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Source channel @githubtrending · Post #15536 · Mar 3

#python#agent#chatbot#large_language_models#llm#llm_agent#mcp#multi_agent#multi_modal#react_agent AgentScope is a simple, production-ready framework to build AI agents fast. Install with `pip install agentscope` (Python 3.10+), then create ReAct agents with tools, memory, voice, human steering, multi-agent workflows, and finetuning in 5 minutes. It supports realtime voice, A2A protocols, RL training, and easy deployment locally, in cloud, or Kubernetes. You benefit by quickly making robust, scalable agents for tasks like games, research, or chats without complex coding, saving time and enabling real-world apps. https://github.com/agentscope-ai/agentscope

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@githubtrending · Post #15523 · 02/25/2026, 12:30 PM

#typescript#agent#agentic#agentic_framework#agentic_workflow#ai#ai_agents#bytedance#deep_research#harness#langchain#langgraph#langmanus#llm#multi_agent#nodejs#podcast#python#superagent#typescript DeerFlow 2.0 is an open-source super agent harness that orchestrates multiple sub-agents, memory systems, and sandboxed execution environments to accomplish complex tasks. Built on LangGraph and LangChain, it combines research, coding, and content creation capabilities with extensible skills and tools. The platform features isolated Docker containers for safe execution, long-term memory that learns your preferences, and the ability to spawn sub-agents that work in parallel on different task angles. You benefit from dramatically reduced research and automation time—tasks that typically take hours complete in minutes—while maintaining full transparency and control over agent decisions through human-in-the-loop collaboration. Whether you need deep research reports, data analysis, slide decks, or custom workflows, DeerFlow handles multi-step complexity without requiring extensive coding knowledge. https://github.com/bytedance/deer-flow