minmo

Boilerplate-free SDK for building voice agents on AssemblyAI's Voice Agent API, with support for Hume, OpenAI Realtime, and ElevenLabs too.

Define a prompt, register Python functions as tools, deploy. minmo handles JSON-Schema generation, local tool hosting + tunneling, and talking to each provider's REST API — so you write the assistant, not the plumbing.

📖 Full documentation

Install

pip install minmo

(Contributing or want an editable checkout instead? pip install -e ".[dev]" after cloning.)

(Set NGROK_AUTHTOKEN in your environment if you plan to use local=True — see pyngrok's docs for how to get one.)

Quickstart

from minmo import VoiceAgent

agent = VoiceAgent(
    prompt="You are a friendly voice assistant. Keep answers short.",
    api_key="YOUR_ASSEMBLYAI_API_KEY",
)


@agent.tool
def get_weather(city: str) -> str:
    """Get the current weather for a city."""
    return f"It's sunny in {city}."


result = agent.deploy(local=True)
print(result)  # the created AssemblyAI agent record, including its id

That's it — deploy(local=True) starts a local tool server, tunnels it publicly, and registers get_weather as a real tool your live voice agent can call.

result always includes an "info" field — a plain-language paragraph telling you whether the agent is hosted on the provider's servers or only exists locally, and how to actually connect to it (usually via mint_token()). Worth printing after every deploy, especially since this differs per provider — see below.

Testing tool logic without burning session minutes

from minmo import VoiceAgent
from minmo.testing import simulate

agent = VoiceAgent(
    prompt="You are a friendly voice assistant.",
    api_key="YOUR_ASSEMBLYAI_API_KEY",
    llm={"base_url": "https://api.openai.com/v1", "model": "gpt-4o-mini", "api_key": "YOUR_OPENAI_KEY"},
)


@agent.tool
def get_weather(city: str) -> str:
    """Get the current weather for a city."""
    return f"It's sunny in {city}."


result = simulate(agent, transcript=["What's the weather in Paris?"])
print(result["tool_calls"])

simulate() calls the llm you configured directly (any OpenAI-compatible endpoint) and runs tool calls against your local Python functions — no AssemblyAI session, no phone call.

Client-side tools (no server, no tunnel)

@agent.tool defaults to transport="http" — minmo hosts the function behind a URL AssemblyAI calls. Pass transport="client" instead to declare a client-side/function tool: no server, no tunnel, no host_url needed for that tool.

@agent.tool(transport="client")
def get_account_balance(account_id: str) -> str:
    """Look up an account's balance."""
    return "$42.00"

minmo only builds the correct agent config for this — declaring the tool as client-side. Running the actual session (the WebSocket connection that receives tool.call and sends back tool.result) is your own code's job: a browser app, a Twilio bridge, whatever already holds that live connection. If every registered tool is transport="client", deploy() skips the local server and tunnel (or host_url requirement) entirely — nothing to host.

Providers

minmo supports AssemblyAI (default), Hume, OpenAI Realtime, and ElevenLabs. They don't all host your agent the same way:

Pass a different provider via VoiceAgent(provider=..., provider_options=...); see each provider's docstring in minmo/providers/ for required options.

CLI

minmo init     # scaffold main.py, .env.example, requirements.txt
minmo deploy   # import main.py, find the VoiceAgent, deploy it
minmo logs     # print the most recent session log

Deploying to a real server (not local=True)

agent.deploy(local=False, host_url="https://your-deployed-tool-server.example.com")
# or set MINMO_HOST_URL in the environment instead of passing host_url

Your host must already be running the tool server — local=True is for development; production tool hosting is up to you (minmo's local server factory, minmo.server.create_tool_server, is reusable if you want to deploy it yourself behind a real domain).

Development

pip install -e ".[dev]"
pytest -q

Pushes are auto-formatted with Black via GitHub Actions, and every push/PR runs the test suite across Python 3.10–3.12.

Contributing

Issues and PRs welcome. Keep changes small and covered by a test.

License

MIT © Anas Elhaag