medium
ai•Jul 20, 2026
Building a Multi-User AI Agent with FastAPI and Streamlit
In this tutorial, we'll expose a local AI agent over HTTP using FastAPI and add a Streamlit UI for a chat-style frontend interface.
freecodecamp
Original source
Key summary
This tutorial shows how to serve a multi-user local AI agent as a REST API using FastAPI, then add a lightweight Streamlit UI on top.
TL;DR
- Use FastAPI to expose a local AI agent over HTTP
- Add a lightweight Streamlit UI for a chat-style frontend interface
- Maintain separate conversation histories for each user session
- Use LangChain, Ollama, and Qwen for AI development
- Run the backend app with FastAPI and the frontend app with Streamlit
- No per-call model API charges with a local AI agent
- Reusable backend with a Streamlit UI
- Support for multiple users with separate sessions
This content is automatically summarized using AI. For full context, always refer to the original article.
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