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Fix #1564 Add conversations API support (#1587)
This pull request resolves #1564 --------- Co-authored-by: Rohan Mehta <rm@openai.com>
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‎examples/memory/openai_session_example.py

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"""
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Example demonstrating session memory functionality.
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This example shows how to use session memory to maintain conversation history
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across multiple agent runs without manually handling .to_input_list().
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"""
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import asyncio
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from agents import Agent, OpenAIConversationsSession, Runner
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async def main():
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# Create an agent
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agent = Agent(
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name="Assistant",
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instructions="Reply very concisely.",
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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("=== Session Example ===")
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print("The agent will remember previous messages automatically.\n")
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# First turn
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print("First turn:")
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print("User: What city is the Golden Gate Bridge in?")
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result = await Runner.run(
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agent,
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"What city is the Golden Gate Bridge in?",
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session=session,
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)
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print(f"Assistant: {result.final_output}")
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print()
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# Second turn - the agent will remember the previous conversation
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print("Second turn:")
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print("User: What state is it in?")
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result = await Runner.run(agent, "What state is it in?", session=session)
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print(f"Assistant: {result.final_output}")
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print()
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# Third turn - continuing the conversation
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print("Third turn:")
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print("User: What's the population of that state?")
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result = await Runner.run(
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agent,
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"What's the population of that state?",
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session=session,
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)
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print(f"Assistant: {result.final_output}")
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print()
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print("=== Conversation Complete ===")
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print("Notice how the agent remembered the context from previous turns!")
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print("Sessions automatically handles conversation history.")
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# Demonstrate the limit parameter - get only the latest 2 items
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print("\n=== Latest Items Demo ===")
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latest_items = await session.get_items(limit=2)
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# print(latest_items)
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print("Latest 2 items:")
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for i, msg in enumerate(latest_items, 1):
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role = msg.get("role", "unknown")
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content = msg.get("content", "")
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print(f" {i}. {role}: {content}")
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print(f"\nFetched {len(latest_items)} out of total conversation history.")
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# Get all items to show the difference
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all_items = await session.get_items()
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# print(all_items)
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print(f"Total items in session: {len(all_items)}")
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if __name__ == "__main__":
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asyncio.run(main())

‎examples/basic/sqlalchemy_session_example.py renamed to ‎examples/memory/sqlalchemy_session_example.py

Lines changed: 32 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -20,28 +20,56 @@ async def main():
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create_tables=True,
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)
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print("=== SQLAlchemySession Example ===")
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print("=== Session Example ===")
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print("The agent will remember previous messages automatically.\n")
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# First turn
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print("First turn:")
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print("User: What city is the Golden Gate Bridge in?")
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result = await Runner.run(
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agent,
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"What city is the Golden Gate Bridge in?",
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session=session,
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)
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print(f"Assistant: {result.final_output}\n")
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print(f"Assistant: {result.final_output}")
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print()
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# Second turn - the agent will remember the previous conversation
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print("Second turn:")
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print("User: What state is it in?")
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result = await Runner.run(agent, "What state is it in?", session=session)
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print(f"Assistant: {result.final_output}")
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print()
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# Third turn - continuing the conversation
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print("Third turn:")
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print("User: What's the population of that state?")
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result = await Runner.run(
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agent,
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"What state is it in?",
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"What's the population of that state?",
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session=session,
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)
42-
print(f"Assistant: {result.final_output}\n")
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print(f"Assistant: {result.final_output}")
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print()
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print("=== Conversation Complete ===")
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print("Notice how the agent remembered the context from previous turns!")
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print("Sessions automatically handles conversation history.")
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# Demonstrate the limit parameter - get only the latest 2 items
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print("\n=== Latest Items Demo ===")
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latest_items = await session.get_items(limit=2)
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print("Latest 2 items:")
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for i, msg in enumerate(latest_items, 1):
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role = msg.get("role", "unknown")
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content = msg.get("content", "")
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print(f" {i}. {role}: {content}")
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print(f"\nFetched {len(latest_items)} out of total conversation history.")
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# Get all items to show the difference
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all_items = await session.get_items()
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print(f"Total items in session: {len(all_items)}")
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if __name__ == "__main__":

‎examples/basic/session_example.py renamed to ‎examples/memory/sqlite_session_example.py

File renamed without changes.

