Tool name conflicts between multiple servers
- Need for different tool subsets across different agents
### Solution
Implements a two-level filtering system:
**Server-level filtering:**
```python
server = MCPServerStdio(
params={"command": "npx", "args": ["-y", "@modelcontextprotocol/server-filesystem", "/path"]},
allowed_tools=["read_file", "write_file"], # whitelist
excluded_tools=["delete_file"] # blacklist
)
```
**Agent-level filtering:**
```python
agent = Agent(
name="Assistant",
mcp_servers=[server1, server2],
mcp_config={
"allowed_tools": {"server1": ["read_file", "write_file"]},
"excluded_tools": {"server2": ["dangerous_tool"]}
}
)
```
### Features
- ✅ Server-level `allowed_tools`/`excluded_tools` parameters for all MCP
server types
- ✅ Agent-level filtering via `mcp_config`
- ✅ Hierarchical filtering (server-level first, then agent-level)
- ✅ Comprehensive test coverage (8 test cases)
- ✅ Updated documentation with examples
### Related Issues
#376, #851, #830, #863
### Testing
All existing tests pass + 8 new test cases covering various filtering
scenarios.
---
docs/ja/mcp.md | 9 +-
docs/mcp.md | 96 +++++++++++-
src/agents/agent.py | 10 +-
src/agents/mcp/__init__.py | 14 +-
src/agents/mcp/server.py | 155 ++++++++++++++++++--
src/agents/mcp/util.py | 94 +++++++++++-
src/agents/tool.py | 1 +
tests/mcp/helpers.py | 49 ++++++-
tests/mcp/test_caching.py | 22 ++-
tests/mcp/test_mcp_util.py | 20 ++-
tests/mcp/test_server_errors.py | 7 +-
tests/mcp/test_tool_filtering.py | 243 +++++++++++++++++++++++++++++++
12 files changed, 675 insertions(+), 45 deletions(-)
create mode 100644 tests/mcp/test_tool_filtering.py
diff --git a/docs/ja/mcp.md b/docs/ja/mcp.md
index 09804beb2..1e394a5e6 100644
--- a/docs/ja/mcp.md
+++ b/docs/ja/mcp.md
@@ -23,13 +23,20 @@ Agents SDK は MCP をサポートしており、これにより幅広い MCP
たとえば、[公式 MCP filesystem サーバー](https://www.npmjs.com/package/@modelcontextprotocol/server-filesystem)を利用する場合は次のようになります。
```python
+from agents.run_context import RunContextWrapper
+
async with MCPServerStdio(
params={
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-filesystem", samples_dir],
}
) as server:
- tools = await server.list_tools()
+ # 注意：実際には通常は MCP サーバーをエージェントに追加し、
+ # フレームワークがツール一覧の取得を自動的に処理するようにします。
+ # list_tools() への直接呼び出しには run_context と agent パラメータが必要です。
+ run_context = RunContextWrapper(context=None)
+ agent = Agent(name="test", instructions="test")
+ tools = await server.list_tools(run_context, agent)
```
## MCP サーバーの利用
diff --git a/docs/mcp.md b/docs/mcp.md
index 76d142029..d30a916ac 100644
--- a/docs/mcp.md
+++ b/docs/mcp.md
@@ -19,13 +19,20 @@ You can use the [`MCPServerStdio`][agents.mcp.server.MCPServerStdio], [`MCPServe
For example, this is how you'd use the [official MCP filesystem server](https://www.npmjs.com/package/@modelcontextprotocol/server-filesystem).
```python
+from agents.run_context import RunContextWrapper
+
async with MCPServerStdio(
params={
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-filesystem", samples_dir],
}
) as server:
- tools = await server.list_tools()
+ # Note: In practice, you typically add the server to an Agent
+ # and let the framework handle tool listing automatically.
+ # Direct calls to list_tools() require run_context and agent parameters.
+ run_context = RunContextWrapper(context=None)
+ agent = Agent(name="test", instructions="test")
+ tools = await server.list_tools(run_context, agent)
```
## Using MCP servers
@@ -41,6 +48,93 @@ agent=Agent(
)
```
+## Tool filtering
+
+You can filter which tools are available to your Agent by configuring tool filters on MCP servers. The SDK supports both static and dynamic tool filtering.
+
+### Static tool filtering
+
+For simple allow/block lists, you can use static filtering:
+
+```python
+from agents.mcp import create_static_tool_filter
+
+# Only expose specific tools from this server
+server = MCPServerStdio(
+ params={
+ "command": "npx",
+ "args": ["-y", "@modelcontextprotocol/server-filesystem", samples_dir],
+ },
+ tool_filter=create_static_tool_filter(
+ allowed_tool_names=["read_file", "write_file"]
+ )
+)
+
+# Exclude specific tools from this server
+server = MCPServerStdio(
+ params={
+ "command": "npx",
+ "args": ["-y", "@modelcontextprotocol/server-filesystem", samples_dir],
+ },
+ tool_filter=create_static_tool_filter(
+ blocked_tool_names=["delete_file"]
+ )
+)
+
+```
+
+**When both `allowed_tool_names` and `blocked_tool_names` are configured, the processing order is:**
+1. First apply `allowed_tool_names` (allowlist) - only keep the specified tools
+2. Then apply `blocked_tool_names` (blocklist) - exclude specified tools from the remaining tools
+
+For example, if you configure `allowed_tool_names=["read_file", "write_file", "delete_file"]` and `blocked_tool_names=["delete_file"]`, only `read_file` and `write_file` tools will be available.
+
+### Dynamic tool filtering
+
+For more complex filtering logic, you can use dynamic filters with functions:
+
+```python
+from agents.mcp import ToolFilterContext
+
+# Simple synchronous filter
+def custom_filter(context: ToolFilterContext, tool) -> bool:
+ """Example of a custom tool filter."""
+ # Filter logic based on tool name patterns
+ return tool.name.startswith("allowed_prefix")
+
+# Context-aware filter
+def context_aware_filter(context: ToolFilterContext, tool) -> bool:
+ """Filter tools based on context information."""
+ # Access agent information
+ agent_name = context.agent.name
+
+ # Access server information
+ server_name = context.server_name
+
+ # Implement your custom filtering logic here
+ return some_filtering_logic(agent_name, server_name, tool)
+
+# Asynchronous filter
+async def async_filter(context: ToolFilterContext, tool) -> bool:
+ """Example of an asynchronous filter."""
+ # Perform async operations if needed
+ result = await some_async_check(context, tool)
+ return result
+
+server = MCPServerStdio(
+ params={
+ "command": "npx",
+ "args": ["-y", "@modelcontextprotocol/server-filesystem", samples_dir],
+ },
+ tool_filter=custom_filter # or context_aware_filter or async_filter
+)
+```
+
+The `ToolFilterContext` provides access to:
+- `run_context`: The current run context
+- `agent`: The agent requesting the tools
+- `server_name`: The name of the MCP server
+
## Caching
Every time an Agent runs, it calls `list_tools()` on the MCP server. This can be a latency hit, especially if the server is a remote server. To automatically cache the list of tools, you can pass `cache_tools_list=True` to [`MCPServerStdio`][agents.mcp.server.MCPServerStdio], [`MCPServerSse`][agents.mcp.server.MCPServerSse], and [`MCPServerStreamableHttp`][agents.mcp.server.MCPServerStreamableHttp]. You should only do this if you're certain the tool list will not change.
diff --git a/src/agents/agent.py b/src/agents/agent.py
index 61a9abe0c..6c87297f1 100644
--- a/src/agents/agent.py
+++ b/src/agents/agent.py
@@ -256,14 +256,18 @@ async def get_prompt(
"""Get the prompt for the agent."""
return await PromptUtil.to_model_input(self.prompt, run_context, self)
- async def get_mcp_tools(self) -> list[Tool]:
+ async def get_mcp_tools(
+ self, run_context: RunContextWrapper[TContext]
+ ) -> list[Tool]:
"""Fetches the available tools from the MCP servers."""
convert_schemas_to_strict = self.mcp_config.get("convert_schemas_to_strict", False)
- return await MCPUtil.get_all_function_tools(self.mcp_servers, convert_schemas_to_strict)
+ return await MCPUtil.get_all_function_tools(
+ self.mcp_servers, convert_schemas_to_strict, run_context, self
+ )
async def get_all_tools(self, run_context: RunContextWrapper[Any]) -> list[Tool]:
"""All agent tools, including MCP tools and function tools."""
- mcp_tools = await self.get_mcp_tools()
+ mcp_tools = await self.get_mcp_tools(run_context)
async def _check_tool_enabled(tool: Tool) -> bool:
if not isinstance(tool, FunctionTool):
diff --git a/src/agents/mcp/__init__.py b/src/agents/mcp/__init__.py
index d4eb8fa68..da5a68b16 100644
--- a/src/agents/mcp/__init__.py
+++ b/src/agents/mcp/__init__.py
@@ -11,7 +11,14 @@
except ImportError:
pass
-from .util import MCPUtil
+from .util import (
+ MCPUtil,
+ ToolFilter,
+ ToolFilterCallable,
+ ToolFilterContext,
+ ToolFilterStatic,
+ create_static_tool_filter,
+)
__all__ = [
"MCPServer",
@@ -22,4 +29,9 @@
"MCPServerStreamableHttp",
"MCPServerStreamableHttpParams",
"MCPUtil",
+ "ToolFilter",
+ "ToolFilterCallable",
+ "ToolFilterContext",
+ "ToolFilterStatic",
+ "create_static_tool_filter",
]
diff --git a/src/agents/mcp/server.py b/src/agents/mcp/server.py
index 3d1e17790..f6c2b58ef 100644
--- a/src/agents/mcp/server.py
+++ b/src/agents/mcp/server.py
@@ -2,10 +2,11 @@
import abc
import asyncio
+import inspect
from contextlib import AbstractAsyncContextManager, AsyncExitStack
from datetime import timedelta
from pathlib import Path
-from typing import Any, Literal
+from typing import TYPE_CHECKING, Any, Literal, cast
from anyio.streams.memory import MemoryObjectReceiveStream, MemoryObjectSendStream
from mcp import ClientSession, StdioServerParameters, Tool as MCPTool, stdio_client
@@ -17,6 +18,11 @@
from ..exceptions import UserError
from ..logger import logger
+from ..run_context import RunContextWrapper
+from .util import ToolFilter, ToolFilterCallable, ToolFilterContext, ToolFilterStatic
+
+if TYPE_CHECKING:
+ from ..agent import Agent
class MCPServer(abc.ABC):
@@ -44,7 +50,11 @@ async def cleanup(self):
pass
@abc.abstractmethod
- async def list_tools(self) -> list[MCPTool]:
+ async def list_tools(
+ self,
+ run_context: RunContextWrapper[Any],
+ agent: Agent[Any],
+ ) -> list[MCPTool]:
"""List the tools available on the server."""
pass
@@ -57,7 +67,12 @@ async def call_tool(self, tool_name: str, arguments: dict[str, Any] | None) -> C
class _MCPServerWithClientSession(MCPServer, abc.ABC):
"""Base class for MCP servers that use a `ClientSession` to communicate with the server."""
- def __init__(self, cache_tools_list: bool, client_session_timeout_seconds: float | None):
+ def __init__(
+ self,
+ cache_tools_list: bool,
+ client_session_timeout_seconds: float | None,
+ tool_filter: ToolFilter = None,
+ ):
"""
Args:
cache_tools_list: Whether to cache the tools list. If `True`, the tools list will be
@@ -68,6 +83,7 @@ def __init__(self, cache_tools_list: bool, client_session_timeout_seconds: float
(by avoiding a round-trip to the server every time).
client_session_timeout_seconds: the read timeout passed to the MCP ClientSession.
+ tool_filter: The tool filter to use for filtering tools.
"""
self.session: ClientSession | None = None
self.exit_stack: AsyncExitStack = AsyncExitStack()
@@ -81,6 +97,88 @@ def __init__(self, cache_tools_list: bool, client_session_timeout_seconds: float
self._cache_dirty = True
self._tools_list: list[MCPTool] | None = None
+ self.tool_filter = tool_filter
+
+ async def _apply_tool_filter(
+ self,
+ tools: list[MCPTool],
+ run_context: RunContextWrapper[Any],
+ agent: Agent[Any],
+ ) -> list[MCPTool]:
+ """Apply the tool filter to the list of tools."""
+ if self.tool_filter is None:
+ return tools
+
+ # Handle static tool filter
+ if isinstance(self.tool_filter, dict):
+ return self._apply_static_tool_filter(tools, self.tool_filter)
+
+ # Handle callable tool filter (dynamic filter)
+ else:
+ return await self._apply_dynamic_tool_filter(tools, run_context, agent)
+
+ def _apply_static_tool_filter(
+ self,
+ tools: list[MCPTool],
+ static_filter: ToolFilterStatic
+ ) -> list[MCPTool]:
+ """Apply static tool filtering based on allowlist and blocklist."""
+ filtered_tools = tools
+
+ # Apply allowed_tool_names filter (whitelist)
+ if "allowed_tool_names" in static_filter:
+ allowed_names = static_filter["allowed_tool_names"]
+ filtered_tools = [t for t in filtered_tools if t.name in allowed_names]
+
+ # Apply blocked_tool_names filter (blacklist)
+ if "blocked_tool_names" in static_filter:
+ blocked_names = static_filter["blocked_tool_names"]
+ filtered_tools = [t for t in filtered_tools if t.name not in blocked_names]
+
+ return filtered_tools
+
+ async def _apply_dynamic_tool_filter(
+ self,
+ tools: list[MCPTool],
+ run_context: RunContextWrapper[Any],
+ agent: Agent[Any],
+ ) -> list[MCPTool]:
+ """Apply dynamic tool filtering using a callable filter function."""
