Quickstart

pip install superdialog

pip install superdialog[livekit]    # LiveKit adapter
pip install superdialog[pipecat]    # PipeCat adapter
pip install superdialog[fastapi]    # FastAPI adapter + uvicorn
pip install superdialog[ws]         # WebSocket runner
pip install superdialog[mcp]        # MCP tool support
pip install superdialog[langchain]  # LangChainAgent

superdialog generate "Confirm a customer appointment. Ask if Friday 4pm works; \
  offer 5pm as an alternative if not. Confirm before saving." \
  --output appointment.yaml

goal: "Confirm the appointment and lock in a time."
persona:
  name: Ava
  voice_style: "Warm and brief. One question at a time."
  identity: "You are Ava, a scheduling assistant."
playbook:
  - id: greet
    purpose: "Open the call."
    say: "Greet the customer and confirm you're calling about their appointment."
    done_when: "Customer is ready to confirm a time."
  - id: confirm_time
    purpose: "Lock in the slot."
    say: "Ask if Friday 4pm works; offer 5pm if not."
    collect: [chosen_time]
    done_when: "Customer has agreed to a time."

from superdialog import DialogMachine

agent = DialogMachine(
    "appointment.yaml",                 # any format: playbook, simple, or legacy flow JSON
    llm="anthropic/claude-haiku-4-5",   # fast model for the speaking turn
)

import asyncio

async def chat():
    reply = await agent.turn("Hello, I'm calling about my appointment.")
    print(reply.text)

    reply = await agent.turn("Friday 4pm works for me.")
    print(reply.text)

asyncio.run(chat())

superdialog chat appointment.yaml

from superdialog import DialogMachine

async def lookup_customer(args, state) -> dict:
    """Look up customer record by phone number."""
    return await crm.get_by_phone(args["phone_number"])

agent = DialogMachine(
    "appointment.yaml",
    llm="anthropic/claude-haiku-4-5",
    tools=[...],   # see the Tools guide for HTTP / Python / MCP shapes
)