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-# AI-Powered Web Application
-
-This project is an AI-powered web application that provides four main functionalities:
-
-1. **Document & Image Analysis**: Upload documents or images for AI-powered summarization and interpretation.
-2. **Intelligent Question Answering**: Ask questions about your documents and images to get AI-powered answers.
-3. **Data Visualization**: Generate visualizations from Excel data using natural language requests.
-4. **Document Translation**: Translate your documents to different languages using AI.
-
-## Project Structure
-
-The project consists of two main parts:
-
-1. **Frontend**: A vanilla JavaScript, HTML, and CSS application with a user-friendly interface for interacting with the AI functionalities.
-2. **Backend**: A Python FastAPI application that serves as a RESTful API for the AI services.
-
-## Technologies Used
-
-### Frontend
-- HTML5
-- CSS3
-- Vanilla JavaScript
-
-### Backend
-- Python
-- FastAPI
-- Hugging Face Transformers
-- Document parsing libraries (Tika, PyPDF2, python-docx, pandas)
-- Data visualization libraries (Matplotlib, Seaborn)
-
-## Getting Started
-
-### Prerequisites
-- Python 3.8 or higher
-- Docker (for deployment)
-
-### Running the Application
-
-```bash
-# Navigate to the backend directory
-cd backend
-
-# Create a virtual environment (optional but recommended)
-python -m venv venv
-source venv/bin/activate  # On Windows: venv\Scripts\activate
-
-# Install dependencies
-pip install -r requirements.txt
-
-# Start the FastAPI server
-uvicorn main:app --reload
-```
-
-### Running with Docker
-
-```bash
-# Build the Docker image
-docker build -t ai-web-app .
-
-# Run the container
-docker run -p 8000:8000 ai-web-app
-```
-
-## Deployment on Hugging Face Spaces
-
-This application can be deployed on Hugging Face Spaces using the Docker SDK. Follow these steps:
-
-1. Create a new Space on Hugging Face Spaces.
-2. Select Docker as the SDK.
-3. Upload the project files to the Space.
-4. The Space will automatically build and deploy the application.
-
-## API Documentation
-
-The API documentation is available at `/docs` when the backend server is running.
-
-## Project Report
-
-The project report should include the following sections:
-
-1. **Backend Architecture and API Design**: Detailed description of the FastAPI backend structure, API endpoint specifications, request/response handling, and API documentation.
-2. **Prompt Engineering and Optimization**: Detailed description of the prompt engineering process, including design, testing, and refinement of prompts for optimal performance.
-3. **Frontend Design and User Experience**: Analysis of the frontend design choices, UI/UX considerations, user workflows, and implementation of interactive elements.
-4. **Deployment and Scalability**: Discussion of Dockerization strategy, deployment process on Hugging Face Spaces, and considerations for web application scalability and performance.
-
-## License
-
-This project is licensed under the MIT License - see the LICENSE file for details.