Update tooltip implementation and add TooltipContent and TooltipTrigger components

- Added fallback model configuration in config.ini
- Updated requirements.txt to include rich for enhanced logging
- Refactored script.py to implement rich logging for better visibility
- Modified functions to include channel link extraction and updated CSV saving logic
- Improved error handling and user feedback throughout the script

.gitignore

@@ -0,0 +1,28 @@
+venv
+temp_thumbnail.png
+video_classifications.csv
+
+# build output
+dist/
+# generated types
+.astro/
+
+# dependencies
+node_modules/
+
+# logs
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+pnpm-debug.log*
+
+
+# environment variables
+.env
+.env.production
+
+# macOS-specific files
+.DS_Store
+
+# jetbrains setting folder
+.idea/

.vscode/extensions.json

@@ -0,0 +1,5 @@
+{
+  "recommendations": [
+    "astro-build.astro-vscode"
+  ]
+}

README.md

@@ -1,185 +1,214 @@
-# AutoDelete YouTube Videos 🗑️🎬
+# YouTube Video Classifier
 
-This script automates the process of deleting videos from your YouTube "Watch Later" playlist using PyAutoGUI.
+An AI-powered tool that automatically classifies YouTube videos in your "Watch Later" playlist based on their titles and thumbnails using vision-language models through Ollama.
 
----
+## Features ✨
 
-## Requirements 📦
+- 🤖 **AI-Powered Classification**: Uses Ollama with Qwen2.5-VL and fallback models to analyze video titles and thumbnails
+- 🔄 **Robust LLM Integration**: Automatic fallback between models with increasing timeouts for reliability
+- 📊 **Comprehensive CSV Storage**: Saves detailed video information including classifications, metadata, and thumbnails
+- 🌐 **Multi-language Detection**: Automatically detects video language using AI
+- 🏷️ **Smart Tagging**: Generates detailed sub-tags for better content organization
+- 🎯 **Smart Categories**: Uses existing classifications or creates new ones automatically
+- 🖥️ **Browser Automation**: Selenium-based interaction with YouTube for reliable data extraction
+- 🎨 **Beautiful Logging**: Rich console output with colors and emojis for better UX
+- ⌨️ **Easy Control**: Press 'q' at any time to safely quit the process
 
-- Python **3.11.10** 🐍
+## Quick Start
 
----
+### Prerequisites
+- Python 3.11.10+
+- Ollama installed locally
+- Chrome or Chromium browser
 
-## Setup & Usage (English) 🇬🇧
+### Setup
 
-### ⚙️ Requirements
+1. **Install Ollama**: Download from [https://ollama.ai](https://ollama.ai)
 
-- Python **3.11.10** 🐍
+2. **Pull Required Models**:
-
-### 1️⃣ Create a Virtual Environment
-
-**With `venv`:**
    ```bash
-python3.11 -m venv venv
+   ollama pull qwen2.5vl:7b
+   ollama pull gemma2:2b
    ```
 
-**With `virtualenv`:**
+3. **Start Ollama Service**:
    ```bash
-python3.11 -m pip install virtualenv
+   ollama serve
-python3.11 -m virtualenv venv
    ```
 
-### 2️⃣ Activate the Virtual Environment
+4. **Clone and Setup Project**:
-
-**On Linux/macOS:**
    ```bash
-source venv/bin/activate
+   git clone <repository-url>
-```
+   cd youtube-video-classifier
-**On Windows:**
-```bash
-venv\Scripts\activate
-```
    
-### 3️⃣ Install Dependencies
+   # Create virtual environment
+   python -m venv venv
+   source venv/bin/activate  # On Windows: venv\Scripts\activate
    
-```bash
+   # Install dependencies
    pip install -r requirements.txt
    ```
 
-### 4️⃣ Run the Script 🚀
+5. **Configure Settings** (optional):
+   Edit `config.ini` to customize your setup
 
+6. **Run the Classifier**:
    ```bash
    python script.py
    ```
 
----
+## How It Works 🔄
 
-## Features & Customization 🛠️
+1. **Browser Initialization**: Opens Chrome/Chromium and navigates to your YouTube "Watch Later" playlist
+2. **Video Detection**: Finds and extracts information from playlist videos using Selenium
+3. **Data Extraction**: Captures video title, thumbnail, channel info, duration, and upload date
+4. **AI Analysis**: Uses Ollama models to:
+   - Classify the video into categories
+   - Detect the primary language
+   - Generate detailed sub-tags
+5. **Smart Fallback**: If primary model fails/times out, automatically switches to fallback model
+6. **Data Storage**: Saves all information to CSV with base64-encoded thumbnails
+7. **Playlist Management**: Removes processed videos from "Watch Later" playlist
+8. **Continuous Processing**: Continues until all videos are processed or user quits
 
-### Features
+## Configuration
 
-- 🖼️ **Image Recognition:**  
+The `config.ini` file allows you to customize various settings:
-  Uses screenshots in the `img` folder to locate and interact with UI elements (browser icon, YouTube buttons, etc).
 
-- 🔍 **Region-based Search:**  
+```ini
-  The script splits the screen into left and right halves to speed up image searches.
+[DEFAULT]
+# Ollama settings
+ollama_host = http://localhost:11434
+ollama_model = qwen2.5vl:7b
+ollama_fallback_model = gemma2:2b
 
-- 🗂️ **Automatic Tab Handling:**  
+# File paths
-  Automatically opens/closes tabs and navigates to your "Watch Later" playlist.
+classifications_csv = video_classifications.csv
+playlist_url = https://www.youtube.com/playlist?list=WL
 
-- ⏱️ **Timing Controls:**  
+# LLM timeout settings (in seconds)
-  You can adjust `sleep` and `duration` values in the code to match your PC's speed.
+llm_primary_timeout = 60
+llm_fallback_timeout = 60
 
-- 🛑 **Hotkey Listener:**  
+# Processing settings
-  Press `q` at any time to safely stop the script.
+enable_delete = false
+enable_playlist_creation = false
+```
 
-- 🖱️ **Easy Customization:**  
+## CSV Output Format 📋
-  Change the images in the `img` folder or tweak the logic in functions like `locate_img` and `change_to_not_available` to adapt to UI changes or other platforms.
 
-### Customization
+The script creates a comprehensive CSV file with the following columns:
 
-- 🖼️ **Browser Image:**  
+- `video_title`: Title of the video
-  Replace the browser icon image in the `img` folder with a screenshot of your browser's icon. Make sure the filename matches the value of the `browser_img` variable in `script.py` (e.g., `brave.png` for Brave browser).
+- `video_url`: YouTube URL of the video
+- `thumbnail_url`: Path to the saved thumbnail
+- `classification`: AI-generated category
+- `language`: Detected language of the video
+- `channel_name`: Name of the YouTube channel
+- `channel_link`: URL to the channel
+- `video_length_seconds`: Duration in seconds
+- `video_date`: Upload date
+- `detailed_subtags`: AI-generated specific tags
+- `playlist_name`: Source playlist name
+- `playlist_link`: Source playlist URL
+- `image_data`: Base64-encoded thumbnail data
+- `timestamp`: When the classification was made
 
-- 🔗 **Playlist URL:**  
+## File Structure 📁
-  You can change the playlist URL by editing the value of the `playlist_url` variable at the top of the `script.py` file.
 
-- ⏱️ **Adjust Timing:**  
+```
-  The script uses `sleep` and `duration` values to wait for your PC to respond. You may need to increase or decrease these values depending on your computer's speed and internet connection.
+├── script.py                 # Main classification script
+├── config.ini               # Configuration settings
+├── requirements.txt         # Python dependencies
+├── video_classifications.csv # Generated results (created when first run)
+└── README.md               # This file
+```
 
-- 📌 **Pin Your Browser:**  
+## Features in Detail
-  For the script to work, your browser must be pinned to your taskbar.
+
+### AI Classification System
+- **Primary Model**: Qwen2.5-VL 7B for high-quality vision-language analysis
+- **Fallback Model**: Gemma2 2B for faster processing when primary model is slow
+- **Timeout Management**: Automatically increases timeout periods if models are struggling
+- **Continuous Retry**: Keeps trying until successful or user cancels
+
+### Data Extraction
+- **Video Metadata**: Title, URL, duration, upload date
+- **Channel Information**: Name and link to channel
+- **Thumbnail Capture**: Screenshots saved as base64 in CSV
+- **Playlist Context**: Source playlist name and URL
+
+### Browser Automation
+- **Multiple Chrome Paths**: Automatically finds Chrome/Chromium installation
+- **WebDriver Management**: Handles chromedriver setup and fallbacks
+- **Robust Selectors**: Multiple CSS selectors for reliable element finding
+- **Error Recovery**: Graceful handling of UI changes and loading delays
+
+### User Experience
+- **Rich Console Output**: Colored logging with emojis and status indicators
+- **Progress Tracking**: Clear indication of current processing status
+- **Safe Exit**: Press 'q' at any time to cleanly stop processing
+- **Error Reporting**: Detailed error messages for troubleshooting
+
+## Testing Your Setup
+
+Before running the main script, you can test individual components:
+
+1. **Test Ollama Connection**:
+   ```python
+   import requests
+   response = requests.get('http://localhost:11434/api/tags')
+   print(response.json())
+   ```
+
+2. **Test Browser Automation**:
+   Run the script and check if Chrome opens correctly
+
+3. **Test Model Response**:
+   The script will verify model availability on startup
+
+## Troubleshooting 🔧
+
+### Common Issues
+
+**Ollama Connection Error**:
+- Ensure Ollama is running: `ollama serve`
+- Check the host URL in config.ini
+- Verify models are installed: `ollama list`
+
+**Browser Issues**:
+- Install Chrome or Chromium
+- Update chromedriver if needed
+- Check if browser is in PATH
+
+**Model Timeout**:
+- The script automatically handles timeouts with fallback
+- Consider increasing timeout values in config.ini
+- Ensure sufficient system resources
+
+**Selenium Errors**:
+- YouTube may have changed their HTML structure
+- Check for browser updates
+- Verify you're logged into YouTube
+
+### Performance Tips
+
+- **For faster processing**: Use smaller models like `gemma2:2b` as primary
+- **For better accuracy**: Use larger models like `qwen2.5vl:7b` as primary
+- **For stability**: Keep both models installed for automatic fallback
+- **For large playlists**: Consider running in smaller batches
+
+## Contributing
+
+1. Fork the repository
+2. Create a feature branch
+3. Test your changes thoroughly
+4. Submit a pull request
+
+## License
+
+MIT License - see LICENSE file for details
 
