Results for "rag"

Efficient toolkit for RAG research with 40+ retrieval and reranking models, 20+ benchmark datasets, and optimized evaluation pipelines (WWW 2025 Resource). MIT licensed.

Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG. Features 350+ connectors with always-in-sync data from SharePoint, Google Drive, S3, Kafka, PostgreSQL and more. BSL 1.1 license (becomes Apache 2.0 after 4 years).

Enterprise RAG pattern for Azure OpenAI at scale. Secure, production-ready architecture using Azure Cognitive Search and Azure OpenAI LLMs for ChatGPT-style Q&A experiences. MIT licensed.

First lightweight RAG framework based on Model Context Protocol (MCP) architecture. Low-code RAG pipeline builder with comprehensive evaluation system and DeepResearch capabilities. From Tsinghua THUNLP, NEUIR, OpenBMB, and AI9stars. Apache 2.0 licensed.

All-in-One Multimodal RAG system for seamless processing of text, images, tables, and equations. Built on LightRAG.

Java library for integrating LLMs into Java applications. Implements RAG, tool calling (including MCP support), and agents with seamless integration into enterprise Java frameworks like Spring Boot. Apache 2.0 licensed.

Graph RAG-based conversational knowledge base tool built on TiDB Vector and LlamaIndex. Features Perplexity-style search with built-in website crawler. Apache 2.0 licensed.

RAG AutoML tool for automatically finding optimal RAG pipelines. Evaluates and optimizes retrieval-augmented generation with AutoML-style automation for your own data and use-case. Apache 2.0 licensed.

Open-source RAG-based tool for chatting with your documents. Hybrid RAG pipeline with full-text and vector retriever, re-ranking, and multi-modal capabilities. Clean Gradio-based UI with support for local and API-based LLMs. Apache 2.0 licensed.

Graph-based RAG with dual-level retrieval system. Simple and fast with comprehensive knowledge discovery (EMNLP 2025).

Lightweight document chunking library for fast, efficient RAG pipelines. Memory-safe with multiple chunking strategies (semantic, token, recursive) and direct vector DB integration. MIT licensed.

Deep-document-understanding RAG engine.

Python toolkit for RAG with DuckDB or PostgreSQL. Lightweight, efficient retrieval-augmented generation without heavy dependencies. MPL 2.0 licensed.

High-accuracy document parsing for LLM and RAG workflows. Converts PDFs, Word, PPTs, and images into structured Markdown/JSON with VLM+OCR dual engine.

Enterprise knowledge platform that combines RAG retrieval, autonomous reasoning agents, wiki generation, and multi-source document ingestion.

Vectorless, reasoning-based RAG framework using document index structure. Achieves high accuracy without vector databases through intelligent context engineering and reasoning-based retrieval. MIT licensed.

Convert any URL to LLM-friendly input with a simple prefix (r.jina.ai). Free service that extracts article content, removes clutter, and returns clean Markdown for RAG and agentic workflows. Apache 2.0 licensed.

Multi-language codebase RAG framework using Tree-sitter and Memgraph knowledge graphs to query, edit, and optimize codebases with AI. MIT licensed.

Unified framework for building enterprise RAG pipelines with small, specialized models. Optimized for AI PC and local deployment with 300+ models in catalog. Apache 2.0 licensed.

Privacy-focused NotebookLM-style workspace for teams to search, organize, and query knowledge with self-hosted RAG.

Memory solution for users, teams, and applications. RAG pipelines with document ingestion, vector indexing, and natural language querying with citations. Supports multiple LLM providers and vector stores. MIT licensed.

Self-hostable knowledge-base and agent platform for document ingestion, RAG pipelines, and enterprise assistant workflows.

PHP Agentic Framework for building production-ready AI driven applications. Connect components (LLMs, vector DBs, memory) to agents that can interact with your data. MIT licensed.

Open-source evaluation and testing library for LLM agents. Red teaming, vulnerability scanning, RAG evaluation, and safety testing with modular architecture. Apache 2.0 licensed.