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fix: Bring up coverage to minimum and add session hitl examples
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‎examples/memory/memory_session_hitl_example.py‎

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"""
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Example demonstrating SQLite in-memory session with human-in-the-loop (HITL) tool approval.
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This example shows how to use SQLite in-memory session memory combined with
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human-in-the-loop tool approval. The session maintains conversation history while
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requiring approval for specific tool calls.
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"""
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import asyncio
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from agents import Agent, Runner, SQLiteSession, function_tool
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async def _needs_approval(_ctx, _params, _call_id) -> bool:
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"""Always require approval for weather tool."""
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return True
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@function_tool(needs_approval=_needs_approval)
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def get_weather(location: str) -> str:
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"""Get weather for a location.
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Args:
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location: The location to get weather for
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Returns:
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Weather information as a string
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"""
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# Simulated weather data
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weather_data = {
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"san francisco": "Foggy, 58°F",
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"oakland": "Sunny, 72°F",
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"new york": "Rainy, 65°F",
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}
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# Check if any city name is in the provided location string
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location_lower = location.lower()
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for city, weather in weather_data.items():
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if city in location_lower:
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return weather
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return f"Weather data not available for {location}"
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async def prompt_yes_no(question: str) -> bool:
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"""Prompt user for yes/no answer.
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Args:
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question: The question to ask
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Returns:
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True if user answered yes, False otherwise
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"""
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print(f"\n{question} (y/n): ", end="", flush=True)
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loop = asyncio.get_event_loop()
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answer = await loop.run_in_executor(None, input)
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normalized = answer.strip().lower()
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return normalized in ("y", "yes")
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async def main():
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# Create an agent with a tool that requires approval
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agent = Agent(
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name="HITL Assistant",
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instructions="You help users with information. Always use available tools when appropriate. Keep responses concise.",
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tools=[get_weather],
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)
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# Create an in-memory SQLite session instance that will persist across runs
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session = SQLiteSession(":memory:")
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session_id = session.session_id
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print("=== Memory Session + HITL Example ===")
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print(f"Session id: {session_id}")
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print("Enter a message to chat with the agent. Submit an empty line to exit.")
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print("The agent will ask for approval before using tools.\n")
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while True:
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# Get user input
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print("You: ", end="", flush=True)
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loop = asyncio.get_event_loop()
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user_message = await loop.run_in_executor(None, input)
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if not user_message.strip():
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break
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# Run the agent
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result = await Runner.run(agent, user_message, session=session)
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# Handle interruptions (tool approvals)
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while result.interruptions:
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# Get the run state
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state = result.to_state()
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for interruption in result.interruptions:
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tool_name = interruption.raw_item.name # type: ignore[union-attr]
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args = interruption.raw_item.arguments or "(no arguments)" # type: ignore[union-attr]
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approved = await prompt_yes_no(
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f"Agent {interruption.agent.name} wants to call '{tool_name}' with {args}. Approve?"
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)
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if approved:
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state.approve(interruption)
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print("Approved tool call.")
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else:
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state.reject(interruption)
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print("Rejected tool call.")
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# Resume the run with the updated state
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result = await Runner.run(agent, state, session=session)
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# Display the response
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reply = result.final_output or "[No final output produced]"
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print(f"Assistant: {reply}\n")
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if __name__ == "__main__":
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asyncio.run(main())

