#python #agent #agentic #agentic_ai #agents #agents_sdk #ai #ai_agents #aiagentframework #genai #genai_chatbot #llm #llms #multi_agent #multi_agent_systems #multi_agents #multi_agents_collaboration
The Agent Development Kit (ADK) is an open-source Python toolkit that helps you easily build, test, and deploy smart AI agents, from simple helpers to complex multi-agent systems. It lets you write agent logic in Python, use many built-in or custom tools, and organize multiple agents to work together. You can deploy agents anywhere, including Google Cloud, and evaluate their performance with built-in tools. ADK supports flexible workflows and works with various AI models, not just Google’s. This means you get full control and flexibility to create powerful AI applications that fit your needs, speeding up development and making it easier to manage AI projects.
https://github.com/google/adk-python
The Agent Development Kit (ADK) is an open-source Python toolkit that helps you easily build, test, and deploy smart AI agents, from simple helpers to complex multi-agent systems. It lets you write agent logic in Python, use many built-in or custom tools, and organize multiple agents to work together. You can deploy agents anywhere, including Google Cloud, and evaluate their performance with built-in tools. ADK supports flexible workflows and works with various AI models, not just Google’s. This means you get full control and flexibility to create powerful AI applications that fit your needs, speeding up development and making it easier to manage AI projects.
https://github.com/google/adk-python
GitHub
GitHub - google/adk-python: An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI…
An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control. - google/adk-python
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#typescript #agentic_ai #agentic_workflow #agents #ai #approval_process #escalation_policy #function_calling #human_as_tool #human_in_the_loop #humanlayer #llm #llms
HumanLayer helps you safely use AI agents to automate important tasks by ensuring a human always reviews high-risk actions, like sending emails or changing private data. This is crucial because AI can make mistakes or create wrong outputs, and some tasks are too sensitive to trust AI alone. HumanLayer’s tools guarantee human oversight in these cases, so you get the benefits of AI automation without risking errors in critical work. This makes AI more reliable and useful for automating complex workflows while keeping control and safety in your hands.
https://github.com/humanlayer/humanlayer
HumanLayer helps you safely use AI agents to automate important tasks by ensuring a human always reviews high-risk actions, like sending emails or changing private data. This is crucial because AI can make mistakes or create wrong outputs, and some tasks are too sensitive to trust AI alone. HumanLayer’s tools guarantee human oversight in these cases, so you get the benefits of AI automation without risking errors in critical work. This makes AI more reliable and useful for automating complex workflows while keeping control and safety in your hands.
https://github.com/humanlayer/humanlayer
GitHub
GitHub - humanlayer/humanlayer: The best way to get AI coding agents to solve hard problems in complex codebases.
The best way to get AI coding agents to solve hard problems in complex codebases. - humanlayer/humanlayer
#python #agent #ai #ai_coding #claude #claude_code #language_server #llms #mcp_server #programming #vibe_coding
Serena is a free, open-source toolkit that turns large language models (LLMs) into powerful coding agents able to work directly on your codebase with IDE-like precision. It uses semantic code analysis to understand code structure and symbols, enabling efficient code search and editing without reading entire files. Serena supports many programming languages and integrates flexibly with various LLMs and development environments via the Model Context Protocol (MCP). This means you can automate complex coding tasks, improve productivity, and reduce costs without subscriptions, making your coding workflow faster and smarter.
https://github.com/oraios/serena
Serena is a free, open-source toolkit that turns large language models (LLMs) into powerful coding agents able to work directly on your codebase with IDE-like precision. It uses semantic code analysis to understand code structure and symbols, enabling efficient code search and editing without reading entire files. Serena supports many programming languages and integrates flexibly with various LLMs and development environments via the Model Context Protocol (MCP). This means you can automate complex coding tasks, improve productivity, and reduce costs without subscriptions, making your coding workflow faster and smarter.
https://github.com/oraios/serena
GitHub
GitHub - oraios/serena: A powerful coding agent toolkit providing semantic retrieval and editing capabilities (MCP server & other…
A powerful coding agent toolkit providing semantic retrieval and editing capabilities (MCP server & other integrations) - oraios/serena
#python #agent #llms
AutoAgent lets you create and use powerful AI agents easily by just using natural language—no coding needed. It supports many large language models (LLMs) like OpenAI and Anthropic, and performs as well as top research AI systems on benchmarks. You can build tools, agents, and workflows quickly, manage data efficiently with its built-in vector database, and interact flexibly through different modes. It’s lightweight, customizable, and cost-effective, making it a personal AI assistant that helps automate complex tasks simply and efficiently. This saves you time and technical effort while giving you advanced AI capabilities.
