Lauren AI

lauren-ai is the official AI/LLM companion to the Lauren web framework. It brings large language model agents into the same decorator-first, DI-driven, module-scoped programming model that the rest of Lauren uses.

@tool()
async def get_weather(city: str) -> dict:
    """Get current weather for a city.

    Args:
        city: The city name, e.g. 'London'.
    """
    return {"city": city, "temperature_c": 18, "condition": "cloudy"}


@agent(model="claude-opus-4-6", system="You are a helpful travel assistant.")
@use_tools(get_weather)
class TravelAgent: ...

Why lauren-ai?

• No global singletons — all LLM clients, agent runners, and vector stores live in the DI container
• Provider-agnostic — swap Anthropic, OpenAI, Ollama, or LiteLLM behind an identical Transport interface
• Streaming is first-class — every token, tool result, and agent turn streams through EventStream or SSE
• Testable without network calls — MockTransport + AgentTestClient = fast, deterministic CI
• Same patterns you already know — @tool() feels like @injectable(), @agent() feels like @interceptor()

Get started

• Installation
• Quick Start
• First Agent