+
+ # Ensure we have a callable filter and cast to help mypy
+ if not callable(self.tool_filter):
+ raise ValueError("Tool filter must be callable for dynamic filtering")
+ tool_filter_func = cast(ToolFilterCallable, self.tool_filter)
+
+ # Create filter context
+ filter_context = ToolFilterContext(
+ run_context=run_context,
+ agent=agent,
+ server_name=self.name,
+ )
+
+ filtered_tools = []
+ for tool in tools:
+ try:
+ # Call the filter function with context
+ result = tool_filter_func(filter_context, tool)
+
+ if inspect.isawaitable(result):
+ should_include = await result
+ else:
+ should_include = result
+
+ if should_include:
+ filtered_tools.append(tool)
+ except Exception as e:
+ logger.error(
+ f"Error applying tool filter to tool '{tool.name}' on server '{self.name}': {e}"
+ )
+ # On error, exclude the tool for safety
+ continue
+
+ return filtered_tools
+
@abc.abstractmethod
def create_streams(
self,
@@ -131,21 +229,30 @@ async def connect(self):
await self.cleanup()
raise
- async def list_tools(self) -> list[MCPTool]:
+ async def list_tools(
+ self,
+ run_context: RunContextWrapper[Any],
+ agent: Agent[Any],
+ ) -> list[MCPTool]:
"""List the tools available on the server."""
if not self.session:
raise UserError("Server not initialized. Make sure you call `connect()` first.")
# Return from cache if caching is enabled, we have tools, and the cache is not dirty
if self.cache_tools_list and not self._cache_dirty and self._tools_list:
- return self._tools_list
-
- # Reset the cache dirty to False
- self._cache_dirty = False
-
- # Fetch the tools from the server
- self._tools_list = (await self.session.list_tools()).tools
- return self._tools_list
+ tools = self._tools_list
+ else:
+ # Reset the cache dirty to False
+ self._cache_dirty = False
+ # Fetch the tools from the server
+ self._tools_list = (await self.session.list_tools()).tools
+ tools = self._tools_list
+
+ # Filter tools based on tool_filter
+ filtered_tools = tools
+ if self.tool_filter is not None:
+ filtered_tools = await self._apply_tool_filter(filtered_tools, run_context, agent)
+ return filtered_tools
async def call_tool(self, tool_name: str, arguments: dict[str, Any] | None) -> CallToolResult:
"""Invoke a tool on the server."""
@@ -206,6 +313,7 @@ def __init__(
cache_tools_list: bool = False,
name: str | None = None,
client_session_timeout_seconds: float | None = 5,
+ tool_filter: ToolFilter = None,
):
"""Create a new MCP server based on the stdio transport.
@@ -223,8 +331,13 @@ def __init__(
name: A readable name for the server. If not provided, we'll create one from the
command.
client_session_timeout_seconds: the read timeout passed to the MCP ClientSession.
+ tool_filter: The tool filter to use for filtering tools.
"""
- super().__init__(cache_tools_list, client_session_timeout_seconds)
+ super().__init__(
+ cache_tools_list,
+ client_session_timeout_seconds,
+ tool_filter,
+ )
self.params = StdioServerParameters(
command=params["command"],
@@ -283,6 +396,7 @@ def __init__(
cache_tools_list: bool = False,
name: str | None = None,
client_session_timeout_seconds: float | None = 5,
+ tool_filter: ToolFilter = None,
):
"""Create a new MCP server based on the HTTP with SSE transport.
@@ -302,8 +416,13 @@ def __init__(
URL.
client_session_timeout_seconds: the read timeout passed to the MCP ClientSession.
+ tool_filter: The tool filter to use for filtering tools.
"""
- super().__init__(cache_tools_list, client_session_timeout_seconds)
+ super().__init__(
+ cache_tools_list,
+ client_session_timeout_seconds,
+ tool_filter,
+ )
self.params = params
self._name = name or f"sse: {self.params['url']}"
@@ -362,6 +481,7 @@ def __init__(
cache_tools_list: bool = False,
name: str | None = None,
client_session_timeout_seconds: float | None = 5,
+ tool_filter: ToolFilter = None,
):
"""Create a new MCP server based on the Streamable HTTP transport.
@@ -382,8 +502,13 @@ def __init__(
URL.
client_session_timeout_seconds: the read timeout passed to the MCP ClientSession.
+ tool_filter: The tool filter to use for filtering tools.
"""
- super().__init__(cache_tools_list, client_session_timeout_seconds)
+ super().__init__(
+ cache_tools_list,
+ client_session_timeout_seconds,
+ tool_filter,
+ )
self.params = params
self._name = name or f"streamable_http: {self.params['url']}"
diff --git a/src/agents/mcp/util.py b/src/agents/mcp/util.py
index 5a963bc01..48da9f841 100644
--- a/src/agents/mcp/util.py
+++ b/src/agents/mcp/util.py
@@ -1,6 +1,9 @@
import functools
import json
-from typing import TYPE_CHECKING, Any
+from dataclasses import dataclass
+from typing import TYPE_CHECKING, Any, Callable, Optional, Union
+
+from typing_extensions import NotRequired, TypedDict
from agents.strict_schema import ensure_strict_json_schema
@@ -10,25 +13,102 @@
from ..run_context import RunContextWrapper
from ..tool import FunctionTool, Tool
from ..tracing import FunctionSpanData, get_current_span, mcp_tools_span
+from ..util._types import MaybeAwaitable
if TYPE_CHECKING:
from mcp.types import Tool as MCPTool
+ from ..agent import Agent
from .server import MCPServer
+@dataclass
+class ToolFilterContext:
+ """Context information available to tool filter functions."""
+
+ run_context: RunContextWrapper[Any]
+ """The current run context."""
+
+ agent: "Agent[Any]"
+ """The agent that is requesting the tool list."""
+
+ server_name: str
+ """The name of the MCP server."""
+
+
+ToolFilterCallable = Callable[["ToolFilterContext", "MCPTool"], MaybeAwaitable[bool]]
+"""A function that determines whether a tool should be available.
+
+Args:
+ context: The context information including run context, agent, and server name.
+ tool: The MCP tool to filter.
+
+Returns:
+ Whether the tool should be available (True) or filtered out (False).
+"""
+
+
+class ToolFilterStatic(TypedDict):
+ """Static tool filter configuration using allowlists and blocklists."""
+
+ allowed_tool_names: NotRequired[list[str]]
+ """Optional list of tool names to allow (whitelist).
+ If set, only these tools will be available."""
+
+ blocked_tool_names: NotRequired[list[str]]
+ """Optional list of tool names to exclude (blacklist).
+ If set, these tools will be filtered out."""
+
+
+ToolFilter = Union[ToolFilterCallable, ToolFilterStatic, None]
+"""A tool filter that can be either a function, static configuration, or None (no filtering)."""
+
+
+def create_static_tool_filter(
+ allowed_tool_names: Optional[list[str]] = None,
+ blocked_tool_names: Optional[list[str]] = None,
+) -> Optional[ToolFilterStatic]:
+ """Create a static tool filter from allowlist and blocklist parameters.
+
+ This is a convenience function for creating a ToolFilterStatic.
+
+ Args:
+ allowed_tool_names: Optional list of tool names to allow (whitelist).
+ blocked_tool_names: Optional list of tool names to exclude (blacklist).
+
+ Returns:
+ A ToolFilterStatic if any filtering is specified, None otherwise.
+ """
+ if allowed_tool_names is None and blocked_tool_names is None:
+ return None
+
+ filter_dict: ToolFilterStatic = {}
+ if allowed_tool_names is not None:
+ filter_dict["allowed_tool_names"] = allowed_tool_names
+ if blocked_tool_names is not None:
+ filter_dict["blocked_tool_names"] = blocked_tool_names
+
+ return filter_dict
+
+
class MCPUtil:
"""Set of utilities for interop between MCP and Agents SDK tools."""
@classmethod
async def get_all_function_tools(
- cls, servers: list["MCPServer"], convert_schemas_to_strict: bool
+ cls,
+ servers: list["MCPServer"],
+ convert_schemas_to_strict: bool,
+ run_context: RunContextWrapper[Any],
+ agent: "Agent[Any]",
) -> list[Tool]:
"""Get all function tools from a list of MCP servers."""
tools = []
tool_names: set[str] = set()
for server in servers:
- server_tools = await cls.get_function_tools(server, convert_schemas_to_strict)
+ server_tools = await cls.get_function_tools(
+ server, convert_schemas_to_strict, run_context, agent
+ )
server_tool_names = {tool.name for tool in server_tools}
if len(server_tool_names & tool_names) > 0:
raise UserError(
@@ -42,12 +122,16 @@ async def get_all_function_tools(
@classmethod
async def get_function_tools(
- cls, server: "MCPServer", convert_schemas_to_strict: bool
+ cls,
+ server: "MCPServer",
+ convert_schemas_to_strict: bool,
+ run_context: RunContextWrapper[Any],
+ agent: "Agent[Any]",
) -> list[Tool]:
"""Get all function tools from a single MCP server."""
with mcp_tools_span(server=server.name) as span:
- tools = await server.list_tools()
+ tools = await server.list_tools(run_context, agent)
span.span_data.result = [tool.name for tool in tools]
return [cls.to_function_tool(tool, server, convert_schemas_to_strict) for tool in tools]
diff --git a/src/agents/tool.py b/src/agents/tool.py
index ce66a53ba..283a9e24f 100644
--- a/src/agents/tool.py
+++ b/src/agents/tool.py
@@ -26,6 +26,7 @@
from .util._types import MaybeAwaitable
if TYPE_CHECKING:
+
from .agent import Agent
ToolParams = ParamSpec("ToolParams")
diff --git a/tests/mcp/helpers.py b/tests/mcp/helpers.py
index 8ff153c18..e0d8a813d 100644
--- a/tests/mcp/helpers.py
+++ b/tests/mcp/helpers.py
@@ -1,3 +1,4 @@
+import asyncio
import json
import shutil
from typing import Any
@@ -6,6 +7,8 @@
from mcp.types import CallToolResult, TextContent
from agents.mcp import MCPServer
+from agents.mcp.server import _MCPServerWithClientSession
+from agents.mcp.util import ToolFilter
tee = shutil.which("tee") or ""
assert tee, "tee not found"
@@ -28,11 +31,41 @@ async def __aexit__(self, exc_type, exc_val, exc_tb):
pass
+class _TestFilterServer(_MCPServerWithClientSession):
+ """Minimal implementation of _MCPServerWithClientSession for testing tool filtering"""
+
+ def __init__(self, tool_filter: ToolFilter, server_name: str):
+ # Initialize parent class properly to avoid type errors
+ super().__init__(
+ cache_tools_list=False,
+ client_session_timeout_seconds=None,
+ tool_filter=tool_filter,
+ )
+ self._server_name: str = server_name
+ # Override some attributes for test isolation
+ self.session = None
+ self._cleanup_lock = asyncio.Lock()
+
+ def create_streams(self):
+ raise NotImplementedError("Not needed for filtering tests")
+
+ @property
+ def name(self) -> str:
+ return self._server_name
+
+
class FakeMCPServer(MCPServer):
- def __init__(self, tools: list[MCPTool] | None = None):
+ def __init__(
+ self,
+ tools: list[MCPTool] | None = None,
+ tool_filter: ToolFilter = None,
+ server_name: str = "fake_mcp_server",
+ ):
self.tools: list[MCPTool] = tools or []
self.tool_calls: list[str] = []
self.tool_results: list[str] = []
+ self.tool_filter = tool_filter
+ self._server_name = server_name
def add_tool(self, name: str, input_schema: dict[str, Any]):
self.tools.append(MCPTool(name=name, inputSchema=input_schema))
@@ -43,8 +76,16 @@ async def connect(self):
async def cleanup(self):
pass
- async def list_tools(self):
- return self.tools
+ async def list_tools(self, run_context=None, agent=None):
+ tools = self.tools
+
+ # Apply tool filtering using the REAL implementation
+ if self.tool_filter is not None:
+ # Use the real _MCPServerWithClientSession filtering logic
+ filter_server = _TestFilterServer(self.tool_filter, self.name)
+ tools = await filter_server._apply_tool_filter(tools, run_context, agent)
+
+ return tools
async def call_tool(self, tool_name: str, arguments: dict[str, Any] | None) -> CallToolResult:
self.tool_calls.append(tool_name)
@@ -55,4 +96,4 @@ async def call_tool(self, tool_name: str, arguments: dict[str, Any] | None) -> C
@property
def name(self) -> str:
- return "fake_mcp_server"
+ return self._server_name
diff --git a/tests/mcp/test_caching.py b/tests/mcp/test_caching.py
index cac409e6e..f31cdf951 100644
--- a/tests/mcp/test_caching.py
+++ b/tests/mcp/test_caching.py
@@ -3,7 +3,9 @@
import pytest
from mcp.types import ListToolsResult, Tool as MCPTool
+from agents import Agent
from agents.mcp import MCPServerStdio
+from agents.run_context import RunContextWrapper
from .helpers import DummyStreamsContextManager, tee
@@ -33,25 +35,29 @@ async def test_server_caching_works(
mock_list_tools.return_value = ListToolsResult(tools=tools)
async with server:
+ # Create test context and agent
+ run_context = RunContextWrapper(context=None)
+ agent = Agent(name="test_agent", instructions="Test agent")
+
# Call list_tools() multiple times
- tools = await server.list_tools()
- assert tools == tools
+ result_tools = await server.list_tools(run_context, agent)
+ assert result_tools == tools
assert mock_list_tools.call_count == 1, "list_tools() should have been called once"
# Call list_tools() again, should return the cached value
- tools = await server.list_tools()
- assert tools == tools
+ result_tools = await server.list_tools(run_context, agent)
+ assert result_tools == tools
assert mock_list_tools.call_count == 1, "list_tools() should not have been called again"
# Invalidate the cache and call list_tools() again
server.invalidate_tools_cache()
- tools = await server.list_tools()
- assert tools == tools
+ result_tools = await server.list_tools(run_context, agent)
+ assert result_tools == tools
assert mock_list_tools.call_count == 2, "list_tools() should be called again"
# Without invalidating the cache, calling list_tools() again should return the cached value
- tools = await server.list_tools()
- assert tools == tools
+ result_tools = await server.list_tools(run_context, agent)
+ assert result_tools == tools
diff --git a/tests/mcp/test_mcp_util.py b/tests/mcp/test_mcp_util.py
index 74356a16d..3230e63dd 100644
--- a/tests/mcp/test_mcp_util.py
+++ b/tests/mcp/test_mcp_util.py
@@ -57,7 +57,10 @@ async def test_get_all_function_tools():
