Update README.md

README.md

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----
-title: Multi-Modal AI Demo
-emoji: 🤖
-colorFrom: blue
-colorTo: purple
-sdk: gradio
-sdk_version: 3.50.2
-app_file: app.py
-pinned: false
----
-
-# Multi-Modal AI Demo
-
-This project demonstrates the use of multi-modal AI capabilities using Hugging Face pretrained models. The application provides the following features:
-
-1. **Image Captioning**: Generate descriptive captions for images
-2. **Visual Question Answering**: Answer questions about the content of images
-3. **Sentiment Analysis**: Analyze the sentiment of text inputs
-
-## Requirements
-
-- Python 3.8+
-- Dependencies listed in `requirements.txt`
-
-## Installation
-
-1. Clone this repository
-2. Install dependencies and setup the application:
-   ```
-   python run.py
-   ```
-   Then select option 5 to perform full setup (install requirements, fix dependencies, and download sample images)
-
-## Known Issues and Solutions
-
-If you encounter errors related to package compatibility (Pydantic, FastAPI, or Gradio errors), use:
-```
-python fix_dependencies.py
-```
-This will install compatible versions of all dependencies to ensure the application runs correctly.
-
-## Usage
-
-Run the web interface:
-```
-python app.py
-```
-
-Then open your browser and navigate to the URL shown in the terminal (typically http://127.0.0.1:7860).
-
-
-## Models Used
-
-This demo uses the following pretrained models from Hugging Face:
-- Image Captioning: `nlpconnect/vit-gpt2-image-captioning`
-- Visual Question Answering: `nlpconnect/vit-gpt2-image-captioning` (simplified)
-- Sentiment Analysis: `distilbert-base-uncased-finetuned-sst-2-english`
-
+---
+title: Multi-Modal AI Demo
+emoji: 🤖
+colorFrom: blue
+colorTo: purple
+sdk: gradio
+sdk_version: 4.19.2
+app_file: app.py
+pinned: false
+---
+
+# Multi-Modal AI Demo
+
+This project demonstrates the use of multi-modal AI capabilities using Hugging Face pretrained models. The application provides the following features:
+
+1. **Image Captioning**: Generate descriptive captions for images
+2. **Visual Question Answering**: Answer questions about the content of images
+3. **Sentiment Analysis**: Analyze the sentiment of text inputs
+
+## Requirements
+
+- Python 3.8+
+- Dependencies listed in `requirements.txt`
+
+## Local Installation
+
+To run this project locally:
+
+1. Clone this repository
+2. Install dependencies:
+   ```
+   pip install -r requirements.txt
+   ```
+3. Run the application:
+   ```
+   python app.py
+   ```
+
+Then open your browser and navigate to the URL shown in the terminal (typically http://127.0.0.1:7860).
+
+## Deploying to Hugging Face Spaces
+
+This project is configured for direct deployment to Hugging Face Spaces. The core files needed for deployment are:
+
+- `app.py` - Main application file
+- `model_utils.py` - Utility functions for model operations
+- `requirements.txt` - Project dependencies
+- `README.md` - This documentation file with Spaces configuration
+
+## Models Used
+
+This demo uses the following pretrained models from Hugging Face:
+- Image Captioning: `nlpconnect/vit-gpt2-image-captioning`
+- Visual Question Answering: `nlpconnect/vit-gpt2-image-captioning` (simplified)
+- Sentiment Analysis: `distilbert-base-uncased-finetuned-sst-2-english`
+