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Tag: #gpt · 13 posts
Posted Apr 12
#c_lang#aarch64#arm#arm64#bios#boot_loader#boot_manager#bootloader#efi#gpt#loongarch#loongarch64#loongson#mbr#risc_v#riscv#riscv64#uefi#x64#x86#x86_64 Limine is a modern bootloader that boots Linux and other OSes on x86, ARM64, RISC-V, and LoongArch64 hardware, supporting MBR/GPT partitions and FAT/ISO filesystems on 32-bit Pentium Pro+ or 64-bit systems. Get binaries via Git (e.g., `git clone --branch=v11.x-binary`), build tools with `make`, and join Matrix/Fluxer chats for help. This lets you easily manage and boot multiple OSes with a clean menu, saving time on custom PC or server setups. https://github.com/Limine-Bootloader/Limine
Posted Feb 25
#javascript#ai#algorithm#artificial_intelligence#chatgpt#claude#cursor#deep_learning#deepseek#gemini#generative_ai#gpt#llm#mcp#openai#python#rag#vibe_coding#vibecoding#vue#vuepress 鱼皮的 AI知识库 offers a free Vibe Coding tutorial for beginners, teaching AI-powered programming with natural language prompts to build and monetize apps fast—no coding skills needed. It covers tools, projects, tips, and paths like making your first work in 10 minutes, plus AI guides on DeepSeek, Cursor, and more. You benefit by quickly creating profitable products, breaking tech barriers, and enjoying AI perks to improve life and work. Start at ai.codefather.cn/vibe. https://github.com/liyupi/ai-guide
Posted Feb 20
#go#ai_agents#ai_security_tool#anthropic#autonomous_agents#golang#gpt#graphql#multi_agent_system#offensive_security#open_source#openai#penetration_testing#penetration_testing_tools#react#security_automation#security_testing#security_tools#self_hosted PentAGI is an AI-powered tool that automates penetration testing with smart agents using 20+ pro tools like nmap and metasploit in a safe Docker sandbox. It researches vulnerabilities, executes attacks, stores knowledge for reuse, and creates detailed reports via a simple web UI. Quick setup needs Docker, an LLM API key (OpenAI/Anthropic), and `docker compose up -d`. This saves you hours of manual work, speeds up secure testing, cuts errors, and helps find issues faster for better protection. https://github.com/vxcontrol/pentagi
Posted Jan 26
#python#agents#ai#ai_engineer#ai_engineering#copilot#data_science#data_scientist#generative_ai#gpt#machine_learning#ml_engineer#ml_engineering#openai AI Data Science Team is a free Python library with AI agents that speed up your data work 10X by handling loading, cleaning, visualization, EDA, feature engineering, modeling, and SQL tasks. Its flagship AI Pipeline Studio app creates visual, reproducible pipelines you can run with Streamlit after easy install (Python 3.10+, OpenAI or Ollama). This saves you hours on repetitive jobs, boosts accuracy, and lets you focus on insights and business results. https://github.com/business-science/ai-data-science-team
Posted Jan 23
#python#deepseek#demo#easy#embedding#flask#gpt#huggingface_transformers#llm#mcp#multimodal#openai#qwen#rag#sentence_transformers#ui#vllm#vlm UltraRAG is a lightweight framework that makes building retrieval-augmented generation (RAG) systems simple and fast. It uses a low-code approach where you write just dozens of lines of YAML configuration instead of complex code to create sophisticated AI workflows with conditional logic and loops. The framework includes a visual development environment where you can drag-and-drop to build pipelines, adjust parameters in real-time, and instantly convert your logic into interactive chat applications. This means you can deploy powerful AI systems that ground answers in your own data—reducing hallucinations and improving accuracy—without needing extensive coding expertise or lengthy development cycles. https://github.com/OpenBMB/UltraRAG
Posted Aug 16
#php#agent#agi#ai#gpt#llm#low_code#mcp#no_code#sandbox#workflow Magic is an open-source AI platform that helps businesses quickly build and use AI tools to boost productivity by up to 100 times. It offers a complete set of AI products, including a smart AI agent for complex tasks, an AI-powered chat system for team communication, and a visual tool to create AI workflows without coding. These tools work together to improve decision-making, automate tasks, and enhance collaboration securely within organizations. You can try Magic via cloud services or self-host it, making it flexible and powerful for different business needs. This platform saves time, improves efficiency, and supports smarter teamwork. https://github.com/dtyq/magic
Posted Aug 8