 ---
 
-# AutoDelete YouTube Videos 🗑️🎬
+**Note**: This tool is for personal use and educational purposes. Please respect YouTube's Terms of Service and rate limits.
-
-Este script automatiza el proceso de eliminar videos de tu lista de "Ver más tarde" en YouTube usando PyAutoGUI.
-
----
-
-## Requisitos 📦
-
-- Python **3.11.10** 🐍
-
----
-
-## Configuración y Uso (Español) 🇪🇸
-
-### ⚙️ Requisitos
-
-- Python **3.11.10** 🐍
-
-### 1️⃣ Crear un Entorno Virtual
-
-**Con `venv`:**
-```bash
-python3.11 -m venv venv
-```
-
-**Con `virtualenv`:**
-```bash
-python3.11 -m pip install virtualenv
-python3.11 -m virtualenv venv
-```
-
-### 2️⃣ Activar el Entorno Virtual
-
-**En Linux/macOS:**
-```bash
-source venv/bin/activate
-```
-**En Windows:**
-```bash
-venv\Scripts\activate
-```
-
-### 3️⃣ Instalar las Dependencias
-
-```bash
-pip install -r requirements.txt
-```
-
-### 4️⃣ Ejecutar el Script 🚀
-
-```bash
-python script.py
-```
-
----
-
-## Funcionalidades y Personalización 🛠️
-
-### Funcionalidades
-
-- 🖼️ **Reconocimiento de Imágenes:**  
-  Usa capturas en la carpeta `img` para localizar e interactuar con elementos de la interfaz (icono del navegador, botones de YouTube, etc).
-
-- 🔍 **Búsqueda por Regiones:**  
-  El script divide la pantalla en mitades izquierda y derecha para acelerar la búsqueda de imágenes.
-
-- 🗂️ **Manejo Automático de Pestañas:**  
-  Abre/cierra pestañas y navega automáticamente a tu lista de "Ver más tarde".
-
-- ⏱️ **Control de Tiempos:**  
-  Puedes ajustar los valores de `sleep` y `duration` en el código según la velocidad de tu PC.
-
-- 🛑 **Escucha de Teclas:**  
-  Presiona `q` en cualquier momento para detener el script de forma segura.
-
-- 🖱️ **Fácil Personalización:**  
-  Cambia las imágenes en la carpeta `img` o ajusta la lógica en funciones como `locate_img` y `change_to_not_available` para adaptarlo a cambios en la interfaz o a otras plataformas.
-
-### Personalización
-
-- 🖼️ **Imagen del Navegador:**  
-  Reemplaza la imagen del icono de tu navegador en la carpeta `img` con una captura de pantalla del icono de tu navegador. Asegúrate de que el nombre del archivo coincida con el valor de la variable `browser_img` en `script.py` (por ejemplo, `brave.png` para el navegador Brave).
-
-- 🔗 **URL de la Playlist:**  
-  Puedes cambiar la URL de la playlist que se usa modificando el valor de la variable `playlist_url` al inicio del archivo `script.py`.
-
-- ⏱️ **Ajusta los Tiempos:**  
-  El script utiliza valores de `sleep` y `duration` para esperar la respuesta de tu PC. Puede que necesites aumentar o disminuir estos valores dependiendo de la velocidad de tu computadora y conexión a internet.
-
-- 📌 **Ancla tu Navegador:**  
-  Para que el script funcione, es indispensable que tengas tu navegador anclado a tu barra de tareas.

config.ini

@@ -0,0 +1,30 @@
+# Configuration file for YouTube Video Classifier
+
+[DEFAULT]
+# Ollama settings
+ollama_host = http://localhost:11434
+ollama_model = qwen2.5vl:7b
+ollama_fallback_model = gemma2:2b
+
+# File paths
+classifications_csv = video_classifications.csv
+browser_image = brave.png
+
+# YouTube settings
+playlist_url = https://www.youtube.com/playlist?list=WL
+
+# Image recognition settings
+confidence_threshold = 0.8
+search_timeout = 0.5
+sleep_duration = 0.2
+
+# Processing settings
+restart_tab_frequency = 90
+enable_delete = false
+enable_playlist_creation = false
+
+# LLM timeout settings (in seconds)
+llm_primary_timeout = 60
+llm_fallback_timeout = 60
+
+

demo_classification.py

@@ -0,0 +1,140 @@
+#!/usr/bin/env python3
+"""
+Demo script showing how the video classification works
+"""
+
+import requests
+import base64
+import time
+import configparser
+config = configparser.ConfigParser()
+config.read('config.ini')
+
+ollama_host = config.get('DEFAULT', 'ollama_host', fallback='http://ollama:11434')
+
+def classify_demo_video(video_obj):
+    """Demonstrate video classification."""
+    try:
+        # If there's a thumbnail, convert image to base64
+        if video_obj.get('thumbnail'):
+            with open(video_obj['thumbnail'], "rb") as image_file:
+                print(image_file.read())
+                image_data = base64.b64encode(image_file.read()).decode('utf-8')
+                print(image_data)
+        else:
+            image_data = None
+
+        existing_classifications = ["Tech Reviews", "Cooking", "Gaming", "Music"]
+        
+        prompt = f"""
+        Please classify this YouTube video based on its title and thumbnail.
+        
+        Video Title: {video_obj['title']}
+        
+        Existing Classifications: {", ".join(existing_classifications)}
+        
+        Instructions:
+        1. If the video fits into one of the existing classifications, use that exact classification name.
+        2. If the video doesn't fit any existing classification, create a new appropriate classification name.
+        3. Classification names should be concise (1-3 words) and descriptive.
+        4. Examples of good classifications: "Tech Reviews", "Cooking", "Gaming", "Education", "Music", "Comedy", etc.
+        5. Respond with ONLY the classification name, nothing else.
+        """
+        
+        print(f"Classifying: '{video_obj['title']}'")
+        print(f"Using thumbnail: {video_obj.get('thumbnail', 'None')}")
+        print("Sending request to Ollama...")
+        
+        # Prepare the request payload
+        payload = {
+            'model': 'qwen2.5vl:7b',
+            'prompt': prompt,
+            'stream': False
+        }
+        
+        # Only include images if image_data is available
+        if image_data:
+            payload['images'] = [image_data]
+        
+        response = requests.post(
+            f'{ollama_host}/api/generate',
+            json=payload,
+            timeout=60
+        )
+        
+        if response.status_code == 200:
+            result = response.json()
+            classification = result['response'].strip().strip('"\'')
+            print(f"✅ Classification: '{classification}'")
+            return classification
+        else:
+            print(f"❌ Error: {response.status_code}")
+            return "Uncategorized"
+            
+    except Exception as e:
+        print(f"❌ Error: {e}")
+        return "Uncategorized"
+
+def run_demo():
+    """Run classification demo with sample videos."""
+    sample_videos = [
+        {
+            "title": "I can't believe this change!", 
+            "thumbnail": "img/iphone_thumbnail.png"
+        },
+        {
+            "title": "iPhone 15 Pro Review - Best Camera Phone?"
+        },
+        {
+            "title": "Easy Pasta Recipe for Beginners", 
+        },
+        {
+            "title": "Minecraft Survival Guide - Episode 1", 
+        },
+        {
+            "title": "Classical Piano Music for Studying", 
+        },
+        {
+            "title": "Machine Learning Explained Simply", 
+        },
+    ]
+    
+    print("YouTube Video Classification Demo")
+    print("=" * 40)
+    
+    results = []
+    
+    for i, video_obj in enumerate(sample_videos, 1):
+        print(f"\n--- Demo {i}/{len(sample_videos)} ---")
+        
+        # Classify the video
+        classification = classify_demo_video(video_obj)
+        results.append((video_obj['title'], classification))
+        
+        time.sleep(1)  # Be nice to the API
+    
+    print("\n" + "=" * 40)
+    print("DEMO RESULTS:")
+    print("=" * 40)
+    
+    for title, classification in results:
+        print(f"{classification:15} | {title}")
+    
+    print("\nDemo complete! The script can:")
+    print("• Use existing categories when appropriate")
+    print("• Create new categories for unique content")
+    print("• Analyze both title and thumbnail information")
+
+if __name__ == '__main__':
+    print(ollama_host)
+    # Check if Ollama is running
+    try:
+        response = requests.get(f'{ollama_host}/api/tags', timeout=5)
+        if response.status_code != 200:
+            print("❌ Ollama is not running. Please start it with: ollama serve")
+            exit(1)
+    except:
+        print("❌ Cannot connect to Ollama. Please start it with: ollama serve")
+        exit(1)
+    
+    run_demo()

requirements.txt

@@ -2,4 +2,13 @@
 opencv-python==4.11.0.86
 pillow==11.3.0
 PyAutoGUI==0.9.54
-keyboard==0.13.5
+pynput==1.8.1
+requests==2.31.0
+pandas~=2.3.1
+ollama==0.2.1
+configparser==6.0.0
+pyperclip==1.8.2
+pytesseract==0.3.10
+selenium==4.15.2
+webdriver-manager==4.0.1
+rich==13.8.0

setup.sh

@@ -0,0 +1,63 @@
+#!/bin/bash
+
+# YouTube Video Classifier Setup Script
+
+echo "🎬 YouTube Video Classifier Setup"
+echo "=================================="
+
+# Check if Python 3.11 is available
+if ! command -v python3 &> /dev/null; then
+    echo "❌ Python 3.11 not found. Please install Python 3.11.10"
+    exit 1
+fi
+
+echo "✅ Python 3.11 found"
+
+# Create virtual environment
+echo "📦 Creating virtual environment..."
+python3 -m venv venv
+
+# Activate virtual environment
+echo "🔧 Activating virtual environment..."
+source venv/bin/activate
+
+# Install requirements
+echo "📥 Installing Python dependencies..."
+pip install -r requirements.txt
+
+# Check if Ollama is installed
+if ! command -v ollama &> /dev/null; then
+    echo "❌ Ollama not found. Please install Ollama from https://ollama.ai"
+    echo "   After installation, run:"
+    echo "   1. ollama serve"
+    echo "   2. ollama pull qwen2.5-vl:7b"
+    exit 1
+fi
+
+echo "✅ Ollama found"
+
+# Check if Ollama is running
+if ! curl -s http://localhost:11434/api/tags &> /dev/null; then
+    echo "⚠️  Ollama is not running. Starting Ollama..."
+    ollama serve &
+    sleep 5
+fi
+
+# Pull Qwen2.5VL model
+echo "🤖 Pulling Qwen2.5VL model..."
+ollama pull qwen2.5vl:7b
+
+# Test setup
+echo "🧪 Testing setup..."
+python test_ollama.py
+
+echo "✅ Setup complete!"
+echo ""
+echo "Next steps:"
+echo "1. Make sure your browser is pinned to the taskbar"
+echo "2. Update the browser image in img/ folder if needed"
+echo "3. Run: python script.py"
+echo ""
+echo "Optional:"
+echo "- Run demo: python demo_classification.py"
+echo "- Analyze results: python playlist_manager.py --analyze"

