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PraisonAI application combines AutoGen and CrewAI or similar frameworks into a low-code solution for building and managing multi-agent LLM systems, focusing on simplicity, customisation, and effici…
Vertex AI (GCP) Claude Proxy via Cloudflare workers
The all-in-one Desktop & Docker AI application with full RAG and AI Agent capabilities.
An Open-source Framework for Autonomous Language Agents
《开源大模型食用指南》基于Linux环境快速部署开源大模型，更适合中国宝宝的部署教程
Claude Engineer is an interactive command-line interface (CLI) that leverages the power of Anthropic's Claude-3.5-Sonnet model to assist with software development tasks. This tool combines the capa…
Free and source-available fair-code licensed workflow automation tool. Easily automate tasks across different services.
Papers about red teaming LLMs and Multimodal models.
The open source Tines / Splunk SOAR alternative.
Multi-lingual large voice generation model, providing inference, training and deployment full-stack ability.
Multilingual Voice Understanding Model
ChatPilot: 实现AgentChat对话，支持Google搜索、文件网址对话（RAG）、代码解释器功能，复现了Kimi Chat(文件，拖进来；网址，发出来)。
A community-supported supercharged version of paperless: scan, index and archive all your physical documents
李白 👤 作为唐代杰出诗人，其诗歌作品在中国文学史上具有重要地位。近年来，随着数字技术和人工智能的快速发展，传统文化普及推广的形式也面临着创新与变革。国内外对于李白诗歌的研究虽已相当深入，但在数字化、智能化普及方面仍存在不足。因此，本项目旨在通过构建李白知识图谱，结合大模型训练出专业的AI智能体，以生成式对话应用的形式，推动李白文化的普及与推广。
Mooncake is the serving platform for Kimi, a leading LLM service provided by Moonshot AI.
A modular graph-based Retrieval-Augmented Generation (RAG) system
Awesome-LLM-Eval: a curated list of tools, datasets/benchmark, demos, leaderboard, papers, docs and models, mainly for Evaluation on LLMs. 一个由工具、基准/数据、演示、排行榜和大模型等组成的精选列表，主要面向基础大模型评测，旨在探求生成式AI的技术边界.
An AI regulatory assistant to pre-check your documentation before FDA or MDR submission.
An Open Robustness Benchmark for Jailbreaking Language Models [arXiv 2024]
🦄️ 🎃 👻 Clash Premium 规则集(RULE-SET)，兼容 ClashX Pro、Clash for Windows 等基于 Clash Premium 内核的客户端。
Basic constrained RL agents used in experiments for the "Benchmarking Safe Exploration in Deep Reinforcement Learning" paper.
Build resilient language agents as graphs.
Ingest, parse, and optimize any data format ➡️ from documents to multimedia ➡️ for enhanced compatibility with GenAI frameworks
