ENDEVSOLS/Long-Trainer

Production-ready RAG framework for Python — multi-tenant chatbots with streaming, tool calling, agent mode (LangGraph), vector search (FAISS), and persistent MongoDB memory. Built on LangChain.

45
/ 100
Emerging

This project helps businesses and organizations build and deploy multiple AI-powered chatbots quickly and efficiently. You provide your documents (PDFs, web pages, text files) and a prompt, and it generates a chatbot that can answer questions based on that content, remembering past conversations. It's designed for operations managers, product owners, or internal IT teams needing to create specialized chatbots for various departments or customers.

Use this if you need to deploy several robust, data-aware chatbots, each with its own knowledge base and memory, without building all the underlying infrastructure from scratch.

Not ideal if you're looking for a simple, single-purpose chatbot for personal use or a very basic website FAQ.

customer-support-automation internal-knowledge-management AI-chatbot-development document-intelligence digital-assistants
No Package No Dependents
Maintenance 10 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 14 / 25

How are scores calculated?

Stars

13

Forks

3

Language

Python

License

MIT

Last pushed

Mar 09, 2026

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/rag/ENDEVSOLS/Long-Trainer"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.