setup_model.py

@@ -0,0 +1,114 @@
+#!/usr/bin/env python3
+"""
+Script to ensure the Qwen2.5VL model is available in the Ollama container
+"""
+
+import configparser
+import time
+import sys
+import requests
+
+def load_config():
+    """Load configuration from config.ini"""
+    config = configparser.ConfigParser()
+    config.read('config.ini')
+
+    ollama_host = config.get('DEFAULT', 'ollama_host', fallback='http://ollama:11434')
+    ollama_model = config.get('DEFAULT', 'ollama_model', fallback='qwen2.5vl:7b')
+
+    return ollama_host, ollama_model
+
+def wait_for_ollama(host, max_attempts=30):
+    """Wait for Ollama container to be ready"""
+    print(f"⏳ Waiting for Ollama container at {host}...")
+
+    for attempt in range(1, max_attempts + 1):
+        try:
+            response = requests.get(f"{host}/api/tags", timeout=5)
+            if response.status_code == 200:
+                print("✅ Ollama container is ready!")
+                return True
+        except requests.exceptions.RequestException:
+            pass
+
+        print(f"   Attempt {attempt}/{max_attempts} - waiting...")
+        time.sleep(2)
+
+    print("❌ Ollama container is not responding after maximum attempts")
+    return False
+
+def check_model_exists(host, model_name):
+    """Check if the model is already available"""
+    try:
+        response = requests.get(f"{host}/api/tags", timeout=5)
+        if response.status_code == 200:
+            models = response.json()
+            model_names = [model['name'] for model in models.get('models', [])]
+            return any(model_name in name for name in model_names), model_names
+        return False, []
+    except requests.exceptions.RequestException as e:
+        print(f"❌ Error checking models: {e}")
+        return False, []
+
+def pull_model(host, model_name):
+    """Pull the model from Ollama"""
+    print(f"📥 Pulling model '{model_name}' (this may take several minutes)...")
+
+    try:
+        response = requests.post(
+            f"{host}/api/pull",
+            json={"name": model_name},
+            timeout=600  # 10 minutes timeout
+        )
+
+        if response.status_code == 200:
+            print(f"✅ Successfully pulled model '{model_name}'")
+            return True
+        else:
+            print(f"❌ Failed to pull model: HTTP {response.status_code}")
+            print(f"Response: {response.text}")
+            return False
+    except requests.exceptions.RequestException as e:
+        print(f"❌ Error pulling model: {e}")
+        return False
+
+def main():
+    """Main function to set up the model"""
+    print("🔧 Model Setup for YouTube Video Classifier")
+    print("=" * 50)
+
+    # Load configuration
+    try:
+        ollama_host, ollama_model = load_config()
+        print("📋 Configuration:")
+        print(f"   Host: {ollama_host}")
+        print(f"   Model: {ollama_model}")
+        print()
+    except Exception as e:
+        print(f"❌ Failed to load configuration: {e}")
+        sys.exit(1)
+
+    # Wait for Ollama to be ready
+    if not wait_for_ollama(ollama_host):
+        sys.exit(1)
+
+    # Check if model exists
+    model_exists, available_models = check_model_exists(ollama_host, ollama_model)
+
+    if model_exists:
+        print(f"✅ Model '{ollama_model}' is already available!")
+    else:
+        print(f"📋 Available models: {available_models}")
+        print(f"❌ Model '{ollama_model}' not found")
+
+        if pull_model(ollama_host, ollama_model):
+            print(f"🎉 Model '{ollama_model}' is now ready for use!")
+        else:
+            print(f"❌ Failed to set up model '{ollama_model}'")
+            sys.exit(1)
+
+    print("\n🎬 YouTube Video Classifier is ready!")
+    print("🧪 Run 'python test_ollama.py' to verify the setup")
+
+if __name__ == "__main__":
+    main()

test_ollama.py

@@ -0,0 +1,99 @@
+#!/usr/bin/env python3
+"""
+Test script to verify Ollama connection and Qwen2.5-VL model
+"""
+
+import requests
+import configparser
+
+def load_config():
+    """Load configuration from config.ini"""
+    config = configparser.ConfigParser()
+    config.read('config.ini')
+
+    ollama_host = config.get('DEFAULT', 'ollama_host', fallback='http://ollama:11434')
+    ollama_model = config.get('DEFAULT', 'ollama_model', fallback='qwen2.5vl:7b')
+
+    return ollama_host, ollama_model
+
+def test_ollama_connection(host, model_name):
+    """Test if Ollama is running and accessible."""
+    try:
+        response = requests.get(f'{host}/api/tags', timeout=5)
+        if response.status_code == 200:
+            models = response.json()
+            print("✅ Ollama is running!")
+            model_names = [model['name'] for model in models.get('models', [])]
+            print(f"Available models: {model_names}")
+
+            # Check if the configured model is available
+            model_available = any(model_name in name for name in model_names)
+            if model_available:
+                print(f"✅ {model_name} model is available!")
+            else:
+                print(f"❌ {model_name} model not found. Available models: {model_names}")
+                print(f"Model may still be downloading. Check with: curl {host}/api/tags")
+
+            return True
+        else:
+            print(f"❌ Ollama responded with status code: {response.status_code}")
+            return False
+    except requests.exceptions.ConnectionError:
+        print("❌ Cannot connect to Ollama container. Is the ollama service running?")
+        print("💡 Try: docker-compose up -d ollama")
+        return False
+    except Exception as e:
+        print(f"❌ Error checking Ollama: {e}")
+        return False
+
+def test_classification(host, model_name):
+    """Test a simple classification without image."""
+    try:
+        response = requests.post(
+            f'{host}/api/generate',
+            json={
+                'model': model_name,
+                'prompt': 'Classify this video title into a category: "How to Cook Pasta - Italian Recipe Tutorial". Respond with only the category name.',
+                'stream': False
+            },
+            timeout=30
+        )
+
+        if response.status_code == 200:
+            result = response.json()
+            classification = result['response'].strip()
+            print(f"✅ Test classification successful: '{classification}'")
+            return True
+        else:
+            print(f"❌ Classification test failed: {response.status_code}")
+            print(f"Response: {response.text}")
+            return False
+    except Exception as e:
+        print(f"❌ Error testing classification: {e}")
+        return False
+
+if __name__ == '__main__':
+    print("Testing Ollama setup for YouTube Video Classifier...")
+    print("-" * 50)
+
+    # Load configuration
+    try:
+        ollama_host, ollama_model = load_config()
+        print(f"📋 Configuration:")
+        print(f"   Host: {ollama_host}")
+        print(f"   Model: {ollama_model}")
+        print()
+    except Exception as e:
+        print(f"❌ Failed to load configuration: {e}")
+        exit(1)
+
+    if test_ollama_connection(ollama_host, ollama_model):
+        print("\nTesting classification...")
+        test_classification(ollama_host, ollama_model)
+
+    print("\nSetup verification complete!")
+    print("\nIf all tests passed, you can run the main script with: python script.py")
+    print("If any tests failed, please:")
+    print("1. Make sure the ollama container is running: docker-compose up -d ollama")
+    print(f"2. Wait for the model to download: curl {ollama_host}/api/tags")
+    print("3. Check container logs: docker-compose logs ollama")

web/README.md

@@ -0,0 +1,13 @@
+# Astro with Tailwind
+
+```sh
+pnpm create astro@latest -- --template with-tailwindcss
+```
+
+[![Open in StackBlitz](https://developer.stackblitz.com/img/open_in_stackblitz.svg)](https://stackblitz.com/github/withastro/astro/tree/latest/examples/with-tailwindcss)
+[![Open with CodeSandbox](https://assets.codesandbox.io/github/button-edit-lime.svg)](https://codesandbox.io/p/sandbox/github/withastro/astro/tree/latest/examples/with-tailwindcss)
+[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/withastro/astro?devcontainer_path=.devcontainer/with-tailwindcss/devcontainer.json)
+
+Astro comes with [Tailwind](https://tailwindcss.com) support out of the box. This example showcases how to style your Astro project with Tailwind.
+
+For complete setup instructions, please see our [Tailwind Integration Guide](https://docs.astro.build/en/guides/integrations-guide/tailwind).

