feat: solution for 'Повторный экзамен: Граф с рефлексией и доработкой'

README.md

@@ -1,15 +1,80 @@
-# Самокорректирующийся агент
+# Graph Reflection and Refinement Demo
 
-This repository contains a simple implementation of a self‑correcting agent using LangChain.  
-The project requires the following Python packages:
+This repository demonstrates how to integrate **LangChain LLMs** (OpenAI or Ollama) into a simple Python script that explains graph theory concepts. The project is intentionally minimal to focus on the LLM integration.
 
-- `langchain-core` – core LangChain functionality.
-- `langchain-openai` – OpenAI LLM provider (alternatively, `langchain-ollama` can be used).
+## Features
 
-Install the dependencies with:
+- **OpenAI LLM** support via `langchain-openai`.
+- **Ollama LLM** support via `langchain-ollama`.
+- Environment variable configuration using `.env` or system variables.
+- Simple prompt chain that explains graph reflection and refinement.
+
+## Setup
+
+1. **Clone the repository**
+
+   ```bash
+   git clone https://git.brojs.ru/kuzakhmetovartur/povtornyy-ekzamen-graf-s-refleksiey-i-do
+   cd povtornyy-ekzamen-graf-s-refleksiey-i-do
+   ```
+
+2. **Create a virtual environment (recommended)**
+
+   ```bash
+   python3 -m venv .venv
+   source .venv/bin/activate
+   ```
+
+3. **Install dependencies**
+
+   ```bash
+   pip install -r requirements.txt
+   ```
+
+4. **Configure environment variables**
+
+   Create a `.env` file in the project root (or set system variables) with one of the following:
+
+   ```dotenv
+   # For OpenAI
+   OPENAI_API_KEY=your_openai_api_key
+   OPENAI_MODEL=gpt-3.5-turbo
+   OPENAI_TEMPERATURE=0.7
+
+   # OR for Ollama
+   OLLAMA_HOST=http://localhost:11434
+   OLLAMA_MODEL=llama2
+   OLLAMA_TEMPERATURE=0.7
+   ```
+
+   Only one of the two configurations is required.
+
+## Usage
+
+Run the script:
 
 ```bash
-pip install -r requirements.txt
+python src/main.py
 ```
 
-Feel free to extend the agent with additional tools or prompts as needed.
+You should see an LLM-generated explanation of graph reflection and refinement printed to the console.
+
+## Project Structure
+
+```
+povtornyy-ekzamen-graf-s-refleksiey-i-do/
+├── src/
+│   └── main.py          # Core script with LangChain integration
+├── requirements.txt     # All required Python packages
+└── README.md            # Project documentation
+```
+
+## Notes
+
+- The script automatically selects the LLM based on the presence of environment variables.
+- If neither `OPENAI_API_KEY` nor `OLLAMA_HOST` is set, the script will raise an error.
+- Feel free to extend the prompt or chain logic to suit more complex use cases.
+
+--- 
+
+Happy coding!