server3.add_tool(names[4], schemas[4])
servers: list[MCPServer] = [server1, server2, server3]
- tools = await MCPUtil.get_all_function_tools(servers, convert_schemas_to_strict=False)
+ run_context = RunContextWrapper(context=None)
+ agent = Agent(name="test_agent", instructions="Test agent")
+
+ tools = await MCPUtil.get_all_function_tools(servers, False, run_context, agent)
assert len(tools) == 5
assert all(tool.name in names for tool in tools)
@@ -70,7 +73,7 @@ async def test_get_all_function_tools():
assert tool.name == names[idx]
# Also make sure it works with strict schemas
- tools = await MCPUtil.get_all_function_tools(servers, convert_schemas_to_strict=True)
+ tools = await MCPUtil.get_all_function_tools(servers, True, run_context, agent)
assert len(tools) == 5
assert all(tool.name in names for tool in tools)
@@ -144,7 +147,8 @@ async def test_agent_convert_schemas_true():
agent = Agent(
name="test_agent", mcp_servers=[server], mcp_config={"convert_schemas_to_strict": True}
)
- tools = await agent.get_mcp_tools()
+ run_context = RunContextWrapper(context=None)
+ tools = await agent.get_mcp_tools(run_context)
foo_tool = next(tool for tool in tools if tool.name == "foo")
assert isinstance(foo_tool, FunctionTool)
@@ -208,7 +212,8 @@ async def test_agent_convert_schemas_false():
agent = Agent(
name="test_agent", mcp_servers=[server], mcp_config={"convert_schemas_to_strict": False}
)
- tools = await agent.get_mcp_tools()
+ run_context = RunContextWrapper(context=None)
+ tools = await agent.get_mcp_tools(run_context)
foo_tool = next(tool for tool in tools if tool.name == "foo")
assert isinstance(foo_tool, FunctionTool)
@@ -245,7 +250,8 @@ async def test_agent_convert_schemas_unset():
server.add_tool("bar", non_strict_schema)
server.add_tool("baz", possible_to_convert_schema)
agent = Agent(name="test_agent", mcp_servers=[server])
- tools = await agent.get_mcp_tools()
+ run_context = RunContextWrapper(context=None)
+ tools = await agent.get_mcp_tools(run_context)
foo_tool = next(tool for tool in tools if tool.name == "foo")
assert isinstance(foo_tool, FunctionTool)
@@ -279,7 +285,9 @@ async def test_util_adds_properties():
server = FakeMCPServer()
server.add_tool("test_tool", schema)
- tools = await MCPUtil.get_all_function_tools([server], convert_schemas_to_strict=False)
+ run_context = RunContextWrapper(context=None)
+ agent = Agent(name="test_agent", instructions="Test agent")
+ tools = await MCPUtil.get_all_function_tools([server], False, run_context, agent)
tool = next(tool for tool in tools if tool.name == "test_tool")
assert isinstance(tool, FunctionTool)
diff --git a/tests/mcp/test_server_errors.py b/tests/mcp/test_server_errors.py
index fbd8db17d..9e0455115 100644
--- a/tests/mcp/test_server_errors.py
+++ b/tests/mcp/test_server_errors.py
@@ -1,7 +1,9 @@
import pytest
+from agents import Agent
from agents.exceptions import UserError
from agents.mcp.server import _MCPServerWithClientSession
+from agents.run_context import RunContextWrapper
class CrashingClientSessionServer(_MCPServerWithClientSession):
@@ -35,8 +37,11 @@ async def test_server_errors_cause_error_and_cleanup_called():
async def test_not_calling_connect_causes_error():
server = CrashingClientSessionServer()
+ run_context = RunContextWrapper(context=None)
+ agent = Agent(name="test_agent", instructions="Test agent")
+
with pytest.raises(UserError):
- await server.list_tools()
+ await server.list_tools(run_context, agent)
with pytest.raises(UserError):
await server.call_tool("foo", {})
diff --git a/tests/mcp/test_tool_filtering.py b/tests/mcp/test_tool_filtering.py
new file mode 100644
index 000000000..c1ffff4b8
--- /dev/null
+++ b/tests/mcp/test_tool_filtering.py
@@ -0,0 +1,243 @@
+"""
+Tool filtering tests use FakeMCPServer instead of real MCPServer implementations to avoid
+external dependencies (processes, network connections) and ensure fast, reliable unit tests.
+FakeMCPServer delegates filtering logic to the real _MCPServerWithClientSession implementation.
+"""
+import asyncio
+
+import pytest
+from mcp import Tool as MCPTool
+
+from agents import Agent
+from agents.mcp import ToolFilterContext, create_static_tool_filter
+from agents.run_context import RunContextWrapper
+
+from .helpers import FakeMCPServer
+
+
+def create_test_agent(name: str = "test_agent") -> Agent:
+ """Create a test agent for filtering tests."""
+ return Agent(name=name, instructions="Test agent")
+
+
+def create_test_context() -> RunContextWrapper:
+ """Create a test run context for filtering tests."""
+ return RunContextWrapper(context=None)
+
+
+# === Static Tool Filtering Tests ===
+
+@pytest.mark.asyncio
+async def test_static_tool_filtering():
+ """Test all static tool filtering scenarios: allowed, blocked, both, none, etc."""
+ server = FakeMCPServer(server_name="test_server")
+ server.add_tool("tool1", {})
+ server.add_tool("tool2", {})
+ server.add_tool("tool3", {})
+ server.add_tool("tool4", {})
+
+ # Create test context and agent for all calls
+ run_context = create_test_context()
+ agent = create_test_agent()
+
+ # Test allowed_tool_names only
+ server.tool_filter = {"allowed_tool_names": ["tool1", "tool2"]}
+ tools = await server.list_tools(run_context, agent)
+ assert len(tools) == 2
+ assert {t.name for t in tools} == {"tool1", "tool2"}
+
+ # Test blocked_tool_names only
+ server.tool_filter = {"blocked_tool_names": ["tool3", "tool4"]}
+ tools = await server.list_tools(run_context, agent)
+ assert len(tools) == 2
+ assert {t.name for t in tools} == {"tool1", "tool2"}
+
+ # Test both filters together (allowed first, then blocked)
+ server.tool_filter = {
+ "allowed_tool_names": ["tool1", "tool2", "tool3"],
+ "blocked_tool_names": ["tool3"]
+ }
+ tools = await server.list_tools(run_context, agent)
+ assert len(tools) == 2
+ assert {t.name for t in tools} == {"tool1", "tool2"}
+
+ # Test no filter
+ server.tool_filter = None
+ tools = await server.list_tools(run_context, agent)
+ assert len(tools) == 4
+
+ # Test helper function
+ server.tool_filter = create_static_tool_filter(
+ allowed_tool_names=["tool1", "tool2"],
+ blocked_tool_names=["tool2"]
+ )
+ tools = await server.list_tools(run_context, agent)
+ assert len(tools) == 1
+ assert tools[0].name == "tool1"
+
+
+# === Dynamic Tool Filtering Core Tests ===
+
+@pytest.mark.asyncio
+async def test_dynamic_filter_sync_and_async():
+ """Test both synchronous and asynchronous dynamic filters"""
+ server = FakeMCPServer(server_name="test_server")
+ server.add_tool("allowed_tool", {})
+ server.add_tool("blocked_tool", {})
+ server.add_tool("restricted_tool", {})
+
+ # Create test context and agent
+ run_context = create_test_context()
+ agent = create_test_agent()
+
+ # Test sync filter
+ def sync_filter(context: ToolFilterContext, tool: MCPTool) -> bool:
+ return tool.name.startswith("allowed")
+
+ server.tool_filter = sync_filter
+ tools = await server.list_tools(run_context, agent)
+ assert len(tools) == 1
+ assert tools[0].name == "allowed_tool"
+
+ # Test async filter
+ async def async_filter(context: ToolFilterContext, tool: MCPTool) -> bool:
+ await asyncio.sleep(0.001) # Simulate async operation
+ return "restricted" not in tool.name
+
+ server.tool_filter = async_filter
+ tools = await server.list_tools(run_context, agent)
+ assert len(tools) == 2
+ assert {t.name for t in tools} == {"allowed_tool", "blocked_tool"}
+
+
+@pytest.mark.asyncio
+async def test_dynamic_filter_context_handling():
+ """Test dynamic filters with context access"""
+ server = FakeMCPServer(server_name="test_server")
+ server.add_tool("admin_tool", {})
+ server.add_tool("user_tool", {})
+ server.add_tool("guest_tool", {})
+
+ # Test context-independent filter
+ def context_independent_filter(context: ToolFilterContext, tool: MCPTool) -> bool:
+ return not tool.name.startswith("admin")
+
+ server.tool_filter = context_independent_filter
+ run_context = create_test_context()
+ agent = create_test_agent()
+ tools = await server.list_tools(run_context, agent)
+ assert len(tools) == 2
+ assert {t.name for t in tools} == {"user_tool", "guest_tool"}
+
+ # Test context-dependent filter (needs context)
+ def context_dependent_filter(context: ToolFilterContext, tool: MCPTool) -> bool:
+ assert context is not None
+ assert context.run_context is not None
+ assert context.agent is not None
+ assert context.server_name == "test_server"
+
+ # Only admin tools for agents with "admin" in name
+ if "admin" in context.agent.name.lower():
+ return True
+ else:
+ return not tool.name.startswith("admin")
+
+ server.tool_filter = context_dependent_filter
+
+ # Should work with context
+ run_context = RunContextWrapper(context=None)
+ regular_agent = create_test_agent("regular_user")
+ tools = await server.list_tools(run_context, regular_agent)
+ assert len(tools) == 2
+ assert {t.name for t in tools} == {"user_tool", "guest_tool"}
+
+ admin_agent = create_test_agent("admin_user")
+ tools = await server.list_tools(run_context, admin_agent)
+ assert len(tools) == 3
+
+
+@pytest.mark.asyncio
+async def test_dynamic_filter_error_handling():
+ """Test error handling in dynamic filters"""
+ server = FakeMCPServer(server_name="test_server")
+ server.add_tool("good_tool", {})
+ server.add_tool("error_tool", {})
+ server.add_tool("another_good_tool", {})
+
+ def error_prone_filter(context: ToolFilterContext, tool: MCPTool) -> bool:
+ if tool.name == "error_tool":
+ raise ValueError("Simulated filter error")
+ return True
+
+ server.tool_filter = error_prone_filter
+
+ # Test with server call
+ run_context = create_test_context()
+ agent = create_test_agent()
+ tools = await server.list_tools(run_context, agent)
+ assert len(tools) == 2
+ assert {t.name for t in tools} == {"good_tool", "another_good_tool"}
+
+
+# === Integration Tests ===
+
+@pytest.mark.asyncio
+async def test_agent_dynamic_filtering_integration():
+ """Test dynamic filtering integration with Agent methods"""
+ server = FakeMCPServer()
+ server.add_tool("file_read", {"type": "object", "properties": {"path": {"type": "string"}}})
+ server.add_tool(
+ "file_write",
+ {
+ "type": "object",
+ "properties": {"path": {"type": "string"}, "content": {"type": "string"}},
+ },
+ )
+ server.add_tool(
+ "database_query", {"type": "object", "properties": {"query": {"type": "string"}}}
+ )
+ server.add_tool(
+ "network_request", {"type": "object", "properties": {"url": {"type": "string"}}}
+ )
+
+ # Role-based filter for comprehensive testing
+ async def role_based_filter(context: ToolFilterContext, tool: MCPTool) -> bool:
+ # Simulate async permission check
+ await asyncio.sleep(0.001)
+
+ agent_name = context.agent.name.lower()
+ if "admin" in agent_name:
+ return True
+ elif "readonly" in agent_name:
+ return "read" in tool.name or "query" in tool.name
+ else:
+ return tool.name.startswith("file_")
+
+ server.tool_filter = role_based_filter
+
+ # Test admin agent
+ admin_agent = Agent(name="admin_user", instructions="Admin", mcp_servers=[server])
+ run_context = RunContextWrapper(context=None)
+ admin_tools = await admin_agent.get_mcp_tools(run_context)
+ assert len(admin_tools) == 4
+
+ # Test readonly agent
+ readonly_agent = Agent(name="readonly_viewer", instructions="Read-only", mcp_servers=[server])
+ readonly_tools = await readonly_agent.get_mcp_tools(run_context)
+ assert len(readonly_tools) == 2
+ assert {t.name for t in readonly_tools} == {"file_read", "database_query"}
+
+ # Test regular agent
+ regular_agent = Agent(name="regular_user", instructions="Regular", mcp_servers=[server])
+ regular_tools = await regular_agent.get_mcp_tools(run_context)
+ assert len(regular_tools) == 2
+ assert {t.name for t in regular_tools} == {"file_read", "file_write"}
+
+ # Test get_all_tools method
+ all_tools = await regular_agent.get_all_tools(run_context)
+ mcp_tool_names = {
+ t.name
+ for t in all_tools
+ if t.name in {"file_read", "file_write", "database_query", "network_request"}
+ }
+ assert mcp_tool_names == {"file_read", "file_write"}
From 25db658f75999f309522819c92f653be5f050134 Mon Sep 17 00:00:00 2001
From: Kazuhiro Sera <seratch@openai.com>
Date: Sat, 28 Jun 2025 00:22:35 +0900
Subject: [PATCH 61/68] Tweak in pyproject.toml (#952)
- Add python 3.13
- Update the homepage URL
---
pyproject.toml | 3 ++-
1 file changed, 2 insertions(+), 1 deletion(-)
diff --git a/pyproject.toml b/pyproject.toml
index 6c0bbe9f1..0dc0ca567 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -23,13 +23,14 @@ classifiers = [
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
+ "Programming Language :: Python :: 3.13",
"Operating System :: OS Independent",
"Topic :: Software Development :: Libraries :: Python Modules",
"License :: OSI Approved :: MIT License",
]
[project.urls]
-Homepage = "https://github.com/openai/openai-agents-python"
+Homepage = "https://openai.github.io/openai-agents-python/"
Repository = "https://github.com/openai/openai-agents-python"
[project.optional-dependencies]
From c772205a7ecdd5e795d537fb902a0ff7724023c2 Mon Sep 17 00:00:00 2001
From: Shiraz Ali <147478490+shirazkk@users.noreply.github.com>
Date: Fri, 27 Jun 2025 20:23:37 +0500
Subject: [PATCH 62/68] Fix incorrect argument description in `on_trace_end`
docstring (#958)
The docstring for the `on_trace_end` method in the `TracingProcessor`
class incorrectly describes the argument `trace`. The current
description states that the argument is the trace that started, but it
should refer to the trace that has finished. This commit updates the
docstring to clarify that the argument represents the trace that has
completed, ensuring accuracy and clarity.