‎examples/memory/openai_session_hitl_example.py‎

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"""
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Example demonstrating OpenAI Conversations session with human-in-the-loop (HITL) tool approval.
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This example shows how to use OpenAI Conversations session memory combined with
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human-in-the-loop tool approval. The session maintains conversation history while
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requiring approval for specific tool calls.
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"""
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import asyncio
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from agents import Agent, OpenAIConversationsSession, Runner, function_tool
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async def _needs_approval(_ctx, _params, _call_id) -> bool:
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"""Always require approval for weather tool."""
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return True
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@function_tool(needs_approval=_needs_approval)
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def get_weather(location: str) -> str:
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"""Get weather for a location.
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Args:
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location: The location to get weather for
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Returns:
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Weather information as a string
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"""
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# Simulated weather data
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weather_data = {
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"san francisco": "Foggy, 58°F",
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"oakland": "Sunny, 72°F",
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"new york": "Rainy, 65°F",
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}
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# Check if any city name is in the provided location string
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location_lower = location.lower()
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for city, weather in weather_data.items():
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if city in location_lower:
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return weather
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return f"Weather data not available for {location}"
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async def prompt_yes_no(question: str) -> bool:
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"""Prompt user for yes/no answer.
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Args:
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question: The question to ask
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Returns:
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True if user answered yes, False otherwise
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"""
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print(f"\n{question} (y/n): ", end="", flush=True)
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loop = asyncio.get_event_loop()
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answer = await loop.run_in_executor(None, input)
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normalized = answer.strip().lower()
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return normalized in ("y", "yes")
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async def main():
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# Create an agent with a tool that requires approval
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agent = Agent(
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name="HITL Assistant",
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instructions="You help users with information. Always use available tools when appropriate. Keep responses concise.",
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tools=[get_weather],
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)
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# Create a session instance that will persist across runs
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session = OpenAIConversationsSession()
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print("=== OpenAI Session + HITL Example ===")
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print("Enter a message to chat with the agent. Submit an empty line to exit.")
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print("The agent will ask for approval before using tools.\n")
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while True:
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# Get user input
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print("You: ", end="", flush=True)
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loop = asyncio.get_event_loop()
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user_message = await loop.run_in_executor(None, input)
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if not user_message.strip():
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break
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# Run the agent
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result = await Runner.run(agent, user_message, session=session)
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# Handle interruptions (tool approvals)
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while result.interruptions:
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# Get the run state
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state = result.to_state()
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for interruption in result.interruptions:
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tool_name = interruption.raw_item.name # type: ignore[union-attr]
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args = interruption.raw_item.arguments or "(no arguments)" # type: ignore[union-attr]
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approved = await prompt_yes_no(
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f"Agent {interruption.agent.name} wants to call '{tool_name}' with {args}. Approve?"
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)
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if approved:
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state.approve(interruption)
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print("Approved tool call.")
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else:
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state.reject(interruption)
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print("Rejected tool call.")
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# Resume the run with the updated state
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result = await Runner.run(agent, state, session=session)
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# Display the response
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reply = result.final_output or "[No final output produced]"
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print(f"Assistant: {reply}\n")
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if __name__ == "__main__":
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asyncio.run(main())

‎src/agents/run.py‎

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Original file line numberDiff line numberDiff line change
@@ -593,7 +593,9 @@ async def run(
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should_run_agent_start_hooks = True
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# save only the new user input to the session, not the combined history
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await self._save_result_to_session(session, original_user_input, [])
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# Skip saving if resuming from state - input is already in session
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if not is_resumed_state:
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await self._save_result_to_session(session, original_user_input, [])
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# If resuming from an interrupted state, execute approved tools first
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if is_resumed_state and run_state is not None and run_state._current_step is not None:

‎src/agents/run_state.py‎

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Original file line numberDiff line numberDiff line change
@@ -202,8 +202,12 @@ def to_json(self) -> dict[str, Any]:
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},
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"approvals": approvals_dict,
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"context": self._context.context
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if hasattr(self._context.context, "__dict__")
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else {},
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if isinstance(self._context.context, dict)
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else (
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self._context.context.__dict__
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if hasattr(self._context.context, "__dict__")
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else {}
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),
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},
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"maxTurns": self._max_turns,
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"inputGuardrailResults": [
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# Add handoff agents to the queue
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for handoff in current.handoffs:
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if hasattr(handoff, "agent") and handoff.agent:
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if handoff.agent.name not in agent_map:
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queue.append(handoff.agent)
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# Handoff can be either an Agent or a Handoff object with an .agent attribute
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handoff_agent = handoff if not hasattr(handoff, "agent") else handoff.agent
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if handoff_agent and handoff_agent.name not in agent_map: # type: ignore[union-attr]
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queue.append(handoff_agent) # type: ignore[arg-type]
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return agent_map
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