Update README.md

README.md

@@ -1,83 +1,92 @@
-# 🌿 AI Plant Guide - English & Arabic
-
-## Overview
-
-AI Plant Guide is a user-friendly Gradio-based application that provides detailed plant information in both English and Arabic. By entering a plant name and selecting a language, users can access insights on scientific names, growing conditions, common uses, and care tips.
-
-## Project Objectives
-- Provide an AI-powered plant guide with bilingual support.
-- Ensure user-friendly interaction through a web-based interface.
-- Leverage state-of-the-art NLP models for accurate and informative responses.
-- Offer quick and efficient responses using GPU acceleration.
-
-## Implemented Pipelines
-1. **User Input Handling**: 
-   - The user enters a plant name and selects a language.
-2. **Model Selection**:
-   - Based on the chosen language, the appropriate transformer model is loaded:
-     - **Microsoft Phi-3-mini-4k-instruct** for English
-     - **ALLaM-7B-Instruct-preview** for Arabic
-3. **Text Generation Pipeline**:
-   - The selected model generates plant details, including:
-     - Scientific name
-     - Growing conditions
-     - Common uses
-     - Care tips
-4. **Output Display**:
-   - The generated information is displayed in a user-friendly interface.
-
-## Instructions for Using the Interface
-1. Open the **Gradio UI** in your browser.
-2. Select a language (**English/Arabic**).
-3. Enter a plant name (e.g., **Lavender**, **Aloe Vera**).
-4. Click **"🔍 Get Plant Info"** to generate information.
-5. View the plant details in the output box.
-
-## Justification for Model and Pipeline Choices
-- **Hugging Face Transformers**: Offers pre-trained state-of-the-art language models optimized for text generation.
-- **Gradio**: Provides an easy-to-use web interface without the need for extensive frontend development.
-- **PyTorch**: Ensures efficient model inference and flexibility for future enhancements.
-- **GPU Acceleration**: Speeds up response times, improving user experience.
-- **Pipeline-Based Design**: Ensures modularity and scalability for future improvements.
-
-## Bilingual Implementation
-- The project supports **English and Arabic** via two specialized transformer models.
-- The UI allows users to choose their preferred language.
-- The prompt structure is adapted for each language to ensure high-quality responses.
-
-## Technologies Used
-- **Gradio** for UI development
-- **Transformers (Hugging Face)** for text generation
-- **PyTorch** for model inference
-- **Microsoft Phi-3-mini-4k-instruct** (English) and **ALLaM-7B-Instruct-preview** (Arabic) models
-- **Spaces GPU Acceleration**
-
-## Installation
-
-### Prerequisites
-Ensure you have Python installed (>=3.8) and required dependencies.
-
-### Steps
-
-1. **Clone the repository**:
-   ```bash
-   git clone https://huggingface.co/spaces/NoufSaleh46/PlantInfo1
-   cd PlantInfo1
-   ```
-2. **Create a virtual environment (optional but recommended)**:
-   ```bash
-   python -m venv venv
-   source venv/bin/activate  # On Windows use `venv\Scripts\activate`
-   ```
-3. **Install dependencies**:
-   ```bash
-   pip install -r requirements.txt
-   ```
-4. **Run the application**:
-   ```bash
-   python app.py
-   ```
-
-## Deployment
-This project is deployed on **Hugging Face Spaces**. You can access it directly [here](https://huggingface.co/spaces/NoufSaleh46/PlantInfo1).
-
+# 🌿 AI Plant Guide - English & Arabic
+
+## Overview
+
+AI Plant Guide is a user-friendly Gradio-based application that provides detailed plant information in both English and Arabic. By entering a plant name and selecting a language, users can access insights on scientific names, growing conditions, common uses, and care tips.
+
+## Project Objectives
+- Provide an AI-powered plant guide with bilingual support.
+- Ensure user-friendly interaction through a web-based interface.
+- Leverage state-of-the-art NLP models for accurate and informative responses.
+- Offer quick and efficient responses using GPU acceleration.
+
+## Implemented Pipelines
+1. **User Input Handling**: 
+   - The user enters a plant name and selects a language.
+2. **Model Selection**:
+   - Based on the chosen language, the appropriate transformer model is loaded:
+     - **Microsoft Phi-3-mini-4k-instruct** for English
+     - **ALLaM-7B-Instruct-preview** for Arabic
+3. **Text Generation Pipeline**:
+   - The selected model generates plant details, including:
+     - Scientific name
+     - Growing conditions
+     - Common uses
+     - Care tips
+4. **Output Display**:
+   - The generated information is displayed in a user-friendly interface.
+
+## Instructions for Using the Interface
+1. Open the **Gradio UI** in your browser.
+2. Select a language (**English/Arabic**).
+3. Enter a plant name (e.g., **Lavender**, **Aloe Vera**).
+4. Click **"🔍 Get Plant Info"** to generate information.
+5. View the plant details in the output box.
+
+## Justification for Model and Pipeline Choices
+- **Hugging Face Transformers**: Offers pre-trained state-of-the-art language models optimized for text generation.
+- **Gradio**: Provides an easy-to-use web interface without the need for extensive frontend development.
+- **PyTorch**: Ensures efficient model inference and flexibility for future enhancements.
+- **GPU Acceleration**: Speeds up response times, improving user experience.
+- **Pipeline-Based Design**: Ensures modularity and scalability for future improvements.
+
+## Bilingual Implementation
+- The project supports **English and Arabic** via two specialized transformer models.
+- The UI allows users to choose their preferred language.
+- The prompt structure is adapted for each language to ensure high-quality responses.
+
+## Technologies Used
+- **Gradio** for UI development
+- **Transformers (Hugging Face)** for text generation
+- **PyTorch** for model inference
+- **Microsoft Phi-3-mini-4k-instruct** (English) and **ALLaM-7B-Instruct-preview** (Arabic) models
+- **Spaces GPU Acceleration**
+
+## Installation
+
+### Prerequisites
+Ensure you have Python installed (>=3.8) and required dependencies.
+
+### Steps
+
+1. **Clone the repository**:
+   ```bash
+   git clone https://huggingface.co/spaces/NoufSaleh46/PlantInfo1
+   cd PlantInfo1
+   ```
+2. **Create a virtual environment (optional but recommended)**:
+   ```bash
+   python -m venv venv
+   source venv/bin/activate  # On Windows use `venv\Scripts\activate`
+   ```
+3. **Install dependencies**:
+   ```bash
+   pip install -r requirements.txt
+   ```
+4. **Run the application**:
+   ```bash
+   python app.py
+   ```
+
+## Deployment
+This project is deployed on **Hugging Face Spaces**. You can access it directly [here](https://huggingface.co/spaces/NoufSaleh46/PlantInfo1).
+
+title: PlantInfo
+emoji: 🦀
+colorFrom: green
+colorTo: blue
+sdk: gradio
+sdk_version: 5.17.1
+app_file: app.py
+pinned: false
+license: apache-2.0