Rag
Showing 36 of 53 projects
Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or self-hosted, so teams move from prototype to production without rebuilding the stack.
A self-hosted, extensible AI platform with a user-friendly web interface supporting Ollama, OpenAI API, and offline RAG.
An open-source web crawler and scraper that converts web content into clean, LLM-ready Markdown for RAG, agents, and data pipelines.
Stop renting your intelligence. Own it with AnythingLLM. Everything you need for a powerful local-first agent experience
A Python ETL framework for stream processing, real-time analytics, and building live LLM/RAG pipelines, powered by a scalable Rust engine.
An intelligent memory layer for AI agents that enables personalized interactions by remembering user preferences and context.
An intelligent memory layer for AI agents that enables personalized interactions by remembering user preferences and learning over time.
Ready-to-deploy Docker templates for building real-time RAG, AI pipelines, and enterprise search applications with live data sync.
A production-ready API for building private, context-aware AI applications that query documents using local LLMs with no data leaving your environment.
An open-source framework for building LLM-powered applications with data ingestion, indexing, and retrieval capabilities.
An open-source query engine for AI analytics that builds self-reasoning agents across live data sources without ETL.
Open Source AI Platform - AI Chat with advanced features that works with every LLM
Open-source vector database and embedding store for building AI applications with semantic search.
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications in Python.
A Python library that enables conversational data analysis on SQL, CSV, and parquet files using LLMs and RAG.
A CLI and library for evaluating, red-teaming, and comparing LLM prompts, agents, and RAGs with simple declarative configs.
A curated list of must-use resources for AI engineering, including books, courses, papers, frameworks, and tools.
A curated collection of must-use resources for AI engineering, including books, courses, papers, frameworks, and tools.
An open-source Java library that simplifies integrating LLMs into Java applications through a unified API and comprehensive toolbox.
An ultra-performant data transformation framework for AI, with incremental processing and data lineage built-in.
A command-line interface tool that integrates multiple LLM providers, offering shell assistance, interactive chat, RAG, AI tools, and local server capabilities.
A polyglot document intelligence framework with a Rust core for extracting text, metadata, and structured data from 91+ file formats.
A low-code multi-agent AI framework that automates complex tasks with planning, research, coding, and delivery to messaging platforms.
Chat with your PDF files using GPT with a simple, accurate RAG architecture that avoids third-party dependencies.
Open-source framework for building full-stack AI-powered applications with unified APIs for multiple languages and model providers.
Open-source framework for building full-stack AI-powered applications with unified APIs across JavaScript, Go, and Python.
An open-source graph-vector database built in Rust that unifies application data, vectors, and graphs for AI applications.
An AI-native database built for LLM applications, offering incredibly fast hybrid search across vectors, tensors, and full-text.
A C#/.NET library for efficient local inference of LLaMA and other large language models, based on llama.cpp.
A free course teaching how to design, train, and deploy a production-ready real-time financial advisor LLM system using RAG and LLMOps.
An open-source AI multi-agent framework in .NET for building and integrating intelligent conversational agents into business applications.
Instill Core is a full-stack AI infrastructure tool for data, model, and pipeline orchestration to build versatile AI-first applications.
A high-performance GraphRAG framework in Rust that transforms documents into knowledge graphs for superior retrieval and generation.
A Ruby gem for building LLM-powered applications with a unified interface for multiple providers, RAG systems, and AI assistants.
A Ruby library for building LLM-powered applications with a unified interface for multiple providers, RAG systems, and AI assistants.
An open-source AI troubleshooting atlas and avatar runtime for diagnosing and fixing RAG, agent, and real-world AI workflow failures.
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