Search Results for "rag"
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Showing 32 open source projects for "rag"
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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.
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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. -
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React Native RAG
Private, local RAGs. Supercharge LLMs with your own knowledge base
React Native RAG supports multiple integration styles, including a simple hook, a class-based API, and direct component usage. Its main value is giving React Native apps a privacy-friendly way to combine local knowledge retrieval with on-device AI workflows. -
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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. ... -
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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. -
Stop vibe-debugging.AppSignal's MCP server hands Claude, Cursor, or Zed your real errors, traces, and the deploy that shipped them. AI writes the fix; you review the diff.
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RAGapp
The easiest way to use Agentic RAG in any enterprise
The easiest way to use Agentic RAG in any enterprise. As simple to configure as OpenAI's custom GPTs, but deployable in your own cloud infrastructure using Docker. Built using LlamaIndex. Just the RAGapp container doesn't come with any authentication layer by design. This is the task of an API Gateway routing the traffic to RAGapp. This step heavily depends on your cloud provider and the services you use. -
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Coze Studio
An AI agent development platform with all-in-one visual tools
Coze Studio is ByteDance’s open‑source, visual AI agent development platform. It offers no-code/low-code workflows to build, debug, and deploy conversational agents, integrating prompting, RAG-based knowledge bases, plugin systems, and workflow orchestration. Developed in Go (backend) and React/TypeScript (frontend), it uses a containerized microservices architecture suitable for enterprise deployment. -
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Verba
Retrieval Augmented Generation (RAG) chatbot powered by Weaviate
Welcome to Verba: The Golden RAGtriever, a community-driven open-source application designed to offer an end-to-end, streamlined, and user-friendly interface for Retrieval-Augmented Generation (RAG) out of the box. In just a few easy steps, explore your datasets and extract insights with ease, either locally with Ollama and Huggingface or through LLM providers such as Anthrophic, Cohere, and OpenAI. This project is built with and for the community, please be aware that it might not be maintained with the same urgency as other Weaviate production applications. -
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Generative AI for Beginners (Version 3)
21 Lessons, Get Started Building with Generative AI
...The course covers everything from model selection, prompt engineering, and chat/text/image app patterns to secure development practices and UX for AI. It also walks through modern application techniques such as function calling, RAG with vector databases, working with open source models, agents, fine-tuning, and using SLMs. Each lesson includes a short video, a written guide, runnable samples for Azure OpenAI, the GitHub Marketplace Model Catalog, and the OpenAI API, plus a “Keep Learning” section for deeper study. -
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Lecca.io
Lecca.io | AI Agents & Automations
Lecca.io is an AI platform that allows you to configure and deploy Large Language Models (LLMs) equipped with powerful tools and workflows. Build, customize, and automate your AI agents with ease. -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Ax
Build LLM powered Agents and "Agentic workflows"
Build intelligent agents quickly — inspired by the power of "Agentic workflows" and the Stanford DSPy paper. Seamlessly integrates with multiple LLMs and VectorDBs to build RAG pipelines or collaborative agents that can solve complex problems. Advanced features streaming validation, multi-modal DSPy, etc. We've renamed from "llmclient" to "ax" to highlight our focus on powering agentic workflows. We agree with many experts like "Andrew Ng" that agentic workflows are the key to unlocking the true power of large language models and what can be achieved with in-context learning. ... -
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ChatOllama
ChatOllama is an open-source AI chatbot
...The platform also includes higher-level capabilities such as AI agents, document-backed knowledge bases, real-time voice chat, and Model Context Protocol integration for external tools. Its RAG functionality allows document upload and knowledge-base-driven interaction, while vector database support adds more scalable retrieval options. Deployment is streamlined with Docker Compose, and the project also includes internationalization and modular feature toggles for controlling what parts of the system are enabled. As a result, ChatOllama feels less like a single chatbot and more like a flexible self-hosted AI workspace. -
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5ire
5ire is a cross-platform desktop AI assistant, MCP client
5ire is a sleek, cross‑platform desktop AI assistant and MCP client that connects to major service providers, supports a local knowledge base and tool integration via MCP servers, enabling robust RAG and assistant features. These components are required as they constitute the runtime environment for the MCP Server. If you don't anticipate using the tools feature immediately, you may choose to skip this installation step and complete it later when the need arises. MCP is an open protocol that standardizes how applications provide context to LLMs. ... -
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FastGPT
FastGPT is a knowledge-based platform built on the LLMs
FastGPT is a knowledge-based platform built on the LLMs, offers a comprehensive suite of out-of-the-box capabilities such as data processing, RAG retrieval, and visual AI workflow orchestration, letting you easily develop and deploy complex question-answering systems without the need for extensive setup or configuration. -
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Project NOMAD
Self-contained, offline survival computer with tools, knowledge, & AI
Project N.O.M.A.D. (Node for Offline Media, Archives, and Data) is a self-contained, offline-first knowledge and education server designed to run on local hardware. It combines AI, educational resources, and critical information tools into a single platform accessible through a web browser. Built as a containerized system managed via Docker, it orchestrates multiple applications through a centralized “Command Center” interface. NOMAD enables users to access offline Wikipedia, AI chat, maps,... -
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DocsGPT
Private AI platform for agents, enterprise search and RAG pipelines
