Delegate independent tasks to specialized agents working concurrently with isolated context.
Stateless Conversation State Management
conversation-state
Stateless conversation management with database-backed history, message persistence, and scalable architecture. Use when handling chat state, loading history, or building stateless APIs.
SKILL.md
Full skill instructions
Stateless Conversation State Management
Load Conversation History
async def load_conversation_history(
session: AsyncSession,
user_id: str,
conversation_id: int | None
) -> tuple[Conversation, list[dict]]:
"""Load or create conversation with message history."""
if conversation_id:
stmt = select(Conversation).where(
Conversation.id == conversation_id,
Conversation.user_id == user_id
)
result = await session.execute(stmt)
conversation = result.scalar_one_or_none()
if not conversation:
raise HTTPException(status_code=404, detail="Conversation not found")
else:
conversation = Conversation(user_id=user_id)
session.add(conversation)
await session.commit()
await session.refresh(conversation)
# Load messages
stmt = select(Message).where(
Message.conversation_id == conversation.id
).order_by(Message.created_at)
result = await session.execute(stmt)
db_messages = result.scalars().all()
messages = [{"role": msg.role, "content": msg.content} for msg in db_messages]
return conversation, messages
Complete Stateless Flow
@app.post("/api/{user_id}/chat")
async def chat(
user_id: str,
request: ChatRequest,
session: AsyncSession = Depends(get_db_session),
current_user: str = Depends(verify_jwt)
):
# 1. Load history from DB
conversation, messages = await load_conversation_history(
session, user_id, request.conversation_id
)
# 2. Save user message
user_msg = Message(
user_id=user_id,
conversation_id=conversation.id,
role="user",
content=request.message
)
session.add(user_msg)
await session.commit()
# 3. Add to history array
messages.append({"role": "user", "content": request.message})
# 4. Run agent
response, tool_calls = await run_agent(messages)
# 5. Save assistant response
assistant_msg = Message(
user_id=user_id,
conversation_id=conversation.id,
role="assistant",
content=response
)
session.add(assistant_msg)
await session.commit()
# 6. Return (server holds NO state)
return ChatResponse(
conversation_id=conversation.id,
response=response,
tool_calls=tool_calls
)
Benefits
- Horizontal scalability (any server handles any request)
- Resilience (server restart doesn't lose conversations)
- Testability (each request independent)
- No sticky sessions needed
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