Python agents

5-dimensional drift detection for production RAG systems.

Windows Registry Manipulation

A framework for retrieval augmented generation evaluation (RAGE)

rage-ts

Python Rage4 API Module

Intelligent CLI-based Project Context Engine with MCP server support

RAGElo: A Tool for Evaluating Retrieval-Augmented Generation Models

Retrieval Augmented Generation.

Training language models to perform agentic multi-hop search through reinforcement learning

Python SDK for ragent-oss storage gateway

RAGents Frontend - A Python-embeddable Next.js frontend for RAG agents

Useful Tools for Database, RAG and LLM

RAG evaluation library — LLM-as-judge for hallucination detection, faithfulness, answer relevancy. Local or self-hosted. Alternative to ragas.

RAG evaluation SDK — RAGの回答品質を3行で計測

A library for evaluating Retrieval-Augmented Generation (RAG) systems

Generate production-ready RAG pipelines from a single config

Prevents silent RAG failures — chunk quality, retrieval fallback, adaptive querying, and answer evaluation in one library.

Framework that helps you build, evaluate, and refine GenAI pipelines.

RAGFL Memory

Efficient Document-Based QA with Retrieval-Augmented Generation (RAG) and Large Language Models (LLM).

Async Python SDK for RAGFlow

Admin Service's client of [RAGFlow](https://github.com/infiniflow/ragflow). The Admin Service provides user management and system monitoring.

Python client for RagFlow API

A mcp server that talk with my ragflow

RAGFlow MCP Server - A Model Context Protocol server integrating with RAGFlow APIs

RAGFlow MCP Server Aider

RAGFlow MCP Server Continue

This mcp server is used to search content from the ragflow knowledge base.

Python client sdk of [RAGFlow](https://github.com/infiniflow/ragflow). RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.

Django ORM 风格的 ragflow-sdk 封装

A simple RAG pipeline

A Discord bot using Swarmauri LLM, RAG agent, and Hikari.

Modular, composable RAG retrieval library —— Build your retrieval pipeline like forging parts.

A library for generating dataset and evaluating these datasets on RAG based solutions

A dummy placeholder package for raggae.

Ragged array library, complying with Python API specification.

Efficient RaggedBuffer datatype that implements 3D arrays with variable-length 2nd dimension.

Typing stubs for Ragged

Fix ragged right edges in LLM-generated ASCII/Unicode box diagrams

RAG dataset generator

A modular RAG library with embeddings and vector store support

Python SDK for ragger.ai RAG API

Simple vector database operations with Qdrant

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llama index based library for building multimodal RAG systems

client tool for raggify, a llama index based library for building multimodal RAG systems

raggify-perception repo

Version control for your RAG pipeline — compare embedding models on your own data

Permission-aware retrieval for RAG applications

scraping stuff

A very basic calculator

RAG made simple

A Python package to test in local

A Python package to test in local

Python Client SDK Generated by Speakeasy.

Convert any website into RAG vector DB

A simple, clean Python library for Retrieval-Augmented Generation (RAG)

MCP Server for RAG documentation search with Qdrant and Ollama

Automatic RAG Pattern Optimization Engine

A lightweight RAG pipeline toolkit powered by HuggingFace

Modular RAG toolkit

ragl: retrieval-augmented generation (RAG) for text.

A medley of tools to make RAG-based applications.

A modular RAG library with embeddings and vector store support

RAG-LAB is an open-source lighter, faster and cheaper RAG toolkit supported by Target Pilot, designed to transform the latest RAG concepts into stable and practical engineering tools. The project currently supports GraphRAG and HybridRAG.

Python tools to create a custom top down raglan sweater

Embedding diagnostics toolkit for RAG systems

RAGLens CLI for debugging retrieval behavior in RAG systems

Portable memory for small text corpora - create searchable .raglet files

Librería para consultas RAG

A modular, production-grade Retrieval-Augmented Generation library

RAGLight is a lightweight and modular Python library for implementing Retrieval-Augmented Generation (RAG). It enhances the capabilities of Large Language Models (LLMs) by combining document retrieval with natural language inference.

Lineage-aware RAG engine for auditable, reproducible, versioned retrieval and answers

Production-ready RAG pipeline evaluation and observability platform

A Python toolkit for Retrieval-Augmented Generation (RAG) with DuckDB or PostgreSQL.

Local-first RAG-lite CLI: condense docs into structured Markdown, then index/query with Chroma + hybrid search

Local-first RAG toolkit backed by a single SQLite database

A tool for uploading and embedding documents for RAG systems

Local-first, provider-agnostic RAG toolkit

Stateful RAG kernel with corpus nectar — agents know what's in the corpus before any query runs

RAGmap is a simple RAG visualization package for exploring document chunks and queries in embedding space

A package for creating retrieval-augmented generation apps

RAGMax - Advanced RAG memory system for AI platforms via MCP

Monitor your LLM calls. Test your LLM app.

A package for integrating RagMetrics with LLM calls

A modular framework for evaluating and optimizing RAG pipelines.

AWS extensions for Ragna

lightweight Extract-Transform-Load (ETL) framework for Python 3+

A lightweight personal AI assistant framework

RAGNARDoc (RAG Native Automatic Reingestion for Documents) is a tool that runs natively on a developer workstation and automatically ingests local documents into various Retrieval Augmented Generation indexes. It is designed as a companion app for workstation RAG applications which would benefit from maintaining an up-to-date view of documents hosted natively on a user's workstation.

Local-first evaluation framework for RAG pipelines and AI agents

Hybrid structure-aware retrieval — BM25 + embeddings + document graph expansion. Runs fully offline, no API key required.

Python SDK for the Ragnerock API.

Multi-knowledge-base RAG system with MCP integration

Documentation RAG pipeline with a Textual dashboard and MCP server

LLM-retrieval based knowledge grounding