Omniparser

🚀 OmniMCP Project Documentation

OmniMCP is a project that offers a range of functionalities. This documentation provides detailed guidance on installation, configuration, usage, and more, helping users quickly get started with the project.

🚀 Quick Start

For a quick start, you can follow the installation steps below and then start using the project.

📦 Installation

Installation Steps

1. Clone the Repository

git clone git@github.com:OpenAdaptAI/OmniMCP.git
cd OmniMCP

2. Install Dependencies Use the following command to install the required Python packages:

pip install -r requirements.txt

3. Configure Environment Variables Create or edit the .env file and add the following content:

# Required Configuration
PROJECT_ROOT=.
LOG_LEVEL=INFO  # Optional: DEBUG, INFO, WARNING, ERROR, CRITICAL

# Optional Configuration
API_KEY=your_api_key_here
MODEL_NAME=gpt-3.5-turbo

4. Run the Project Start the project:

python -m OmniMCP.main

📚 Documentation

Environment Variable Reference

Configuration File Example

# Required Configuration
PROJECT_ROOT=/path/to/OmniMCP

# Log Settings
LOG_LEVEL=DEBUG  # More detailed debug information

# Model and API Settings
MODEL_NAME=gpt-4
API_KEY=your_api_key_here

💻 Usage Examples

Basic Usage

from OmniMCP import main, config

# Initialize the configuration
config.init()

# Run the main program
main.run()

Advanced Usage

Run the project from the command line:

python -m OmniMCP.main [--help] [-c CONFIG_PATH]

Parameter Description

🔧 Technical Details

Logging

The project supports multiple log levels:

• DEBUG: Displays detailed debug information.
• INFO: Displays regular information messages.
• WARNING: Displays warning messages.
• ERROR: Displays error messages.
• CRITICAL: Displays critical error messages.

The log output format is [Time] - [Level] - [Module]: Message, and it is output to the console and files by default.

Precautions

⚠️ Important Note

• Ensure that all environment variables are correctly configured before using the project in a production environment.
• The project depends on a stable network connection and a valid API key.
• If you encounter any issues, refer to the Troubleshooting section or contact the maintenance team.

Troubleshooting

Common Issues

1. Unable to start the project
   • Check if the configuration file is correct.
   • Ensure that all dependencies are installed.
   • Check the log files for more information.
2. API request fails
   • Confirm that the API key is valid.
   • Check the network connection.
   • Try changing the model name.

Contribution Guidelines

How to Contribute Code

1. Clone the repository

git clone git@github.com:OpenAdaptAI/OmniMCP.git
cd OmniMCP

2. Create a feature branch

git checkout -b feature/new-feature

3. Commit changes

git add .
git commit -m "Add new feature"
git push origin feature/new-feature

4. Submit a pull request Create a Pull Request on GitHub and describe your changes.

Contribution Guidelines

💡 Usage Tip

• Ensure that your code style is consistent with the project.
• Follow the Commit Specification for commit messages.
• If you encounter issues or have suggestions for improvement, open an Issue.

📄 License

This project is licensed under the MIT License:

MIT License

Contact Information

If you need to contact the maintenance team, please send an email to: contact@OmniMCP.com or visit the project homepage: https://github.com/OpenAdaptAI/OmniMCP