LLM-Explore

测试各种 LLM 模型的集合之地，探索各种工程化的可能性。

Project Start

Use uv for package management

推荐创建虚拟环境 venv

uv venv --python 3.12

安装包 package install: uv sync

TODO List

• agno agent framework usage
  • Agent Class - agent->agno-usage->concept->agent->agent.ipynb
  • Five levels of agentic systems
    • Level 1: Agents with tools and instructions - agent->agno-usage->five-level->1_tools_instructions.ipynb
      • Writing your own tools
        • Stock agent
      • Exceptions
      • Hooks
      • Human in the loop
      • Tool kits
      • MCP
      • Writing your own toolkit
      • Selecting tools
      • Async tools
      • Tool Result Caching
    • Level 2: Agents with knowledge and storage
    • Level 3: Agents with memory and reasoning
    • Level 4: Teams of Agents with collaboration and coordination
    • Level 5: Multi-Agent Workflows with state and determinism
• web search agent use Tavily API
• deer flow deep researcher
• gpt deep researcher
• agno python agent framework
• sequential thinking GitHub repository
• skyWork mock agentic seek deep researcher
• langGraph multi agent system
• chainlit cook book
• csv\pandas\sql agent
• langchain usage
• claude prompt
• chainlit weather agent, auto inject function description, and use light llm correct unstructured output format
• instructor prompt engineering
• MCP client
• MCP server

Reflection

• Langchain 这样的框架可以用来提供快速化产品构建，整合资源是产品快速构建的第一手段
• 对于构建 Agent ，先从 prompt 开始，从 jupyter notebook 开始，逐步完善，最后整合到 .py 文件，再到 UI 界面
• 对话式的 UI 都可以优先使用 chainlit，然后是 streamlit，再然后是 taipy，最后是其他的 UI 框架