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https://github.com/kazkozdev/video-analyser
⚡ The YouTube Video Analyzer Pro brings AI-powered analysis capabilities to your fingertips, offering deep insights for content creators and marketers.
https://github.com/kazkozdev/video-analyser
ai content-analytics fastapi llama3 llm ollama-api python3 video-analysis video-analysis-client whisper youtube youtube-analytics youtube-api youtube-subscribers
Last synced: 18 days ago
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⚡ The YouTube Video Analyzer Pro brings AI-powered analysis capabilities to your fingertips, offering deep insights for content creators and marketers.
- Host: GitHub
- URL: https://github.com/kazkozdev/video-analyser
- Owner: KazKozDev
- License: mit
- Created: 2024-11-10T16:23:48.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2024-11-13T21:04:48.000Z (3 months ago)
- Last Synced: 2025-01-13T03:15:18.738Z (18 days ago)
- Topics: ai, content-analytics, fastapi, llama3, llm, ollama-api, python3, video-analysis, video-analysis-client, whisper, youtube, youtube-analytics, youtube-api, youtube-subscribers
- Language: Python
- Homepage:
- Size: 5.81 MB
- Stars: 2
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# YouTube Video Analyzer Pro
[](https://fastapi.tiangolo.com)
[](https://www.python.org)
[](https://openai.com/research/whisper)
[](https://ai.meta.com/llama/)
[](https://opensource.org/licenses/MIT)
[](https://github.com/KazKozDev/video-analyser/pulls)
[](https://developers.google.com/youtube/v3)
[](https://github.com/KazKozDev/video-analyser)
## 🌟 Overview
YouTube Video Analyzer Pro is a cutting-edge tool that brings professional-grade video analysis capabilities to content creators and viewers alike. Leveraging advanced AI technologies, it provides deep insights into video content, audience engagement, and market positioning.
## ✨ Key Features
### 🧠 AI-Powered Content Analysis
- **Smart Summarization**
- Generate concise, intelligent video summaries using Llama 3.2 AI
- Extract key topics and main points automatically
- Identify crucial timestamps and segments
### 🎯 Advanced Transcription System
- **Multi-Layer Transcription**
- Primary: YouTube's native transcription API
- Backup: Whisper AI for videos without existing transcripts
- Smart timestamps with topic segmentation
- Custom processing for cleaner output
## 🎬 Demo Preview
### 🌍 Professional Translation Hub
- **Enterprise-Grade Translation Support**
```
🇬🇧 English → Source Language
🇪🇸 Spanish → Native Quality
🇫🇷 French → Professional Grade
🇩🇪 German → High Accuracy
🇮🇹 Italian → Natural Flow
🇷🇺 Russian → Precise Translation
```
### 💬 Comment Intelligence
- **Sentiment Analysis**
- Emotional tone detection in comments
- Key themes and patterns identification
- Audience sentiment tracking
- Controversy detection
- **Engagement Metrics**
- Comment frequency analysis
- User interaction patterns
- Community feedback categorization
- **Strategic Insights**
- Viewer pain points identification
- Content improvement suggestions
- Community engagement opportunities
### 🔍 Content Discovery Engine
- **Channel Analysis**
- Similar video recommendations
- Content pattern detection
- Performance metric tracking
- **Competitor Intelligence**
- Related content from other creators
- Niche trend analysis
- Market positioning insights
## 🛠️ Technology Stack
### Backend Infrastructure
```mermaid
graph TD
A[FastAPI] --> B[Python 3.9+]
B --> C[YouTube Data API]
B --> D[AI Models]
D --> E[Whisper AI]
D --> F[Llama 3.2]
```
### AI Processing Pipeline
- **Speech Recognition**: Whisper AI
- **Content Analysis**: Llama 3.2 (Ollama llama3.2-vision:11b model)
- **Translation Engine**: Custom AI Pipeline
- **Comment Analysis**: Advanced NLP Models
### Frontend Architecture
- **Framework**: React
- **UI Components**: Modern Material Design
- **Data Visualization**: Dynamic Charts
- **Responsive Design**: Mobile-First Approach
## ⚡ Performance & Scalability
### Free Tier Benefits
- Full access to all features
- Unlimited video analysis
- Complete comment processing
- All languages supported
### ⚡ Processing Times
| Operation | Short Videos (<10min) | Long Videos (>10min) |
|-----------|---------------------|-------------------|
| 🔍 Basic Analysis | ~30 seconds | 1-2 minutes |
| 📝 Transcription | 1-2 minutes | 3-5 minutes |
| 🌍 Translation | 2-3 minutes | 5-10 minutes |
| 💬 Comment Analysis | 1-2 minutes | 2-3 minutes |
Note: Processing times may vary depending on server load and video complexity. All operations run locally for maximum privacy and security.
## 🚀 Getting Started
### System Requirements
- Python 3.9+
- 8GB RAM minimum
- GPU recommended for faster processing
- YouTube API Key
- Ollama installed (for Llama 3.2 model)
### Installing Ollama and Llama Model
1. **Install Ollama**
```bash
# For Linux/WSL
curl -fsSL https://ollama.com/install.sh | sh
# For macOS
brew install ollama
# For Windows
# Download from https://ollama.com/download
```
2. **Download Llama Model**
```bash
# Start Ollama service
ollama serve
# In a new terminal, pull the model
ollama pull llama3.2-vision:11b
```
Note: The model is approximately 11GB in size, so ensure you have sufficient disk space and a stable internet connection.
### Quick Start
1. **Clone & Setup**
```bash
git clone https://github.com/KazKozDev/video-analyser.git
cd video-analyser
```
2. **Environment Setup**
```bash
python -m venv venv
source venv/bin/activate # Windows: venv\Scripts\activate
pip install -r requirements.txt
```
3. **Configuration**
```bash
cp .env.example .env
# Add your YouTube API key to .env
```
4. **Launch**
```bash
uvicorn server:app --reload
```
Visit `http://localhost:8000` and start analyzing! 🎉
## 📊 Use Cases
### Content Creators
- **Channel Optimization**
- Content performance analysis
- Audience retention insights
- Engagement optimization
- Competitor research
- Multilingual reach expansion
### Marketing Teams
- **Market Research**
- Trend analysis
- Competitor tracking
- Audience insights
- Content strategy development
### Researchers & Analysts
- **Data Collection**
- Transcript extraction
- Comment analysis
- Engagement metrics
- Cross-channel comparisons
## 🤝 Contributing
We welcome contributions! Check our [Contributing Guide](https://github.com/KazKozDev/video-analyser/blob/main/CONTRIBUTING.md) for more information.
1. Fork the repo
2. Create a feature branch
```bash
git checkout -b feature/amazing-feature
```
3. Commit changes
```bash
git commit -m 'Add amazing feature'
```
4. Push to the branch
```bash
git push origin feature/amazing-feature
```
5. Open a Pull Request
## 📝 License
Distributed under the MIT License. See [LICENSE](https://github.com/KazKozDev/video-analyser/blob/main/LICENSE) for more information.
## 🙏 Acknowledgments
- OpenAI for the incredible Whisper AI
- Meta for Llama 3.2
- YouTube API Team
- All contributors and supporters
## ⭐ Support the Project
If you found this tool useful, consider:
- Giving it a star ⭐
- Sharing it with others
- Contributing to its development
- Reporting issues or suggesting features
## 📧 Contact
KazKozDev - [@KazKozDev](https://github.com/KazKozDev)
Project Link: [https://github.com/KazKozDev/video-analyser](https://github.com/KazKozDev/video-analyser)
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