konevenkatesh/tender_rag_project
A comprehensive Retrieval-Augmented Generation (RAG) application that helps organizations analyze, query, and prepare responses to tender documents using advanced AI models. Built with hybrid search, multi-language support, and professional export capabilities.
Stars
—
Forks
—
Language
Python
License
MIT
Category
Last pushed
Nov 23, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/rag/konevenkatesh/tender_rag_project"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
GrapeCity-AI/gc-qa-rag
A RAG (Retrieval-Augmented Generation) solution Based on Advanced Pre-generated QA Pairs. 基于高级...
Vbj1808/Dokis
Lightweight RAG provenance middleware. Verifies every claim in an LLM response is grounded in a...
UKPLab/PeerQA
Code and Data for PeerQA: A Scientific Question Answering Dataset from Peer Reviews, NAACL 2025
Arfazrll/RAG-DocsInsight-Engine
Retrieval Augmented Generation (RAG) engine for intelligent document analysis. integrating LLM,...
Zhanli-Li/DeepRead
[DeepRead] This is the official implementation of the DeepRead paper.