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2 changes: 1 addition & 1 deletion .github/workflows/pr-test.yml
Original file line number Diff line number Diff line change
Expand Up @@ -352,7 +352,7 @@ jobs:
volume_size: 100
disk_size: 100
image: "ghcr.io/${{ github.repository }}/fastvideo-dev:py3.12-latest"
test_command: "uv pip install -e .[test] && pytest ./fastvideo/dataset/ -vs && pytest ./fastvideo/workflow/ -vs"
test_command: "uv pip install -e .[test] && pytest ./fastvideo/dataset/ -vs && pytest ./fastvideo/workflow/ -vs && pytest ./fastvideo/entrypoints/ -vs"
timeout_minutes: 30
secrets:
RUNPOD_API_KEY: ${{ secrets.RUNPOD_API_KEY }}
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18 changes: 18 additions & 0 deletions assets/full.svg
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56 changes: 56 additions & 0 deletions examples/inference/gradio/local/README.md
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# FastVideo Gradio Local Demo

This is a Gradio-based web interface for generating videos using the FastVideo framework. The demo allows users to create videos from text prompts with various customization options.

## Overview

The demo uses the FastVideo framework to generate videos based on text prompts. It provides a simple web interface built with Gradio that allows users to:

- Enter text prompts to generate videos
- Customize video parameters (dimensions, number of frames, etc.)
- Use negative prompts to guide the generation process
- Set or randomize seeds for reproducibility

---

## Usage

Run the demo with:

```bash
python examples/inference/gradio/local/gradio_local_demo.py
```

This will start a web server at `http://0.0.0.0:7860` where you can access the interface.

---

## Model Initialization

This demo initializes a `VideoGenerator` with the minimum required arguments for inference. Users can seamlessly adjust inference options between generations, including prompts, resolution, video length, *without ever needing to reload the model*.

## Video Generation

The core functionality is in the `generate_video` function, which:
1. Processes user inputs
2. Uses the FastVideo VideoGenerator from earlier to run inference (`generator.generate_video()`)

## Gradio Interface

The interface is built with several components:
- A text input for the prompt
- A video display for the result
- Inference options in a collapsible accordion:
- Height and width sliders
- Number of frames slider
- Guidance scale slider
- Negative prompt options
- Seed controls

### Inference Options

- **Height/Width**: Control the resolution of the generated video
- **Number of Frames**: Set how many frames to generate
- **Guidance Scale**: Control how closely the generation follows the prompt
- **Negative Prompt**: Specify what you don't want to see in the video
- **Seed**: Control randomness for reproducible results
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