‎examples/reasoning_content/main.py

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@@ -47,6 +47,7 @@ async def stream_with_reasoning_content():
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handoffs=[],
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tracing=ModelTracing.DISABLED,
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previous_response_id=None,
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conversation_id=None,
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prompt=None,
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):
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if event.type == "response.reasoning_summary_text.delta":
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handoffs=[],
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tracing=ModelTracing.DISABLED,
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previous_response_id=None,
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conversation_id=None,
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prompt=None,
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)
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‎src/agents/__init__.py

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TResponseInputItem,
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)
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from .lifecycle import AgentHooks, RunHooks
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from .memory import Session, SQLiteSession
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from .memory import OpenAIConversationsSession, Session, SessionABC, SQLiteSession
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from .model_settings import ModelSettings
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from .models.interface import Model, ModelProvider, ModelTracing
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from .models.multi_provider import MultiProvider
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"RunHooks",
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"AgentHooks",
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"Session",
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"SessionABC",
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"SQLiteSession",
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"OpenAIConversationsSession",
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"RunContextWrapper",
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"TContext",
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"RunErrorDetails",

‎src/agents/extensions/models/litellm_model.py

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@@ -82,7 +82,8 @@ async def get_response(
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output_schema: AgentOutputSchemaBase | None,
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handoffs: list[Handoff],
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tracing: ModelTracing,
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previous_response_id: str | None,
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previous_response_id: str | None = None, # unused
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conversation_id: str | None = None, # unused
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prompt: Any | None = None,
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) -> ModelResponse:
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with generation_span(
@@ -171,7 +172,8 @@ async def stream_response(
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output_schema: AgentOutputSchemaBase | None,
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handoffs: list[Handoff],
173174
tracing: ModelTracing,
174-
previous_response_id: str | None,
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previous_response_id: str | None = None, # unused
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conversation_id: str | None = None, # unused
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prompt: Any | None = None,
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) -> AsyncIterator[TResponseStreamEvent]:
177179
with generation_span(

‎src/agents/memory/__init__.py

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@@ -1,3 +1,10 @@
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from .session import Session, SQLiteSession
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from .openai_conversations_session import OpenAIConversationsSession
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from .session import Session, SessionABC
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from .sqlite_session import SQLiteSession
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__all__ = ["Session", "SQLiteSession"]
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__all__ = [
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"Session",
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"SessionABC",
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"SQLiteSession",
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"OpenAIConversationsSession",
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]

‎src/agents/memory/openai_conversations_session.py

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from __future__ import annotations
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from openai import AsyncOpenAI
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from agents.models._openai_shared import get_default_openai_client
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from ..items import TResponseInputItem
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from .session import SessionABC
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async def start_openai_conversations_session(openai_client: AsyncOpenAI | None = None) -> str:
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_maybe_openai_client = openai_client
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if openai_client is None:
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_maybe_openai_client = get_default_openai_client() or AsyncOpenAI()
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# this never be None here
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_openai_client: AsyncOpenAI = _maybe_openai_client # type: ignore [assignment]
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response = await _openai_client.conversations.create(items=[])
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return response.id
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_EMPTY_SESSION_ID = ""
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class OpenAIConversationsSession(SessionABC):
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def __init__(
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self,
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*,
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conversation_id: str | None = None,
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openai_client: AsyncOpenAI | None = None,
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):
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self._session_id: str | None = conversation_id
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_openai_client = openai_client
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if _openai_client is None:
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_openai_client = get_default_openai_client() or AsyncOpenAI()
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# this never be None here
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self._openai_client: AsyncOpenAI = _openai_client
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async def _get_session_id(self) -> str:
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if self._session_id is None:
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self._session_id = await start_openai_conversations_session(self._openai_client)
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return self._session_id
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async def _clear_session_id(self) -> None:
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self._session_id = None
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async def get_items(self, limit: int | None = None) -> list[TResponseInputItem]:
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session_id = await self._get_session_id()
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all_items = []
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if limit is None:
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async for item in self._openai_client.conversations.items.list(
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conversation_id=session_id,
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order="asc",
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):
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# calling model_dump() to make this serializable
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all_items.append(item.model_dump())
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else:
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async for item in self._openai_client.conversations.items.list(
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conversation_id=session_id,
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limit=limit,
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order="desc",
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):
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# calling model_dump() to make this serializable
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all_items.append(item.model_dump())
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if limit is not None and len(all_items) >= limit:
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break
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all_items.reverse()
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return all_items # type: ignore
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async def add_items(self, items: list[TResponseInputItem]) -> None:
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session_id = await self._get_session_id()
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await self._openai_client.conversations.items.create(
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conversation_id=session_id,
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items=items,
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)
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async def pop_item(self) -> TResponseInputItem | None:
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session_id = await self._get_session_id()
80+
items = await self.get_items(limit=1)
81+
if not items:
82+
return None
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item_id: str = str(items[0]["id"]) # type: ignore [typeddict-item]
84+
await self._openai_client.conversations.items.delete(
85+
conversation_id=session_id, item_id=item_id
86+
)
87+
return items[0]
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async def clear_session(self) -> None:
90+
session_id = await self._get_session_id()
91+
await self._openai_client.conversations.delete(
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conversation_id=session_id,
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)
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await self._clear_session_id()

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