web/astro.config.mjs

@@ -0,0 +1,16 @@
+// @ts-check
+import { defineConfig } from 'astro/config';
+import tailwindcss from '@tailwindcss/vite';
+
+import react from '@astrojs/react';
+
+// https://astro.build/config
+export default defineConfig({
+  vite: {
+      plugins: [tailwindcss()]
+	},
+
+  integrations: [react({
+    experimentalDisableStreaming: true,
+  })]
+});

web/components.json

@@ -0,0 +1,21 @@
+{
+  "$schema": "https://ui.shadcn.com/schema.json",
+  "style": "new-york",
+  "rsc": false,
+  "tsx": true,
+  "tailwind": {
+    "config": "",
+    "css": "src/styles/global.css",
+    "baseColor": "neutral",
+    "cssVariables": true,
+    "prefix": ""
+  },
+  "aliases": {
+    "components": "@/components",
+    "utils": "@/lib/utils",
+    "ui": "@/components/ui",
+    "lib": "@/lib",
+    "hooks": "@/hooks"
+  },
+  "iconLibrary": "lucide"
+}

web/package.json

@@ -0,0 +1,37 @@
+{
+  "name": "web",
+  "type": "module",
+  "version": "0.0.1",
+  "scripts": {
+    "dev": "astro dev",
+    "build": "astro build",
+    "preview": "astro preview",
+    "astro": "astro"
+  },
+  "dependencies": {
+    "@astrojs/mdx": "^4.3.0",
+    "@astrojs/react": "^4.3.0",
+    "@base-ui-components/react": "1.0.0-beta.1",
+    "@radix-ui/react-slot": "^1.2.3",
+    "@tailwindcss/vite": "^4.1.3",
+    "@tanstack/react-virtual": "^3.13.12",
+    "@types/canvas-confetti": "^1.9.0",
+    "@types/react": "^19.1.8",
+    "@types/react-dom": "^19.1.6",
+    "astro": "^5.11.0",
+    "canvas-confetti": "^1.9.3",
+    "class-variance-authority": "^0.7.1",
+    "clsx": "^2.1.1",
+    "date-fns": "^4.1.0",
+    "lucide-react": "^0.525.0",
+    "next-themes": "^0.4.6",
+    "papaparse": "^5.5.3",
+    "react": "^19.1.0",
+    "react-dom": "^19.1.0",
+    "tailwind-merge": "^3.3.1",
+    "tailwindcss": "^4.1.3"
+  },
+  "devDependencies": {
+    "tw-animate-css": "^1.3.5"
+  }
+}

web/public/favicon.svg

@@ -0,0 +1,9 @@
+<svg xmlns="http://www.w3.org/2000/svg" fill="none" viewBox="0 0 128 128">
+    <path d="M50.4 78.5a75.1 75.1 0 0 0-28.5 6.9l24.2-65.7c.7-2 1.9-3.2 3.4-3.2h29c1.5 0 2.7 1.2 3.4 3.2l24.2 65.7s-11.6-7-28.5-7L67 45.5c-.4-1.7-1.6-2.8-2.9-2.8-1.3 0-2.5 1.1-2.9 2.7L50.4 78.5Zm-1.1 28.2Zm-4.2-20.2c-2 6.6-.6 15.8 4.2 20.2a17.5 17.5 0 0 1 .2-.7 5.5 5.5 0 0 1 5.7-4.5c2.8.1 4.3 1.5 4.7 4.7.2 1.1.2 2.3.2 3.5v.4c0 2.7.7 5.2 2.2 7.4a13 13 0 0 0 5.7 4.9v-.3l-.2-.3c-1.8-5.6-.5-9.5 4.4-12.8l1.5-1a73 73 0 0 0 3.2-2.2 16 16 0 0 0 6.8-11.4c.3-2 .1-4-.6-6l-.8.6-1.6 1a37 37 0 0 1-22.4 2.7c-5-.7-9.7-2-13.2-6.2Z" />
+    <style>
+        path { fill: #000; }
+        @media (prefers-color-scheme: dark) {
+            path { fill: #FFF; }
+        }
+    </style>
+</svg>

web/src/components/Button.astro

@@ -0,0 +1,19 @@
+---
+// Click button, get confetti!
+// Styled by Tailwind :)
+---
+
+<button
+	class="appearance-none py-2 px-4 bg-purple-500 text-white font-semibold rounded-lg shadow-md hover:bg-purple-700 focus:outline-none focus:ring-2 focus:ring-purple-400 focus:ring-opacity-75"
+>
+	<slot />
+</button>
+
+<script>
+	import confetti from 'canvas-confetti';
+	const button = document.body.querySelector('button');
+
+	if (button) {
+		button.addEventListener('click', () => confetti());
+	}
+</script>

web/src/components/SearchAndFilter.tsx

@@ -0,0 +1,129 @@
+import React from 'react';
+import { Input } from './ui/input';
+import { Select } from './ui/select';
+import { Button } from './ui/button';
+import { Badge } from './ui/badge';
+import type { VideoData } from '../types/video';
+import { getUniqueValues } from '../utils/search';
+
+interface SearchAndFilterProps {
+  data: VideoData[];
+  searchTerm: string;
+  onSearchChange: (term: string) => void;
+  filters: {
+    classification: string;
+    language: string;
+    playlist_name: string;
+  };
+  onFilterChange: (filters: any) => void;
+  totalResults: number;
+  filteredResults: number;
+}
+
+export function SearchAndFilter({
+  data,
+  searchTerm,
+  onSearchChange,
+  filters,
+  onFilterChange,
+  totalResults,
+  filteredResults
+}: SearchAndFilterProps) {
+  const classifications = getUniqueValues(data, 'classification');
+  const languages = getUniqueValues(data, 'language');
+  const playlists = getUniqueValues(data, 'playlist_name');
+
+  const clearFilters = () => {
+    onSearchChange('');
+    onFilterChange({
+      classification: 'all',
+      language: 'all',
+      playlist_name: 'all'
+    });
+  };
+
+  const activeFiltersCount = Object.values(filters).filter(value => value !== 'all').length + (searchTerm ? 1 : 0);
+
+  return (
+    <div className="space-y-4 p-6 bg-card border rounded-lg">
+      <div className="flex items-center justify-between">
+        <div className="space-y-1">
+          <h2 className="text-lg font-semibold">Search & Filter</h2>
+          <p className="text-sm text-muted-foreground">
+            {filteredResults} of {totalResults} videos
+            {activeFiltersCount > 0 && (
+              <Badge variant="secondary" className="ml-2">
+                {activeFiltersCount} filter{activeFiltersCount !== 1 ? 's' : ''} active
+              </Badge>
+            )}
+          </p>
+        </div>
+        {activeFiltersCount > 0 && (
+          <Button variant="outline" size="sm" onClick={clearFilters}>
+            Clear All
+          </Button>
+        )}
+      </div>
+
+      <div className="grid grid-cols-1 md:grid-cols-2 lg:grid-cols-4 gap-4">
+        {/* Search */}
+        <div className="space-y-2">
+          <label className="text-sm font-medium">Search</label>
+          <Input
+            placeholder="Search videos, channels, tags..."
+            value={searchTerm}
+            onChange={(e) => onSearchChange(e.target.value)}
+          />
+        </div>
+
+        {/* Classification Filter */}
+        <div className="space-y-2">
+          <label className="text-sm font-medium">Classification</label>
+          <Select
+            value={filters.classification}
+            onChange={(e) => onFilterChange({ ...filters, classification: e.target.value })}
+          >
+            <option value="all">All Classifications</option>
+            {classifications.map((classification) => (
+              <option key={classification} value={classification}>
+                {classification}
+              </option>
+            ))}
+          </Select>
+        </div>
+
+        {/* Language Filter */}
+        <div className="space-y-2">
+          <label className="text-sm font-medium">Language</label>
+          <Select
+            value={filters.language}
+            onChange={(e) => onFilterChange({ ...filters, language: e.target.value })}
+          >
+            <option value="all">All Languages</option>
+            {languages.map((language) => (
+              <option key={language} value={language}>
+                {language}
+              </option>
+            ))}
+          </Select>
+        </div>
+
+        {/* Playlist Filter */}
+        <div className="space-y-2">
+          <label className="text-sm font-medium">Playlist</label>
+          <Select
+            value={filters.playlist_name}
+            onChange={(e) => onFilterChange({ ...filters, playlist_name: e.target.value })}
+          >
+            <option value="all">All Playlists</option>
+            {playlists.map((playlist) => (
+              <option key={playlist} value={playlist}>
+                {playlist}
+              </option>
+            ))}
+          </Select>
+        </div>
+      </div>
+    </div>
+  );
+}

web/src/components/StatsOverview.tsx

@@ -0,0 +1,41 @@
+import React from 'react';
+import { Badge } from './ui/badge';
+import type { VideoData } from '../types/video';
+import { getUniqueValues } from '../utils/search';
+
+interface StatsOverviewProps {
+  data: VideoData[];
+}
+
+export function StatsOverview({ data }: StatsOverviewProps) {
+  const totalVideos = data.length;
+  const totalDuration = data.reduce((sum, video) => sum + video.video_length_seconds, 0);
+  const uniqueChannels = getUniqueValues(data, 'channel_name').length;
+  const uniqueClassifications = getUniqueValues(data, 'classification').length;
+  const uniqueLanguages = getUniqueValues(data, 'language').length;
+
+  const formatTotalDuration = (seconds: number) => {
+    const hours = Math.floor(seconds / 3600);
+    const minutes = Math.floor((seconds % 3600) / 60);
+    return `${hours}h ${minutes}m`;
+  };
+
+  const stats = [
+    { label: 'Total Videos', value: totalVideos.toLocaleString() },
+    { label: 'Total Duration', value: formatTotalDuration(totalDuration) },
+    { label: 'Channels', value: uniqueChannels },
+    { label: 'Categories', value: uniqueClassifications },
+    { label: 'Languages', value: uniqueLanguages },
+  ];
+
+  return (
+    <div className="grid grid-cols-2 md:grid-cols-5 gap-4">
+      {stats.map((stat) => (
+        <div key={stat.label} className="text-center p-4 bg-card border rounded-lg">
+          <div className="text-2xl font-bold text-primary">{stat.value}</div>
+          <div className="text-sm text-muted-foreground">{stat.label}</div>
+        </div>
+      ))}
+    </div>
+  );
+}

web/src/components/ThemeProvider.tsx

@@ -0,0 +1,75 @@
+import React, { createContext, useContext, useEffect, useState } from 'react'
+
+type Theme = 'dark' | 'light' | 'system'
+
+type ThemeProviderProps = {
+  children: React.ReactNode
+  defaultTheme?: Theme
+  storageKey?: string
+}
+
+type ThemeProviderState = {
+  theme: Theme
+  setTheme: (theme: Theme) => void
+}
+
+const initialState: ThemeProviderState = {
+  theme: 'system',
+  setTheme: () => null,
+}
+
+const ThemeProviderContext = createContext<ThemeProviderState>(initialState)
+
+export function ThemeProvider({
+  children,
+  defaultTheme = 'system',
+  storageKey = 'vite-ui-theme',
+  ...props
+}: ThemeProviderProps) {
+  const [theme, setTheme] = useState<Theme>(
+    () => (localStorage ? localStorage.getItem(storageKey) as Theme : undefined) || defaultTheme
+  )
+
+  useEffect(() => {
+    const root = window.document.documentElement
+
+    root.classList.remove('light', 'dark')
+
+    if (theme === 'system') {
+      const systemTheme = window.matchMedia('(prefers-color-scheme: dark)')
+        .matches
+        ? 'dark'
+        : 'light'
+
+      root.classList.add(systemTheme)
+      return
+    }
+
+    root.classList.add(theme)
+  }, [theme])
+
+  const value = {
+    theme,
+    setTheme: (theme: Theme) => {
+      if (localStorage) {
+        localStorage.setItem(storageKey, theme)
+      }
+      setTheme(theme)
+    },
+  }
+
+  return (
+    <ThemeProviderContext.Provider {...props} value={value}>
+      {children}
+    </ThemeProviderContext.Provider>
+  )
+}
+
+export const useTheme = () => {
+  const context = useContext(ThemeProviderContext)
+
+  if (context === undefined)
+    throw new Error('useTheme must be used within a ThemeProvider')
+
+  return context
+}

