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A ready-to-deploy chatbot API with streaming, history, and billing.

The AI Chatbot API template configures FastAPI AI Kit for conversational AI applications. Streaming responses, conversation history management, context window optimization, and per-token billing are all pre-wired. Drop in your API key and deploy a production chatbot backend.

FastAPIOpenAI / AnthropicPostgreSQLRedisStripeDocker

What's included

  • Streaming SSE chat endpoint with OpenAI and Anthropic support
  • Conversation history storage and automatic context injection
  • Token tracking per message for cost visibility and billing
  • JWT + API key auth with per-key rate limiting
  • Stripe usage-based billing (per token or per message)
  • Redis caching for repeated queries
  • Health check and monitoring endpoints
  • Docker + deployment configs (Railway, Render, Fly.io)

Code preview

main.py
# The chatbot endpoint — works out of the box
@router.post("/v1/chat")
@rate_limit(per_minute=30)
async def chat(
    body: ChatRequest,
    key: APIKey = Depends(verify_api_key),
    db: AsyncSession = Depends(get_db),
):
    # Load conversation history
    history = await get_conversation(db, body.session_id)

    # Stream response with token tracking
    return StreamingResponse(
        llm.stream(
            messages=[*history, {"role": "user", "content": body.message}],
            track_tokens=True,
            billing_key=key.id,
        ),
        media_type="text/event-stream",
    )

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