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LangGraph Reflection Demo

This project demonstrates a simple LangGraph agent that:

  1. Generates a short answer (510 sentences) to a usersupplied question.
  2. Critiques the answer for completeness, concreteness, and fluff.
  3. If the critique indicates needs_revision, rewrites the answer up to a maximum number of rounds.

Features

  • Separate nodes for drafting, reflecting, and rewriting.
  • LLMbased critic that returns a verdict (ok or needs_revision) and 23 critique points.
  • Controlled loop: rewrites only if the verdict is needs_revision and the round count is below max_rounds.
  • CLI interface: pass a question via -q or input interactively.
  • Configurable maximum rounds via -m (default 2).

Requirements

  • Python 3.10+
  • langgraph
  • langchain-openai

Install dependencies:

pip install -r requirements.txt

Usage

  1. Set your OpenAI API key:
export OPENAI_API_KEY="your_api_key_here"
  1. Run the demo:
python src/main.py -q "Explain the difference between a tool and a resource in MCP."

Or simply:

python src/main.py

and enter the question when prompted.

The script will output the final answer, the number of rounds performed, the verdict, and the critique points.

Project Structure

src/
├── main.py      # CLI entry point
├── graph.py     # LangGraph definition
└── nodes.py     # Node implementations
requirements.txt
README.md

License

MIT License