AI
Get up and running with OpenAI gpt-oss, DeepSeek-R1, Gemma 3 and other models.
👾 A Python API wrapper for Poe.com. With this, you will have free access to GPT-4, Claude, Llama, Gemini, Mistral and more! 🚀
《开源大模型食用指南》针对中国宝宝量身打造的基于Linux环境快速微调（全参数/Lora）、部署国内外开源大模型（LLM）/多模态大模型（MLLM）教程
🔥🔥🔥AI-driven database tool and SQL client, The hottest GUI client, supporting MySQL, Oracle, PostgreSQL, DB2, SQL Server, DB2, SQLite, H2, ClickHouse, and more.
🚀🚀 「大模型」2小时完全从0训练26M的小参数GPT！🌏 Train a 26M-parameter GPT from scratch in just 2h!
Zero shot vulnerability discovery using LLMs
Use LLMs to track and extract websites, RSS feeds, and social media
Papers and resources related to the security and privacy of LLMs 🤖
LangChain 的中文入门教程
Periodic cyber security newsletters that capture the latest news, summaries of conference talks, research, best practices, tools, events, vulnerabilities, and analysis of trending threats and attacks
Agentic AI framework for enterprise workflow automation.
A high-throughput and memory-efficient inference and serving engine for LLMs
Mirror Flowers 是一个开箱即用的代码安全审计工具，集成本地静态扫描（行级污点追踪 + AST）与 AI 验证，帮助你快速发现并定位高风险问题，并给出修复建议。
Use any LLMs (Large Language Models) for Deep Research. Support SSE API and MCP server.
A curated list of resources dedicated to open source GitHub repositories related to ChatGPT and OpenAI API
Model Context Protocol Servers
The Python Risk Identification Tool for generative AI (PyRIT) is an open source framework built to empower security professionals and engineers to proactively identify risks in generative AI systems.
AI-powered reverse engineering assistant that bridges IDA Pro with language models through MCP.
Automated Penetration Testing with EZ and Agents
The Triton TensorRT-LLM Backend
🚀 One-stop solution for creating your digital avatar from chat history 💡 Fine-tune LLMs with your chat logs to capture your unique style, then bind to a chatbot to bring your digital self to life. …
An autonomous LLM-agent for large-scale, repository-level code auditing
XBOW Validation Benchmarks
本仓库包含对 Claude Code v1.0.33 进行逆向工程的完整研究和分析资料。包括对混淆源代码的深度技术分析、系统架构文档，以及重构 Claude Code agent 系统的实现蓝图。主要发现包括实时 Steering 机制、多 Agent 架构、智能上下文管理和工具执行管道。该项目为理解现代 AI agent 系统设计和实现提供技术参考。