sukanyabag/QnA-Langchain-VectorDB
An implementation of Retrieval Augmented Generation (RAG) to enhance Large Language Models for Document Q&A and Information Retrieval.
This tool helps you quickly get answers to specific questions from your documents. You provide your documents and ask questions, and it delivers concise, relevant answers drawn directly from your content. It's designed for anyone who needs to extract precise information from large text collections without manual searching.
No commits in the last 6 months.
Use this if you frequently need to find specific facts or answers within a large body of text, like reports, manuals, or research papers.
Not ideal if you're looking for a tool to generate creative text, summarize entire documents, or engage in open-ended conversations without a specific knowledge base.
Stars
7
Forks
3
Language
Python
License
—
Category
Last pushed
Nov 29, 2023
Commits (30d)
0
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curl "https://pt-edge.onrender.com/api/v1/quality/rag/sukanyabag/QnA-Langchain-VectorDB"
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