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RasaGPT

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๐Ÿ’ฌ RasaGPT is the first headless LLM chatbot platform built on top of Rasa and Langchain. Built w/ Rasa, FastAPI, Langchain, LlamaIndex, SQLModel, pgvector, ngrok, telegram

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OSS

RasaGPT

Added 1 June 2026

#ai #chatbot #chatgpt #fastapi #gpt-3 #gpt-4 #langchain #llama-index

Overview

RasaGPT is an open-source headless LLM chatbot platform built on Rasa and Langchain. It combines FastAPI, LlamaIndex, pgvector, and Telegram to provide a modular backend for conversational AI. The project uses SQLModel for database management and ngrok for tunneling.

Best for

Best for
Developers building custom LLM chatbots with Rasa and Langchain

Use cases

  • Build custom chatbots with Rasa and LLM integration
  • Implement retrieval-augmented generation using pgvector
  • Deploy a headless chatbot backend for Telegram

Notes

RasaGPT is an open-source headless LLM chatbot platform built on Rasa and Langchain. It combines FastAPI, LlamaIndex, pgvector, and Telegram to provide a modular backend for conversational AI. The project uses SQLModel for database management and ngrok for tunneling.

2,466 stars on GitHub. Last updated 2025-11-12. Licensed MIT.

Use cases

  • Build custom chatbots with Rasa and LLM integration
  • Implement retrieval-augmented generation using pgvector
  • Deploy a headless chatbot backend for Telegram

Pros

  • Open-source with active community (2466 stars)
  • Modular architecture leveraging Rasa, Langchain, and LlamaIndex
  • Supports vector storage via pgvector for RAG workflows

Cons

  • Community project without commercial support
  • Complex setup due to multiple dependencies (Rasa, FastAPI, etc.)
  • Headless design requires separate frontend development

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

Pros

  • Open-source with active community (2466 stars)
  • Modular architecture leveraging Rasa, Langchain, and LlamaIndex
  • Supports vector storage via pgvector for RAG workflows

Cons

  • Community project without commercial support
  • Complex setup due to multiple dependencies (Rasa, FastAPI, etc.)
  • Headless design requires separate frontend development