DocsGPT is an open-source AI platform for deploying private RAG pipelines, AI agents, and enterprise search on your own infrastructure. Connect any data source (PDFs, DOCX, CSV, Excel, HTML, audio, GitHub, databases, URLs) and get accurate, hallucination-free answers with source citations. Choose your LLM: OpenAI, Anthropic, Google Gemini, or local models. Works with Qdrant, MongoDB, and Elasticsearch and more. -
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Sim
Build, deploy, and orchestrate AI agents
Sim is an open-source platform designed to build, deploy, and orchestrate AI agent workflows through a unified intelligence layer. It positions itself as infrastructure for managing an “AI workforce,” enabling developers and teams to coordinate multiple agents and automate complex processes from a central environment. The project focuses on low-code and no-code accessibility while still supporting advanced customization through TypeScript and modern web tooling. Its architecture supports... -
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Eliza
Autonomous agents for everyone
Build and deploy autonomous AI agents with consistent personalities across Discord, Twitter, and Telegram. Full support for voice, text, and media interactions. Built-in RAG memory system, document processing, media analysis, and autonomous trading capabilities. Supports multiple AI models including Llama, GPT-4, and Claude. Create custom actions, add new platform integrations, and extend functionality through a modular plugin system. Full TypeScript support. -
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Reor Project
Private & local AI personal knowledge management app
Reor is an AI-powered desktop note-taking app: it automatically links related notes, answers questions on your notes, provides semantic search and can generate AI flashcards. Everything is stored locally and you can edit your notes with an Obsidian-like markdown editor. The hypothesis of the project is that AI tools for thought should run models locally by default. Reor stands on the shoulders of the giants Ollama, Transformers.js & LanceDB to enable both LLMs and embedding models to run locally. -
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KnowNote
A local-first AI knowledge base & NotebookLM alternative
...Unlike many NotebookLM alternatives that rely on Docker or cloud deployments, KnowNote runs natively on desktop platforms without complex setup, meaning all data stays local unless the user opts to integrate with self-managed or private LLM APIs. Its retrieval-augmented generation (RAG) system offers semantic search and traceable source references, and it supports multiple LLM providers through a flexible plugin-style provider architecture. -
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Dify-Plus
Dify-Plus is an enterprise-grade enhanced version of Dify
Dify-Plus is an enterprise-enhanced extension of the Dify platform that adds advanced management, governance, and operational capabilities for deploying AI applications in production environments. It builds on top of Dify’s core functionality, which includes agent workflows, RAG pipelines, and model orchestration, by introducing a dedicated administrative backend powered by gin-vue-admin. The platform is designed to address real-world enterprise challenges such as user management, usage tracking, cost control, and secure access to AI services. It includes features like quota management, API key monitoring, usage analytics, and permission-based controls, allowing organizations to regulate how AI resources are consumed across teams. dify-plus also enhances collaboration by providing centralized application management, template synchronization, and role-based access systems. -
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Spring AI Alibaba Examples
Spring AI Alibaba examples for building and testing AI apps
Spring AI Alibaba Examples provides a collection of example projects that demonstrate how to use Spring AI and Spring AI Alibaba across different scenarios, from basic setups to more advanced AI applications. It is designed to help developers understand core concepts, explore practical implementations, and follow best practices when building AI-powered systems using the Spring ecosystem. Each module focuses on a specific use case such as chat, image processing, audio handling, graph... -
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Flock
Flock is a workflow-based low-code platform for building chatbots
Flock is a workflow-based low-code platform designed for building AI applications such as chatbots, retrieval-augmented generation systems, and multi-agent workflows. The platform uses a visual workflow architecture where different nodes represent processing steps such as input processing, model inference, retrieval operations, and tool execution. Developers can connect these nodes to create complex pipelines that orchestrate multiple language models and external services. Built on... -
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WeKnora
LLM framework for document understanding and semantic retrieval
...It focuses on analyzing complex and heterogeneous documents by combining multiple processing stages such as multimodal document parsing, vector indexing, and intelligent retrieval. It follows the Retrieval-Augmented Generation (RAG) paradigm, where relevant document segments are retrieved and used by language models to generate accurate, context-aware responses. This approach enables the system to provide more reliable answers by grounding model reasoning in the content of uploaded documents. WeKnora is designed with a modular architecture that separates components for document processing, search strategies, and model inference, allowing developers to customize or extend different parts of the pipeline. ... -
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Harbor LLM
Run a full local LLM stack with one command using Docker
Harbor is an open source, containerized toolkit designed to simplify running local large language model (LLM) environments. It combines a CLI and companion app to launch backends, frontends, and supporting services with minimal setup. With a single command, users can start preconfigured tools like Ollama and Open WebUI, enabling chat, workflows, and integrations immediately. Harbor supports multiple inference engines, including llama.cpp and vLLM, and connects them seamlessly to user... -
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RuoYi AI
Enterprise AI platform for building, deploying, and managing apps
RuoYi AI is a full-stack enterprise-oriented AI development platform designed to help developers rapidly build, deploy, and manage intelligent applications using modern large language models and AI ecosystems. It provides a unified framework for integrating multiple AI models from different providers, allowing teams to switch or combine models through a consistent interface without vendor lock-in. RuoYi AI includes built-in support for retrieval-augmented generation, enabling organizations...
