GitHub Trends

#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

#typescript#agent#ai#ai_memory#anthropic#artifact#artifacts#canvas#content_creation#deepseek_r1#gemini#manus#n8n#qwen#rag#vibe_workflow#workflow Refly.AI is the first vibe workflow platform for non-technical creators, letting you build, share, and monetize AI automations with simple prompts and a visual canvas—no coding needed. Key features include visualized steps for easy debugging, ready-to-use agents that simplify complex tasks, a copilot to turn words into workflows, and a marketplace to earn from your creations. Use the free cloud version or self-host it to automate 90% of repetitive work like content, research, and scheduling, saving hours and boosting productivity. https://github.com/refly-ai/refly

#python#agent#agentic_ai#grpo#kimi_ai#llms#lora#qwen#qwen3#reinforcement_learning#rl ART is a tool that helps you train smart agents for real-world tasks using reinforcement learning, especially with the GRPO method. The standout feature is RULER, which lets you skip the hard work of designing reward functions by using a large language model to automatically score how well your agent is doing—just describe your task, and RULER takes care of the rest. This makes building and improving agents much faster and easier, works for any task, and often performs as well as or better than hand-crafted rewards. You can install ART with a simple command and start training agents right away, even on your own computer or with cloud resources. https://github.com/OpenPipe/ART

#jupyter_notebook#chatglm#chatglm3#gemma_2b_it#glm_4#internlm2#llama3#llm#lora#minicpm#q_wen#qwen#qwen1_5#qwen2 This guide helps beginners set up and use open-source large language models (LLMs) on Linux or cloud platforms like AutoDL, with step-by-step instructions for environment setup, model deployment, and fine-tuning for models such as LLaMA, ChatGLM, and InternLM[2][4][5]. It covers everything from basic installation to advanced techniques like LoRA and distributed fine-tuning, and supports integration with tools like LangChain and online demo deployment. The main benefit is making powerful AI models accessible and easy to use for students, researchers, and anyone interested in experimenting with or customizing LLMs for their own projects[2][4][5]. https://github.com/datawhalechina/self-llm

#python#llm#qwen#tts#wechat WeClone is a tool that helps create a digital clone of you using your WeChat chat logs. It fine-tunes a large language model to mimic your way of speaking, including your tone and humor. This clone can be used as a chatbot on platforms like WeChat, QQ, and Telegram. The benefit is that you can have a personalized digital avatar that feels like you, making interactions more natural and fun. It also ensures data privacy by filtering out sensitive information and allowing local deployment. https://github.com/xming521/WeClone