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Getting Started

Get up and running with the Estuary Python SDK in minutes. This guide walks you through installation, configuration, and sending your first message to an AI character.

Prerequisites​

Before you begin, ensure you have:

RequirementDetails
Python3.11 or later
Estuary AccountSign up at app.estuary-ai.com
API KeyGenerated from your Estuary dashboard (starts with est_)
Character IDThe UUID of your AI character

Installation​

Install the SDK from PyPI:

pip install estuary-sdk

Optional Extras​

The core SDK has minimal dependencies (python-socketio + aiohttp). Install optional extras for additional features:

# Audio recording and playback (sounddevice + numpy)
pip install "estuary-sdk[audio]"

# LiveKit WebRTC voice
pip install "estuary-sdk[livekit]"

# Everything
pip install "estuary-sdk[all]"

Quick Start​

Here is a minimal example that connects to a character and exchanges text messages:

import asyncio
from estuary_sdk import EstuaryClient, EstuaryConfig

config = EstuaryConfig(
    server_url="https://api.estuary-ai.com",
    api_key="est_your_api_key",
    character_id="your-character-uuid",
    player_id="user-123",
)

async def main():
    async with EstuaryClient(config) as client:
        # Listen for bot responses
        async def on_response(response):
            if response.is_final:
                print("Bot:", response.text)

        client.on("bot_response", on_response)

        # Connect and send a message
        session = await client.connect()
        print("Connected! Session:", session.session_id)

        client.send_text("Hello! Tell me about yourself.")

        # Keep running to receive responses
        await asyncio.sleep(10)

asyncio.run(main())

What Happens Under the Hood​

  1. client.connect() opens a WebSocket connection to the Estuary server, authenticates with your API key, and returns a SessionInfo object.
  2. client.send_text() sends your message over the WebSocket.
  3. The server processes your message through the AI pipeline and streams the response back.
  4. The bot_response event fires for each chunk of the response. When is_final is True, the full response text is available.

Complete Example​

This example demonstrates connection lifecycle handling, streaming responses, and cleanup:

import asyncio
from estuary_sdk import EstuaryClient, EstuaryConfig, ConnectionState

config = EstuaryConfig(
    server_url="https://api.estuary-ai.com",
    api_key="est_your_api_key",
    character_id="your-character-uuid",
    player_id="user-123",
    auto_reconnect=True,
    debug=True,
)

async def main():
    async with EstuaryClient(config) as client:
        # Connection events
        async def on_connected(session):
            print("Connected! Conversation:", session.conversation_id)

        async def on_disconnected(reason):
            print("Disconnected:", reason)

        async def on_reconnecting(attempt):
            print(f"Reconnecting (attempt {attempt})...")

        # Response events
        async def on_response(response):
            if response.is_final:
                print("Bot:", response.text)
            else:
                print(response.partial, end="", flush=True)

        # Error handling
        async def on_error(err):
            print("Error:", err)

        async def on_auth_error(message):
            print("Authentication failed:", message)

        async def on_quota(data):
            print(f"Quota exceeded: {data}")

        client.on("connected", on_connected)
        client.on("disconnected", on_disconnected)
        client.on("reconnecting", on_reconnecting)
        client.on("bot_response", on_response)
        client.on("error", on_error)
        client.on("auth_error", on_auth_error)
        client.on("quota_exceeded", on_quota)

        # Connect and send
        await client.connect()
        client.send_text("Hello!")

        # Keep running
        await asyncio.sleep(30)

asyncio.run(main())

Next Steps​

Now that you have a working connection:

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