Step-by-step guide to connecting Anthropic's Claude to a FastAPI Python API. Streaming handling, context management, cost control, and proven production patterns.
Integrating Claude into a FastAPI backend is more straightforward than it seems, but there are several patterns that make the difference between a prototype and a production system. First, installation: pip install anthropic. The client is asynchronous by default, which fits perfectly with FastAPI.
For response streaming (essential for UX), use async with client.messages.stream() and yield the chunks to the client with StreamingResponse. Managing conversation context is the main challenge: Claude does not maintain state between calls, so you must persist the message history in Redis or PostgreSQL and send it on every request. We recommend truncating by tokens (not by number of messages) using the token counter from the SDK itself.
For production cost control, implement a FastAPI middleware that records input_tokens and output_tokens from each response in your database. This lets you calculate the exact cost per user, per endpoint, and per day. A pattern we have found very useful: using Claude Haiku for initial intent classification (cheap and fast) and Claude Sonnet only for final responses that require high quality.
This can reduce total cost by up to 60% with no perceptible impact on user experience.