Autogen Video Refinement

The application is tailored to transform extended videos into succinct yet informative clips. It's a valuable tool for editors tasked with navigating through hours of footage, enabling them to streamline the process and craft engaging short films or highlight reels more efficiently.

Features

📥 Download Video: Downloads a video file from a provided link.
🗣️ Speech Recognition: Utilizes the whisper model to extract utterances from the video and converts them to text, saving the transcription as a script file.
⏱️ Video Duration: Determines the duration of the video.
📝 Short Transcription: Creates a short transcription from the full transcription that highlights the best parts of the video.
🎥 Short Video Creation: Creates a short video by joining segments from the original video based on the short transcription.

Tecnologies Used:

MoviePy - Video editing library
PyAutoGen - Library for automating software tasks. (Microsoft Autogen)
Whisper - Automatic speech recognition model
OpenAI - API for interacting with OpenAI services.

Installation

Prerequisites:

Python (3.7 or later): Download and install Python from https://www.python.org/downloads/ if you haven't already.
Virtual Environment (Recommended): It's highly recommended to create a virtual environment to isolate project dependencies. Here's how to create one using venv:

Bash
```
python -m venv venv
source venv/bin/activate  # macOS/Linux
venv\Scripts\activate.bat  # Windows
```

Installation:

Clone the Repository: Use git to clone the project from GitHub:

Bash

git clone https://github.com/langschain/Autogen_Video_Refinement.git
cd Autogen_Video_Refinement

Install Dependencies: Navigate to the project directory and install required packages using pip:

Bash
```
pip install -r requirements.txt
```
This will install autogen, whisper, moviepy, requests, openai, pydantic, and dotenv.

Optional: API Keys

OpenAI API Key: If you plan to use OpenAI's GPT-3 functionality, obtain an API key from https://beta.openai.com/account/api-keys and set the OPENAI_API_KEY environment variable in your .env file (create one if it doesn't exist).

Running the Application:

Create a .env File (Optional):
- Create a file named .env in the project's root directory.
- Add any environment variables required by the project, such as OPENAI_API_KEY. For example:
  
  OPENAI_API_KEY=your_openai_api_key
Load Environment Variables:
- Uncomment the load_dotenv() line at the beginning of the main.py script to load variables from the .env file.
Execute the Script:
- Run the main.py script using Python:
  
  Bash
```
python main.py
```

Additional Notes:

The code includes comments and docstrings to enhance readability.
Consider using a linter or code formatter to maintain consistent style.

Usage

Add a video url in the autogen's final prompt. Sample Video Link

https://github.com/langschain/Autogen_Video_Refinement/raw/master/sample_video.mp4

License

MIT License

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.