Changes:
- Updated the argument description for `trace` in `on_trace_end` to
clarify it refers to the trace that finished.
---
src/agents/tracing/processor_interface.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/src/agents/tracing/processor_interface.py b/src/agents/tracing/processor_interface.py
index 4dcd897c7..0a05bcae2 100644
--- a/src/agents/tracing/processor_interface.py
+++ b/src/agents/tracing/processor_interface.py
@@ -23,7 +23,7 @@ def on_trace_end(self, trace: "Trace") -> None:
"""Called when a trace is finished.
Args:
- trace: The trace that started.
+ trace: The trace that finished.
"""
pass
From 381e90d9b4fda8e7a52c4c8c85c893843ef997a2 Mon Sep 17 00:00:00 2001
From: Kazuhiro Sera <seratch@openai.com>
Date: Sat, 28 Jun 2025 00:24:10 +0900
Subject: [PATCH 63/68] Fix #944 by updating the models document page to cover
extra_args (#950)
This pull request resolves #944
---
docs/ja/models.md | 106 ---------------------------------------
docs/ja/models/index.md | 107 +++++++++++++++++++++++++++-------------
docs/models/index.md | 16 ++++++
3 files changed, 89 insertions(+), 140 deletions(-)
delete mode 100644 docs/ja/models.md
diff --git a/docs/ja/models.md b/docs/ja/models.md
deleted file mode 100644
index 5a76d60ec..000000000
--- a/docs/ja/models.md
+++ /dev/null
@@ -1,106 +0,0 @@
-# モデル
-
-Agents SDK には、OpenAI モデルの 2 種類のサポートが標準で用意されています。
-
-- **推奨**: [`OpenAIResponsesModel`][agents.models.openai_responses.OpenAIResponsesModel] は、新しい [Responses API](https://platform.openai.com/docs/api-reference/responses) を使って OpenAI API を呼び出します。
-- [`OpenAIChatCompletionsModel`][agents.models.openai_chatcompletions.OpenAIChatCompletionsModel] は、[Chat Completions API](https://platform.openai.com/docs/api-reference/chat) を使って OpenAI API を呼び出します。
-
-## モデルの組み合わせ
-
-1 つのワークフロー内で、各エージェントごとに異なるモデルを使いたい場合があります。たとえば、トリアージには小型で高速なモデルを使い、複雑なタスクにはより大きく高性能なモデルを使うことができます。[`Agent`][agents.Agent] を設定する際、以下のいずれかの方法で特定のモデルを選択できます。
-
-1. OpenAI モデル名を直接渡す。
-2. 任意のモデル名と、その名前を Model インスタンスにマッピングできる [`ModelProvider`][agents.models.interface.ModelProvider] を渡す。
-3. [`Model`][agents.models.interface.Model] 実装を直接指定する。
-
-!!!note
-
- SDK は [`OpenAIResponsesModel`][agents.models.openai_responses.OpenAIResponsesModel] と [`OpenAIChatCompletionsModel`][agents.models.openai_chatcompletions.OpenAIChatCompletionsModel] の両方の形状をサポートしていますが、各ワークフローで 1 つのモデル形状のみを使うことを推奨します。なぜなら、2 つの形状はサポートする機能やツールが異なるためです。ワークフローでモデル形状を組み合わせて使う場合は、利用するすべての機能が両方で利用可能かご確認ください。
-
-```python
-from agents import Agent, Runner, AsyncOpenAI, OpenAIChatCompletionsModel
-import asyncio
-
-spanish_agent = Agent(
- name="Spanish agent",
- instructions="You only speak Spanish.",
- model="o3-mini", # (1)!
-)
-
-english_agent = Agent(
- name="English agent",
- instructions="You only speak English",
- model=OpenAIChatCompletionsModel( # (2)!
- model="gpt-4o",
- openai_client=AsyncOpenAI()
- ),
-)
-
-triage_agent = Agent(
- name="Triage agent",
- instructions="Handoff to the appropriate agent based on the language of the request.",
- handoffs=[spanish_agent, english_agent],
- model="gpt-3.5-turbo",
-)
-
-async def main():
- result = await Runner.run(triage_agent, input="Hola, ¿cómo estás?")
- print(result.final_output)
-```
-
-1. OpenAI モデル名を直接設定します。
-2. [`Model`][agents.models.interface.Model] 実装を指定します。
-
-エージェントで使用するモデルをさらに細かく設定したい場合は、[`ModelSettings`][agents.models.interface.ModelSettings] を渡すことができます。これにより、temperature などのオプションのモデル設定パラメーターを指定できます。
-
-```python
-from agents import Agent, ModelSettings
-
-english_agent = Agent(
- name="English agent",
- instructions="You only speak English",
- model="gpt-4o",
- model_settings=ModelSettings(temperature=0.1),
-)
-```
-
-## 他の LLM プロバイダーの利用
-
-他の LLM プロバイダーは、3 つの方法で利用できます（[こちら](https://github.com/openai/openai-agents-python/tree/main/examples/model_providers/) に code examples があります）。
-
-1. [`set_default_openai_client`][agents.set_default_openai_client] は、`AsyncOpenAI` のインスタンスを LLM クライアントとしてグローバルに利用したい場合に便利です。これは、LLM プロバイダーが OpenAI 互換の API エンドポイントを持ち、`base_url` と `api_key` を設定できる場合に使います。[examples/model_providers/custom_example_global.py](https://github.com/openai/openai-agents-python/tree/main/examples/model_providers/custom_example_global.py) に設定例があります。
-2. [`ModelProvider`][agents.models.interface.ModelProvider] は `Runner.run` レベルで利用します。これにより、「この実行のすべてのエージェントでカスタムモデルプロバイダーを使う」と指定できます。[examples/model_providers/custom_example_provider.py](https://github.com/openai/openai-agents-python/tree/main/examples/model_providers/custom_example_provider.py) に設定例があります。
-3. [`Agent.model`][agents.agent.Agent.model] で、特定のエージェントインスタンスにモデルを指定できます。これにより、エージェントごとに異なるプロバイダーを組み合わせて使うことができます。[examples/model_providers/custom_example_agent.py](https://github.com/openai/openai-agents-python/tree/main/examples/model_providers/custom_example_agent.py) に設定例があります。
-
-`platform.openai.com` の API キーがない場合は、`set_tracing_disabled()` でトレーシングを無効にするか、[別のトレーシングプロセッサー](tracing.md) を設定することを推奨します。
-
-!!! note
-
- これらの code examples では Chat Completions API/モデルを使っています。なぜなら、ほとんどの LLM プロバイダーはまだ Responses API をサポートしていないためです。もし LLM プロバイダーが Responses API をサポートしている場合は、Responses の利用を推奨します。
-
-## 他の LLM プロバイダー利用時のよくある問題
-
-### Tracing クライアントの 401 エラー
-
-トレーシングに関連するエラーが発生した場合、これはトレースが OpenAI サーバーにアップロードされるため、OpenAI API キーがないことが原因です。解決方法は 3 つあります。
-
-1. トレーシングを完全に無効化する: [`set_tracing_disabled(True)`][agents.set_tracing_disabled]。
-2. トレーシング用の OpenAI キーを設定する: [`set_tracing_export_api_key(...)`][agents.set_tracing_export_api_key]。この API キーはトレースのアップロードのみに使われ、[platform.openai.com](https://platform.openai.com/) のものが必要です。
-3. OpenAI 以外のトレースプロセッサーを使う。[トレーシングのドキュメント](tracing.md#custom-tracing-processors) をご覧ください。
-
-### Responses API サポート
-
-SDK はデフォルトで Responses API を使いますが、ほとんどの他の LLM プロバイダーはまだ対応していません。そのため、404 エラーなどが発生する場合があります。解決方法は 2 つあります。
-
-1. [`set_default_openai_api("chat_completions")`][agents.set_default_openai_api] を呼び出します。これは、環境変数で `OPENAI_API_KEY` と `OPENAI_BASE_URL` を設定している場合に有効です。
-2. [`OpenAIChatCompletionsModel`][agents.models.openai_chatcompletions.OpenAIChatCompletionsModel] を使います。[こちら](https://github.com/openai/openai-agents-python/tree/main/examples/model_providers/) に code examples があります。
-
-### structured outputs サポート
-
-一部のモデルプロバイダーは [structured outputs](https://platform.openai.com/docs/guides/structured-outputs) をサポートしていません。その場合、次のようなエラーが発生することがあります。
-
-```
-BadRequestError: Error code: 400 - {'error': {'message': "'response_format.type' : value is not one of the allowed values ['text','json_object']", 'type': 'invalid_request_error'}}
-```
-
-これは一部のモデルプロバイダーの制限で、JSON 出力には対応していても、出力に使う `json_schema` を指定できない場合があります。現在この問題の修正に取り組んでいますが、JSON schema 出力をサポートしているプロバイダーの利用を推奨します。そうでない場合、不正な JSON によりアプリが頻繁に動作しなくなる可能性があります。
\ No newline at end of file
diff --git a/docs/ja/models/index.md b/docs/ja/models/index.md
index a40ae38f6..410c01676 100644
--- a/docs/ja/models/index.md
+++ b/docs/ja/models/index.md
@@ -4,21 +4,52 @@ search:
---
# モデル
-Agents SDK には、標準で 2 種類の OpenAI モデルサポートが含まれています。
+Agents SDK は OpenAI モデルを 2 つの形態で即利用できます。
-- **推奨**: [`OpenAIResponsesModel`][agents.models.openai_responses.OpenAIResponsesModel] — 新しい [Responses API](https://platform.openai.com/docs/api-reference/responses) を利用して OpenAI API を呼び出します。
-- [`OpenAIChatCompletionsModel`][agents.models.openai_chatcompletions.OpenAIChatCompletionsModel] — [Chat Completions API](https://platform.openai.com/docs/api-reference/chat) を利用して OpenAI API を呼び出します。
+- **推奨**: [`OpenAIResponsesModel`][agents.models.openai_responses.OpenAIResponsesModel] は、新しい [Responses API](https://platform.openai.com/docs/api-reference/responses) を使用して OpenAI API を呼び出します。
+- [`OpenAIChatCompletionsModel`][agents.models.openai_chatcompletions.OpenAIChatCompletionsModel] は、[Chat Completions API](https://platform.openai.com/docs/api-reference/chat) を使用して OpenAI API を呼び出します。
+
+## 非 OpenAI モデル
+
+ほとんどの非 OpenAI モデルは [LiteLLM インテグレーション](./litellm.md) 経由で利用できます。まず、litellm 依存グループをインストールします:
+
+```bash
+pip install "openai-agents[litellm]"
+```
+
+次に、`litellm/` 接頭辞を付けて任意の [サポート対象モデル](https://docs.litellm.ai/docs/providers) を使用します:
+
+```python
+claude_agent = Agent(model="litellm/anthropic/claude-3-5-sonnet-20240620", ...)
+gemini_agent = Agent(model="litellm/gemini/gemini-2.5-flash-preview-04-17", ...)
