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README.md

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+# LangGraph Reflection Demo
+
+This project demonstrates a simple LangGraph that generates an answer to a question, reflects on it, and rewrites it if necessary. The graph loops until the answer is deemed satisfactory or a maximum number of rounds is reached.
+
+## Features
+
+- **Draft generation** – 5–10 sentence answer to a user question.
+- **Reflection** – LLM critiques the draft and decides if it is acceptable.
+- **Rewrite** – If the draft needs improvement, the LLM rewrites it based on the critique.
+- **Loop control** – The process repeats until the answer is good enough or the maximum number of rounds is exceeded.
+- **CLI** – Run the graph from the command line.
+
+## Installation
+
+```bash
+# Clone the repository
+git clone https://github.com/yourusername/langgraph-reflection-demo.git
+cd langgraph-reflection-demo
+
+# Create a virtual environment (optional but recommended)
+python -m venv venv
+source venv/bin/activate  # On Windows use `venv\Scripts\activate`
+
+# Install dependencies
+pip install -r requirements.txt
+
+# Set your OpenAI API key
+export OPENAI_API_KEY="your-openai-key"
+```
+
+> **Note**: If you prefer to use Ollama instead of OpenAI, replace `langchain-openai` with `langchain-ollama` in `requirements.txt` and adjust the LLM import in `nodes.py`.
+
+## Usage
+
+```bash
+python main.py "Explain the theory of relativity in simple terms."
+```
+
+Optional arguments:
+
+- `--max-rounds N` – Maximum number of rewrite attempts (default: 2).
+- `--model MODEL` – LLM model name (default: `gpt-3.5-turbo`).
+
+Example:
+
+```bash
+python main.py "What is quantum computing?" --max-rounds 3 --model gpt-4
+```
+
+The script will print:
+
+```
+Initial draft:
+...
+
+Reflection verdict: needs_revision
+Critique:
+...
+
+Rewritten draft:
+...
+
+Final answer:
+...
+```
+
+## Testing
+
+Run the unit tests with:
+
+```bash
+pytest
+```
+
+The tests require a valid OpenAI API key set in the environment.
+
+## License
+
+MIT License