Implement Summary Agents skeletton

[HelloThisIsFlo]

Note

Introduce a LangGraph-based agent that generates emotional and (placeholder) technical summaries from a conversation, with I/O helpers and prompt scaffolding, and register it in langgraph.json.

• Agents:
  • Walk and Learn Summary: Add src/agents/walkandlearn_summary/graph.py implementing a LangGraph with nodes load_conversation, emotional_summary, technical_summary (placeholder), and write_output; uses gpt-4o-mini and writes a formatted markdown summary.
  • Prompts: Add src/agents/walkandlearn_summary/prompts.py with placeholder system prompts for emotional and technical summaries.
  • I/O Utilities: Add src/agents/walkandlearn_summary/io.py for reading input, writing output, and formatting the combined summary.
• Config:
  • Register new graph in langgraph.json under "Walk and Learn Summary".
• Packaging:
  • Add __init__.py files to src/ and src/agents/, and re-export graph in src/agents/walkandlearn_summary/__init__.py.

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