updated README

README.md

@@ -9,6 +9,108 @@ app_file: app.py
 pinned: false
 license: mit
 short_description: A multi-agent application that converts images into drawio
+tag: agent-demo-track,mcp-server-track
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+# Image to Draw.io Converter
+
+A multi-agent application that converts images into editable [Draw.io](https://app.diagrams.net/) diagrams using advanced LLM-based object detection and diagram generation. The system is built with [LangGraph](https://github.com/langchain-ai/langgraph) and features a modern [Gradio](https://gradio.app/) web interface, which is also exposed as an MCP server for integration with external clients.
+
+---
+
+## Features
+
+- **Multi-Agent Pipeline (LangGraph):**
+  - **Supervisor Agent:** Orchestrates the workflow and coordinates the agents.
+  - **Object Detection Agent (React):** Uses an LLM to detect and extract objects from the uploaded image.
+  - **Draw.io Generator Agent (React):** Converts detected objects into Draw.io XML diagrams.
+
+- **Automated Workflow:**
+  1. Upload an image via the Gradio interface.
+  2. The object detection agent identifies and extracts key objects.
+  3. The diagram generator agent creates a Draw.io XML diagram.
+  4. Download the `.drawio` file or preview the SVG directly in the browser.
+
+- **Modern Gradio UI:**
+  - Simple drag-and-drop image upload.
+  - Real-time status updates and diagram preview.
+  - Downloadable Draw.io file and copyable XML.
+  - SVG preview of the generated diagram.
+  - Exposed as an MCP server for programmatic access.
+
+---
+
+## Requirements
+
+- Python 3.10+
+- Install dependencies:
+  ```sh
+  pip install -r requirements.txt
+  ```
+- API keys for your LLM provider (e.g., Google Gemini).
+- Configure your `.env` file:
+  ```
+  GEMINI_API_KEY=your_gemini_api_key
+  GEMINI_MODEL_NAME=gemini-2.5-pro-preview-06-05
+  GEMINI_THINKING_BUDGET=128
+  ```
+
+---
+
+## Usage
+
+1. **Install dependencies:**
+   ```sh
+   pip install -r requirements.txt
+   ```
+
+2. **Configure environment:**
+   - Create a `.env` file in the project root with your API keys and model settings.
+
+3. **Start the application:**
+   ```sh
+   python app.py
+   ```
+
+4. **Access the web interface:**
+   - Open the provided local URL in your browser.
+   - Upload an image (diagram, sketch, chart, etc.).
+   - Click "Generate Diagram".
+   - Download the `.drawio` file or copy the XML.
+   - Open the file in [diagrams.net](https://app.diagrams.net/) for further editing.
+
+---
+
+## MCP Server Integration
+
+The Gradio app is also exposed as an MCP server (`mcp_server=True`), allowing integration with any MCP-compatible client or workflow. This enables automated or remote usage in larger pipelines.
+
+---
+
+## Project Structure
+
+- `app.py` — Main entry point, Gradio UI, and workflow orchestration.
+- `nodes/` — Agent and LangGraph node definitions.
+- `tools/` — LLM tools for object detection and Draw.io generation.
+- `output_llm/` — Generated Draw.io files, SVG previews, and logs.
+- `files/` — Uploaded user images.
+
+---
+
+## Notes
+
+- The LLM model and thinking budget are fully configurable via `.env` for maximum flexibility.
+- The application is designed for easy extension with new agents or tools.
+- Performances can vary a lot based on the LLM: in my experience, Gemini 2.5 pro performed much better than Gemini 2.5 flash.
+
+---
+
+## License
+
+MIT License
+
+---
+
+**Author:** Giustino Esposito