Pavansomisetty21/RAG-based-Intelligent-Conversational-AI-Agent-for-Knowledge-Extraction-Using-LangChain-Gemini-LLM

In this we implements a Retrieval-Augmented Generation (RAG) based conversational AI agent designed for intelligent knowledge extraction from PDF documents. Leveraging LangChain and Google’s Gemini LLM

33
/ 100
Emerging

This project helps you quickly get answers from long PDF documents by allowing you to chat with their content. You input a PDF file, and the system provides answers to your questions based on the information within that PDF, remembering previous parts of your conversation. Anyone who needs to extract specific information from documents without manually reading through them, such as researchers, analysts, or students, would find this useful.

No commits in the last 6 months.

Use this if you need to rapidly find specific information or get summaries from large PDF documents through a conversational interface.

Not ideal if you need to analyze highly structured data within tables or images in PDFs, or if your documents are not primarily text-based.

document-analysis information-extraction research-assistance data-retrieval report-query
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 4 / 25
Maturity 16 / 25
Community 13 / 25

How are scores calculated?

Stars

7

Forks

2

Language

Jupyter Notebook

License

MIT

Last pushed

Sep 21, 2024

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/vector-db/Pavansomisetty21/RAG-based-Intelligent-Conversational-AI-Agent-for-Knowledge-Extraction-Using-LangChain-Gemini-LLM"

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