AdalFlow: The library to build & auto-optimize LLM applications.

An easy-to-use python toolkit for flexibly adapting various neural ranking models to any target domain.

Testing speed and accuracy of RAG with, and without Cross Encoder Reranker.

🥤 RAGLite is a Python toolkit for Retrieval-Augmented Generation (RAG) with PostgreSQL or SQLite

An OpenAI Compatible API which integrates LLM, Embedding and Reranker. 一个集成 LLM、Embedding 和 Reranker 的 OpenAI 兼容 API

This is RAG Modules Repo. This includes various modules in the RAG ecosystem.

A small reranker service using mixedbread.ai reranker model

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.

Multi-Objective Recommender System

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.

Retrieval-Augmented Generation without Vector-DB

A chatbot built on Ktor using GPT + Embeddings to answer questions

Reranker API

AICUP 2024 Esan LLM RAG QA

BETA - SearchAugmentedLLM empowers LLMs with relevant web information. Given a query, it searches Google, processes top results, chunks the content, ranks by relevance, and returns the most pertinent text to provide context to the LLM. Ideal for RAG (Retrieval Augmented Generation) applications.

Discriminative Reranker in Java

A Python cli-command tool for creating reports for any Google query.