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Langchain Chat Websocket

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LangChain LLM chat with streaming response over websockets

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OSS

Langchain Chat Websocket

Added 1 June 2026

#async #fastapi #langchain #langchain-python #llm #openai #openai-api #openai-chatgpt

Overview

A web-based chat application that uses LangChain to interact with large language models and streams responses over websockets. It provides a simple HTML interface for real-time conversational AI with streaming output.

Best for

Best for
Developers who need a quick, lightweight streaming chat demo using LangChain and websockets

Use cases

  • Building a real-time streaming chat interface for LLMs
  • Prototyping LangChain-based conversational agents with low-latency responses
  • Demonstrating websocket integration for LLM streaming in web apps

Notes

A web-based chat application that uses LangChain to interact with large language models and streams responses over websockets. It provides a simple HTML interface for real-time conversational AI with streaming output.

97 stars on GitHub. Last updated 2023-11-30. Licensed Apache-2.0.

Use cases

  • Building a real-time streaming chat interface for LLMs
  • Prototyping LangChain-based conversational agents with low-latency responses
  • Demonstrating websocket integration for LLM streaming in web apps

Pros

  • Simple HTML-based setup with no complex dependencies
  • Streaming responses via websockets for low-latency user experience
  • Open source and free to use or modify

Cons

  • Limited to basic chat functionality with no advanced features like memory or tool use
  • Small community (97 stars) means less support and fewer contributions
  • Minimal documentation beyond the repository README

Indexed from awesome-langchain and enriched against its public facts.

Pros

  • Simple HTML-based setup with no complex dependencies
  • Streaming responses via websockets for low-latency user experience
  • Open source and free to use or modify

Cons

  • Limited to basic chat functionality with no advanced features like memory or tool use
  • Small community (97 stars) means less support and fewer contributions
  • Minimal documentation beyond the repository README
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