+```
+
+### 非 OpenAI モデルを利用するその他の方法
+
+他の LLM プロバイダーを統合する方法は、あと 3 つあります（[こちら](https://github.com/openai/openai-agents-python/tree/main/examples/model_providers/) に例があります）。
+
+1. [`set_default_openai_client`][agents.set_default_openai_client]
+ `AsyncOpenAI` インスタンスを LLM クライアントとしてグローバルに使用したい場合に便利です。LLM プロバイダーが OpenAI 互換の API エンドポイントを持ち、`base_url` と `api_key` を設定できる場合に使用します。設定例は [examples/model_providers/custom_example_global.py](https://github.com/openai/openai-agents-python/tree/main/examples/model_providers/custom_example_global.py) にあります。
+2. [`ModelProvider`][agents.models.interface.ModelProvider]
+ `Runner.run` レベルでカスタムモデルプロバイダーを指定できます。これにより「この run のすべてのエージェントでカスタムプロバイダーを使う」と宣言できます。設定例は [examples/model_providers/custom_example_provider.py](https://github.com/openai/openai-agents-python/tree/main/examples/model_providers/custom_example_provider.py) にあります。
+3. [`Agent.model`][agents.agent.Agent.model]
+ 特定のエージェントインスタンスにモデルを指定できます。エージェントごとに異なるプロバイダーを組み合わせることが可能です。設定例は [examples/model_providers/custom_example_agent.py](https://github.com/openai/openai-agents-python/tree/main/examples/model_providers/custom_example_agent.py) にあります。ほとんどのモデルを簡単に利用する方法として [LiteLLM インテグレーション](./litellm.md) を利用できます。
+
+`platform.openai.com` の API キーを持っていない場合は、`set_tracing_disabled()` でトレーシングを無効化するか、[別のトレーシングプロセッサー](../tracing.md) を設定することをお勧めします。
+
+!!! note
+ これらの例では、Responses API をまだサポートしていない LLM プロバイダーが多いため、Chat Completions API/モデルを使用しています。LLM プロバイダーが Responses API をサポートしている場合は、Responses を使用することを推奨します。
## モデルの組み合わせ
-1 つのワークフロー内で、エージェントごとに異なるモデルを使用したい場合があります。たとえば、振り分けには小さく高速なモデルを、複雑なタスクには大きく高性能なモデルを使う、といった使い分けです。[`Agent`][agents.Agent] を設定する際は、以下のいずれかで特定のモデルを指定できます。
+1 つのワークフロー内でエージェントごとに異なるモデルを使用したい場合があります。たとえば、振り分けには小さく高速なモデルを、複雑なタスクには大きく高性能なモデルを使用するといったケースです。[`Agent`][agents.Agent] を設定する際、次のいずれかの方法でモデルを選択できます。
-1. OpenAI モデル名を直接渡す
-2. 任意のモデル名と、それを `Model` インスタンスへマッピングできる [`ModelProvider`][agents.models.interface.ModelProvider] を渡す
+1. モデル名を直接指定する
+2. 任意のモデル名と、その名前を Model インスタンスへマッピングできる [`ModelProvider`][agents.models.interface.ModelProvider] を指定する
3. [`Model`][agents.models.interface.Model] 実装を直接渡す
!!!note
- SDK は [`OpenAIResponsesModel`][agents.models.openai_responses.OpenAIResponsesModel] と [`OpenAIChatCompletionsModel`][agents.models.openai_chatcompletions.OpenAIChatCompletionsModel] の両方の形に対応していますが、ワークフローごとに 1 つのモデル形を使用することを推奨します。2 つの形ではサポートする機能・ツールが異なるためです。どうしても混在させる場合は、利用するすべての機能が両方で利用可能であることを確認してください。
+ SDK は [`OpenAIResponsesModel`][agents.models.openai_responses.OpenAIResponsesModel] と [`OpenAIChatCompletionsModel`][agents.models.openai_chatcompletions.OpenAIChatCompletionsModel] の両形態をサポートしていますが、各ワークフローで 1 つのモデル形態に統一することを推奨します。2 つの形態はサポートする機能とツールが異なるためです。混在させる場合は、使用する機能が双方で利用可能かを必ず確認してください。
```python
from agents import Agent, Runner, AsyncOpenAI, OpenAIChatCompletionsModel
@@ -51,10 +82,10 @@ async def main():
print(result.final_output)
```
-1. OpenAI モデル名を直接指定
+1. OpenAI のモデル名を直接設定
2. [`Model`][agents.models.interface.Model] 実装を提供
-エージェントで使用するモデルをさらに細かく設定したい場合は、`temperature` などのオプションを指定できる [`ModelSettings`][agents.models.interface.ModelSettings] を渡します。
+エージェントで使用するモデルをさらに構成したい場合は、`temperature` などのオプションパラメーターを指定できる [`ModelSettings`][agents.models.interface.ModelSettings] を渡せます。
```python
from agents import Agent, ModelSettings
@@ -67,50 +98,58 @@ english_agent = Agent(
)
```
-## 他の LLM プロバイダーの利用
-
-他の LLM プロバイダーは 3 通りの方法で利用できます（コード例は [こちら](https://github.com/openai/openai-agents-python/tree/main/examples/model_providers/)）。
-
-1. [`set_default_openai_client`][agents.set_default_openai_client]
- OpenAI 互換の API エンドポイントを持つ場合に、`AsyncOpenAI` インスタンスをグローバルに LLM クライアントとして設定できます。`base_url` と `api_key` を設定するケースです。設定例は [examples/model_providers/custom_example_global.py](https://github.com/openai/openai-agents-python/tree/main/examples/model_providers/custom_example_global.py)。
+OpenAI の Responses API を使用する場合、`user` や `service_tier` など[その他のオプションパラメーター](https://platform.openai.com/docs/api-reference/responses/create) があります。トップレベルで指定できない場合は、`extra_args` で渡してください。
-2. [`ModelProvider`][agents.models.interface.ModelProvider]
- `Runner.run` レベルで「この実行中のすべてのエージェントにカスタムモデルプロバイダーを使う」と宣言できます。設定例は [examples/model_providers/custom_example_provider.py](https://github.com/openai/openai-agents-python/tree/main/examples/model_providers/custom_example_provider.py)。
-
-3. [`Agent.model`][agents.agent.Agent.model]
- 特定の Agent インスタンスにモデルを指定できます。エージェントごとに異なるプロバイダーを組み合わせられます。設定例は [examples/model_providers/custom_example_agent.py](https://github.com/openai/openai-agents-python/tree/main/examples/model_providers/custom_example_agent.py)。多くのモデルを簡単に使う方法として [LiteLLM 連携](./litellm.md) があります。
-
-`platform.openai.com` の API キーを持たない場合は、`set_tracing_disabled()` でトレーシングを無効化するか、[別のトレーシングプロセッサー](../tracing.md) を設定することを推奨します。
+```python
+from agents import Agent, ModelSettings
-!!! note
- これらの例では Chat Completions API/モデルを使用しています。多くの LLM プロバイダーがまだ Responses API をサポートしていないためです。もしプロバイダーが Responses API をサポートしている場合は、Responses の使用を推奨します。
+english_agent = Agent(
+ name="English agent",
+ instructions="You only speak English",
+ model="gpt-4o",
+ model_settings=ModelSettings(
+ temperature=0.1,
+ extra_args={"service_tier": "flex", "user": "user_12345"},
+ ),
+)
+```
-## 他の LLM プロバイダーでよくある問題
+## 他の LLM プロバイダー使用時の一般的な問題
### Tracing クライアントの 401 エラー
-トレースは OpenAI サーバーへアップロードされるため、OpenAI API キーがない場合にエラーになります。解決策は次の 3 つです。
+Tracing 関連のエラーが発生する場合、トレースは OpenAI サーバーへアップロードされるため、OpenAI API キーが必要です。対応方法は次の 3 つです。
1. トレーシングを完全に無効化する: [`set_tracing_disabled(True)`][agents.set_tracing_disabled]
-2. トレーシング用の OpenAI キーを設定する: [`set_tracing_export_api_key(...)`][agents.set_tracing_export_api_key]
- このキーはトレースのアップロードにのみ使用され、[platform.openai.com](https://platform.openai.com/) のものが必要です。
-3. OpenAI 以外のトレースプロセッサーを使う。詳しくは [tracing ドキュメント](../tracing.md#custom-tracing-processors) を参照してください。
+2. トレース用に OpenAI キーを設定する: [`set_tracing_export_api_key(...)`][agents.set_tracing_export_api_key]
+ この API キーはトレースのアップロードのみに使用され、[platform.openai.com](https://platform.openai.com/) で取得したものが必要です。
+3. OpenAI 以外のトレースプロセッサーを使用する。詳細は [tracing のドキュメント](../tracing.md#custom-tracing-processors) を参照してください。
-### Responses API サポート
+### Responses API のサポート
-SDK は既定で Responses API を使用しますが、多くの LLM プロバイダーはまだ対応していません。そのため 404 などのエラーが発生する場合があります。対処方法は 2 つです。
+SDK はデフォルトで Responses API を使用しますが、ほとんどの LLM プロバイダーはまだ非対応です。その結果、404 などのエラーが発生することがあります。対処方法は次の 2 つです。
1. [`set_default_openai_api("chat_completions")`][agents.set_default_openai_api] を呼び出す
- 環境変数 `OPENAI_API_KEY` と `OPENAI_BASE_URL` を設定している場合に機能します。
+ `OPENAI_API_KEY` と `OPENAI_BASE_URL` を環境変数で設定している場合に有効です。
2. [`OpenAIChatCompletionsModel`][agents.models.openai_chatcompletions.OpenAIChatCompletionsModel] を使用する
- コード例は [こちら](https://github.com/openai/openai-agents-python/tree/main/examples/model_providers/) にあります。
+ 例は [こちら](https://github.com/openai/openai-agents-python/tree/main/examples/model_providers/) にあります。
### structured outputs のサポート
一部のモデルプロバイダーは [structured outputs](https://platform.openai.com/docs/guides/structured-outputs) をサポートしていません。その場合、次のようなエラーが発生することがあります。
```
+
BadRequestError: Error code: 400 - {'error': {'message': "'response_format.type' : value is not one of the allowed values ['text','json_object']", 'type': 'invalid_request_error'}}
+
```
-これは一部プロバイダーの制限で、JSON 出力はサポートしていても `json_schema` を指定できません。現在修正に取り組んでいますが、JSON スキーマ出力をサポートしているプロバイダーを利用することを推奨します。そうでない場合、不正な JSON によりアプリが頻繁に壊れる可能性があります。
\ No newline at end of file
+これは一部プロバイダーの制限で、JSON 出力自体はサポートしていても `json_schema` を指定できないことが原因です。修正に向けて取り組んでいますが、JSON スキーマ出力をサポートしているプロバイダーを使用することをお勧めします。そうでないと、不正な JSON が返されてアプリが頻繁に壊れる可能性があります。
+
+## プロバイダーを跨いだモデルの組み合わせ
+
+モデルプロバイダーごとの機能差に注意しないと、エラーが発生します。たとえば OpenAI は structured outputs、マルチモーダル入力、ホスト型の file search や web search をサポートしていますが、多くの他プロバイダーは非対応です。以下の制限に留意してください。
+
+- 対応していないプロバイダーには未サポートの `tools` を送らない
+- テキストのみのモデルを呼び出す前にマルチモーダル入力を除外する
+- structured JSON 出力をサポートしていないプロバイダーでは、不正な JSON が返ることがある点に注意する
\ No newline at end of file
diff --git a/docs/models/index.md b/docs/models/index.md
index 1c89d778a..b3b2b7f0b 100644
--- a/docs/models/index.md
+++ b/docs/models/index.md
@@ -93,6 +93,22 @@ english_agent = Agent(
)
```
+Also, when you use OpenAI's Responses API, [there are a few other optional parameters](https://platform.openai.com/docs/api-reference/responses/create) (e.g., `user`, `service_tier`, and so on). If they are not available at the top level, you can use `extra_args` to pass them as well.
+
+```python
+from agents import Agent, ModelSettings
+
+english_agent = Agent(
+ name="English agent",
+ instructions="You only speak English",
+ model="gpt-4o",
+ model_settings=ModelSettings(
+ temperature=0.1,
+ extra_args={"service_tier": "flex", "user": "user_12345"},
+ ),
+)
+```
+
## Common issues with using other LLM providers
### Tracing client error 401
From 017ad69de11c945b90cdbfe68a6c56c61ac93ff5 Mon Sep 17 00:00:00 2001
From: tconley1428 <tconley1428@gmail.com>
Date: Fri, 27 Jun 2025 08:25:06 -0700
Subject: [PATCH 64/68] Annotating the openai.Omit type so that ModelSettings
can be serialized by pydantic (#938)
Because `openai.Omit` is not a type which can be serialized by
`pydantic`, it produces difficulty in consistently
serializing/deserializing types across the agents SDK, many of which are
`pydantic` types. This adds an annotation to enable `pydantic` to
serialize `Omit`, in particular in the case of `ModelSettings` which
contains `Omit` in its `extra_headers`
---
src/agents/model_settings.py | 44 ++++++++++++++++++++--
tests/model_settings/test_serialization.py | 31 +++++++++++++++
2 files changed, 71 insertions(+), 4 deletions(-)
diff --git a/src/agents/model_settings.py b/src/agents/model_settings.py
index 709046b7a..26af94ba3 100644
--- a/src/agents/model_settings.py
+++ b/src/agents/model_settings.py
@@ -1,14 +1,50 @@
from __future__ import annotations
import dataclasses
+from collections.abc import Mapping
from dataclasses import dataclass, fields, replace
-from typing import Any, Literal
+from typing import Annotated, Any, Literal, Union
-from openai._types import Body, Headers, Query
+from openai import Omit as _Omit
+from openai._types import Body, Query
from openai.types.responses import ResponseIncludable
from openai.types.shared import Reasoning
-from pydantic import BaseModel
-
+from pydantic import BaseModel, GetCoreSchemaHandler
+from pydantic_core import core_schema
+from typing_extensions import TypeAlias
+
+
+class _OmitTypeAnnotation:
+ @classmethod
+ def __get_pydantic_core_schema__(
+ cls,
+ _source_type: Any,
+ _handler: GetCoreSchemaHandler,
+ ) -> core_schema.CoreSchema:
+ def validate_from_none(value: None) -> _Omit:
+ return _Omit()
+
+ from_none_schema = core_schema.chain_schema(
+ [
+ core_schema.none_schema(),
+ core_schema.no_info_plain_validator_function(validate_from_none),
+ ]
+ )
+ return core_schema.json_or_python_schema(
+ json_schema=from_none_schema,
+ python_schema=core_schema.union_schema(
+ [
+ # check if it's an instance first before doing any further work
+ core_schema.is_instance_schema(_Omit),
+ from_none_schema,
+ ]
+ ),
+ serialization=core_schema.plain_serializer_function_ser_schema(
+ lambda instance: None
+ ),
+ )
+Omit = Annotated[_Omit, _OmitTypeAnnotation]
+Headers: TypeAlias = Mapping[str, Union[str, Omit]]
@dataclass
class ModelSettings:
diff --git a/tests/model_settings/test_serialization.py b/tests/model_settings/test_serialization.py
index 2bbc7ce2c..94d11def3 100644
--- a/tests/model_settings/test_serialization.py
+++ b/tests/model_settings/test_serialization.py
@@ -2,6 +2,8 @@
from dataclasses import fields
from openai.types.shared import Reasoning
+from pydantic import TypeAdapter
+from pydantic_core import to_json
from agents.model_settings import ModelSettings
@@ -132,3 +134,32 @@ def test_extra_args_resolve_both_none() -> None:
assert resolved.extra_args is None
assert resolved.temperature == 0.5
assert resolved.top_p == 0.9
+
+def test_pydantic_serialization() -> None:
+
+ """Tests whether ModelSettings can be serialized with Pydantic."""
