How One Developer Runs a Free LLM Chatbot on a Static Site Using Hugging Face

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A developer has deployed an AI chatbot on a personal static website at near-zero cost by hosting a LangGraph agent on Hugging Face's free CPU tier, which provides two shared cores. The static site itself remains a plain HTML repository, while a single endpoint URL connects it to the remotely hosted language model. Because free Hugging Face Spaces go idle after 48 hours without traffic, the developer uses Uptime Kuma to ping a lightweight health-check endpoint every five minutes, keeping the container awake without triggering costly LLM calls. A key tradeoff is that the vector index is rebuilt from scratch on every cold start, meaning any visitor after a long quiet period waits for an embedding job to complete before getting a response. To control costs, the API enforces per-IP rate limiting and a CORS allowlist, ensuring only the developer's own domain can trigger the paid language model calls.

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