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Build a real-time chatbot API with Python, FastAPI, and SSE

By PulseAugur Editorial · [1 sources] ·

This article provides a technical guide on building a real-time chatbot API using Python's FastAPI framework and Server-Sent Events (SSE). It explains why SSE is a suitable choice for streaming LLM responses due to its unidirectional nature and simplicity compared to WebSockets. The guide includes code examples for setting up the project, defining the SSE endpoint with FastAPI's StreamingResponse, and handling the streaming of tokens from an OpenAI-compatible LLM API. AI

IMPACT Enables developers to create more responsive chatbot interfaces by streaming LLM responses.

RANK_REASON Technical guide on implementing a specific software pattern.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Build a real-time chatbot API with Python, FastAPI, and SSE

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Tool
Technical guide on implementing a specific software pattern.
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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product, infra
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High
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62 days old
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Ayi NEDJIMI ·

    How to Build a Streaming Chatbot API in Python with FastAPI and SSE

    <p>Most chatbot UIs feel slow when they wait for the complete LLM response before showing anything. Server-Sent Events (SSE) fix this: the backend streams tokens as they're generated, and users see output appear character by character. Here's how to wire that up with FastAPI.</p>…

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