+
+ # First, lets create a ModelSettings instance
+ model_settings = ModelSettings(
+ temperature=0.5,
+ top_p=0.9,
+ frequency_penalty=0.0,
+ presence_penalty=0.0,
+ tool_choice="auto",
+ parallel_tool_calls=True,
+ truncation="auto",
+ max_tokens=100,
+ reasoning=Reasoning(),
+ metadata={"foo": "bar"},
+ store=False,
+ include_usage=False,
+ extra_query={"foo": "bar"},
+ extra_body={"foo": "bar"},
+ extra_headers={"foo": "bar"},
+ extra_args={"custom_param": "value", "another_param": 42},
+ )
+
+ json = to_json(model_settings)
+ deserialized = TypeAdapter(ModelSettings).validate_json(json)
+
+ assert model_settings == deserialized
From 27912d4af85baf3acdefc950e4f611db406e1138 Mon Sep 17 00:00:00 2001
From: Daniel Hashmi <151331476+DanielHashmi@users.noreply.github.com>
Date: Fri, 27 Jun 2025 20:59:19 +0500
Subject: [PATCH 65/68] Import Path Inconsistency (#960)
There's an inconsistent import style in the tracing module where one
import uses an absolute path in line number 3 while all others use
relative imports
Additionally: Also fixed the ordering of the imports
---
src/agents/tracing/__init__.py | 3 +--
1 file changed, 1 insertion(+), 2 deletions(-)
diff --git a/src/agents/tracing/__init__.py b/src/agents/tracing/__init__.py
index 64b0bd71f..b45c06d75 100644
--- a/src/agents/tracing/__init__.py
+++ b/src/agents/tracing/__init__.py
@@ -1,7 +1,5 @@
import atexit
-from agents.tracing.provider import DefaultTraceProvider, TraceProvider
-
from .create import (
agent_span,
custom_span,
@@ -20,6 +18,7 @@
)
from .processor_interface import TracingProcessor
from .processors import default_exporter, default_processor
+from .provider import DefaultTraceProvider, TraceProvider
from .setup import get_trace_provider, set_trace_provider
from .span_data import (
AgentSpanData,
From fcafae1d50a3345f795518308e3e87eab15ce1b0 Mon Sep 17 00:00:00 2001
From: Jinseop Song <152702069+axion66@users.noreply.github.com>
Date: Sat, 28 Jun 2025 01:06:13 +0900
Subject: [PATCH 66/68] Add reasoning content - fix on #494 (#871)
my personal update on
https://github.com/openai/openai-agents-python/pull/494
Key changes:
- Updated `ResponseReasoningItem` to use the correct structure with
`id`, `summary`, and `type="reasoning"` fields
- Fixed `ResponseReasoningSummaryPartAddedEvent` to include
`summary_index` parameter and use a dictionary for the `part` parameter
- Fixed `ResponseReasoningSummaryTextDeltaEvent` to include
`summary_index` parameter
- Updated `ResponseReasoningSummaryPartDoneEvent` to include
`summary_index` and use a dictionary for `part`
- Changed how the `Summary` object is accessed in tests (using `.text`
property instead of subscript notation)
- Updated `chatcmpl_converter.py` to use the `Summary` class instead of
a dictionary for better handlign
Fixes #494
---
examples/reasoning_content/__init__.py | 3 +
examples/reasoning_content/main.py | 124 ++++++++
examples/reasoning_content/runner_example.py | 88 ++++++
src/agents/models/chatcmpl_converter.py | 12 +
src/agents/models/chatcmpl_stream_handler.py | 142 ++++++++-
tests/test_reasoning_content.py | 289 +++++++++++++++++++
6 files changed, 643 insertions(+), 15 deletions(-)
create mode 100644 examples/reasoning_content/__init__.py
create mode 100644 examples/reasoning_content/main.py
create mode 100644 examples/reasoning_content/runner_example.py
create mode 100644 tests/test_reasoning_content.py
diff --git a/examples/reasoning_content/__init__.py b/examples/reasoning_content/__init__.py
new file mode 100644
index 000000000..f24b2606d
--- /dev/null
+++ b/examples/reasoning_content/__init__.py
@@ -0,0 +1,3 @@
+"""
+Examples demonstrating how to use models that provide reasoning content.
+"""
diff --git a/examples/reasoning_content/main.py b/examples/reasoning_content/main.py
new file mode 100644
index 000000000..5f67e1779
--- /dev/null
+++ b/examples/reasoning_content/main.py
@@ -0,0 +1,124 @@
+"""
+Example demonstrating how to use the reasoning content feature with models that support it.
+
+Some models, like deepseek-reasoner, provide a reasoning_content field in addition to the regular content.
+This example shows how to access and use this reasoning content from both streaming and non-streaming responses.
+
+To run this example, you need to:
+1. Set your OPENAI_API_KEY environment variable
+2. Use a model that supports reasoning content (e.g., deepseek-reasoner)
+"""
+
+import asyncio
+import os
+from typing import Any, cast
+
+from agents import ModelSettings
+from agents.models.interface import ModelTracing
+from agents.models.openai_provider import OpenAIProvider
+from agents.types import ResponseOutputRefusal, ResponseOutputText # type: ignore
+
+MODEL_NAME = os.getenv("EXAMPLE_MODEL_NAME") or "deepseek-reasoner"
+
+
+async def stream_with_reasoning_content():
+ """
+ Example of streaming a response from a model that provides reasoning content.
+ The reasoning content will be emitted as separate events.
+ """
+ provider = OpenAIProvider()
+ model = provider.get_model(MODEL_NAME)
+
+ print("\n=== Streaming Example ===")
+ print("Prompt: Write a haiku about recursion in programming")
+
+ reasoning_content = ""
+ regular_content = ""
+
+ async for event in model.stream_response(
+ system_instructions="You are a helpful assistant that writes creative content.",
+ input="Write a haiku about recursion in programming",
+ model_settings=ModelSettings(),
+ tools=[],
+ output_schema=None,
+ handoffs=[],
+ tracing=ModelTracing.DISABLED,
+ previous_response_id=None,
+ prompt=None
+ ):
+ if event.type == "response.reasoning_summary_text.delta":
+ print(
+ f"\033[33m{event.delta}\033[0m", end="", flush=True
+ ) # Yellow for reasoning content
+ reasoning_content += event.delta
+ elif event.type == "response.output_text.delta":
+ print(f"\033[32m{event.delta}\033[0m", end="", flush=True) # Green for regular content
+ regular_content += event.delta
+
+ print("\n\nReasoning Content:")
+ print(reasoning_content)
+ print("\nRegular Content:")
+ print(regular_content)
+ print("\n")
+
+
+async def get_response_with_reasoning_content():
+ """
+ Example of getting a complete response from a model that provides reasoning content.
+ The reasoning content will be available as a separate item in the response.
+ """
+ provider = OpenAIProvider()
+ model = provider.get_model(MODEL_NAME)
+
+ print("\n=== Non-streaming Example ===")
+ print("Prompt: Explain the concept of recursion in programming")
+
+ response = await model.get_response(
+ system_instructions="You are a helpful assistant that explains technical concepts clearly.",
+ input="Explain the concept of recursion in programming",
+ model_settings=ModelSettings(),
+ tools=[],
+ output_schema=None,
+ handoffs=[],
+ tracing=ModelTracing.DISABLED,
+ previous_response_id=None,
+ prompt=None
+ )
+
+ # Extract reasoning content and regular content from the response
+ reasoning_content = None
+ regular_content = None
+
+ for item in response.output:
+ if hasattr(item, "type") and item.type == "reasoning":
+ reasoning_content = item.summary[0].text
+ elif hasattr(item, "type") and item.type == "message":
+ if item.content and len(item.content) > 0:
+ content_item = item.content[0]
+ if isinstance(content_item, ResponseOutputText):
+ regular_content = content_item.text
+ elif isinstance(content_item, ResponseOutputRefusal):
+ refusal_item = cast(Any, content_item)
+ regular_content = refusal_item.refusal
+
+ print("\nReasoning Content:")
+ print(reasoning_content or "No reasoning content provided")
+
+ print("\nRegular Content:")
+ print(regular_content or "No regular content provided")
+
+ print("\n")
+
+
+async def main():
+ try:
+ await stream_with_reasoning_content()
+ await get_response_with_reasoning_content()
+ except Exception as e:
+ print(f"Error: {e}")
+ print("\nNote: This example requires a model that supports reasoning content.")
+ print("You may need to use a specific model like deepseek-reasoner or similar.")
+
+
+if __name__ == "__main__":
+ asyncio.run(main())
diff --git a/examples/reasoning_content/runner_example.py b/examples/reasoning_content/runner_example.py
new file mode 100644
index 000000000..e51f85799
--- /dev/null
+++ b/examples/reasoning_content/runner_example.py
@@ -0,0 +1,88 @@
+"""
+Example demonstrating how to use the reasoning content feature with the Runner API.
+
+This example shows how to extract and use reasoning content from responses when using
+the Runner API, which is the most common way users interact with the Agents library.
+
+To run this example, you need to:
+1. Set your OPENAI_API_KEY environment variable
+2. Use a model that supports reasoning content (e.g., deepseek-reasoner)
+"""
+
+import asyncio
+import os
+from typing import Any
+
+from agents import Agent, Runner, trace
+from agents.items import ReasoningItem
+
+MODEL_NAME = os.getenv("EXAMPLE_MODEL_NAME") or "deepseek-reasoner"
+
+
+async def main():
+ print(f"Using model: {MODEL_NAME}")
+
+ # Create an agent with a model that supports reasoning content
+ agent = Agent(
+ name="Reasoning Agent",
+ instructions="You are a helpful assistant that explains your reasoning step by step.",
+ model=MODEL_NAME,
+ )
+
+ # Example 1: Non-streaming response
+ with trace("Reasoning Content - Non-streaming"):
+ print("\n=== Example 1: Non-streaming response ===")
+ result = await Runner.run(
+ agent, "What is the square root of 841? Please explain your reasoning."
+ )
+
+ # Extract reasoning content from the result items
+ reasoning_content = None
+ # RunResult has 'response' attribute which has 'output' attribute
+ for item in result.response.output: # type: ignore
+ if isinstance(item, ReasoningItem):
+ reasoning_content = item.summary[0].text # type: ignore
+ break
+
+ print("\nReasoning Content:")
+ print(reasoning_content or "No reasoning content provided")
+
+ print("\nFinal Output:")
+ print(result.final_output)
+
+ # Example 2: Streaming response
+ with trace("Reasoning Content - Streaming"):
+ print("\n=== Example 2: Streaming response ===")
+ print("\nStreaming response:")
+
+ # Buffers to collect reasoning and regular content
+ reasoning_buffer = ""
+ content_buffer = ""
+
+ # RunResultStreaming is async iterable
+ stream = Runner.run_streamed(agent, "What is 15 x 27? Please explain your reasoning.")
