Update README.md

README.md

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 short_description: Medical Image
 ---
+# MedSketch AI – Advanced Clinical Diagram Generator 🖼️
 
+**MedSketch AI** is a web application built with Streamlit that leverages cutting-edge AI models (like OpenAI's DALL-E 3 via the GPT-4o API endpoint access) to generate medical diagrams and illustrations from text prompts. It allows users to specify styles, associate metadata, perform batch generation, annotate the results, and export annotations.
+
+[![Streamlit App](https://static.streamlit.io/badges/streamlit_badge_black_white.svg)](https://your-deployed-app-url.com) <!-- Replace with your deployment URL -->
+<!-- Add other badges if applicable (e.g., license, build status) -->
+
+[Insert Screenshot/GIF of the App Here - Highly Recommended!]
+*A visual demonstration of MedSketch AI in action.*
+
+---
+
+## ✨ Features
+
+*   **AI-Powered Generation:** Create medical diagrams using models like OpenAI's DALL-E 3 (accessed via API). (Placeholder for Stable Diffusion LoRA integration).
+*   **Style Presets & Customization:** Apply predefined styles (Anatomical, H&E, IHC) or define custom styles. Control stylization strength.
+*   **Batch Processing:** Generate multiple diagrams simultaneously by entering one prompt per line.
+*   **Metadata Association:** Tag generated images with optional Patient ID, Region of Interest (ROI), and UMLS/SNOMED CT codes.
+*   **Interactive Annotation:** Draw annotations (freehand) directly onto the generated images using `streamlit-drawable-canvas`.
+*   **Session History:** Keep track of generated images and their associated metadata within the current session.
+*   **Annotation Export:** Download all annotations made during the session as a structured JSON file, including associated metadata and generation details.
+*   **Robust Error Handling:** Provides informative feedback on API errors or other issues.
+*   **Configurable:** Easy setup using Streamlit Secrets or environment variables for API keys.
+*   **Clear History:** Option to clear the session history and annotations.
+
+##  Prerequisites
+
+*   **Python:** Version 3.8 or higher recommended.
+*   **pip:** Python package installer.
+*   **Git:** For cloning the repository.
+*   **OpenAI API Key:** You need an API key from OpenAI to use the DALL-E 3 / GPT-4o generation features.
+
+## 🚀 Installation & Setup
+
+1.  **Clone the Repository:**
+    ```bash
+    git clone https://github.com/your-username/medsketch-ai.git # Replace with your repo URL
+    cd medsketch-ai
+    ```
+
+2.  **Create `requirements.txt`:**
+    Create a file named `requirements.txt` in the project root with the following content:
+    ```txt
+    streamlit
+    openai
+    streamlit-drawable-canvas
+    Pillow
+    requests
+    ```
+
+3.  **Install Dependencies:**
+    ```bash
+    pip install -r requirements.txt
+    ```
+
+4.  **Configure OpenAI API Key:**
+    You **must** provide your OpenAI API key. There are two primary methods:
+
+    *   **a) Streamlit Secrets (Recommended for Deployment):**
+        *   Create a directory named `.streamlit` in your project root if it doesn't exist.
+        *   Inside `.streamlit`, create a file named `secrets.toml`.
+        *   Add your API key to `secrets.toml`:
+          ```toml
+          # .streamlit/secrets.toml
+          OPENAI_API_KEY="sk-YourSecretOpenAI_ApiKeyGoesHere"
+          ```
+        *   **Important:** Ensure `.streamlit/secrets.toml` is added to your `.gitignore` file to prevent accidentally committing your secret key.
+
+    *   **b) Environment Variable (Good for Local Development):**
+        *   Set the `OPENAI_API_KEY` environment variable in your terminal session:
+          *   **Linux/macOS:**
+            ```bash
+            export OPENAI_API_KEY='sk-YourSecretOpenAI_ApiKeyGoesHere'
+            ```
+          *   **Windows (Command Prompt):**
+            ```bash
+            set OPENAI_API_KEY=sk-YourSecretOpenAI_ApiKeyGoesHere
+            ```
+          *   **Windows (PowerShell):**
+            ```bash
+            $env:OPENAI_API_KEY='sk-YourSecretOpenAI_ApiKeyGoesHere'
+            ```
