Merge branch 'main' into hironow/add-voice-from-openai-fm

Author: hironow

.github/workflows/issues.yml

@@ -17,7 +17,10 @@ jobs:
           stale-issue-label: "stale"
           stale-issue-message: "This issue is stale because it has been open for 7 days with no activity."
           close-issue-message: "This issue was closed because it has been inactive for 3 days since being marked as stale."
-          days-before-pr-stale: -1
-          days-before-pr-close: -1
-          any-of-labels: 'question,needs-more-info'
+          any-of-issue-labels: 'question,needs-more-info'
+          days-before-pr-stale: 10
+          days-before-pr-close: 7
+          stale-pr-label: "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 }}

.github/workflows/tests.yml

@@ -8,6 +8,9 @@ on:
     branches:
       - main
 
+env:
+  UV_FROZEN: "1"
+
 jobs:
   lint:
     runs-on: ubuntu-latest

.gitignore

@@ -135,10 +135,10 @@ dmypy.json
 cython_debug/
 
 # PyCharm
-#.idea/
+.idea/
 
 # Ruff stuff:
 .ruff_cache/
 
 # PyPI configuration file
-.pypirc
+.pypirc

Makefile

@@ -5,6 +5,7 @@ sync:
 .PHONY: format
 format: 
 	uv run ruff format
+	uv run ruff check --fix
 
 .PHONY: lint
 lint: 
@@ -36,7 +37,6 @@ snapshots-create:
 .PHONY: old_version_tests
 old_version_tests: 
 	UV_PROJECT_ENVIRONMENT=.venv_39 uv run --python 3.9 -m pytest
-	UV_PROJECT_ENVIRONMENT=.venv_39 uv run --python 3.9 -m mypy .
 
 .PHONY: build-docs
 build-docs:

README.md

@@ -30,7 +30,7 @@ source env/bin/activate
 pip install openai-agents
 ```
 
-For voice support, install with the optional `voice` group: `pip install openai-agents[voice]`.
+For voice support, install with the optional `voice` group: `pip install 'openai-agents[voice]'`.
 
 ## Hello world example
 

docs/agents.md

@@ -142,4 +142,6 @@ Supplying a list of tools doesn't always mean the LLM will use a tool. You can f
 
 !!! note
 
-    If requiring tool use, you should consider setting [`Agent.tool_use_behavior`] to stop the Agent from running when a tool output is produced. Otherwise, the Agent might run in an infinite loop, where the LLM produces a tool call , and the tool result is sent to the LLM, and this infinite loops because the LLM is always forced to use a tool.
+    To prevent infinite loops, the framework automatically resets `tool_choice` to "auto" after a tool call. This behavior is configurable via [`agent.reset_tool_choice`][agents.agent.Agent.reset_tool_choice]. The infinite loop is because tool results are sent to the LLM, which then generates another tool call because of `tool_choice`, ad infinitum.
+
+    If you want the Agent to completely stop after a tool call (rather than continuing with auto mode), you can set [`Agent.tool_use_behavior="stop_on_first_tool"`] which will directly use the tool output as the final response without further LLM processing.

docs/assets/images/graph.png

@@ -41,14 +41,14 @@ async def fetch_user_age(wrapper: RunContextWrapper[UserInfo]) -> str:  # (2)!
     return f"User {wrapper.context.name} is 47 years old"
 
 async def main():
-    user_info = UserInfo(name="John", uid=123)  # (3)!
+    user_info = UserInfo(name="John", uid=123)
 
-    agent = Agent[UserInfo](  # (4)!
+    agent = Agent[UserInfo](  # (3)!
         name="Assistant",
         tools=[fetch_user_age],
     )
 
-    result = await Runner.run(
+    result = await Runner.run(  # (4)!
         starting_agent=agent,
         input="What is the age of the user?",
         context=user_info,

docs/assets/images/mcp-tracing.jpg

@@ -29,7 +29,7 @@ Output guardrails run in 3 steps:
 
 !!! Note
 
-    Output guardrails are intended to run on the final agent input, so an agent's guardrails only run if the agent is the *last* agent. Similar to the input guardrails, we do this because guardrails tend to be related to the actual Agent - you'd run different guardrails for different agents, so colocating the code is useful for readability.
+    Output guardrails are intended to run on the final agent output, so an agent's guardrails only run if the agent is the *last* agent. Similar to the input guardrails, we do this because guardrails tend to be related to the actual Agent - you'd run different guardrails for different agents, so colocating the code is useful for readability.
 
 ## Tripwires