https://github.com/HKUDS/AutoAgent
AutoAgent lets you create and use powerful AI agents easily by just using natural language—no coding needed. It supports many large language models (LLMs) like OpenAI and Anthropic, and performs as well as top research AI systems on benchmarks. You can build tools, agents, and workflows quickly, manage data efficiently with its built-in vector database, and interact flexibly through different modes. It’s lightweight, customizable, and cost-effective, making it a personal AI assistant that helps automate complex tasks simply and efficiently. This saves you time and technical effort while giving you advanced AI capabilities.
https://github.com/HKUDS/AutoAgent
GitHub
GitHub - HKUDS/AutoAgent: "AutoAgent: Fully-Automated and Zero-Code LLM Agent Framework"
"AutoAgent: Fully-Automated and Zero-Code LLM Agent Framework" - HKUDS/AutoAgent
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#python #llms #mlx
MLX LM is a Python tool that helps you run and fine-tune large language models (LLMs) efficiently on Apple Silicon Macs. It connects easily to thousands of models on Hugging Face, supports model quantization to save memory, and allows distributed training. You can generate text or chat with models via simple commands or Python code. It also offers features like prompt caching and memory optimization for handling long texts, making it faster and less resource-heavy. This means you can run powerful AI models locally on your Mac without needing expensive cloud services, saving cost and improving speed.
https://github.com/ml-explore/mlx-lm
MLX LM is a Python tool that helps you run and fine-tune large language models (LLMs) efficiently on Apple Silicon Macs. It connects easily to thousands of models on Hugging Face, supports model quantization to save memory, and allows distributed training. You can generate text or chat with models via simple commands or Python code. It also offers features like prompt caching and memory optimization for handling long texts, making it faster and less resource-heavy. This means you can run powerful AI models locally on your Mac without needing expensive cloud services, saving cost and improving speed.
https://github.com/ml-explore/mlx-lm
GitHub
GitHub - ml-explore/mlx-lm: Run LLMs with MLX
Run LLMs with MLX. Contribute to ml-explore/mlx-lm development by creating an account on GitHub.
#python #agent_framework #data_analysis #deep_research #deep_search #llms #multi_agent_system #nlp #public_opinion_analysis #python3 #sentiment_analysis
You can use the "Weibo Public Opinion Analysis System" (called "微舆") to automatically analyze public opinion from over 30 major social media platforms and millions of comments. It uses AI agents working together to monitor, search, analyze text and videos, and generate detailed reports based on real-time data. The system supports easy setup, custom models, and integration with your own databases, helping you understand public sentiment, trends, and make better decisions. It offers continuous monitoring, deep multi-angle analysis, and flexible report generation, all accessible by simply asking questions like chatting. This saves you time and gives clear insights into public opinion dynamics.
https://github.com/666ghj/BettaFish
You can use the "Weibo Public Opinion Analysis System" (called "微舆") to automatically analyze public opinion from over 30 major social media platforms and millions of comments. It uses AI agents working together to monitor, search, analyze text and videos, and generate detailed reports based on real-time data. The system supports easy setup, custom models, and integration with your own databases, helping you understand public sentiment, trends, and make better decisions. It offers continuous monitoring, deep multi-angle analysis, and flexible report generation, all accessible by simply asking questions like chatting. This saves you time and gives clear insights into public opinion dynamics.
https://github.com/666ghj/BettaFish
GitHub
GitHub - 666ghj/BettaFish: 微舆:人人可用的多Agent舆情分析助手,打破信息茧房,还原舆情原貌,预测未来走向,辅助决策!从0实现,不依赖任何框架。
微舆:人人可用的多Agent舆情分析助手,打破信息茧房,还原舆情原貌,预测未来走向,辅助决策!从0实现,不依赖任何框架。 - 666ghj/BettaFish
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#typescript #agent #agentic #agentic_ai #agents #agents_sdk #ai #ai_agents #aiagentframework #genai #genai_chatbot #llm #llms #multi_agent #multi_agent_systems #multi_agents #multi_agents_collaboration
Agent Development Kit (ADK) for TypeScript is an open-source toolkit to build, test, and deploy advanced AI agents with full control in code. Key features include rich tools like Google Search, custom functions, and multi-agent hierarchies for scalable apps, plus a dev UI for easy debugging. Install via
https://github.com/google/adk-js
Agent Development Kit (ADK) for TypeScript is an open-source toolkit to build, test, and deploy advanced AI agents with full control in code. Key features include rich tools like Google Search, custom functions, and multi-agent hierarchies for scalable apps, plus a dev UI for easy debugging. Install via
npm install @google/adk. You benefit by creating flexible, versioned AI agents that integrate tightly with Google Cloud, run anywhere from laptop to cloud, and speed up development like regular software.https://github.com/google/adk-js
GitHub
GitHub - google/adk-js: An open-source, code-first Typescript toolkit for building, evaluating, and deploying sophisticated AI…
An open-source, code-first Typescript toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control. - google/adk-js
#python #docker #fastapi #kbqa #kgqa #llms #neo4j #rag #vue
Yuxi-Know (语析) is a free, open-source platform built with LangGraph, Vue.js, FastAPI, and LightRAG to create smart agents using RAG knowledge bases and knowledge graphs. The latest v0.4.0-beta (Dec 2025) adds file uploads, multimodal image support, mind maps from files, evaluation tools, dark mode, and better graph visuals. It helps you quickly build and deploy custom AI agents for Q&A, analysis, and searches without starting from scratch, saving time and effort on development.
