Popular GitHub Repositories for Retrival

Transformers for Information Retrieval, Text Classification, NER, QA, Language Modelling, Language Generation, T5, Multi-Modal, and Conversational AI

? Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generation ?. Our toolkit integrates 40 pre-retrieved benchmark datasets and supports 7+ retrieval techniques, 24+ state-of-the-art Reranking models, and multiple RAG methods.

? AI interface for tinkerers (Ollama, Haystack RAG, Python)

MindSQL: A Python Text-to-SQL RAG Library simplifying database interactions. Seamlessly integrates with PostgreSQL, MySQL, SQLite, Snowflake, and BigQuery. Powered by GPT-4 and Llama 2, it enables natural language queries. Supports ChromaDB and Faiss for context-aware responses.

Advanced Retrieval-Augmented Generation (RAG) through practical notebooks, using the power of the Langchain, OpenAI GPTs ,META LLAMA3 ,Agents.

An enterprise-grade AI retriever designed to streamline AI integration into your applications, ensuring cutting-edge accuracy.

A curated list of awesome resources related to Semantic Search? and Semantic Similarity tasks.

Semantic Search demo featuring UForm, USearch, UCall, and StreamLit, to visual and retrieve from image datasets, similar to "CLIP Retrieval"

BestRAG: A library for hybrid RAG, combining dense, sparse, and late interaction methods for efficient document storage and search.

This project contains source code to demonstrate the usage of Retrival Augmented Generation (RAG) feature using Spring AI using PG Vector as the Database and Ollama as the Local LLM

Avalok AI is easy to use platform to build search on documents including S3 bucket. We add ability to add RAG to get answers to your questions.

ZeroPal: A concise RAG example for LightZero QA.

A self-hosted, privacy-focused RAG (Retrieval-Augmented Generation) interface for intelligent document interaction. Turn any document into a knowledge base you can chat with.

Dataviz AI is an AI powered web application that enables users to generate animated infographic videos based on input Data , text,files. This MVP leverages the Pexels API for video content and incorporates advanced natural language processing (NLP) techniques, including LangChain and stable diffusion techniques, to analyze and create visual impact

? Briefly utilizes open-source LLM's with text embeddings and vectorstores to chat with your documents

An AI-powered email assistant that retrieves emails and generates intelligent responses

IntelliSearch is an advanced retrieval-based question-answering and recommendation system that leverages embeddings and a large language model (LLM) to provide accurate and relevant information to users.

[WORK IN PROGRESS] Complete vector search stack • Document processing pipeline • Semantic chunking • Embedding generation • Advanced retrieval strategies • Production-ready microservice

AI-powered customer support assistant designed to handle food delivery complaints efficiently. Built using LangChain, RAG (Retrieval-Augmented Generation), PostgreSQL, and email automation, the chatbot provides empathetic, context-aware responses to customer queries regarding order status, payment issues, and refunds.

Efficiently search and retrieve information from PDF documents using a Retrieval-Augmented Generation (RAG) approach. This project leverages DeepSeek-R1 (1.5B) for advanced language understanding, FAISS for high-speed vector search, and Hugging Face’s ecosystem for enhanced NLP capabilities. With an intuitive Streamlit interface and Ollama for mode