+        *   The application will automatically look for this environment variable if the Streamlit secret is not found.
+
+## ▶️ Running the Application
+
+Once the dependencies are installed and the API key is configured, run the Streamlit app from your project's root directory:
+
+```bash
+streamlit run app.py
+Use code with caution.
+Markdown
+Your default web browser should automatically open to the application's URL (usually http://localhost:8501).
+📖 Usage Guide
+Configure Settings (Sidebar):
+Select Model: Choose between "GPT-4o (API)" (uses DALL-E 3) or the placeholder "Stable Diffusion LoRA".
+Select Preset Style: Choose a visual style like "Anatomical Diagram", "H&E Histology", etc., or select "Custom" and enter your own style description.
+Stylization Strength: Adjust the slider to control how strongly the style influences the output (this is conceptually passed in the prompt).
+(Optional) Metadata: Enter relevant Patient/Case ID, ROI, or UMLS/SNOMED codes. These will be associated with the generated images in the history and export.
+Enter Prompts (Main Area):
+In the text area, describe the medical diagram(s) you want to generate.
+For batch generation, enter one prompt per line.
+Generate:
+Click the "🚀 Generate Diagram(s)" button.
+View Results:
+Generated images will appear below the button, organized in columns.
+Each result includes the image, the prompt used, and a download button (⬇️ Download PNG).
+Annotate (Optional):
+Below each image, an annotation canvas (✏️ Annotate:) is provided.
+Use your mouse to draw directly on the image (default is freehand red lines).
+Annotations are automatically saved to the session state.
+Review History & Export Annotations (Bottom Section):
+The "📚 Session History & Annotations" section appears once generations are complete.
+It lists the prompts used, model/style settings, and associated metadata for each generated item.
+You can expand each item to view the raw JSON data of any annotations made.
+Click "⬇️ Export All Annotations (JSON)" to download a JSON file containing all annotations from the current session, enriched with metadata and generation details.
+Clear History (Sidebar):
+Use the "⚠️ Clear History & Annotations" button in the sidebar to reset the session.
+🛠️ Technology Stack
+Framework: Streamlit
+AI Generation: OpenAI API (DALL-E 3)
+Annotation: streamlit-drawable-canvas
+Image Handling: Pillow (PIL Fork)
+API Requests: requests (for image download if using URL format)
+Language: Python
+💡 Future Enhancements (Roadmap)
+Implement actual Stable Diffusion LoRA model integration.
+Support for additional AI image generation models.
+More advanced annotation tools (shapes, text, colors).
+Ability to load/edit existing annotations.
+Improved image storage/retrieval in session state (potentially using caching or temporary files).
+User accounts and persistent storage (beyond session).
+More sophisticated prompt engineering assistance.
+🙏 Contributing
+Contributions are welcome! If you have suggestions for improvements or find a bug, please feel free to:
+Open an issue to discuss the change or report the bug.
+Fork the repository, make your changes, and submit a pull request.
+Please ensure your code follows basic Python best practices and includes documentation where necessary.
+📜 License
+This project is licensed under the MIT License - see the LICENSE.txt file for details.
+(You should create a LICENSE.txt file in your repository containing the text of the MIT License or your chosen license).
+**To make this README complete:**
+
+1.  **Replace Placeholders:** Update `https://github.com/your-username/medsketch-ai.git` and `https://your-deployed-app-url.com` with your actual URLs.
+2.  **Add Screenshot/GIF:** Capture a compelling visual of your app and embed it where indicated. This significantly improves understanding.
+3.  **Create `LICENSE.txt`:** Add a file named `LICENSE.txt` to your repository containing the full text of the MIT license (or whichever license you choose). You can easily find standard license text online (e.g., choosealicense.com).
+4.  **Commit `requirements.txt`:** Make sure the `requirements.txt` file described is actually created and committed to your repository.
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference