Connect AI agents to phone numbers with 10 lines of code
Project description
Patter
Connect AI agents to phone numbers with 10 lines of code
Quickstart • Features • Installation • Documentation • Self-Hosting
Patter is an open-source platform that gives your AI agent a voice and a phone number. Point it at any function that returns a string, and Patter handles the rest: telephony, speech-to-text, text-to-speech, and real-time audio streaming.
Quickstart
Python
import asyncio
from patter import Patter, IncomingMessage
async def on_message(msg: IncomingMessage) -> str:
# Your agent logic here — return what the AI should say
return f"You said: {msg.text}"
async def main():
phone = Patter(api_key="pt_xxx")
await phone.connect(on_message=on_message) # starts listening for inbound calls
asyncio.run(main())
TypeScript
import { Patter } from "getpatter";
const phone = new Patter({ apiKey: "pt_xxx" });
await phone.connect({
onMessage: async (msg) => {
// Your agent logic here — return what the AI should say
return `You said: ${msg.text}`;
},
});
Local Mode (No Cloud Required)
Run Patter entirely in your process — no Patter account, no cloud backend.
Python
import asyncio
from patter import Patter
async def main():
phone = Patter(
mode="local",
twilio_sid="AC...", twilio_token="...",
openai_key="sk-...",
phone_number="+1...",
webhook_url="xxx.ngrok-free.dev",
)
agent = phone.agent(
system_prompt="You are a friendly customer service agent for Acme Corp.",
voice="alloy",
first_message="Hello! Thanks for calling. How can I help?",
)
print("Listening for calls...")
await phone.serve(agent=agent, port=8000)
asyncio.run(main())
TypeScript
import { Patter } from "getpatter";
const phone = new Patter({
mode: "local",
twilioSid: "AC...", twilioToken: "...",
openaiKey: "sk-...",
phoneNumber: "+1...",
webhookUrl: "xxx.ngrok-free.dev",
});
const agent = phone.agent({
systemPrompt: "You are a friendly customer service agent for Acme Corp.",
voice: "alloy",
firstMessage: "Hello! Thanks for calling. How can I help?",
});
console.log("Listening for calls...");
await phone.serve({ agent, port: 8000 });
Local vs Cloud
| Cloud Mode | Local Mode | |
|---|---|---|
| Setup | Patter API key only | Twilio/Telnyx + OpenAI keys |
| Infrastructure | Managed by Patter | Runs in your process |
| Backend | wss://api.getpatter.com |
Built-in (FastAPI / Express) |
| Webhook | Configured automatically | Requires public URL (e.g. ngrok) |
| Voice modes | All three | All three |
| Best for | Production, multi-tenant | Development, on-prem, full control |
Features
Voice
- Three voice modes: OpenAI Realtime, ElevenLabs ConvAI, Pipeline (any STT + TTS)
- Any STT: Deepgram, OpenAI Whisper
- Any TTS: ElevenLabs, OpenAI TTS
- Natural barge-in with mark-based audio tracking
- DTMF keypad input forwarded to agent as
[DTMF: 1]
Agent
- Bring your own agent (any LLM in pipeline mode)
- System prompt with dynamic
{variable}substitution - Conversation history tracked per call (
data.historyin all callbacks) - Tool calling via webhooks with automatic 3x retry
- Built-in tools:
transfer_call,end_call(auto-injected)
Telephony
- Twilio and Telnyx carriers
- Inbound and outbound calls
- Call transfer to humans (
transfer_callsystem tool) - Call recording (
recording: trueinserve()) - Answering machine detection (
machineDetection: truefor outbound) - Voicemail drop (
voicemailMessage: "..."plays on voicemail detection) - Custom parameters passthrough via TwiML
Developer Experience
pip install patter/npm install getpatter- 10 lines of code to connect an agent to a phone
- Local mode (embedded, no backend) + Cloud mode
- Python + TypeScript SDKs with full parity
- MCP server for Claude Desktop
- Open-source (MIT)
Complete Example
const phone = new Patter({
mode: 'local',
twilioSid: process.env.TWILIO_SID,
twilioToken: process.env.TWILIO_TOKEN,
openaiKey: process.env.OPENAI_KEY,
phoneNumber: '+16592214527',
webhookUrl: 'your-domain.ngrok-free.dev',
});
const agent = phone.agent({
systemPrompt: `You are a customer service agent for Acme Corp.