+
+ async for event in stream: # type: ignore
+ if isinstance(event, ReasoningItem):
+ # This is reasoning content
+ reasoning_item: Any = event
+ reasoning_buffer += reasoning_item.summary[0].text
+ print(
+ f"\033[33m{reasoning_item.summary[0].text}\033[0m", end="", flush=True
+ ) # Yellow for reasoning
+ elif hasattr(event, "text"):
+ # This is regular content
+ content_buffer += event.text
+ print(
+ f"\033[32m{event.text}\033[0m", end="", flush=True
+ ) # Green for regular content
+
+ print("\n\nCollected Reasoning Content:")
+ print(reasoning_buffer)
+
+ print("\nCollected Final Answer:")
+ print(content_buffer)
+
+
+if __name__ == "__main__":
+ asyncio.run(main())
diff --git a/src/agents/models/chatcmpl_converter.py b/src/agents/models/chatcmpl_converter.py
index 1d599e8c0..25d9f083d 100644
--- a/src/agents/models/chatcmpl_converter.py
+++ b/src/agents/models/chatcmpl_converter.py
@@ -33,8 +33,10 @@
ResponseOutputMessageParam,
ResponseOutputRefusal,
ResponseOutputText,
+ ResponseReasoningItem,
)
from openai.types.responses.response_input_param import FunctionCallOutput, ItemReference, Message
+from openai.types.responses.response_reasoning_item import Summary
from ..agent_output import AgentOutputSchemaBase
from ..exceptions import AgentsException, UserError
@@ -85,6 +87,16 @@ def convert_response_format(
def message_to_output_items(cls, message: ChatCompletionMessage) -> list[TResponseOutputItem]:
items: list[TResponseOutputItem] = []
+ # Handle reasoning content if available
+ if hasattr(message, "reasoning_content") and message.reasoning_content:
+ items.append(
+ ResponseReasoningItem(
+ id=FAKE_RESPONSES_ID,
+ summary=[Summary(text=message.reasoning_content, type="summary_text")],
+ type="reasoning",
+ )
+ )
+
message_item = ResponseOutputMessage(
id=FAKE_RESPONSES_ID,
content=[],
diff --git a/src/agents/models/chatcmpl_stream_handler.py b/src/agents/models/chatcmpl_stream_handler.py
index d18f5912a..0cf1e6a3e 100644
--- a/src/agents/models/chatcmpl_stream_handler.py
+++ b/src/agents/models/chatcmpl_stream_handler.py
@@ -20,21 +20,38 @@
ResponseOutputMessage,
ResponseOutputRefusal,
ResponseOutputText,
+ ResponseReasoningItem,
+ ResponseReasoningSummaryPartAddedEvent,
+ ResponseReasoningSummaryPartDoneEvent,
+ ResponseReasoningSummaryTextDeltaEvent,
ResponseRefusalDeltaEvent,
ResponseTextDeltaEvent,
ResponseUsage,
)
+from openai.types.responses.response_reasoning_item import Summary
+from openai.types.responses.response_reasoning_summary_part_added_event import (
+ Part as AddedEventPart,
+)
+from openai.types.responses.response_reasoning_summary_part_done_event import Part as DoneEventPart
from openai.types.responses.response_usage import InputTokensDetails, OutputTokensDetails
from ..items import TResponseStreamEvent
from .fake_id import FAKE_RESPONSES_ID
+# Define a Part class for internal use
+class Part:
+ def __init__(self, text: str, type: str):
+ self.text = text
+ self.type = type
+
+
@dataclass
class StreamingState:
started: bool = False
text_content_index_and_output: tuple[int, ResponseOutputText] | None = None
refusal_content_index_and_output: tuple[int, ResponseOutputRefusal] | None = None
+ reasoning_content_index_and_output: tuple[int, ResponseReasoningItem] | None = None
function_calls: dict[int, ResponseFunctionToolCall] = field(default_factory=dict)
@@ -75,12 +92,65 @@ async def handle_stream(
delta = chunk.choices[0].delta
- # Handle text
- if delta.content:
+ # Handle reasoning content
+ if hasattr(delta, "reasoning_content"):
+ reasoning_content = delta.reasoning_content
+ if reasoning_content and not state.reasoning_content_index_and_output:
+ state.reasoning_content_index_and_output = (
+ 0,
+ ResponseReasoningItem(
+ id=FAKE_RESPONSES_ID,
+ summary=[Summary(text="", type="summary_text")],
+ type="reasoning",
+ ),
+ )
+ yield ResponseOutputItemAddedEvent(
+ item=ResponseReasoningItem(
+ id=FAKE_RESPONSES_ID,
+ summary=[Summary(text="", type="summary_text")],
+ type="reasoning",
+ ),
+ output_index=0,
+ type="response.output_item.added",
+ sequence_number=sequence_number.get_and_increment(),
+ )
+
+ yield ResponseReasoningSummaryPartAddedEvent(
+ item_id=FAKE_RESPONSES_ID,
+ output_index=0,
+ summary_index=0,
+ part=AddedEventPart(text="", type="summary_text"),
+ type="response.reasoning_summary_part.added",
+ sequence_number=sequence_number.get_and_increment(),
+ )
+
+ if reasoning_content and state.reasoning_content_index_and_output:
+ yield ResponseReasoningSummaryTextDeltaEvent(
+ delta=reasoning_content,
+ item_id=FAKE_RESPONSES_ID,
+ output_index=0,
+ summary_index=0,
+ type="response.reasoning_summary_text.delta",
+ sequence_number=sequence_number.get_and_increment(),
+ )
+
+ # Create a new summary with updated text
+ current_summary = state.reasoning_content_index_and_output[1].summary[0]
+ updated_text = current_summary.text + reasoning_content
+ new_summary = Summary(text=updated_text, type="summary_text")
+ state.reasoning_content_index_and_output[1].summary[0] = new_summary
+
+ # Handle regular content
+ if delta.content is not None:
if not state.text_content_index_and_output:
- # Initialize a content tracker for streaming text
+ content_index = 0
+ if state.reasoning_content_index_and_output:
+ content_index += 1
+ if state.refusal_content_index_and_output:
+ content_index += 1
+
state.text_content_index_and_output = (
- 0 if not state.refusal_content_index_and_output else 1,
+ content_index,
ResponseOutputText(
text="",
type="output_text",
@@ -98,14 +168,16 @@ async def handle_stream(
# Notify consumers of the start of a new output message + first content part
yield ResponseOutputItemAddedEvent(
item=assistant_item,
- output_index=0,
+ output_index=state.reasoning_content_index_and_output
+ is not None, # fixed 0 -> 0 or 1
type="response.output_item.added",
sequence_number=sequence_number.get_and_increment(),
)
yield ResponseContentPartAddedEvent(
content_index=state.text_content_index_and_output[0],
item_id=FAKE_RESPONSES_ID,
- output_index=0,
+ output_index=state.reasoning_content_index_and_output
+ is not None, # fixed 0 -> 0 or 1
part=ResponseOutputText(
text="",
type="output_text",
@@ -119,7 +191,8 @@ async def handle_stream(
content_index=state.text_content_index_and_output[0],
delta=delta.content,
item_id=FAKE_RESPONSES_ID,
- output_index=0,
+ output_index=state.reasoning_content_index_and_output
+ is not None, # fixed 0 -> 0 or 1
type="response.output_text.delta",
sequence_number=sequence_number.get_and_increment(),
)
@@ -130,9 +203,14 @@ async def handle_stream(
# This is always set by the OpenAI API, but not by others e.g. LiteLLM
if hasattr(delta, "refusal") and delta.refusal:
if not state.refusal_content_index_and_output:
- # Initialize a content tracker for streaming refusal text
+ refusal_index = 0
+ if state.reasoning_content_index_and_output:
+ refusal_index += 1
+ if state.text_content_index_and_output:
+ refusal_index += 1
+
state.refusal_content_index_and_output = (
- 0 if not state.text_content_index_and_output else 1,
+ refusal_index,
ResponseOutputRefusal(refusal="", type="refusal"),
)
# Start a new assistant message if one doesn't exist yet (in-progress)
@@ -146,14 +224,16 @@ async def handle_stream(
# Notify downstream that assistant message + first content part are starting
yield ResponseOutputItemAddedEvent(
item=assistant_item,
- output_index=0,
+ output_index=state.reasoning_content_index_and_output
+ is not None, # fixed 0 -> 0 or 1
type="response.output_item.added",
sequence_number=sequence_number.get_and_increment(),
)
yield ResponseContentPartAddedEvent(
content_index=state.refusal_content_index_and_output[0],
item_id=FAKE_RESPONSES_ID,
- output_index=0,
+ output_index=state.reasoning_content_index_and_output
+ is not None, # fixed 0 -> 0 or 1
part=ResponseOutputText(
text="",
type="output_text",
@@ -167,7 +247,8 @@ async def handle_stream(
content_index=state.refusal_content_index_and_output[0],
delta=delta.refusal,
item_id=FAKE_RESPONSES_ID,
- output_index=0,
+ output_index=state.reasoning_content_index_and_output
+ is not None, # fixed 0 -> 0 or 1
type="response.refusal.delta",
sequence_number=sequence_number.get_and_increment(),
)
@@ -197,14 +278,37 @@ async def handle_stream(
) or ""
state.function_calls[tc_delta.index].call_id += tc_delta.id or ""
+ if state.reasoning_content_index_and_output:
+ yield ResponseReasoningSummaryPartDoneEvent(
+ item_id=FAKE_RESPONSES_ID,
+ output_index=0,
+ summary_index=0,
+ part=DoneEventPart(
+ text=state.reasoning_content_index_and_output[1].summary[0].text,
+ type="summary_text",
+ ),
+ type="response.reasoning_summary_part.done",
+ sequence_number=sequence_number.get_and_increment(),
+ )
+ yield ResponseOutputItemDoneEvent(
+ item=state.reasoning_content_index_and_output[1],
+ output_index=0,
+ type="response.output_item.done",
+ sequence_number=sequence_number.get_and_increment(),
+ )
+
function_call_starting_index = 0
+ if state.reasoning_content_index_and_output:
+ function_call_starting_index += 1
+
if state.text_content_index_and_output:
function_call_starting_index += 1
# Send end event for this content part
yield ResponseContentPartDoneEvent(
content_index=state.text_content_index_and_output[0],
item_id=FAKE_RESPONSES_ID,
- output_index=0,
+ output_index=state.reasoning_content_index_and_output
+ is not None, # fixed 0 -> 0 or 1
part=state.text_content_index_and_output[1],
type="response.content_part.done",
sequence_number=sequence_number.get_and_increment(),
@@ -216,7 +320,8 @@ async def handle_stream(
yield ResponseContentPartDoneEvent(
content_index=state.refusal_content_index_and_output[0],
item_id=FAKE_RESPONSES_ID,
- output_index=0,
+ output_index=state.reasoning_content_index_and_output
+ is not None, # fixed 0 -> 0 or 1
part=state.refusal_content_index_and_output[1],
type="response.content_part.done",
sequence_number=sequence_number.get_and_increment(),
@@ -261,6 +366,12 @@ async def handle_stream(
# Finally, send the Response completed event
outputs: list[ResponseOutputItem] = []
+
+ # include Reasoning item if it exists
+ if state.reasoning_content_index_and_output:
+ outputs.append(state.reasoning_content_index_and_output[1])
+
+ # include text or refusal content if they exist
if state.text_content_index_and_output or state.refusal_content_index_and_output:
assistant_msg = ResponseOutputMessage(
id=FAKE_RESPONSES_ID,
@@ -278,7 +389,8 @@ async def handle_stream(
# send a ResponseOutputItemDone for the assistant message
yield ResponseOutputItemDoneEvent(
item=assistant_msg,
- output_index=0,
+ output_index=state.reasoning_content_index_and_output
+ is not None, # fixed 0 -> 0 or 1
type="response.output_item.done",
sequence_number=sequence_number.get_and_increment(),
)
diff --git a/tests/test_reasoning_content.py b/tests/test_reasoning_content.py
new file mode 100644
index 000000000..5160e09c2
--- /dev/null
+++ b/tests/test_reasoning_content.py
@@ -0,0 +1,289 @@
+from __future__ import annotations
+
+from collections.abc import AsyncIterator
+from typing import Any, cast
+
+import pytest
+from openai.types.chat import ChatCompletion, ChatCompletionChunk, ChatCompletionMessage
+from openai.types.chat.chat_completion_chunk import Choice, ChoiceDelta
+from openai.types.completion_usage import (
+ CompletionTokensDetails,
+ CompletionUsage,
+ PromptTokensDetails,
+)
+from openai.types.responses import (
+ Response,
+ ResponseOutputMessage,
+ ResponseOutputText,
+ ResponseReasoningItem,
+)
+
+from agents.model_settings import ModelSettings
+from agents.models.interface import ModelTracing
+from agents.models.openai_chatcompletions import OpenAIChatCompletionsModel
+from agents.models.openai_provider import OpenAIProvider
+
+
+# Helper functions to create test objects consistently
+def create_content_delta(content: str) -> dict[str, Any]:
+ """Create a delta dictionary with regular content"""
+ return {
+ "content": content,
+ "role": None,
+ "function_call": None,
+ "tool_calls": None
+ }
+
+def create_reasoning_delta(content: str) -> dict[str, Any]:
+ """Create a delta dictionary with reasoning content. The Only difference is reasoning_content"""
+ return {
+ "content": None,
+ "role": None,
+ "function_call": None,
+ "tool_calls": None,
+ "reasoning_content": content
+ }
+
+
+def create_chunk(delta: dict[str, Any], include_usage: bool = False) -> ChatCompletionChunk:
+ """Create a ChatCompletionChunk with the given delta"""
+ # Create a ChoiceDelta object from the dictionary
+ delta_obj = ChoiceDelta(
+ content=delta.get("content"),
+ role=delta.get("role"),
+ function_call=delta.get("function_call"),
+ tool_calls=delta.get("tool_calls"),
+ )
+
+ # Add reasoning_content attribute dynamically if present in the delta
+ if "reasoning_content" in delta:
+ # Use direct assignment for the reasoning_content attribute
+ delta_obj_any = cast(Any, delta_obj)
+ delta_obj_any.reasoning_content = delta["reasoning_content"]
+
+ # Create the chunk
+ chunk = ChatCompletionChunk(
+ id="chunk-id",
+ created=1,
+ model="deepseek is usually expected",
+ object="chat.completion.chunk",
+ choices=[Choice(index=0, delta=delta_obj)],
+ )
+
+ if include_usage:
+ chunk.usage = CompletionUsage(
+ completion_tokens=4,
+ prompt_tokens=2,
+ total_tokens=6,
+ completion_tokens_details=CompletionTokensDetails(reasoning_tokens=2),
+ prompt_tokens_details=PromptTokensDetails(cached_tokens=0),
+ )
+
+ return chunk
+
+
+async def create_fake_stream(
+ chunks: list[ChatCompletionChunk],
+) -> AsyncIterator[ChatCompletionChunk]:
+ for chunk in chunks:
+ yield chunk
+
+
+@pytest.mark.allow_call_model_methods
+@pytest.mark.asyncio
+async def test_stream_response_yields_events_for_reasoning_content(monkeypatch) -> None:
+ """
+ Validate that when a model streams reasoning content,
+ `stream_response` emits the appropriate sequence of events including
+ `response.reasoning_summary_text.delta` events for each chunk of the reasoning content and
+ constructs a completed response with a `ResponseReasoningItem` part.
+ """
+ # Create test chunks
+ chunks = [
+ # Reasoning content chunks
+ create_chunk(create_reasoning_delta("Let me think")),
+ create_chunk(create_reasoning_delta(" about this")),
+ # Regular content chunks
+ create_chunk(create_content_delta("The answer")),
+ create_chunk(create_content_delta(" is 42"), include_usage=True),
+ ]
+
+ async def patched_fetch_response(self, *args, **kwargs):
+ resp = Response(
+ id="resp-id",
+ created_at=0,
+ model="fake-model",
+ object="response",
+ output=[],
+ tool_choice="none",
+ tools=[],
+ parallel_tool_calls=False,
+ )
+ return resp, create_fake_stream(chunks)
+
+ monkeypatch.setattr(OpenAIChatCompletionsModel, "_fetch_response", patched_fetch_response)
+ model = OpenAIProvider(use_responses=False).get_model("gpt-4")
+ output_events = []
+ async for event in model.stream_response(
+ system_instructions=None,
+ input="",
+ model_settings=ModelSettings(),
+ tools=[],
+ output_schema=None,
+ handoffs=[],
+ tracing=ModelTracing.DISABLED,
+ previous_response_id=None,
+ prompt=None,
+ ):
+ output_events.append(event)
+
+ # verify reasoning content events were emitted
+ reasoning_delta_events = [
+ e for e in output_events if e.type == "response.reasoning_summary_text.delta"
+ ]
+ assert len(reasoning_delta_events) == 2
+ assert reasoning_delta_events[0].delta == "Let me think"
+ assert reasoning_delta_events[1].delta == " about this"
+
+ # verify regular content events were emitted
+ content_delta_events = [e for e in output_events if e.type == "response.output_text.delta"]
+ assert len(content_delta_events) == 2
+ assert content_delta_events[0].delta == "The answer"
+ assert content_delta_events[1].delta == " is 42"
+
+ # verify the final response contains both types of content
+ response_event = output_events[-1]
+ assert response_event.type == "response.completed"
+ assert len(response_event.response.output) == 2
+
+ # first item should be reasoning
+ assert isinstance(response_event.response.output[0], ResponseReasoningItem)
+ assert response_event.response.output[0].summary[0].text == "Let me think about this"
+
+ # second item should be message with text
+ assert isinstance(response_event.response.output[1], ResponseOutputMessage)
+ assert isinstance(response_event.response.output[1].content[0], ResponseOutputText)
+ assert response_event.response.output[1].content[0].text == "The answer is 42"
+
+
+@pytest.mark.allow_call_model_methods
+@pytest.mark.asyncio
+async def test_get_response_with_reasoning_content(monkeypatch) -> None:
+ """
+ Test that when a model returns reasoning content in addition to regular content,
+ `get_response` properly includes both in the response output.
