RAG-Chatbot and Chatbot-with-RAG-and-LangChain

Both are educational implementations of RAG chatbots using LangChain, making them direct competitors offering similar functionality with different deployment approaches (Databutton vs. standalone).

Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 22/25
Maintenance 2/25
Adoption 5/25
Maturity 9/25
Community 18/25
Stars: 166
Forks: 52
Downloads:
Commits (30d): 0
Language: Python
License: MIT
Stars: 14
Forks: 14
Downloads:
Commits (30d): 0
Language: Python
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About RAG-Chatbot

avrabyt/RAG-Chatbot

RAG enabled Chatbots using LangChain and Databutton

Implements PDF document indexing and semantic similarity search to augment LLM prompts with relevant context from uploaded files, with session-based index caching and secure API key management through Databutton's secret store. The architecture separates concerns into frontend (Streamlit/Databutton app), document processing pipeline (PDF parsing and vector indexing), and LLM integration, retrieving top-N semantically similar chunks before passing them to the language model for context-aware generation.

About Chatbot-with-RAG-and-LangChain

ThomasJanssen-tech/Chatbot-with-RAG-and-LangChain

Build a Chatbot which uses Retrieval Augmented Generation (RAG) to answer based on your own data!

Scores updated daily from GitHub, PyPI, and npm data. How scores work