# VideoWorkFlow

**Repository Path**: varlorchristie/video-work-flow

## Basic Information

- **Project Name**: VideoWorkFlow
- **Description**: 全自动Ai视频工作台
- **Primary Language**: Unknown
- **License**: Apache-2.0
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 2
- **Forks**: 0
- **Created**: 2026-05-06
- **Last Updated**: 2026-05-13

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README



# Video Work Flow

A desktop application for building and running AI-powered video and image generation workflows, built with Tauri and React.

## Features

- **Visual Workflow Editor** - Drag-and-drop nodes to create complex AI generation pipelines
- **Multi-Provider Support** - Connect to various LLM providers (OpenAI, Ollama, LM Studio, etc.)
- **ComfyUI Integration** - Generate images and videos using ComfyUI workflows
- **Real-time Execution** - Monitor workflow execution with live status updates
- **Execution History** - Track and review past workflow runs
- **Output Management** - View and manage generated files

## Tech Stack

- **Frontend**: React + TypeScript + React Flow
- **Backend**: Tauri (Rust)
- **Database**: SQLite

## Getting Started

### Prerequisites

- Node.js 18+
- Rust 1.70+
- pnpm

### Installation

```bash
# Install dependencies
pnpm install

# Build the application
pnpm tauri build
```

### Development

```bash
# Start frontend dev server
pnpm dev

# Start Tauri dev mode
pnpm tauri dev
```

## Project Structure

```
src/                    # React frontend
  components/           # UI components
  hooks/                # Custom React hooks
  stores/               # State management
  utils/                # Utility functions
src-tauri/              # Rust backend
  src/
    comfyui.rs          # ComfyUI API client
    db.rs               # Database operations
    executor.rs         # Workflow execution engine
    provider.rs         # LLM provider management
    workflow.rs         # Workflow definitions
```

## Usage

1. **Add a Provider**: Go to Settings → Providers to add your LLM provider
2. **Create a Workflow**: Use the visual editor to add nodes and connect them
3. **Run Workflow**: Click the run button to execute your workflow
4. **View Outputs**: Check the Output Files section for generated content

## License

MIT