web/src/components/ThemeToggle.tsx

@@ -0,0 +1,21 @@
+import React from 'react'
+import { Moon, Sun } from 'lucide-react'
+import { Button } from './ui/button'
+import { useTheme } from './ThemeProvider'
+
+export function ThemeToggle() {
+  const { theme, setTheme } = useTheme()
+
+  return (
+    <Button
+      variant="outline"
+      size="icon"
+      onClick={() => setTheme(theme === 'light' ? 'dark' : 'light')}
+      className="relative"
+    >
+      <Sun className="h-[1.2rem] w-[1.2rem] rotate-0 scale-100 transition-all dark:-rotate-90 dark:scale-0" />
+      <Moon className="absolute h-[1.2rem] w-[1.2rem] rotate-90 scale-0 transition-all dark:rotate-0 dark:scale-100" />
+      <span className="sr-only">Toggle theme</span>
+    </Button>
+  )
+}

web/src/components/VideoClassifierApp.tsx

@@ -0,0 +1,136 @@
+import React, { useState, useEffect, useMemo } from 'react';
+import { VirtualTable } from './VirtualTable';
+import { SearchAndFilter } from './SearchAndFilter';
+import { StatsOverview } from './StatsOverview';
+import { Button } from './ui/button';
+import { ThemeProvider } from './ThemeProvider';
+import { ThemeToggle } from './ThemeToggle';
+import type { VideoData } from '../types/video';
+import { searchVideos, filterVideos } from '../utils/search';
+
+interface ApiResponse {
+  videos?: VideoData[];
+  error?: string;
+  message?: string;
+}
+
+export default function VideoClassifierApp({ videos }: { videos: VideoData[] }) {
+  const [searchTerm, setSearchTerm] = useState('');
+  const [filters, setFilters] = useState({
+    classification: 'all',
+    language: 'all',
+    playlist_name: 'all'
+  });
+
+  // Filter and search data
+  const filteredData = useMemo(() => {
+    let result = videos;
+    
+    // Apply filters
+    result = filterVideos(result, filters);
+    
+    // Apply search
+    result = searchVideos(result, searchTerm);
+    
+    return result;
+  }, [videos, searchTerm, filters]);
+
+  if (!videos) {
+    return (
+      <div className="min-h-screen flex items-center justify-center p-6">
+        <div className="max-w-md text-center space-y-4">
+          <div className="text-6xl">📁</div>
+          <h1 className="text-2xl font-bold text-destructive">CSV File Not Found</h1>
+          <p className="text-muted-foreground">
+            It seems the <code className="bg-background px-1 rounded">video_classifications.csv</code> file is missing or not properly configured.
+          </p>
+          <div className="bg-muted p-4 rounded-lg text-sm text-left">
+            <p className="font-medium mb-2">To fix this:</p>
+            <ol className="list-decimal list-inside space-y-1 text-muted-foreground">
+              <li>Make sure <code className="bg-background px-1 rounded">video_classifications.csv</code> exists in your project root</li>
+              <li>Run your YouTube classifier script to generate the CSV</li>
+              <li>Refresh this page</li>
+            </ol>
+          </div>
+        </div>
+      </div>
+    );
+  }
+
+  return (
+    <ThemeProvider defaultTheme="system" storageKey="video-classifier-theme">
+      <div className="min-h-screen bg-background">
+        <div className="container mx-auto px-6 py-8 space-y-8">
+          {/* Header */}
+          <div className="text-center space-y-4">
+            <div className="flex items-center justify-center gap-4">
+              <h1 className="text-4xl font-bold bg-gradient-to-r from-primary to-primary/60 bg-clip-text text-transparent">
+                YouTube Video Classifier
+              </h1>
+              <ThemeToggle />
+            </div>
+            <p className="text-muted-foreground max-w-2xl mx-auto">
+              AI-powered video classification and management platform. Search, filter, and organize your YouTube video collection with intelligent categorization.
+            </p>
+          </div>
+
+          {/* Stats Overview */}
+          {videos.length > 0 && (
+            <StatsOverview data={videos} />
+          )}
+
+          {/* Search and Filter */}
+          {videos.length > 0 && (
+            <SearchAndFilter
+              data={videos}
+              searchTerm={searchTerm}
+              onSearchChange={setSearchTerm}
+              filters={filters}
+              onFilterChange={setFilters}
+              totalResults={videos.length}
+              filteredResults={filteredData.length}
+            />
+          )}
+
+          {/* Results */}
+          {videos.length > 0 ? (
+            filteredData.length > 0 ? (
+              <VirtualTable data={filteredData} />
+            ) : (
+              <div className="text-center py-12">
+                <div className="text-6xl mb-4">🔍</div>
+                <h3 className="text-lg font-medium mb-2">No results found</h3>
+                <p className="text-muted-foreground">
+                  Try adjusting your search terms or filters
+                </p>
+              </div>
+            )
+          ) : (
+            <div className="text-center py-12">
+              <div className="text-6xl mb-4">📹</div>
+              <h3 className="text-lg font-medium mb-2">No videos found</h3>
+              <p className="text-muted-foreground">
+                Your CSV file appears to be empty
+              </p>
+            </div>
+          )}
+
+          {/* Footer */}
+          <div className="text-center text-sm text-muted-foreground border-t pt-8">
+            <p>
+              {videos.length} videos indexed
+            </p>
+            <Button
+              variant="ghost"
+              size="sm"
+              onClick={() => window.location.reload}
+              className="mt-2"
+            >
+              Refresh Data
+            </Button>
+          </div>
+        </div>
+      </div>
+    </ThemeProvider>
+  );
+}

web/src/components/VirtualTable.tsx

@@ -0,0 +1,172 @@
+import React, { useRef } from 'react';
+import { useVirtualizer } from '@tanstack/react-virtual';
+import type { VideoData } from '../types/video';
+import { formatDuration, formatDate } from '../utils/csvParser';
+import { Badge } from './ui/badge';
+import { Button } from './ui/button';
+import { Tooltip,TooltipContent, TooltipTrigger  } from './ui/tooltip';
+
+interface VirtualTableProps {
+  data: VideoData[];
+}
+
+export function VirtualTable({ data }: VirtualTableProps) {
+  const parentRef = useRef<HTMLDivElement>(null);
+
+  console.log(data);
+  const rowVirtualizer = useVirtualizer({
+    count: data.length,
+    getScrollElement: () => parentRef.current,
+    estimateSize: () => 120,
+    overscan: 5,
+  });
+
+  const virtualItems = rowVirtualizer.getVirtualItems();
+
+  return (
+    <div className="border rounded-lg overflow-hidden">
+      {/* Table Header */}
+      <div className="bg-muted/50 border-b">
+        <div className="grid grid-cols-12 gap-3 px-4 py-3 text-sm font-medium text-muted-foreground">
+          <div className="col-span-3 flex items-center">Video</div>
+          <div className="col-span-2 flex items-center">Channel</div>
+          <div className="col-span-2 flex items-center">Classification</div>
+          <div className="col-span-1 flex items-center">Language</div>
+          <div className="col-span-1 flex items-center">Duration</div>
+          <div className="col-span-2 flex items-center">Date</div>
+          <div className="col-span-1 flex items-center">Actions</div>
+        </div>
+      </div>
+
+      {/* Virtual Container */}
+      <div
+        ref={parentRef}
+        className="h-[600px] overflow-auto"
+        style={{
+          contain: 'strict',
+        }}
+      >
+        <div
+          style={{
+            height: `${rowVirtualizer.getTotalSize()}px`,
+            width: '100%',
+            position: 'relative',
+          }}
+        >
+          {virtualItems.map((virtualItem) => {
+            const video = data[virtualItem.index];
+            console.log(data, virtualItem, video);
+            if (!video) return null;
+
+            return (
+              <div
+                key={virtualItem.key}
+                data-index={virtualItem.index}
+                style={{
+                  position: 'absolute',
+                  top: 0,
+                  left: 0,
+                  width: '100%',
+                  transform: `translateY(${virtualItem.start}px)`,
+                }}
+              >
+                <div className="border-b hover:bg-muted/50 transition-colors">
+                  <div className="grid grid-cols-12 gap-3 px-4 py-3 items-center min-h-[80px]">
+                    {/* Video Info */}
+                    <div className="col-span-3 space-y-2 min-w-0">
+                      <Tooltip>
+                        <TooltipContent>
+                          {video.video_title}
+                        </TooltipContent>
+                        <TooltipTrigger>
+                        <h3 className="text-start font-medium text-sm leading-tight truncate sm:w-[150px] lg:w-[200px] xl:w-[250px] 2xl:w-[300px]">
+                          {video.video_title}
+                        </h3>
+                        </TooltipTrigger>
+                      </Tooltip>
+                      <div className="flex flex-wrap gap-1">
+                        {video.detailed_subtags.split(',').slice(0, 2).map((tag, i) => (
+                            <Badge variant="secondary" className="text-xs max-w-20 truncate">
+                              {tag.trim()}
+                            </Badge>
+                        ))}
+                        {video.detailed_subtags.split(',').length > 2 && (
+                          <Tooltip>
+                            <TooltipContent>
+                              {video.detailed_subtags.split(',').slice(2).join(', ')}
+                            </TooltipContent>
+                            <TooltipTrigger>
+                            <Badge variant="outline" className="text-xs">
+                              +{video.detailed_subtags.split(',').length - 2}
+                            </Badge>
+                            </TooltipTrigger>
+                          </Tooltip>
+                        )}
+                      </div>
+                    </div>
+
+                    {/* Channel */}
+                    <div className="col-span-2 min-w-0">
+                      <Tooltip content={video.channel_name}>
+                        <div className="text-sm font-medium truncate">{video.channel_name}</div>
+                      </Tooltip>
+                      <Tooltip content={video.playlist_name}>
+                        <div className="text-xs text-muted-foreground truncate">{video.playlist_name}</div>
+                      </Tooltip>
+                    </div>
+
+                    {/* Classification */}
+                    <div className="col-span-2 min-w-0">
+                      <Badge variant="default" className="text-xs truncate max-w-full">
+                        {video.classification}
+                      </Badge>
+                    </div>
+
+                    {/* Language */}
+                    <div className="col-span-1 min-w-0">
+                      <Badge variant="outline" className="text-xs truncate max-w-full">
+                        {video.language}
+                      </Badge>
+                    </div>
+
+                    {/* Duration */}
+                    <div className="col-span-1 text-sm font-mono">
+                      {formatDuration(video.video_length_seconds)}
+                    </div>
+
+                    {/* Date */}
+                    <div className="col-span-2 space-y-1 min-w-0">
+                      <div className="text-sm">{formatDate(video.video_date)}</div>
+                      <div className="text-xs text-muted-foreground truncate">
+                        Added: {formatDate(video.timestamp)}
+                      </div>
+                    </div>
+
+                    {/* Actions */}
+                    <div className="col-span-1">
+                      <Button
+                        size="sm"
+                        variant="outline"
+                        onClick={() => window.open(video.video_url, '_blank')}
+                        className="text-xs"
+                      >
+                        Watch
+                      </Button>
+                    </div>
+                  </div>
+                </div>
+              </div>
+            );
+          })}
+        </div>
+      </div>
+
+      {/* Footer */}
+      <div className="bg-muted/50 border-t px-4 py-3">
+        <div className="text-sm text-muted-foreground text-center">
+          Showing {data.length} videos
+        </div>
+      </div>
+    </div>
+  );
+}

