https://github.com/apreshill/pxt-primetime
https://github.com/apreshill/pxt-primetime
Last synced: 5 months ago
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- Host: GitHub
- URL: https://github.com/apreshill/pxt-primetime
- Owner: apreshill
- Created: 2025-12-10T21:29:09.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2025-12-16T22:06:16.000Z (6 months ago)
- Last Synced: 2025-12-19T15:45:49.445Z (6 months ago)
- Language: Jupyter Notebook
- Size: 58.6 MB
- Stars: 2
- Watchers: 0
- Forks: 0
- Open Issues: 1
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Metadata Files:
- Readme: README.md
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README
# pxt-primetime
Build multimodal AI applications with Pixeltable. Learn data-centric workflows, semantic search, and content generation using video as an example.
## Prerequisites
- Python 3.10+
- [uv](https://docs.astral.sh/uv/) - Fast Python package installer (`pip install uv` or `brew install uv`)
- [ffmpeg](https://ffmpeg.org/) - Required for video processing (`brew install ffmpeg` on macOS, `apt install ffmpeg` on Linux)
## Setup
1. Clone this repo and navigate to it:
```bash
git clone
cd pxt-primetime
```
2. Create a virtual environment and install all dependencies:
```bash
uv sync
```
This will automatically install all dependencies listed above.
**If you already have Pixeltable installed**, `uv sync` will upgrade it to the required version (>=0.5.6) along with all other dependencies.
3. Configure API keys (optional, but recommended):
- **Gemini API Key** (recommended): Required for video generation in `03_generate-from-data.ipynb`. You can use the [free tier](https://ai.google.dev/gemini-api/docs/pricing). Set as environment variable:
```bash
export GEMINI_API_KEY='your-api-key-here'
```
Or the notebook will prompt you to enter it when you run it.
- **OpenAI API Key** (optional): For faster transcription using OpenAI's Whisper API instead of the local model. Set as environment variable:
```bash
export OPENAI_API_KEY='your-api-key-here'
```
**Security Note**: Keep your keys secure by using environment variables, never commit them to git, and delete unused keys.
4. Open VS Code/Cursor in this project folder (or reload if already open)
## Dependencies
All dependencies are automatically installed when you run `uv sync` (see Setup section above). This project uses **Pixeltable v0.5.6**. The following is a reference of what gets installed - you don't need to install these manually:
### Core Dependencies
* **pixeltable** (>=0.5.6): Primary library for this project. Provides table, view, and computed column functionality.
### Video Processing
* **opencv-python**: Required for video processing operations
* **scenedetect**: Required for scene boundary detection in videos
* **pytube**: For downloading videos from YouTube (if needed)
### Text Processing & Embeddings
* **sentence-transformers** (>=2.0.0): Required for Hugging Face sentence embeddings
* Used in: `02_iterating-with-data.ipynb` - creating embedding indexes on transcript text
### Audio Processing & Transcription
* **openai-whisper**: Required for local Whisper transcription (`pxt.functions.whisper.transcribe()`)
* Used in: `02_iterating-with-data.ipynb` - transcribing audio chunks
* **openai** (optional): For OpenAI Whisper API transcription (`pxt.functions.openai.transcriptions()`)
* Used in: `02_iterating-with-data.ipynb` - faster transcription alternative (requires API key)
* Note: Install separately with `uv add openai` if you want to use the OpenAI API instead of local Whisper
### Video Generation
* **google-genai**: Required for Gemini video generation (`pxt.functions.gemini.generate_videos()`)
* Used in: `03_generate-from-data.ipynb` - generating intro/outro videos using Gemini's Veo model
* Requires: Gemini API key (free tier available)
### Development
* **ipykernel**: For running Jupyter notebooks
* **jupyter**: For notebook interface
## Notebooks
This project contains three progressive notebooks that build on each other. **Run them in order** (Act 1 → Act 2 → Act 3) as each notebook depends on tables and data created in previous notebooks:
- `01_data-centric-workflows.ipynb` - Act 1: Data-centric Workflows
- `02_iterating-with-data.ipynb` - Act 2: Iterating with Data
- `03_generate-from-data.ipynb` - Act 3: Generate New Content from Data
## Running Notebooks
1. Open a notebook
2. Click the kernel selector in the top-right corner
3. Select the kernel showing `.venv` with the full path to this project's `.venv/bin/python`
- Look for the path that includes `/pxt-primetime/.venv/bin/python`
- This confirms you're using this project's environment, not another venv or system Python