Features
Train VLA models in Solo Hub cloud
Train Small Language Models (SLMs) in cloud
Run SLMs locally with Solo Studio
Single-command deployment to robots
Sim-to-sim-to-real bridge for domain transfer
Integration with OpenClaw gripper hardware
Integration with Sonic AGIBot X2 humanoid
Physical AI Gym for testing models
Real-time inference and control loop
@ai_fn decorator for LLM-powered Python functions
@ai_classifier decorator for text classification
Structured data extraction via Pydantic models
Agent loops with tool calling and function calling
Built-in streaming (SSE) support
Async-first API for concurrent applications
Rate limiting and automatic retries
LLM response caching for performance
Concurrency control for workload management
CLI tool for monitoring and debugging
SQLite state store for persistence
OpenAI and Anthropic model support
Embeddings generation for semantic search
Local execution with no cloud dependency
Self-hosted deployable as a library
