1.langgenius / dify
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.
Ranked by Attention Score: stars gained over the last 180 complete days
32 repositories by Attention Score · May 7, 2026 – Nov 2, 2026 (UTC)
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 high-throughput and memory-efficient inference and serving engine for LLMs
AI Agent Assistant & development framework that integrates lots of IM platforms, LLMs, plugins and AI feature, and can be your openclaw alternative. ✨
ARIS ⚔️ (Auto-Research-In-Sleep) — Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in — works with Claude Code, Codex, OpenClaw, or any LLM agent.
[EMNLP2025] LightRAG: Simple and Fast Retrieval-Augmented Generation
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
🌟 The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming
A modular graph-based Retrieval-Augmented Generation (RAG) system
Open-source, secure environment with real-world tools for enterprise-grade agents.
Automate browser based workflows with AI
The official gpt4free repository | various collection of powerful language models | opus 4.6 gpt 5.3 kimi 2.5 deepseek v3.2 gemini 3
open-source agentic AI data assistant for the next generation of AI + Data products.
A generative speech model for daily dialogue.
Langchain-Chatchat(原Langchain-ChatGLM)基于 Langchain 与 ChatGLM, Qwen 与 Llama 等语言模型的 RAG 与 Agent 应用 | Langchain-Chatchat (formerly langchain-ChatGLM), local knowledge based LLM (like ChatGLM, Qwen and Llama) RAG and Agent app with langchain
BISHENG is an open LLM devops platform for next generation Enterprise AI applications. Powerful and comprehensive features include: GenAI workflow, RAG, Agent, Unified model management, Evaluation, SFT, Dataset Management, Enterprise-level System Management, Observability and more.
🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
MedicalGPT: Training Your Own Medical GPT Model with ChatGPT Training Pipeline. 训练医疗大模型,实现了包括增量预训练(PT)、有监督微调(SFT)、RLHF、DPO、ORPO、GRPO。
ChatGPT 中文指南🔥,ChatGPT 中文调教指南,指令指南,应用开发指南,精选资源清单,更好的使用 chatGPT 让你的生产力 up up up! 🚀
RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding.
Semantic cache for LLMs. Fully integrated with LangChain and llama_index.
[CVPR 2024 Oral] InternVL Family: A Pioneering Open-Source Alternative to GPT-4o. 接近GPT-4o表现的开源多模态对话模型
Build high-quality LLM apps - from prototyping, testing to production deployment and monitoring.
README file generator, powered by AI.
[COLM 2024] OpenAgents: An Open Platform for Language Agents in the Wild
Large Language Model Text Generation Inference
Databricks’ Dolly, a large language model trained on the Databricks Machine Learning Platform
AudioGPT: Understanding and Generating Speech, Music, Sound, and Talking Head
Private chat with local GPT with document, images, video, etc. 100% private, Apache 2.0. Supports oLLaMa, Mixtral, llama.cpp, and more. Demo: https://gpt.h2o.ai/ https://gpt-docs.h2o.ai/
⚡A curated list of awesome resources related to the Ⱥlgorand Blockchain ⛓
An open source implementation of OpenAI's ChatGPT Code interpreter
Extract knowledge from all information sources using gpt and other language models. Index and make Q&A session with information sources.