Solo Server

Solo Server is a command-line tool that simplifies the creation and management of AI model servers for various modalities such as text, images, audio, and video. It provides easy-to-use templates and an interactive setup to help you quickly start projects and deploy AI models without hassle.

Features

• Quick Project Initialization: Start new AI server projects rapidly with built-in templates.
• Multi-Modality Support: Templates available for text (LLM), computer vision, audio processing, video processing, tabular data, and more.
• Interactive CLI: User-friendly prompts guide you through project setup.
• Optional Components: Install only the components you need using pip extras (e.g., [llm], [cv], [all]).
• Simple Server Management: Easily start, stop, and manage your server with straightforward commands.
• Extensible Templates: Customize existing templates or add new ones to suit your specific needs.
• Deployment Ready: Package your application into Docker containers for easy deployment.

Installation

Solo Server requires Python 3.7 or higher.

Install Core Package

pip install solo-server

Install with Optional Components

If you need support for specific AI modalities, install the corresponding extras:

• Language Models (LLM):

  pip install solo-server[llm]

• Computer Vision (CV):

  pip install solo-server[cv]

• Audio Processing:

  pip install solo-server[audio]

• All Components:

  pip install solo-server[all]

Getting Started

Initialize a New Project

Run the init command to start a new project. This will guide you through an interactive setup.

solo-server init

Example Interaction:

Welcome to Solo Server Project Initialization!
----------------------------------------------
Enter your project name [my_project]: my_ai_project
Choose a project template [basic]: llm
Project 'my_ai_project' initialized successfully!

Navigate to Your Project

cd my_ai_project

Install Project Dependencies

pip install -r requirements.txt

Run the Server

solo-server start

Your server should now be running at http://localhost:8000.

Templates

Solo Server provides several templates to kickstart your project:

• basic: A minimal project setup.
• llm: Language models and text processing.
• cv: Computer vision projects.
• audio: Audio analysis and speech recognition.
• multimodal: Combining multiple data types (e.g., text and images).
• tabular: Data analysis on tabular datasets.
• video: Video processing and analysis.
• compound: Complex projects involving multiple AI components.

Core Commands

• solo-server init: Initialize a new project with an interactive setup.
• solo-server start: Start the server for the current project.
• solo-server stop: Stop the running server.
• solo-server restart: Restart the server.
• solo-server status: Check the status of the server.
• solo-server install: Install project dependencies.
• solo-server config: Manage project configuration.
  • solo-server config init: Generate a default configuration file.
  • solo-server config show: Display the current configuration.
  • solo-server config set <parameter> <value>: Set a configuration parameter.
• solo-server generate: Generate code snippets or files based on templates.
  • solo-server generate <type> <name>: Generate a new component (e.g., endpoint, model).
• solo-server help: Display help information about commands.

Examples

Example: Creating a Language Model Server

1. Initialize the Project

   solo-server init

   Select the llm template.

2. Install Dependencies

   pip install -r requirements.txt

3. Run the Server

   solo-server start

4. Test the Endpoint

   Send a POST request to the server:

   curl -X POST -H "Content-Type: application/json" \
        -d '{"prompt": "Hello, world!"}' \
        http://localhost:8000

Example: Packaging Your Application into a Docker Container

1. Create a Dockerfile

   # Dockerfile
   
   FROM python:3.9-slim
   
   WORKDIR /app
   
   COPY requirements.txt .
   
   RUN pip install --no-cache-dir -r requirements.txt
   
   COPY . .
   
   EXPOSE 8000
   
   CMD ["solo-server", "start"]

2. Build the Docker Image

   docker build -t my-ai-server .

3. Run the Docker Container

   docker run -p 8000:8000 my-ai-server

Contributing

Contributions are welcome! Please read the contributing guidelines before submitting a pull request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

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