Search Results for "rag"
Sort By:
Showing 159 open source projects for "rag"
View related business solutions-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
-
1
RAG-Survey
Collecting awesome papers of RAG for AIGC
RAG-Survey is an open-source research repository that collects and organizes academic papers related to retrieval-augmented generation (RAG) systems used in modern AI applications. Retrieval-augmented generation combines large language models with external knowledge retrieval systems to improve factual accuracy and contextual understanding. -
2
All-in-RAG
Big Model Application Development Practice 1
All-in-RAG is an open-source educational project designed to teach developers how to build applications using retrieval-augmented generation techniques. The repository provides a structured learning path that covers both theoretical foundations and practical implementation steps for RAG systems. It explains the full development pipeline required to create knowledge-aware AI assistants, including data preparation, document indexing, vector embedding generation, and retrieval strategies. ... -
3
rag-search
RAG Search API
...It is built to be easily deployable, requiring only environment configuration and dependency installation to run a functional RAG service. The system supports configurable filtering, scoring thresholds, and reranking options, allowing developers to fine-tune retrieval quality. Its architecture is modular, separating handlers, services, and utilities to support customization and extension. Overall, rag-search serves as a practical starter backend for teams building AI search or question-answering applications on their own data. -
4
RAG Anything
RAG-Anything: All-in-One RAG Framework
RAG-Anything is an open-source unified framework that extends the Retrieval-Augmented Generation (RAG) paradigm to fully multimodal document and knowledge retrieval, enabling systems to ingest, parse, represent, and query rich content that includes text, images, tables, formulas, and other structured or visual elements. Traditional RAG systems are typically limited to text and cannot effectively work across heterogeneous document layouts, but RAG-Anything addresses this by modeling multimodal content in ways that preserve cross-modal relationships and semantic context, often treating content elements as interconnected knowledge entities rather than separate data silos. ... -
Go From AI Idea to AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
-
5
RAG API
ID-based RAG FastAPI: Integration with Langchain and PostgreSQL
rag_api is an open-source REST API for building Retrieval-Augmented Generation (RAG) systems using LLMs like GPT. It lets users index documents, search semantically, and retrieve relevant content for use in generative AI workflows. Designed for rapid prototyping, it is ideal for chatbot development, document assistants, and knowledge-based LLM apps. -
6
RAG-Retrieval
Unify Efficient Fine-tuning of RAG Retrieval, including Embedding
RAG-Retrieval is an open-source framework for building and training retrieval systems used in retrieval-augmented generation pipelines. Retrieval-augmented generation combines large language models with external knowledge retrieval to improve factual accuracy and domain-specific reasoning. This repository provides end-to-end infrastructure for training retrieval models, performing inference, and distilling embedding models for improved performance. -
7
Code-Graph-RAG
The ultimate RAG for your monorepo
Code-Graph-RAG is an advanced retrieval-augmented generation system designed specifically for understanding and interacting with large, multi-language codebases by transforming them into structured knowledge graphs. It uses Tree-sitter to parse source code into abstract syntax trees, extracting relationships between functions, classes, and modules to build a graph-based representation of the entire codebase. -
8
RAG Web UI
RAG Web UI is an intelligent dialogue system based on RAG
RAG Web UI is an open-source intelligent dialogue system built on retrieval-augmented generation technology, designed to enable users to create AI-powered question answering systems grounded in their own knowledge bases. It combines document retrieval with large language models to provide accurate, context-aware responses based on indexed data rather than generic model knowledge. -
9
Advanced RAG Techniques
Advanced techniques for RAG systems
Advanced RAG Techniques is a comprehensive collection of tutorials and implementations focused on advanced Retrieval-Augmented Generation (RAG) systems. It is designed to help practitioners move beyond basic RAG setups and explore techniques that improve retrieval quality, context construction, and answer robustness. The repository organizes techniques into categories such as foundational RAG, query enhancement, context enrichment, and advanced retrieval, making it easier to navigate specific areas of interest. ... -
$300 in Free Credit Towards Top Cloud ServicesStart your project in minutes. After credits run out, 20+ products include free monthly usage. Only pay when you're ready to scale.