#other#agent#ai#artificial_intelligence#autogpt#autonomous_agents#awesome#babyagi#copilot#gpt#gpt_4#gpt_engineer#openai#python Codeium is a free AI-powered coding assistant that helps you write code faster and better by providing real-time autocomplete suggestions, generating code from natural language, explaining code, and assisting with refactoring. It supports over 70 programming languages and integrates with many popular IDEs like Visual Studio Code. Codeium learns from your coding style and project context to offer relevant suggestions, saving you time and reducing errors. It also includes a chat feature to answer coding questions instantly, so you don’t need to switch to a browser for help. This boosts your productivity and code quality efficiently. https://github.com/e2b-dev/awesome-ai-agents
Posted Jun 24
#other#automl#chatgpt#data_analysis#data_science#data_visualization#data_visualizations#deep_learning#gpt#gpt_3#jax#keras#machine_learning#ml#nlp#python#pytorch#scikit_learn#tensorflow#transformer This is a comprehensive, regularly updated list of 920 top open-source Python machine learning libraries, organized into 34 categories like frameworks, data visualization, NLP, image processing, and more. Each project is ranked by quality using GitHub and package manager metrics, helping you find the best tools for your needs. Popular libraries like TensorFlow, PyTorch, scikit-learn, and Hugging Face transformers are included, along with specialized ones for time series, reinforcement learning, and model interpretability. This resource saves you time by guiding you to high-quality, actively maintained libraries for building, optimizing, and deploying machine learning models efficiently. https://github.com/ml-tooling/best-of-ml-python
Posted Jun 20
#jupyter_notebook#ai#artificial_intelligence#chatgpt#deep_learning#from_scratch#gpt#language_model#large_language_models#llm#machine_learning#python#pytorch#transformer You can learn how to build your own large language model (LLM) like GPT from scratch with clear, step-by-step guidance, including coding, training, and fine-tuning, all explained with examples and diagrams. This approach mirrors how big models like ChatGPT are made but is designed to run on a regular laptop without special hardware. You also get access to code for loading pretrained models and fine-tuning them for tasks like text classification or instruction following. This helps you deeply understand how LLMs work inside and lets you create your own functional AI assistant, gaining practical skills in AI development[1][2][3][4]. https://github.com/rasbt/LLMs-from-scratch
Posted Jun 8
#rust#ai#ai_engineering#anthropic#artificial_intelligence#deep_learning#genai#generative_ai#gpt#large_language_models#llama#llm#llmops#llms#machine_learning#ml#ml_engineering#mlops#openai#python#rust TensorZero is a free, open-source tool that helps you build and improve large language model (LLM) applications by using real-world data and feedback. It gives you one simple API to connect with all major LLM providers, collects data from your app’s use, and lets you easily test and improve prompts, models, and strategies. You can see how your LLMs perform, compare different options, and make them smarter, faster, and cheaper over time—all while keeping your data private and under your control. This means you get better results with less effort and cost, and your apps keep improving as you use them[1][2][3]. https://github.com/tensorzero/tensorzero
Posted Jun 8
#other#agents#agi#ai#anthropic#artifacts#awesome#awesome_list#bots#chatbot#chatgpt#claude#exploit#gemini#google#gpt#hack#jailbreak#openai#prompts#spam AI tools like autonomous software engineers can help developers by completing tasks independently or working alongside them. This can increase productivity by automating repetitive tasks, allowing developers to focus on more complex and creative work. AI also helps reduce errors and improves code quality, making the development process faster and more efficient. Overall, using AI in software development can lead to better outcomes and more innovative solutions. https://github.com/friuns2/BlackFriday-GPTs-Prompts
Posted Jun 7
#java#anthropic#chatgpt#chroma#embeddings#gemini#gpt#huggingface#java#langchain#llama#milvus#ollama#onnx#openai#openai_api#pgvector#pinecone#vector_database#weaviate LangChain4j helps you add powerful AI to your Java applications by making it easy to use Large Language Models (LLMs). It provides a simple way to switch between different LLMs and embedding stores without needing to learn each one's specific API. This means you can easily experiment with different models and tools, making your development process faster and more flexible. LangChain4j also offers many examples and tools to help you build complex AI applications quickly, such as chatbots and retrieval systems. This simplifies the integration of AI into your projects, allowing you to focus on creating better applications. https://github.com/langchain4j/langchain4j