feat: solution for 'Untitled Task'

README.md

@@ -1,34 +1 @@
-# LangGraph Streaming Agent
-
-This project demonstrates how to use LangGraph's streaming capabilities to display LLM responses token by token in real time.
-
-## Prerequisites
-
-- Python 3.10+
-- An OpenAI API key. Set it in a `.env` file or export `OPENAI_API_KEY`.
-
-## Installation
-
-bash
-git clone <repo-url>
-cd <repo-dir>
-python -m venv .venv
-source .venv/bin/activate  # On Windows use `.venv\Scripts\activate`
-pip install -r requirements.txt
-
-
-## Usage
-
-bash
-python src/main.py
-
-
-You will be prompted to enter a question. The answer will stream to the console as it is generated.
-
-## How it works
-
-The script builds a simple LangGraph agent that uses the OpenAI LLM. It calls `agent.stream()` with `stream_mode=['messages', 'updates']` and iterates over the returned chunks, printing each token as it arrives.
-
-## License
-
-MIT
+# LangGraph Streaming Agent\n\nThis project demonstrates how to use LangGraph to stream responses from an AI agent in real-time. Instead of waiting for the entire answer, the agent outputs tokens as they are generated, providing a more interactive experience.\n\n## Prerequisites\n\n- Python 3.10 or higher\n- An OpenAI API key (set as `OPENAI_API_KEY` in your environment)\n\n## Installation\n\nbash\npip install -r requirements.txt\n\n\n## Running the Agent\n\nbash\npython src/main.py\n\n\nThe agent will ask a simple math question and stream the answer token by token. You will see a separator when the agent moves to a new step.\n\n## Customization\n\n- Modify the `messages` in `src/main.py` to ask different questions.\n- Add or replace tools in the `tools` list to extend the agent's capabilities.\n