https://github.com/rhiteshks/qa-chatbot-using-rag-smai

SMAI Project. Made an abstractive qa RAG chatbot using Langchain and experimented with variety of vector stores and retrievers and evaluated them using Ragas
https://github.com/rhiteshks/qa-chatbot-using-rag-smai

chromadb cohere faiss-vector-database langchain-python matryoshka nlp openai-api ragas

Last synced: about 3 hours ago
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SMAI Project. Made an abstractive qa RAG chatbot using Langchain and experimented with variety of vector stores and retrievers and evaluated them using Ragas

• Host: GitHub
• URL: https://github.com/rhiteshks/qa-chatbot-using-rag-smai
• Owner: RhiteshKS
• Created: 2024-03-21T03:23:46.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2024-06-02T08:48:55.000Z (4 months ago)
• Last Synced: 2024-09-27T12:39:16.972Z (about 3 hours ago)
• Topics: chromadb, cohere, faiss-vector-database, langchain-python, matryoshka, nlp, openai-api, ragas
• Language: Jupyter Notebook
• Homepage:
• Size: 1.24 MB
• Stars: 0
• Watchers: 1
• Forks: 1
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

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README

        
# QA-chatbot-using-RAG-SMAI

SMAI Project. We make an abstractive qa chatbot using RAG using Langchain and experiment with variety of vector stores and retrievers and evaluate them.

## To-Do List

- [x] Make a basic RAG pipleline. (Completed)

- [x] Use different types of embedding models and make observations. (Completed)

- [x] Use different types of retrievers and experiment with them.(Completed)

- [x] Use advanced RAG techniques such as Contextual Compression, Ensemble retriever, ColBERT retriever etc.(Completed)

- [x] Use Cohere reranker, cross encoder reranker(Completed)

- [x] Evaluate our RAG pipeline using different eval metrics.(Completed)

  

Check out the presentation slides: https://github.com/RhiteshKS/QA-chatbot-using-RAG-SMAI/blob/main/qa%20chatbot%20rag.pdf