How to Build an AI Agent Using LangChain and FastAPI in Python

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A technical guide published on DEV Community walks developers through building an AI agent by combining LangChain and FastAPI using Python 3.11. LangChain agents work by running a loop of thought, action, and observation, where a language model decides which tool to invoke until a final answer is reached. The stack relies on FastAPI for the web layer, Uvicorn as the ASGI server, and Poetry for strict dependency management to avoid silent breaking changes. A simple calculator agent is used as the working example, exposing arithmetic tools to the language model via LangChain's Tool interface and ConversationBufferMemory for context retention. The guide also highlights production pitfalls such as LLM hallucination of non-existent tools and latency spikes, recommending executor timeouts and action whitelisting as safeguards.

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