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73 lines
1.7 KiB
Markdown
73 lines
1.7 KiB
Markdown
# YouTube Summarizer by TCSenpai
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YouTube Summarizer is a Streamlit-based web application that allows users to generate summaries of YouTube videos using AI-powered language models.
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## Features
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- Fetch and cache YouTube video transcripts
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- Summarize video content using Ollama AI models
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- Display video information (title and channel)
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- Customizable Ollama URL and model selection
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## Installation
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1. Clone the repository:
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```
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git clone https://github.com/yourusername/youtube-summarizer.git
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cd youtube-summarizer
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```
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2. Install the required dependencies:
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```
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pip install -r requirements.txt
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```
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3. Set up environment variables:
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Create a `.env` file in the root directory and add the following:
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```
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YOUTUBE_API_KEY=your_youtube_api_key
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OLLAMA_MODEL=default_model_name
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```
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## Usage
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1. Run the Streamlit app:
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```
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streamlit run src/main.py
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```
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2. Open your web browser and navigate to the provided local URL (usually `http://localhost:8501`).
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3. Enter a YouTube video URL in the input field.
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4. (Optional) Customize the Ollama URL and select a different AI model.
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5. Click the "Summarize" button to generate a summary of the video.
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## Dependencies
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- Streamlit
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- Pytube
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- Ollama
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- YouTube Data API
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- Python-dotenv
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## Project Structure
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- `src/main.py`: Main Streamlit application
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- `src/ollama_client.py`: Ollama API client for model interaction
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- `src/video_info.py`: YouTube API integration for video information
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- `transcript_cache/`: Directory for caching video transcripts
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## Contributing
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Contributions are welcome! Please feel free to submit a Pull Request.
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## License
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WTFPL License
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## Credits
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Icon: "https://www.flaticon.com/free-icons/subtitles" by Freepik - Flaticon |