Description:
RAGFlow is an open-source Retrieval-Augmented Generation engine that fuses RAG with agent capabilities to create a superior context layer for LLMs, delivering scalable workflows, documents, and multi-agent coordination.
Keep Calm and Read the Friendly Manual :-)
Description:
RAGFlow is an open-source Retrieval-Augmented Generation engine that fuses RAG with agent capabilities to create a superior context layer for LLMs, delivering scalable workflows, documents, and multi-agent coordination.
Description:
LLaMA-Factory is an easy-to-use platform for training and fine-tuning large language models locally, enabling zero-code fine-tuning across 100+ models with multimodal support and a modular toolkit.
Description:
Goose is an open-source, on-machine AI agent that automates engineering tasks end-to-end—from building projects to debugging—working with any LLM and MCP servers, available as a desktop app and CLI.
Description:
An open-source AI-powered task-management system that can drop into Cursor, Lovable, Windsurf, Roo, and more. It helps break projects into actionable tasks for AI agents, supports multiple editors via MCP, and integrates Claude Code. MIT license with Commons Clause.
Description:
An automatic evaluator for instruction-following language models. Human-validated, high-quality, cheap, and fast.
Description:
Ray is an AI compute engine with a core distributed runtime and AI libraries for accelerating ML workloads.
Description:
bolt.diy is an open-source, in-browser AI-powered full-stack web app builder. It supports 19 LLM providers, integrates with Git and Supabase, offers live WebContainer previews, templates, and one-click deployments to Vercel, Netlify, or GitHub Pages for rapid prototyping and deployment.
Description:
Chef by Convex is the AI app builder that builds full-stack web apps with a built-in database, zero config auth, file uploads, real-time UIs, and background workflows.
Description:
Local Deep Researcher is a fully local web research assistant that uses any LLM hosted by Ollama or LMStudio. Give it a topic and it will generate a web search query, gather web search results, summarize the results of web search, reflect on the summary to examine knowledge gaps, generate a new search query to address the gaps, and repeat for a user-defined number of cycles. It will provide the user a final markdown summary with all sources used to generate the summary.
Description:
Open-source platform to build and deploy AI agent workflows.