The customer is {customer_name} with order #{order_id}.
Check inventory before answering stock questions.
Transfer to a human if the customer is upset.`,
voice: 'alloy',
language: 'en',
firstMessage: 'Hi {customer_name}! How can I help with order #{order_id}?',
variables: {
customer_name: 'John',
order_id: '12345',
},
tools: [{
name: 'check_inventory',
description: 'Check product stock',
parameters: { type: 'object', properties: { product: { type: 'string' } } },
webhookUrl: 'https://api.acme.com/inventory',
}],
// Built-in: transfer_call, end_call (auto-injected)
});
await phone.serve({
agent,
port: 8000,
recording: true,
onCallStart: async (data) => console.log(`Call from ${data.caller}`),
onCallEnd: async (data) => console.log(`Transcript: ${data.transcript?.length} turns`),
onTranscript: async (data) => console.log(`${data.role}: ${data.text}`),
});
// Outbound with machine detection
await phone.call({
to: '+1234567890',
machineDetection: true,
voicemailMessage: 'Hi, please call us back at 555-0123.',
});
How It Works
Your Code (on_message handler)
│
▼
Patter SDK ──WebSocket──► Patter Backend ──────────────────────────────┐
│ │
┌───────┴────────┐ │
▼ ▼ ▼
STT Engine TTS Engine Telephony Provider
(Deepgram / (ElevenLabs / (Twilio / Telnyx)
Whisper / OpenAI TTS) │
OpenAI RT) │ │
│ └───────────────────────►│
└────────────────────────────────────────►│
▼
Phone Call
The audio path: Phone → Telephony → WebSocket → Backend → STT → your handler → TTS → Backend → WebSocket → Phone
Installation
# Python
pip install patter
# TypeScript / Node.js
npm install getpatter
Documentation
Inbound Calls (AI answers the phone)
Python
import asyncio
from patter import Patter, IncomingMessage
async def agent(msg: IncomingMessage) -> str:
if "hours" in msg.text.lower():
return "We're open Monday through Friday, 9 to 5."
return "How can I help you today?"
async def main():
phone = Patter(api_key="pt_xxx")
await phone.connect(
on_message=agent,
on_call_start=lambda data: print(f"Call from {data['caller']}"),
on_call_end=lambda data: print("Call ended"),
)
await asyncio.Event().wait() # keep the process alive
asyncio.run(main())
TypeScript
import { Patter } from "getpatter";
const phone = new Patter({ apiKey: "pt_xxx" });
await phone.connect({
onMessage: async (msg) => {
if (msg.text.toLowerCase().includes("hours")) {
return "We're open Monday through Friday, 9 to 5.";
}
return "How can I help you today?";
},
onCallStart: (data) => console.log(`Call from ${data.caller}`),
onCallEnd: () => console.log("Call ended"),
});
Outbound Calls (AI calls someone)
Python
import asyncio
from patter import Patter, IncomingMessage
async def agent(msg: IncomingMessage) -> str:
return "Thanks for picking up. This is a reminder about your appointment tomorrow."
async def main():
phone = Patter(api_key="pt_xxx")
await phone.connect(on_message=agent)
await phone.call(
to="+14155551234",
first_message="Hi, this is an automated reminder from Acme Corp.",
)
asyncio.run(main())
TypeScript
import { Patter } from "getpatter";
const phone = new Patter({ apiKey: "pt_xxx" });
await phone.connect({
onMessage: async () =>
"Thanks for picking up. This is a reminder about your appointment tomorrow.",
});
await phone.call({
to: "+14155551234",
firstMessage: "Hi, this is an automated reminder from Acme Corp.",
});
Outbound with Machine Detection + Voicemail Drop
Python
await phone.call(
to="+14155551234",
first_message="Hi, this is an automated reminder from Acme Corp.",
machine_detection=True,
voicemail_message="Hi, we tried to reach you. Please call us back at 555-0123.",
)
TypeScript
await phone.call({
to: "+14155551234",
firstMessage: "Hi, this is an automated reminder from Acme Corp.",
machineDetection: true,
voicemailMessage: "Hi, we tried to reach you. Please call us back at 555-0123.",
});
Dynamic Variables in Prompts
Inject call-specific data into system prompts and first messages using {variable} placeholders.
