WaveSpeed AI Open Source
Explore our open-source projects and contribute to the future of AI. From high-performance attention mechanisms to serverless deployment frameworks.
waverless
by WaveSpeedAI
Serverless deployment framework for WaveSpeed AI models, enabling scalable and cost-effective AI inference.
Key Features:
- •Serverless architecture
- •Auto-scaling capabilities
- •Pay-per-use pricing model
- •Easy deployment and management
Project Goal:
To make AI model deployment effortless and cost-effective through serverless infrastructure, reducing operational overhead.
ParaAttention
by chengzeyi
A high-performance parallel attention mechanism implementation for large-scale AI models.
Key Features:
- •Optimized attention computation for transformer models
- •Parallel processing capabilities for faster inference
- •Memory-efficient implementation
- •Compatible with popular deep learning frameworks
Project Goal:
To accelerate attention mechanisms in large language models and vision transformers, enabling faster training and inference times.
wavespeed-desktop
by WaveSpeedAI
Cross-platform desktop application for WaveSpeed AI, bringing AI capabilities to your local machine.
Key Features:
- •Cross-platform support (Windows, macOS, Linux)
- •Local and cloud model execution
- •Intuitive user interface
- •Offline capabilities
Project Goal:
To deliver a powerful desktop experience that combines the convenience of local execution with the scalability of cloud computing.
wavespeed-python
by WaveSpeedAI
Official Python SDK for WaveSpeed AI, providing easy access to our AI models and services.
Key Features:
- •Comprehensive API coverage
- •Type-safe implementations
- •Async/await support
- •Detailed documentation and examples
Project Goal:
To empower Python developers with a robust, easy-to-use SDK for integrating WaveSpeed AI into their applications.
Comfy-WaveSpeed
by chengzeyi
WaveSpeed AI integration for ComfyUI, bringing powerful AI models to the ComfyUI workflow.
Key Features:
- •Seamless ComfyUI integration
- •Access to WaveSpeed AI models
- •Custom nodes for image and video generation
- •Easy-to-use workflow components
Project Goal:
To bridge WaveSpeed AI's powerful models with ComfyUI's intuitive workflow interface, making advanced AI accessible to creators.
wavespeed-comfyui
by WaveSpeedAI
Official WaveSpeed AI nodes and extensions for ComfyUI, providing native support for our AI models.
Key Features:
- •Native WaveSpeed AI model support
- •Optimized inference nodes
- •Batch processing capabilities
- •Advanced parameter controls
Project Goal:
To provide the best-in-class ComfyUI experience with WaveSpeed AI models, optimized for performance and ease of use.
agent-mcp-lab
by WaveSpeedAI
An experimental laboratory for Multi-Agent Communication Protocol (MCP) development and testing.
Key Features:
- •Multi-agent communication framework
- •Protocol testing environment
- •Agent behavior simulation
- •Extensible agent architecture
Project Goal:
To research and develop robust multi-agent communication protocols that enable AI agents to collaborate effectively on complex tasks.
