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lovia

A lightweight, elegant, provider-neutral Agent framework for Python. Start with one Agent and typed Tools. Add streaming, persistence, context management, plugins, a Workspace, or a Web UI only when the application needs them.

pip install lovia

from lovia import Agent

agent = Agent(
    name="assistant",
    instructions="Explain complex science with vivid, everyday analogies.",
    model="<model>",
)

result = agent.run_sync("Explain why the sky is blue in three sentences.")
print(result.output)

Build your first Agent → Try the Web UI →

Why lovia

  • A small, deliberate core

    The core needs only an HTTP client and a data-validation library; integrations stay opt-in.

  • A loop you can follow

    Model Turns, Tool calls, retries, and failures follow one explicit path. Typed events and the canonical Transcript show exactly what happened.

  • Context without rewritten history

    Compaction changes only the next provider view. The complete record stays intact, while stable prompt prefixes keep provider caches useful.

  • One extension model

    Skills, MCP, Todo, and Memory use the same Plugin seam available to your own capabilities, instead of growing separate integration systems.

Choose a path

I want to… Start here Then add
Build my first Agent Quickstart Agents, Running agents
Connect a model or gateway Quickstart Providers & models
Give the model capabilities Tools Built-in tools, Workspace
Build a longer-running assistant Plugins Skills, Todo, Memory
Make Runs production-ready Provider retries Budgets, Sessions, Guardrails
Add a chat experience Web UI Web server, HTTP API
Test behavior Testing Evals, Observability

Learn from runnable examples

The repository examples form a feature-by-feature learning path. Every script is small enough to copy and modify:

Documentation version

This site follows the current main branch. Compare it with your installed version using python -c "import lovia; print(lovia.__version__)".

For contributors

The architecture notes document the module map, RunLoop, Transcript invariants, Plugins, persistence, and context compaction.

中文文档：docs/zh。