Python
agent = phone.agent(
system_prompt="You are helping {customer_name}, account #{account_id}.",
first_message="Hi {customer_name}! How can I help you today?",
variables={
"customer_name": "Jane",
"account_id": "A-789",
},
)
TypeScript
const agent = phone.agent({
systemPrompt: "You are helping {customer_name}, account #{account_id}.",
firstMessage: "Hi {customer_name}! How can I help you today?",
variables: {
customer_name: "Jane",
account_id: "A-789",
},
});
Tool Calling via Webhooks
Agents can call external APIs mid-conversation. Patter POSTs to your webhook URL and retries up to 3 times on failure.
Python
agent = phone.agent(
system_prompt="You are a booking assistant. Check availability before confirming.",
tools=[{
"name": "check_availability",
"description": "Check appointment availability for a given date",
"parameters": {
"type": "object",
"properties": {
"date": {"type": "string", "description": "ISO date, e.g. 2025-06-15"},
},
"required": ["date"],
},
"webhook_url": "https://api.example.com/availability",
}],
)
TypeScript
const agent = phone.agent({
systemPrompt: "You are a booking assistant. Check availability before confirming.",
tools: [{
name: "check_availability",
description: "Check appointment availability for a given date",
parameters: {
type: "object",
properties: {
date: { type: "string", description: "ISO date, e.g. 2025-06-15" },
},
required: ["date"],
},
webhookUrl: "https://api.example.com/availability",
}],
});
Built-in Tools: Transfer & End Call
transfer_call and end_call are automatically injected into every agent — no configuration needed.
- The agent calls
transfer_callwhen it decides to route to a human (e.g. "Let me transfer you now.") - The agent calls
end_callwhen the conversation is complete (e.g. after a confirmed booking.)
Call Recording
Python
await phone.serve(agent=agent, port=8000, recording=True)
TypeScript
await phone.serve({ agent, port: 8000, recording: true });
Conversation History
Every callback receives data.history — the full conversation so far as a list of {role, text} turns.
Python
await phone.serve(
agent=agent,
port=8000,
on_transcript=lambda data: print(f"[{data['role']}] {data['text']}"),
on_call_end=lambda data: print(f"Full history: {data['history']}"),
)
TypeScript
await phone.serve({
agent,
port: 8000,
onTranscript: (data) => console.log(`[${data.role}] ${data.text}`),
onCallEnd: (data) => console.log(`Full history:`, data.history),
});
Custom Voice (choose your providers)
Python
phone = Patter(api_key="pt_xxx", backend_url="ws://localhost:8000")
await phone.connect(
on_message=agent,
provider="twilio",
provider_key="ACxxxxxxxx",
provider_secret="your_auth_token",
number="+14155550000",
stt=Patter.deepgram(api_key="dg_xxx", language="en"),
tts=Patter.elevenlabs(api_key="el_xxx", voice="rachel"),
)
TypeScript
const phone = new Patter({ apiKey: "pt_xxx", backendUrl: "ws://localhost:8000" });
await phone.connect({
onMessage: agent,
provider: "twilio",
providerKey: "ACxxxxxxxx",
providerSecret: "your_auth_token",
number: "+14155550000",
stt: Patter.deepgram({ apiKey: "dg_xxx", language: "en" }),
tts: Patter.elevenlabs({ apiKey: "el_xxx", voice: "rachel" }),
});
Voice Modes
| Mode | Latency | Quality | Best For |
|---|---|---|---|
| OpenAI Realtime | Lowest | High | Fluid, low-latency conversations |
| Deepgram + ElevenLabs | Low | High | Independent control over STT and TTS |
| ElevenLabs ConvAI | Low | High | ElevenLabs-managed conversation flow |
The voice mode is configured on the backend. Your on_message handler works identically regardless of mode.
