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AdalFlow: The library to build & auto-optimize LLM applications.
🥤 RAGLite is a Python toolkit for Retrieval-Augmented Generation (RAG) with PostgreSQL or SQLite
Rust library for generating vector embeddings, reranking locally
An easy-to-use python toolkit for flexibly adapting various neural ranking models to target domain.
Testing speed and accuracy of RAG with, and without Cross Encoder Reranker.
SearchAugmentedLLM empowers LLMs with information from the web
A comprehensive RAG FastAPI service that handles document uploads and retrievals, built with Python. Uses PyMuPDF for document processing, turbopuffer for vector storage, OpenAI for models, and cohere for reranking.
This is RAG Modules Repo. This includes various modules in the RAG ecosystem.
Free Web Search API, Free Rerank API, The World Engine For AGI.
Multi-Objective Recommender System
This repository hosts the code to launch a streamlit Q&A app that locally uses LLMs in a RAG-Reranker workflow
The method of re-ranking involves a two-stage retrieval system, with re-rankers playing a crucial role in evaluating the relevance of each document to the query. RAG systems can be optimized to mitigate hallucinations and ensure dependable search outcomes by selecting the optimal reranking model.
Retrieval-Augmented Generation without Vector-DB
AICUP 2024 Esan LLM RAG QA
A Python cli-command tool for creating reports for any Google query.
Given user submitted bio, returns top 500 stories from Hacker News front page , ranked in the order of relevancy to user's interests.