+ """
+ # create a message with reasoning content
+ msg = ChatCompletionMessage(
+ role="assistant",
+ content="The answer is 42",
+ )
+ # Use dynamic attribute for reasoning_content
+ # We need to cast to Any to avoid mypy errors since reasoning_content is not a defined attribute
+ msg_with_reasoning = cast(Any, msg)
+ msg_with_reasoning.reasoning_content = "Let me think about this question carefully"
+
+ # create a choice with the message
+ mock_choice = {
+ "index": 0,
+ "finish_reason": "stop",
+ "message": msg_with_reasoning,
+ "delta": None
+ }
+
+ chat = ChatCompletion(
+ id="resp-id",
+ created=0,
+ model="deepseek is expected",
+ object="chat.completion",
+ choices=[mock_choice], # type: ignore[list-item]
+ usage=CompletionUsage(
+ completion_tokens=10,
+ prompt_tokens=5,
+ total_tokens=15,
+ completion_tokens_details=CompletionTokensDetails(reasoning_tokens=6),
+ prompt_tokens_details=PromptTokensDetails(cached_tokens=0),
+ ),
+ )
+
+ async def patched_fetch_response(self, *args, **kwargs):
+ return chat
+
+ monkeypatch.setattr(OpenAIChatCompletionsModel, "_fetch_response", patched_fetch_response)
+ model = OpenAIProvider(use_responses=False).get_model("gpt-4")
+ resp = await model.get_response(
+ system_instructions=None,
+ input="",
+ model_settings=ModelSettings(),
+ tools=[],
+ output_schema=None,
+ handoffs=[],
+ tracing=ModelTracing.DISABLED,
+ previous_response_id=None,
+ prompt=None,
+ )
+
+ # should have produced a reasoning item and a message with text content
+ assert len(resp.output) == 2
+
+ # first output should be the reasoning item
+ assert isinstance(resp.output[0], ResponseReasoningItem)
+ assert resp.output[0].summary[0].text == "Let me think about this question carefully"
+
+ # second output should be the message with text content
+ assert isinstance(resp.output[1], ResponseOutputMessage)
+ assert isinstance(resp.output[1].content[0], ResponseOutputText)
+ assert resp.output[1].content[0].text == "The answer is 42"
+
+
+@pytest.mark.allow_call_model_methods
+@pytest.mark.asyncio
+async def test_stream_response_with_empty_reasoning_content(monkeypatch) -> None:
+ """
+ Test that when a model streams empty reasoning content,
+ the response still processes correctly without errors.
+ """
+ # create test chunks with empty reasoning content
+ chunks = [
+ create_chunk(create_reasoning_delta("")),
+ create_chunk(create_content_delta("The answer is 42"), include_usage=True),
+ ]
+
+ async def patched_fetch_response(self, *args, **kwargs):
+ resp = Response(
+ id="resp-id",
+ created_at=0,
+ model="fake-model",
+ object="response",
+ output=[],
+ tool_choice="none",
+ tools=[],
+ parallel_tool_calls=False,
+ )
+ return resp, create_fake_stream(chunks)
+
+ monkeypatch.setattr(OpenAIChatCompletionsModel, "_fetch_response", patched_fetch_response)
+ model = OpenAIProvider(use_responses=False).get_model("gpt-4")
+ output_events = []
+ async for event in model.stream_response(
+ system_instructions=None,
+ input="",
+ model_settings=ModelSettings(),
+ tools=[],
+ output_schema=None,
+ handoffs=[],
+ tracing=ModelTracing.DISABLED,
+ previous_response_id=None,
+ prompt=None
+ ):
+ output_events.append(event)
+
+ # verify the final response contains the content
+ response_event = output_events[-1]
+ assert response_event.type == "response.completed"
+
+ # should only have the message, not an empty reasoning item
+ assert len(response_event.response.output) == 1
+ assert isinstance(response_event.response.output[0], ResponseOutputMessage)
+ assert isinstance(response_event.response.output[0].content[0], ResponseOutputText)
+ assert response_event.response.output[0].content[0].text == "The answer is 42"
From 86642716e764ef7cfceb206c576d5e40358819a9 Mon Sep 17 00:00:00 2001
From: Rohan Mehta <rm@openai.com>
Date: Fri, 27 Jun 2025 14:32:34 -0400
Subject: [PATCH 67/68] Add safety check handling for ComputerTool (#923)
### Summary
- handle safety checks when using computer tools
- expose new `on_safety_check` callback and data structure
- return acknowledged checks in computer output
- test acknowledging safety checks
### Test plan
- `make format`
- `make lint`
- `make mypy`
- `make tests`
Resolves #843
------
https://chatgpt.com/codex/tasks/task_i_684f207b8b588321a33642a2a9c96a1a
---
src/agents/_run_impl.py | 30 +++++++++++++++++++++++
src/agents/tool.py | 24 +++++++++++++++++++
tests/test_computer_action.py | 45 ++++++++++++++++++++++++++++++++++-
3 files changed, 98 insertions(+), 1 deletion(-)
diff --git a/src/agents/_run_impl.py b/src/agents/_run_impl.py
index a75c5e825..4ac8b316b 100644
--- a/src/agents/_run_impl.py
+++ b/src/agents/_run_impl.py
@@ -28,6 +28,9 @@
ActionType,
ActionWait,
)
+from openai.types.responses.response_input_item_param import (
+ ComputerCallOutputAcknowledgedSafetyCheck,
+)
from openai.types.responses.response_input_param import ComputerCallOutput, McpApprovalResponse
from openai.types.responses.response_output_item import (
ImageGenerationCall,
@@ -67,6 +70,7 @@
from .stream_events import RunItemStreamEvent, StreamEvent
from .tool import (
ComputerTool,
+ ComputerToolSafetyCheckData,
FunctionTool,
FunctionToolResult,
HostedMCPTool,
@@ -638,6 +642,29 @@ async def execute_computer_actions(
results: list[RunItem] = []
# Need to run these serially, because each action can affect the computer state
for action in actions:
+ acknowledged: list[ComputerCallOutputAcknowledgedSafetyCheck] | None = None
+ if action.tool_call.pending_safety_checks and action.computer_tool.on_safety_check:
+ acknowledged = []
+ for check in action.tool_call.pending_safety_checks:
+ data = ComputerToolSafetyCheckData(
+ ctx_wrapper=context_wrapper,
+ agent=agent,
+ tool_call=action.tool_call,
+ safety_check=check,
+ )
+ maybe = action.computer_tool.on_safety_check(data)
+ ack = await maybe if inspect.isawaitable(maybe) else maybe
+ if ack:
+ acknowledged.append(
+ ComputerCallOutputAcknowledgedSafetyCheck(
+ id=check.id,
+ code=check.code,
+ message=check.message,
+ )
+ )
+ else:
+ raise UserError("Computer tool safety check was not acknowledged")
+
results.append(
await ComputerAction.execute(
agent=agent,
@@ -645,6 +672,7 @@ async def execute_computer_actions(
hooks=hooks,
context_wrapper=context_wrapper,
config=config,
+ acknowledged_safety_checks=acknowledged,
)
)
@@ -998,6 +1026,7 @@ async def execute(
hooks: RunHooks[TContext],
context_wrapper: RunContextWrapper[TContext],
config: RunConfig,
+ acknowledged_safety_checks: list[ComputerCallOutputAcknowledgedSafetyCheck] | None = None,
) -> RunItem:
output_func = (
cls._get_screenshot_async(action.computer_tool.computer, action.tool_call)
@@ -1036,6 +1065,7 @@ async def execute(
"image_url": image_url,
},
type="computer_call_output",
+ acknowledged_safety_checks=acknowledged_safety_checks,
),
)
diff --git a/src/agents/tool.py b/src/agents/tool.py
index 283a9e24f..3aab47752 100644
--- a/src/agents/tool.py
+++ b/src/agents/tool.py
@@ -7,6 +7,10 @@
from typing import TYPE_CHECKING, Any, Callable, Literal, Union, overload
from openai.types.responses.file_search_tool_param import Filters, RankingOptions
+from openai.types.responses.response_computer_tool_call import (
+ PendingSafetyCheck,
+ ResponseComputerToolCall,
+)
from openai.types.responses.response_output_item import LocalShellCall, McpApprovalRequest
from openai.types.responses.tool_param import CodeInterpreter, ImageGeneration, Mcp
from openai.types.responses.web_search_tool_param import UserLocation
@@ -142,11 +146,31 @@ class ComputerTool:
as well as implements the computer actions like click, screenshot, etc.
"""
+ on_safety_check: Callable[[ComputerToolSafetyCheckData], MaybeAwaitable[bool]] | None = None
+ """Optional callback to acknowledge computer tool safety checks."""
+
@property
def name(self):
return "computer_use_preview"
+@dataclass
+class ComputerToolSafetyCheckData:
+ """Information about a computer tool safety check."""
+
+ ctx_wrapper: RunContextWrapper[Any]
+ """The run context."""
+
+ agent: Agent[Any]
+ """The agent performing the computer action."""
+
+ tool_call: ResponseComputerToolCall
+ """The computer tool call."""
+
+ safety_check: PendingSafetyCheck
+ """The pending safety check to acknowledge."""
+
+
@dataclass
class MCPToolApprovalRequest:
"""A request to approve a tool call."""
diff --git a/tests/test_computer_action.py b/tests/test_computer_action.py
index 70dcabd59..a306b1841 100644
--- a/tests/test_computer_action.py
+++ b/tests/test_computer_action.py
@@ -18,6 +18,7 @@
ActionScroll,
ActionType,
ActionWait,
+ PendingSafetyCheck,
ResponseComputerToolCall,
)
@@ -31,8 +32,9 @@
RunContextWrapper,
RunHooks,
)
-from agents._run_impl import ComputerAction, ToolRunComputerAction
+from agents._run_impl import ComputerAction, RunImpl, ToolRunComputerAction
from agents.items import ToolCallOutputItem
+from agents.tool import ComputerToolSafetyCheckData
class LoggingComputer(Computer):
@@ -309,3 +311,44 @@ async def test_execute_invokes_hooks_and_returns_tool_call_output() -> None:
assert raw["output"]["type"] == "computer_screenshot"
assert "image_url" in raw["output"]
assert raw["output"]["image_url"].endswith("xyz")
+
+
+@pytest.mark.asyncio
+async def test_pending_safety_check_acknowledged() -> None:
+ """Safety checks should be acknowledged via the callback."""
+
+ computer = LoggingComputer(screenshot_return="img")
+ called: list[ComputerToolSafetyCheckData] = []
+
+ def on_sc(data: ComputerToolSafetyCheckData) -> bool:
+ called.append(data)
+ return True
+
+ tool = ComputerTool(computer=computer, on_safety_check=on_sc)
+ safety = PendingSafetyCheck(id="sc", code="c", message="m")
+ tool_call = ResponseComputerToolCall(
+ id="t1",
+ type="computer_call",
+ action=ActionClick(type="click", x=1, y=1, button="left"),
+ call_id="t1",
+ pending_safety_checks=[safety],
+ status="completed",
+ )
+ run_action = ToolRunComputerAction(tool_call=tool_call, computer_tool=tool)
+ agent = Agent(name="a", tools=[tool])
+ ctx = RunContextWrapper(context=None)
+
+ results = await RunImpl.execute_computer_actions(
+ agent=agent,
+ actions=[run_action],
+ hooks=RunHooks[Any](),
+ context_wrapper=ctx,
+ config=RunConfig(),
+ )
+
+ assert len(results) == 1
+ raw = results[0].raw_item
+ assert isinstance(raw, dict)
+ assert raw.get("acknowledged_safety_checks") == [{"id": "sc", "code": "c", "message": "m"}]
+ assert len(called) == 1
+ assert called[0].safety_check.id == "sc"
From 18cb55e4c45f096d00263c3561d6f22a2299368e Mon Sep 17 00:00:00 2001
From: Rohan Mehta <rm@openai.com>
Date: Fri, 27 Jun 2025 16:56:19 -0400
Subject: [PATCH 68/68] v0.1.0 (#963)
There's a small breaking change so incrementing the minor version
number.
---
docs/release.md | 16 +++++++++++-----
pyproject.toml | 2 +-
uv.lock | 2 +-
3 files changed, 13 insertions(+), 7 deletions(-)
diff --git a/docs/release.md b/docs/release.md
index 3bfc6e9b8..a86103f96 100644
--- a/docs/release.md
+++ b/docs/release.md
@@ -1,4 +1,4 @@
-# Release process
+# Release process/changelog
The project follows a slightly modified version of semantic versioning using the form `0.Y.Z`. The leading `0` indicates the SDK is still evolving rapidly. Increment the components as follows:
@@ -12,7 +12,13 @@ If you don't want breaking changes, we recommend pinning to `0.0.x` versions in
We will increment `Z` for non-breaking changes:
-- Bug fixes
-- New features
-- Changes to private interfaces
-- Updates to beta features
+- Bug fixes
+- New features
+- Changes to private interfaces
+- Updates to beta features
+
+## Breaking change changelog
+
+### 0.1.0
+
+In this version, [`MCPServer.list_tools()`][agents.mcp.server.MCPServer] has two new params: `run_context` and `agent`. You'll need to add these params to any classes that subclass `MCPServer`.
diff --git a/pyproject.toml b/pyproject.toml
index 0dc0ca567..e659348ca 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
[project]
name = "openai-agents"
-version = "0.0.19"
+version = "0.1.0"
description = "OpenAI Agents SDK"
readme = "README.md"
requires-python = ">=3.9"
diff --git a/uv.lock b/uv.lock
index 679d8d2c1..d882c9bc5 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1480,7 +1480,7 @@ wheels = [
[[package]]
name = "openai-agents"
-version = "0.0.19"
+version = "0.1.0"
source = { editable = "." }
dependencies = [
{ name = "griffe" },