新增示例库逻辑

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# Configuration
After installation, you need to configure services to use Pixelle-Video.
---
## LLM Configuration
LLM (Large Language Model) is used to generate video scripts.
### Quick Preset Selection
1. Select a preset model from the dropdown:
- Qianwen (recommended, great value)
- GPT-4o
- DeepSeek
- Ollama (local, completely free)
2. The system will auto-fill `base_url` and `model`
3. Click「🔑 Get API Key」to register and obtain credentials
4. Enter your API Key
---
## Image Configuration
Two options available:
### Local Deployment (Recommended)
Using local ComfyUI service:
1. Install and start ComfyUI
2. Enter ComfyUI URL (default `http://127.0.0.1:8188`)
3. Click "Test Connection" to verify
### Cloud Deployment
Using RunningHub cloud service:
1. Register for a RunningHub account
2. Obtain API Key
3. Enter API Key in configuration
---
## Save Configuration
After filling in all required configuration, click the "Save Configuration" button.
Configuration will be saved to `config.yaml` file.
---
## Next Steps
- [Quick Start](quick-start.md) - Create your first video

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# Installation
This page will guide you through installing Pixelle-Video.
---
## System Requirements
### Required
- **Python**: 3.10 or higher
- **Operating System**: Windows, macOS, or Linux
- **Package Manager**: uv (recommended) or pip
### Optional
- **GPU**: NVIDIA GPU with 6GB+ VRAM recommended for local ComfyUI
- **Network**: Stable internet connection for LLM API and image generation services
---
## Installation Steps
### Step 1: Clone the Repository
```bash
git clone https://github.com/PixelleLab/Pixelle-Video.git
cd Pixelle-Video
```
### Step 2: Install Dependencies
!!! tip "Recommended: Use uv"
This project uses `uv` as the package manager, which is faster and more reliable than traditional pip.
#### Using uv (Recommended)
```bash
# Install uv if you haven't already
curl -LsSf https://astral.sh/uv/install.sh | sh
# Install project dependencies (uv will create a virtual environment automatically)
uv sync
```
#### Using pip
```bash
# Create virtual environment
python -m venv venv
# Activate virtual environment
# Windows:
venv\Scripts\activate
# macOS/Linux:
source venv/bin/activate
# Install dependencies
pip install -e .
```
---
## Verify Installation
Run the following command to verify the installation:
```bash
# Using uv
uv run streamlit run web/app.py
# Or using pip (activate virtual environment first)
streamlit run web/app.py
```
Your browser should automatically open `http://localhost:8501` and display the Pixelle-Video web interface.
!!! success "Installation Successful!"
If you can see the web interface, the installation was successful! Next, check out the [Configuration Guide](configuration.md) to set up your services.
---
## Optional: Install ComfyUI (Local Deployment)
If you want to run image generation locally, you'll need to install ComfyUI:
### Quick Install
```bash
# Clone ComfyUI
git clone https://github.com/comfyanonymous/ComfyUI.git
cd ComfyUI
# Install dependencies
pip install -r requirements.txt
```
### Start ComfyUI
```bash
python main.py
```
ComfyUI runs on `http://127.0.0.1:8188` by default.
!!! info "ComfyUI Models"
ComfyUI requires downloading model files to work. Please refer to the [ComfyUI documentation](https://github.com/comfyanonymous/ComfyUI) for information on downloading and configuring models.
---
## Next Steps
- [Configuration](configuration.md) - Configure LLM and image generation services
- [Quick Start](quick-start.md) - Create your first video

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# Quick Start
Already installed and configured? Let's create your first video!
---
## Start the Web Interface
```bash
# Using uv
uv run streamlit run web/app.py
```
Your browser will automatically open `http://localhost:8501`
---
## Create Your First Video
### Step 1: Check Configuration
On first use, expand the「⚙ System Configuration」panel and confirm:
- **LLM Configuration**: Select an AI model (e.g., Qianwen, GPT) and enter API Key
- **Image Configuration**: Configure ComfyUI address or RunningHub API Key
If not yet configured, see the [Configuration Guide](configuration.md).
Click "Save Configuration" when done.
---
### Step 2: Enter a Topic
In the left panel's「📝 Content Input」section:
1. Select「**AI Generate Content**」mode
2. Enter a topic in the text box, for example:
```
Why develop a reading habit
```
3. (Optional) Set number of scenes, default is 5 frames
!!! tip "Topic Examples"
- Why develop a reading habit
- How to improve work efficiency
- The importance of healthy eating
- The meaning of travel
---
### Step 3: Configure Voice and Visuals
In the middle panel:
**Voice Settings**
- Select TTS workflow (default Edge-TTS works well)
- For voice cloning, upload a reference audio file
**Visual Settings**
- Select image generation workflow (default works well)
- Set image dimensions (default 1024x1024)
- Choose video template (recommend portrait 1080x1920)
---
### Step 4: Generate Video
Click the「🎬 Generate Video」button in the right panel!
The system will show real-time progress:
- Generate script
- Generate images (for each scene)
- Synthesize voice
- Compose video
!!! info "Generation Time"
Generating a 5-scene video takes about 2-5 minutes, depending on: LLM API response speed, image generation speed, TTS workflow type, and network conditions
---
### Step 5: Preview Video
Once complete, the video will automatically play in the right panel!
You'll see:
- 📹 Video preview player
- ⏱️ Video duration
- 📦 File size
- 🎬 Number of scenes
- 📐 Video dimensions
The video file is saved in the `output/` folder.
---
## Next Steps
Congratulations! You've successfully created your first video 🎉
Next, you can:
- **Adjust Styles** - See the [Custom Visual Style](../tutorials/custom-style.md) tutorial
- **Clone Voices** - See the [Voice Cloning with Reference Audio](../tutorials/voice-cloning.md) tutorial
- **Use API** - See the [API Usage Guide](../user-guide/api.md)
- **Develop Templates** - See the [Template Development Guide](../user-guide/templates.md)