web/src/components/ui/badge.tsx

@@ -0,0 +1,36 @@
+import * as React from "react"
+import { cva, type VariantProps } from "class-variance-authority"
+
+import { cn } from "@/lib/utils"
+
+const badgeVariants = cva(
+  "inline-flex items-center rounded-md border px-2.5 py-0.5 text-xs font-semibold transition-colors focus:outline-none focus:ring-2 focus:ring-ring focus:ring-offset-2",
+  {
+    variants: {
+      variant: {
+        default:
+          "border-transparent bg-primary text-primary-foreground shadow hover:bg-primary/80",
+        secondary:
+          "border-transparent bg-secondary text-secondary-foreground hover:bg-secondary/80",
+        destructive:
+          "border-transparent bg-destructive text-destructive-foreground shadow hover:bg-destructive/80",
+        outline: "text-foreground",
+      },
+    },
+    defaultVariants: {
+      variant: "default",
+    },
+  }
+)
+
+export interface BadgeProps
+  extends React.HTMLAttributes<HTMLDivElement>,
+    VariantProps<typeof badgeVariants> {}
+
+function Badge({ className, variant, ...props }: BadgeProps) {
+  return (
+    <div className={cn(badgeVariants({ variant }), className)} {...props} />
+  )
+}
+
+export { Badge, badgeVariants }

web/src/components/ui/button.tsx

@@ -0,0 +1,59 @@
+import * as React from "react"
+import { Slot } from "@radix-ui/react-slot"
+import { cva, type VariantProps } from "class-variance-authority"
+
+import { cn } from "@/lib/utils"
+
+const buttonVariants = cva(
+  "inline-flex items-center justify-center gap-2 whitespace-nowrap rounded-md text-sm font-medium transition-all disabled:pointer-events-none disabled:opacity-50 [&_svg]:pointer-events-none [&_svg:not([class*='size-'])]:size-4 shrink-0 [&_svg]:shrink-0 outline-none focus-visible:border-ring focus-visible:ring-ring/50 focus-visible:ring-[3px] aria-invalid:ring-destructive/20 dark:aria-invalid:ring-destructive/40 aria-invalid:border-destructive",
+  {
+    variants: {
+      variant: {
+        default:
+          "bg-primary text-primary-foreground shadow-xs hover:bg-primary/90",
+        destructive:
+          "bg-destructive text-white shadow-xs hover:bg-destructive/90 focus-visible:ring-destructive/20 dark:focus-visible:ring-destructive/40 dark:bg-destructive/60",
+        outline:
+          "border bg-background shadow-xs hover:bg-accent hover:text-accent-foreground dark:bg-input/30 dark:border-input dark:hover:bg-input/50",
+        secondary:
+          "bg-secondary text-secondary-foreground shadow-xs hover:bg-secondary/80",
+        ghost:
+          "hover:bg-accent hover:text-accent-foreground dark:hover:bg-accent/50",
+        link: "text-primary underline-offset-4 hover:underline",
+      },
+      size: {
+        default: "h-9 px-4 py-2 has-[>svg]:px-3",
+        sm: "h-8 rounded-md gap-1.5 px-3 has-[>svg]:px-2.5",
+        lg: "h-10 rounded-md px-6 has-[>svg]:px-4",
+        icon: "size-9",
+      },
+    },
+    defaultVariants: {
+      variant: "default",
+      size: "default",
+    },
+  }
+)
+
+function Button({
+  className,
+  variant,
+  size,
+  asChild = false,
+  ...props
+}: React.ComponentProps<"button"> &
+  VariantProps<typeof buttonVariants> & {
+    asChild?: boolean
+  }) {
+  const Comp = asChild ? Slot : "button"
+
+  return (
+    <Comp
+      data-slot="button"
+      className={cn(buttonVariants({ variant, size, className }))}
+      {...props}
+    />
+  )
+}
+
+export { Button, buttonVariants }

web/src/components/ui/input.tsx

@@ -0,0 +1,25 @@
+import * as React from "react"
+
+import { cn } from "@/lib/utils"
+
+export interface InputProps
+  extends React.InputHTMLAttributes<HTMLInputElement> {}
+
+const Input = React.forwardRef<HTMLInputElement, InputProps>(
+  ({ className, type, ...props }, ref) => {
+    return (
+      <input
+        type={type}
+        className={cn(
+          "flex h-9 w-full rounded-md border border-input bg-transparent px-3 py-1 text-sm shadow-sm transition-colors file:border-0 file:bg-transparent file:text-sm file:font-medium file:text-foreground placeholder:text-muted-foreground focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring disabled:cursor-not-allowed disabled:opacity-50",
+          className
+        )}
+        ref={ref}
+        {...props}
+      />
+    )
+  }
+)
+Input.displayName = "Input"
+
+export { Input }

web/src/components/ui/select.tsx

@@ -0,0 +1,23 @@
+import * as React from "react"
+import { cn } from "@/lib/utils"
+
+const Select = React.forwardRef<
+  HTMLSelectElement,
+  React.SelectHTMLAttributes<HTMLSelectElement>
+>(({ className, children, ...props }, ref) => {
+  return (
+    <select
+      className={cn(
+        "flex h-9 w-full rounded-md border border-input bg-background px-3 py-1 text-sm shadow-sm transition-colors focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring disabled:cursor-not-allowed disabled:opacity-50",
+        className
+      )}
+      ref={ref}
+      {...props}
+    >
+      {children}
+    </select>
+  )
+})
+Select.displayName = "Select"
+
+export { Select }

web/src/components/ui/tooltip.tsx

@@ -0,0 +1,103 @@
+import * as React from "react"
+import { Tooltip as BaseTooltip } from "@base-ui-components/react/tooltip"
+
+import { cn } from "@/lib/utils"
+
+function TooltipProvider({
+	delay = 0,
+	closeDelay = 0,
+	...props
+}: React.ComponentProps<typeof BaseTooltip.Provider>) {
+	return (
+		<BaseTooltip.Provider
+			data-slot="tooltip-provider"
+			delay={delay}
+			closeDelay={closeDelay}
+			{...props}
+		/>
+	)
+}
+
+function Tooltip({ ...props }: React.ComponentProps<typeof BaseTooltip.Root>) {
+	return (
+		<TooltipProvider>
+			<BaseTooltip.Root data-slot="tooltip" {...props} />
+		</TooltipProvider>
+	)
+}
+
+function TooltipTrigger({
+	...props
+}: React.ComponentProps<typeof BaseTooltip.Trigger>) {
+	return <BaseTooltip.Trigger data-slot="tooltip-trigger" {...props} />
+}
+
+function TooltipPortal({
+	...props
+}: React.ComponentProps<typeof BaseTooltip.Portal>) {
+	return <BaseTooltip.Portal data-slot="tooltip-portal" {...props} />
+}
+
+function TooltipPositioner({
+	...props
+}: React.ComponentProps<typeof BaseTooltip.Positioner>) {
+	return <BaseTooltip.Positioner data-slot="tooltip-positioner" {...props} />
+}
+
+function TooltipArrow({
+	...props
+}: React.ComponentProps<typeof BaseTooltip.Arrow>) {
+	return <BaseTooltip.Arrow data-slot="tooltip-arrow" {...props} />
+}
+
+function TooltipContent({
+	className,
+	align = "center",
+	sideOffset = 8,
+	side = "top",
+	children,
+	...props
+}: React.ComponentProps<typeof BaseTooltip.Popup> & {
+	align?: BaseTooltip.Positioner.Props["align"]
+	side?: BaseTooltip.Positioner.Props["side"]
+	sideOffset?: BaseTooltip.Positioner.Props["sideOffset"]
+}) {
+	return (
+		<TooltipPortal>
+			<TooltipPositioner sideOffset={sideOffset} align={align} side={side}>
+				<BaseTooltip.Popup
+					data-slot="tooltip-content"
+					className={cn(
+						"bg-popover text-popover-foreground outline-border z-50 w-fit origin-[var(--transform-origin)] rounded-md px-3 py-1.5 text-xs text-balance shadow-sm outline -outline-offset-1 transition-[transform,scale,opacity] data-[ending-style]:scale-95 data-[ending-style]:opacity-0 data-[starting-style]:scale-95 data-[starting-style]:opacity-0",
+						className
+					)}
+					{...props}
+				>
+					{children}
+					<TooltipArrow className="data-[side=bottom]:top-[-8px] data-[side=left]:right-[-13px] data-[side=left]:rotate-90 data-[side=right]:left-[-13px] data-[side=right]:-rotate-90 data-[side=top]:bottom-[-8px] data-[side=top]:rotate-180">
+						<svg width="20" height="10" viewBox="0 0 20 10" fill="none">
+							<path
+								d="M9.66437 2.60207L4.80758 6.97318C4.07308 7.63423 3.11989 8 2.13172 8H0V9H20V8H18.5349C17.5468 8 16.5936 7.63423 15.8591 6.97318L11.0023 2.60207C10.622 2.2598 10.0447 2.25979 9.66437 2.60207Z"
+								className="fill-popover"
+							/>
+							<path
+								d="M10.3333 3.34539L5.47654 7.71648C4.55842 8.54279 3.36693 9 2.13172 9H0V8H2.13172C3.11989 8 4.07308 7.63423 4.80758 6.97318L9.66437 2.60207C10.0447 2.25979 10.622 2.2598 11.0023 2.60207L15.8591 6.97318C16.5936 7.63423 17.5468 8 18.5349 8H20V9H18.5349C17.2998 9 16.1083 8.54278 15.1901 7.71648L10.3333 3.34539Z"
+								className="fill-border"
+							/>
+						</svg>
+					</TooltipArrow>
+				</BaseTooltip.Popup>
+			</TooltipPositioner>
+		</TooltipPortal>
+	)
+}
+
+export {
+	Tooltip,
+	TooltipTrigger,
+	TooltipContent,
+	TooltipPortal,
+	TooltipPositioner,
+	TooltipArrow,
+	TooltipProvider,
+}

