# VideoAgent

## Dataset

Our VideoEdit benchmark dataset is available for download at [VideoEdit Dataset](https://drive.google.com/file/d/1RRsWS4HyZtY3O3Tof-lPDsK6YgFQtn2Z/view?usp=sharing).
## 🚀Quick Start

### 🖥️ **Environment**

```
GPU Memory: 8GB  
OS: Linux, Windows
```

### 📥 **Clone and Install**

```bash
conda create --name videoagent python=3.10
conda activate videoagent
conda install -y -c conda-forge pynini==2.1.5 ffmpeg
pip install -r requirements.txt
```

### 🤖 **LLM Configuration**

```bash
# VideoAgent\environment\config\config.yml
# Applicable scenarios and LLM configuration
# Claude is required as it powers the Agentic Graph Router 
llm:
  deepseek_api_key: ""  
  deepseek_base_url: ""  

  claude_api_key: ""  
  claude_base_url: ""

  gpt_api_key: ""  
  gpt_base_url: ""  

  gemini_api_key: ""  
  gemini_base_url: ""  
```

### 🎯 **Usage**

```bash
python main.py
# The console will output:
User Requirement: ...
# Requirement Example:
# 1. I need to create a reworded version of an existing video where the speech content is modified while maintaining the original speaker's voice. The video should have the same visuals as the original, but with updated dialogue that follows my specific requirements.
# 2. I have a standup comedy script that I'd like to turn into a professional-looking video. I need the script to be performed with good comedic timing and audience reactions, then matched with relevant video footage to create a complete standup comedy special. I already have a reference script and some footage I want to use for the video.
```
The current LLM selections are optimized for each function.
You can also adjust the model names in `VideoAgent\environment\config\llm.py` if needed.