MCP Server (Claude Desktop)
Patter ships an MCP server so you can control calls directly from Claude Desktop.
{
"mcpServers": {
"patter": {
"command": "patter-mcp",
"env": { "PATTER_API_KEY": "pt_xxx" }
}
}
}
Self-Hosting
Run the full stack yourself — no Patter Cloud account needed.
# 1. Clone the repo
git clone https://github.com/your-org/patter
cd patter
# 2. Copy env and fill in your keys
cp .env.example .env
# 3. Start the backend
cd backend
pip install -e ".[dev]"
alembic upgrade head
uvicorn app.main:app --reload
Then point your SDK at your local backend:
phone = Patter(
api_key="pt_xxx",
backend_url="ws://localhost:8000",
rest_url="http://localhost:8000",
)
Required environment variables:
| Variable | Description |
|---|---|
PATTER_DATABASE_URL |
PostgreSQL connection string |
PATTER_ENCRYPTION_KEY |
Key for encrypting stored provider credentials |
PATTER_SECRET_KEY |
JWT / HMAC signing secret |
See backend/.env.example for the full list.
API Reference
Patter (Python & TypeScript)
| Method | Description |
|---|---|
Patter(api_key, backend_url?, rest_url?) |
Create client. backend_url defaults to wss://api.getpatter.com. |
connect(on_message, ...) |
Connect and start receiving calls. Blocks until disconnected. |
call(to, first_message?, machine_detection?, voicemail_message?, ...) |
Place an outbound call. |
disconnect() |
Gracefully close the connection. |
serve() options:
| Option | Type | Description |
|---|---|---|
agent |
Agent |
Agent configuration to use for calls |
port |
int |
Port to listen on |
recording |
bool |
Enable call recording via the telephony provider |
onCallStart |
callable |
Called when a call connects; receives data.caller, data.call_id |
onCallEnd |
callable |
Called when a call ends; receives data.history, data.transcript, data.duration |
onTranscript |
callable |
Called on each transcript turn; receives data.role, data.text, data.history |
agent() options:
| Option | Type | Description |
|---|---|---|
system_prompt |
str |
Prompt with optional {variable} placeholders |
variables |
dict |
Values substituted into system_prompt and first_message |
voice |
str |
TTS voice name |
language |
str |
BCP-47 language code |
first_message |
str |
Opening message (supports {variable} placeholders) |
tools |
list |
Tool definitions with name, description, parameters, webhook_url |
call() options:
| Option | Type | Description |
|---|---|---|
to |
str |
Destination phone number |
first_message |
str |
Opening message for the outbound call |
machine_detection |
bool |
Enable answering machine detection |
voicemail_message |
str |
Message to play when voicemail is detected |
Static provider helpers (for self-hosted mode):
| Helper | Type | Description |
|---|---|---|
Patter.deepgram(api_key, language?) |
STT | Deepgram Nova |
Patter.whisper(api_key, language?) |
STT | OpenAI Whisper |
Patter.elevenlabs(api_key, voice?) |
TTS | ElevenLabs |
Patter.openai_tts(api_key, voice?) |
TTS | OpenAI TTS |
IncomingMessage
| Field | Type | Description |
|---|---|---|
text |
str |
Transcribed speech from the caller (includes [DTMF: N] for keypad presses) |
call_id |
str |
Unique identifier for the current call |
history |
list |
Conversation turns so far: [{role, text}, ...] |
Contributing
Pull requests are welcome.
# Run tests
cd backend && pytest tests/ -v
cd sdk && pytest tests/ -v
# Install dev dependencies
cd backend && pip install -e ".[dev]"
cd sdk && pip install -e ".[dev]"
Please open an issue before submitting large changes so we can discuss the approach first.
License
MIT — see LICENSE.
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