-
10
Ollama RAG Chatbot
Chat with multiple PDFs locally
Ollama RAG Chatbot is a local-first retrieval chatbot project built to let users chat with the contents of multiple PDF documents through a simple interface. The project is framed as an experiment, but its setup and packaging make it approachable for practical local use as well. It supports running on a local machine or in Kaggle, which lowers the barrier for users who want to test RAG workflows without building everything from scratch. -
11
Agentic RAG for Dummies
A modular Agentic RAG built with LangGraph
Agentic RAG for Dummies is an educational repository that demonstrates how to build retrieval-augmented generation systems combined with autonomous AI agents. The project explains the principles behind agentic retrieval pipelines where language models can dynamically decide when to retrieve information, analyze results, and plan further actions. -
12
RAG from Scratch
Demystify RAG by building it from scratch
RAG From Scratch is an educational open-source project designed to teach developers how retrieval-augmented generation systems work by building them step by step. Instead of relying on complex frameworks or cloud services, the repository demonstrates the entire RAG pipeline using transparent and minimal implementations. The project walks through key concepts such as generating embeddings, building vector databases, retrieving relevant documents, and integrating the retrieved context into language model prompts. ... -
13
Controllable-RAG-Agent
This repository provides an advanced RAG
Controllable-RAG-Agent is an advanced Retrieval-Augmented Generation (RAG) system designed specifically for complex, multi-step question answering over your own documents. Instead of relying solely on simple semantic search, it builds a deterministic control graph that acts as the “brain” of the agent, orchestrating planning, retrieval, reasoning, and verification across many steps. -
14
Advanced + Agentic RAG Cookbooks
Advanced RAG cookbooks for building accurate LLM applications
Athina AI’s RAG Cookbooks is a GitHub repository that showcases advanced and agentic Retrieval-Augmented Generation techniques for building more accurate AI applications. It provides ready-to-use notebooks, implementations, and explanations that help developers move from basic RAG setups to more sophisticated workflows. Athina AI’s RAG Cookbooks covers the full RAG pipeline, including indexing, retrieval, augmentation, and generation, while also addressing evaluation to measure accuracy and relevance. ... -
15
RAGFlow
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. It offers a streamlined RAG workflow for businesses of any scale, combining LLM (Large Language Models) to provide truthful question-answering capabilities, backed by well-founded citations from various complex formatted data. -
16
kotaemon
An open-source RAG-based tool for chatting with your documents
An open-source clean & customizable RAG UI for chatting with your documents. Built with both end users and developers in mind. This project serves as a functional RAG UI for both end users who want to do QA on their documents and developers who want to build their own RAG pipeline. -
17
RAGHub
A community-driven collection of RAG
RAGHub is an open-source directory and knowledge hub dedicated to organizing tools, frameworks, and research resources related to Retrieval-Augmented Generation systems. The project was created to help developers navigate the rapidly expanding ecosystem of RAG technologies, where new frameworks and tools are constantly emerging. Instead of implementing a specific algorithm, RAGHub functions as a curated catalog that collects and categorizes RAG-related projects across multiple categories such as frameworks, engines, evaluation tools, and data preparation systems. The repository is community-driven, meaning developers can contribute new tools, frameworks, or educational resources to keep the dRAGHub is an open-source directory and knowledge hub dedicated to organizing tools, frameworks, and research resources related to Retrieval-Augmented Generation systems. -
18
MCP Server RAG Web Browser
A MCP Server for the RAG Web Browser Actor
The MCP Server for the RAG Web Browser Actor allows AI assistants and LLMs to perform web searches and extract information from web pages. It facilitates interaction with the web, enabling up-to-date context retrieval for AI applications. -
19
Chipper
AI interface for tinkerers (Ollama, Haystack RAG, Python)
Chipper is an AI interface designed for tinkerers and developers, providing a platform to experiment with various AI models and techniques. It offers integration with tools like Ollama and Haystack for Retrieval-Augmented Generation (RAG), enabling users to build and test AI applications efficiently. Chipper supports Python and provides a modular architecture, allowing for customization and extension based on specific project requirements. -
20
pgai
A suite of tools to develop RAG, semantic search, and other AI apps
...It integrates tools for vector storage, advanced indexing, and AI model interactions, facilitating the development of applications like semantic search and Retrieval-Augmented Generation (RAG) without leaving the SQL environment. -
21
Cognita
Open source RAG framework for building scalable modular AI apps
Cognita is an open source framework designed to help developers build, organize, and deploy Retrieval-Augmented Generation (RAG) applications in a structured and production-ready way. It addresses the gap between quick experimentation in notebooks and the complexity of deploying scalable AI systems by introducing a modular and API-driven architecture. Cognita provides reusable components such as parsers, data loaders, embedders, retrievers, and query controllers, allowing teams to customize each stage of the RAG pipeline independently. ... -
22
Korvus
Korvus is a search SDK that unifies the entire RAG pipeline
Korvus is an open-source retrieval-augmented generation (RAG) pipeline designed to run entirely inside PostgreSQL, allowing developers to build AI search and knowledge systems directly within a database environment. The project consolidates the typical steps of a RAG pipeline—including embedding generation, document retrieval, reranking, and text generation—into a single query executed within the Postgres ecosystem. -
23
Raglite
RAGLite is a Python toolkit for Retrieval-Augmented Generation
Raglite is a lightweight framework for building Retrieval-Augmented Generation (RAG) pipelines with minimal configuration. It connects large language models to vector databases for context-aware responses, enabling developers to prototype and deploy RAG systems quickly. Raglite focuses on simplicity and modularity for fast experimentation. -
24
LightRAG
"LightRAG: Simple and Fast Retrieval-Augmented Generation"
LightRAG is a lightweight Retrieval-Augmented Generation (RAG) framework designed for efficient document retrieval and response generation. It is optimized for speed and lower resource consumption, making it ideal for real-time applications. -
25
Langflow
Low-code app builder for RAG and multi-agent AI applications
Langflow is a low-code app builder for RAG and multi-agent AI applications. It’s Python-based and agnostic to any model, API, or database.