web/src/env.d.ts

@@ -0,0 +1,2 @@
+/// <reference path="../.astro/types.d.ts" />
+/// <reference types="astro/client" />

web/src/layouts/main.astro

@@ -0,0 +1,17 @@
+---
+import { Button } from '@/components/ui/button';
+import '../styles/global.css';
+const { content } = Astro.props;
+---
+
+<html lang="en">
+	<head>
+		<meta charset="utf-8" />
+		<meta name="viewport" content="width=device-width" />
+		<link rel="icon" type="image/svg+xml" href="/favicon.svg" />
+		<title>{content.title}</title>
+	</head>
+	<body>
+		<slot />
+	</body>
+</html>

web/src/lib/utils.ts

@@ -0,0 +1,6 @@
+import { clsx, type ClassValue } from "clsx"
+import { twMerge } from "tailwind-merge"
+
+export function cn(...inputs: ClassValue[]) {
+  return twMerge(clsx(inputs))
+}

web/src/pages/api/videos.ts

@@ -0,0 +1,51 @@
+import type { APIRoute } from 'astro';
+import { readFileSync, existsSync } from 'fs';
+import { join } from 'path';
+import { parseCSV } from '../../utils/csvParser';
+
+export const GET: APIRoute = async () => {
+  try {
+    // Look for CSV file in the project root (outside web folder)
+    const csvPath = join(process.cwd(), '..', 'video_classifications.csv');
+    
+    if (!existsSync(csvPath)) {
+      return new Response(
+        JSON.stringify({ 
+          error: 'CSV file not found',
+          message: 'video_classifications.csv not found in project root',
+          path: csvPath
+        }), 
+        {
+          status: 404,
+          headers: {
+            'Content-Type': 'application/json',
+          },
+        }
+      );
+    }
+
+    const csvContent = readFileSync(csvPath, 'utf-8');
+    const videos = parseCSV(csvContent);
+
+    return new Response(JSON.stringify({ videos }), {
+      status: 200,
+      headers: {
+        'Content-Type': 'application/json',
+      },
+    });
+  } catch (error) {
+    console.error('Error reading CSV file:', error);
+    return new Response(
+      JSON.stringify({ 
+        error: 'Failed to read CSV file',
+        message: error instanceof Error ? error.message : 'Unknown error'
+      }), 
+      {
+        status: 500,
+        headers: {
+          'Content-Type': 'application/json',
+        },
+      }
+    );
+  }
+};

web/src/pages/index.astro

@@ -0,0 +1,27 @@
+---
+import VideoClassifierApp from '@/components/VideoClassifierApp';
+import '../styles/global.css';
+import { join } from 'path';
+import { readFileSync } from 'fs';
+import { parseCSV } from '@/utils/csvParser';
+
+ const csvPath = join(process.cwd(), '..', 'video_classifications.csv')
+    const csvContent = readFileSync(csvPath, 'utf-8');
+    const videos = parseCSV(csvContent);
+
+---
+
+<html lang="en">
+	<head>
+		<meta charset="utf-8" />
+		<meta name="viewport" content="width=device-width, initial-scale=1.0" />
+		<link rel="icon" type="image/svg+xml" href="/favicon.svg" />
+		<meta name="generator" content={Astro.generator} />
+		<title>YouTube Video Classifier</title>
+		<meta name="description" content="AI-powered YouTube video classification and management platform" />
+	</head>
+
+	<body class="min-h-screen bg-background">
+		<VideoClassifierApp client:only videos={videos}  />
+	</body>
+</html>

web/src/pages/markdown-page.md

@@ -0,0 +1,16 @@
+---
+title: 'Markdown + Tailwind'
+layout: ../layouts/main.astro
+---
+
+<div class="grid place-items-center h-screen content-center">
+ <div class="py-2 px-4 bg-purple-500 text-white font-semibold rounded-lg shadow-md">
+  Tailwind classes also work in Markdown!
+ </div>
+ <a
+  href="/"
+  class="p-4 underline hover:text-purple-500 transition-colors ease-in-out duration-200"
+ >
+  Go home
+ </a>
+</div>