https://github.com/xerrors/Yuxi-Know
Yuxi-Know (语析) is a free, open-source platform built with LangGraph, Vue.js, FastAPI, and LightRAG to create smart agents using RAG knowledge bases and knowledge graphs. The latest v0.4.0-beta (Dec 2025) adds file uploads, multimodal image support, mind maps from files, evaluation tools, dark mode, and better graph visuals. It helps you quickly build and deploy custom AI agents for Q&A, analysis, and searches without starting from scratch, saving time and effort on development.
https://github.com/xerrors/Yuxi-Know
GitHub
GitHub - xerrors/Yuxi-Know: 结合LightRAG 知识库的知识图谱智能体平台。 An agent platform that integrates a LightRAG knowledge base and knowledge…
结合LightRAG 知识库的知识图谱智能体平台。 An agent platform that integrates a LightRAG knowledge base and knowledge graphs. Build with LangChain v1 + Vue + FastAPI, support DeepAgents、MinerU PDF、Neo4j 、MCP. - xerr...
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#python #large_language_models #llms #long_video_understanding #multi_modal_llms #rag #retrieval_augmented_generation
Vimo is a desktop app that lets me chat with any video, from short clips to hundreds of hours, in simple natural language. I can drag and drop videos, ask questions, find exact moments, compare multiple videos, and export useful insights, all on macOS, Windows, or Linux. Powering this is the VideoRAG algorithm, which deeply understands visual, audio, and contextual information, giving accurate answers even for very long videos. This helps me save time, understand complex content faster, and turn large video libraries into searchable, usable knowledge.
https://github.com/HKUDS/VideoRAG
Vimo is a desktop app that lets me chat with any video, from short clips to hundreds of hours, in simple natural language. I can drag and drop videos, ask questions, find exact moments, compare multiple videos, and export useful insights, all on macOS, Windows, or Linux. Powering this is the VideoRAG algorithm, which deeply understands visual, audio, and contextual information, giving accurate answers even for very long videos. This helps me save time, understand complex content faster, and turn large video libraries into searchable, usable knowledge.
https://github.com/HKUDS/VideoRAG
GitHub
GitHub - HKUDS/VideoRAG: [KDD'2026] "VideoRAG: Chat with Your Videos"
[KDD'2026] "VideoRAG: Chat with Your Videos". Contribute to HKUDS/VideoRAG development by creating an account on GitHub.
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#javascript #agent #agentic #agentic_ai #ai #ai_agents #automation #cursor #design #figma #generative_ai #llm #llms #mcp #model_context_protocol
Cursor Talk to Figma MCP lets Cursor AI read and edit your Figma designs directly, using tools like `get_selection` for info, `set_text_content` for bulk text changes, `create_rectangle` for shapes, and `set_instance_overrides` for components. Setup is quick: install Bun, run `bun setup` and `bun socket`, add the Figma plugin. This saves you hours by skipping context switches, automating repetitive tasks like text replacement or override propagation, speeding up design-to-code workflows, and keeping everything in sync for faster, precise builds.
https://github.com/grab/cursor-talk-to-figma-mcp
Cursor Talk to Figma MCP lets Cursor AI read and edit your Figma designs directly, using tools like `get_selection` for info, `set_text_content` for bulk text changes, `create_rectangle` for shapes, and `set_instance_overrides` for components. Setup is quick: install Bun, run `bun setup` and `bun socket`, add the Figma plugin. This saves you hours by skipping context switches, automating repetitive tasks like text replacement or override propagation, speeding up design-to-code workflows, and keeping everything in sync for faster, precise builds.
https://github.com/grab/cursor-talk-to-figma-mcp
GitHub
GitHub - grab/cursor-talk-to-figma-mcp: TalkToFigma: MCP integration between Cursor and Figma, allowing Cursor Agentic AI to communicate…
TalkToFigma: MCP integration between Cursor and Figma, allowing Cursor Agentic AI to communicate with Figma for reading designs and modifying them programmatically. - grab/cursor-talk-to-figma-mcp