web/src/styles/global.css

@@ -0,0 +1,194 @@
+@import 'tailwindcss';
+@import "tw-animate-css";
+
+@custom-variant dark (&:is(.dark *));
+
+@theme inline {
+  --radius-sm: calc(var(--radius) - 4px);
+  --radius-md: calc(var(--radius) - 2px);
+  --radius-lg: var(--radius);
+  --radius-xl: calc(var(--radius) + 4px);
+  --color-background: var(--background);
+  --color-foreground: var(--foreground);
+  --color-card: var(--card);
+  --color-card-foreground: var(--card-foreground);
+  --color-popover: var(--popover);
+  --color-popover-foreground: var(--popover-foreground);
+  --color-primary: var(--primary);
+  --color-primary-foreground: var(--primary-foreground);
+  --color-secondary: var(--secondary);
+  --color-secondary-foreground: var(--secondary-foreground);
+  --color-muted: var(--muted);
+  --color-muted-foreground: var(--muted-foreground);
+  --color-accent: var(--accent);
+  --color-accent-foreground: var(--accent-foreground);
+  --color-destructive: var(--destructive);
+  --color-border: var(--border);
+  --color-input: var(--input);
+  --color-ring: var(--ring);
+  --color-chart-1: var(--chart-1);
+  --color-chart-2: var(--chart-2);
+  --color-chart-3: var(--chart-3);
+  --color-chart-4: var(--chart-4);
+  --color-chart-5: var(--chart-5);
+  --color-sidebar: var(--sidebar);
+  --color-sidebar-foreground: var(--sidebar-foreground);
+  --color-sidebar-primary: var(--sidebar-primary);
+  --color-sidebar-primary-foreground: var(--sidebar-primary-foreground);
+  --color-sidebar-accent: var(--sidebar-accent);
+  --color-sidebar-accent-foreground: var(--sidebar-accent-foreground);
+  --color-sidebar-border: var(--sidebar-border);
+  --color-sidebar-ring: var(--sidebar-ring);
+  --font-sans: Poppins, sans-serif;
+  --font-mono: Fira Code, monospace;
+  --font-serif: Lora, serif;
+  --radius: 0.4rem;
+  --tracking-tighter: calc(var(--tracking-normal) - 0.05em);
+  --tracking-tight: calc(var(--tracking-normal) - 0.025em);
+  --tracking-wide: calc(var(--tracking-normal) + 0.025em);
+  --tracking-wider: calc(var(--tracking-normal) + 0.05em);
+  --tracking-widest: calc(var(--tracking-normal) + 0.1em);
+  --tracking-normal: var(--tracking-normal);
+  --shadow-2xl: var(--shadow-2xl);
+  --shadow-xl: var(--shadow-xl);
+  --shadow-lg: var(--shadow-lg);
+  --shadow-md: var(--shadow-md);
+  --shadow: var(--shadow);
+  --shadow-sm: var(--shadow-sm);
+  --shadow-xs: var(--shadow-xs);
+  --shadow-2xs: var(--shadow-2xs);
+  --spacing: var(--spacing);
+  --letter-spacing: var(--letter-spacing);
+  --shadow-offset-y: var(--shadow-offset-y);
+  --shadow-offset-x: var(--shadow-offset-x);
+  --shadow-spread: var(--shadow-spread);
+  --shadow-blur: var(--shadow-blur);
+  --shadow-opacity: var(--shadow-opacity);
+  --color-shadow-color: var(--shadow-color);
+  --color-destructive-foreground: var(--destructive-foreground);
+}
+
+:root {
+  --radius: 0.625rem;
+  --background: oklch(1 0 0);
+  --foreground: oklch(0.145 0 0);
+  --card: oklch(1 0 0);
+  --card-foreground: oklch(0.145 0 0);
+  --popover: oklch(1 0 0);
+  --popover-foreground: oklch(0.145 0 0);
+  --primary: oklch(0.205 0 0);
+  --primary-foreground: oklch(0.985 0 0);
+  --secondary: oklch(0.97 0 0);
+  --secondary-foreground: oklch(0.205 0 0);
+  --muted: oklch(0.97 0 0);
+  --muted-foreground: oklch(0.556 0 0);
+  --accent: oklch(0.97 0 0);
+  --accent-foreground: oklch(0.205 0 0);
+  --destructive: oklch(0.577 0.245 27.325);
+  --border: oklch(0.922 0 0);
+  --input: oklch(0.922 0 0);
+  --ring: oklch(0.708 0 0);
+  --chart-1: oklch(0.646 0.222 41.116);
+  --chart-2: oklch(0.6 0.118 184.704);
+  --chart-3: oklch(0.398 0.07 227.392);
+  --chart-4: oklch(0.828 0.189 84.429);
+  --chart-5: oklch(0.769 0.188 70.08);
+  --sidebar: oklch(0.985 0 0);
+  --sidebar-foreground: oklch(0.145 0 0);
+  --sidebar-primary: oklch(0.205 0 0);
+  --sidebar-primary-foreground: oklch(0.985 0 0);
+  --sidebar-accent: oklch(0.97 0 0);
+  --sidebar-accent-foreground: oklch(0.205 0 0);
+  --sidebar-border: oklch(0.922 0 0);
+  --sidebar-ring: oklch(0.708 0 0);
+  --destructive-foreground: oklch(1.0000 0 0);
+  --font-sans: Poppins, sans-serif;
+  --font-serif: Lora, serif;
+  --font-mono: Fira Code, monospace;
+  --shadow-color: hsl(325.78 58.18% 56.86% / 0.5);
+  --shadow-opacity: 1.0;
+  --shadow-blur: 0px;
+  --shadow-spread: 0px;
+  --shadow-offset-x: 3px;
+  --shadow-offset-y: 3px;
+  --letter-spacing: 0em;
+  --spacing: 0.25rem;
+  --shadow-2xs: 3px 3px 0px 0px hsl(325.7800 58.1800% 56.8600% / 0.50);
+  --shadow-xs: 3px 3px 0px 0px hsl(325.7800 58.1800% 56.8600% / 0.50);
+  --shadow-sm: 3px 3px 0px 0px hsl(325.7800 58.1800% 56.8600% / 1.00), 3px 1px 2px -1px hsl(325.7800 58.1800% 56.8600% / 1.00);
+  --shadow: 3px 3px 0px 0px hsl(325.7800 58.1800% 56.8600% / 1.00), 3px 1px 2px -1px hsl(325.7800 58.1800% 56.8600% / 1.00);
+  --shadow-md: 3px 3px 0px 0px hsl(325.7800 58.1800% 56.8600% / 1.00), 3px 2px 4px -1px hsl(325.7800 58.1800% 56.8600% / 1.00);
+  --shadow-lg: 3px 3px 0px 0px hsl(325.7800 58.1800% 56.8600% / 1.00), 3px 4px 6px -1px hsl(325.7800 58.1800% 56.8600% / 1.00);
+  --shadow-xl: 3px 3px 0px 0px hsl(325.7800 58.1800% 56.8600% / 1.00), 3px 8px 10px -1px hsl(325.7800 58.1800% 56.8600% / 1.00);
+  --shadow-2xl: 3px 3px 0px 0px hsl(325.7800 58.1800% 56.8600% / 2.50);
+  --tracking-normal: 0em;
+}
+
+.dark {
+  --background: oklch(0.145 0 0);
+  --foreground: oklch(0.985 0 0);
+  --card: oklch(0.205 0 0);
+  --card-foreground: oklch(0.985 0 0);
+  --popover: oklch(0.205 0 0);
+  --popover-foreground: oklch(0.985 0 0);
+  --primary: oklch(0.922 0 0);
+  --primary-foreground: oklch(0.205 0 0);
+  --secondary: oklch(0.269 0 0);
+  --secondary-foreground: oklch(0.985 0 0);
+  --muted: oklch(0.269 0 0);
+  --muted-foreground: oklch(0.708 0 0);
+  --accent: oklch(0.269 0 0);
+  --accent-foreground: oklch(0.985 0 0);
+  --destructive: oklch(0.704 0.191 22.216);
+  --border: oklch(1 0 0 / 10%);
+  --input: oklch(1 0 0 / 15%);
+  --ring: oklch(0.556 0 0);
+  --chart-1: oklch(0.488 0.243 264.376);
+  --chart-2: oklch(0.696 0.17 162.48);
+  --chart-3: oklch(0.769 0.188 70.08);
+  --chart-4: oklch(0.627 0.265 303.9);
+  --chart-5: oklch(0.645 0.246 16.439);
+  --sidebar: oklch(0.205 0 0);
+  --sidebar-foreground: oklch(0.985 0 0);
+  --sidebar-primary: oklch(0.488 0.243 264.376);
+  --sidebar-primary-foreground: oklch(0.985 0 0);
+  --sidebar-accent: oklch(0.269 0 0);
+  --sidebar-accent-foreground: oklch(0.985 0 0);
+  --sidebar-border: oklch(1 0 0 / 10%);
+  --sidebar-ring: oklch(0.556 0 0);
+  --destructive-foreground: oklch(0.2497 0.0305 234.1628);
+  --radius: 0.4rem;
+  --font-sans: Poppins, sans-serif;
+  --font-serif: Lora, serif;
+  --font-mono: Fira Code, monospace;
+  --shadow-color: #324859;
+  --shadow-opacity: 1.0;
+  --shadow-blur: 0px;
+  --shadow-spread: 0px;
+  --shadow-offset-x: 3px;
+  --shadow-offset-y: 3px;
+  --letter-spacing: 0em;
+  --spacing: 0.25rem;
+  --shadow-2xs: 3px 3px 0px 0px hsl(206.1538 28.0576% 27.2549% / 0.50);
+  --shadow-xs: 3px 3px 0px 0px hsl(206.1538 28.0576% 27.2549% / 0.50);
+  --shadow-sm: 3px 3px 0px 0px hsl(206.1538 28.0576% 27.2549% / 1.00), 3px 1px 2px -1px hsl(206.1538 28.0576% 27.2549% / 1.00);
+  --shadow: 3px 3px 0px 0px hsl(206.1538 28.0576% 27.2549% / 1.00), 3px 1px 2px -1px hsl(206.1538 28.0576% 27.2549% / 1.00);
+  --shadow-md: 3px 3px 0px 0px hsl(206.1538 28.0576% 27.2549% / 1.00), 3px 2px 4px -1px hsl(206.1538 28.0576% 27.2549% / 1.00);
+  --shadow-lg: 3px 3px 0px 0px hsl(206.1538 28.0576% 27.2549% / 1.00), 3px 4px 6px -1px hsl(206.1538 28.0576% 27.2549% / 1.00);
+  --shadow-xl: 3px 3px 0px 0px hsl(206.1538 28.0576% 27.2549% / 1.00), 3px 8px 10px -1px hsl(206.1538 28.0576% 27.2549% / 1.00);
+  --shadow-2xl: 3px 3px 0px 0px hsl(206.1538 28.0576% 27.2549% / 2.50);
+}
+
+@layer base {
+  * {
+    @apply border-border outline-ring/50;
+  }
+  body {
+    @apply bg-background text-foreground;
+    letter-spacing: var(--tracking-normal);
+  }
+}
+
+button {
+  cursor: pointer;
+}

web/src/types/video.ts

@@ -0,0 +1,22 @@
+export interface VideoData {
+  video_title: string;
+  video_url: string;
+  thumbnail_url: string;
+  classification: string;
+  language: string;
+  channel_name: string;
+  channel_link: string;
+  video_length_seconds: number;
+  video_date: string;
+  detailed_subtags: string;
+  playlist_name: string;
+  playlist_link: string;
+  image_data: string;
+  timestamp: string;
+}
+
+export interface FilterOptions {
+  classification: string[];
+  language: string[];
+  playlist_name: string[];
+}

web/src/utils/csvParser.ts

@@ -0,0 +1,41 @@
+import Papa from 'papaparse';
+import type { VideoData } from '../types/video';
+
+export function parseCSV(csvText: string): VideoData[] {
+  const result = Papa.parse<VideoData>(csvText, {
+    header: true,
+    skipEmptyLines: true,
+    transform: (value, field) => {
+      // Convert numeric fields
+      if (field === 'video_length_seconds') {
+        return parseInt(value) || 0;
+      }
+      return value;
+    }
+  });
+
+  if (result.errors.length > 0) {
+    console.warn('CSV parsing errors:', result.errors);
+  }
+
+  return result.data;
+}
+
+export function formatDuration(seconds: number): string {
+  const minutes = Math.floor(seconds / 60);
+  const remainingSeconds = seconds % 60;
+  return `${minutes}:${remainingSeconds.toString().padStart(2, '0')}`;
+}
+
+export function formatDate(dateString: string): string {
+  try {
+    const date = new Date(dateString);
+    return date.toLocaleDateString('en-US', {
+      year: 'numeric',
+      month: 'short',
+      day: 'numeric'
+    });
+  } catch {
+    return dateString;
+  }
+}

web/src/utils/search.ts

@@ -0,0 +1,57 @@
+import type { VideoData } from '../types/video';
+
+export function searchVideos(videos: VideoData[], searchTerm: string): VideoData[] {
+  if (!searchTerm.trim()) return videos;
+
+  const term = searchTerm.toLowerCase();
+  
+  return videos.filter(video => {
+    const searchableFields = [
+      video.video_title,
+      video.channel_name,
+      video.detailed_subtags,
+      video.classification,
+      video.language,
+      video.playlist_name,
+      video.video_length_seconds.toString(),
+      formatDateForSearch(video.video_date),
+      formatDateForSearch(video.timestamp)
+    ];
+
+    return searchableFields.some(field => 
+      field && field.toLowerCase().includes(term)
+    );
+  });
+}
+
+function formatDateForSearch(dateString: string): string {
+  try {
+    const date = new Date(dateString);
+    return date.toLocaleDateString('en-US');
+  } catch {
+    return dateString;
+  }
+}
+
+export function filterVideos(
+  videos: VideoData[], 
+  filters: { classification?: string; language?: string; playlist_name?: string }
+): VideoData[] {
+  return videos.filter(video => {
+    if (filters.classification && filters.classification !== 'all' && video.classification !== filters.classification) {
+      return false;
+    }
+    if (filters.language && filters.language !== 'all' && video.language !== filters.language) {
+      return false;
+    }
+    if (filters.playlist_name && filters.playlist_name !== 'all' && video.playlist_name !== filters.playlist_name) {
+      return false;
+    }
+    return true;
+  });
+}
+
+export function getUniqueValues(videos: VideoData[], field: keyof VideoData): string[] {
+  const values = videos.map(video => video[field] as string).filter(Boolean);
+  return [...new Set(values)].sort();
+}

web/tsconfig.json

@@ -0,0 +1,20 @@
+{
+  "extends": "astro/tsconfigs/strict",
+  "include": [
+    ".astro/types.d.ts",
+    "**/*"
+  ],
+  "exclude": [
+    "dist"
+  ],
+  "compilerOptions": {
+    "jsx": "react-jsx",
+    "jsxImportSource": "react",
+    "baseUrl": ".",
+    "paths": {
+      "@/*": [
+        "./src/*"
+      ]
+    }
+  }
+}