Calls

Voice calls are real-time conversations through your agent’s phone numbers. Calls can be inbound (received) or outbound (initiated via API). Each call includes metadata like duration, status, and transcript. You can also stream transcripts in real time via Server-Sent Events.

How calls are handled depends on your agent’s voice mode.

Voice modes

Switch modes at any time via PATCH /v1/agents/:id. The backend automatically re-provisions voice infrastructure and rebinds phone numbers with no downtime.

Call flow (webhook mode)

When voiceMode is "webhook":

Call flow (built-in AI mode)

When voiceMode is "hosted":

Voice capabilities

Both modes share the same low-latency engine:

Webhook response format

For voice webhooks, your server must return a JSON object ({...}) telling the agent what to say. Non-object responses (numbers, strings, arrays) are ignored and the caller hears silence.

Streaming response (recommended)

Return Content-Type: application/x-ndjson with newline-delimited JSON chunks. TTS starts speaking on the very first chunk while your server continues processing.

{"text": "Let me check that for you.", "interim": true}
{"text": "Your order #4521 shipped yesterday via FedEx."}

Mark interim chunks with "interim": true — the final chunk (without interim) closes the turn. Use this for tool calls, LLM token forwarding, or any time your response takes more than ~1 second.

Simple response

Return a single JSON object for instant replies where no processing delay is expected.

1
{ "text": "How can I help you?" }

Response fields

Example: streaming handler (Python / FastAPI)

1
from fastapi.responses import StreamingResponse
2
import json, openai
3
4
@app.post('/webhook')
5
async def handle_voice(payload: dict):
6
    if payload['channel'] != 'voice':
7
        return Response(status_code=200)
8
9
    history = payload.get('recentHistory', [])
10
    context = "\n".join([
11
        f"{'Customer' if h['direction'] == 'inbound' else 'Agent'}: {h['content']}"
12
        for h in history
13
    ])
14
15
    async def generate():
16
        yield json.dumps({"text": "One moment, let me check.", "interim": True}) + "\n"
17
18
        stream = openai.chat.completions.create(
19
            model="gpt-4",
20
            stream=True,
21
            messages=[
22
                {"role": "system", "content": "You are a helpful phone agent."},
23
                {"role": "user", "content": f"Conversation:\n{context}\n\nRespond."}
24
            ]
25
        )
26
        full = ""
27
        for chunk in stream:
28
            delta = chunk.choices[0].delta.content or ""
29
            full += delta
30
        yield json.dumps({"text": full}) + "\n"
31
32
    return StreamingResponse(generate(), media_type="application/x-ndjson")

Example: streaming handler (Node.js / Express)

1
const OpenAI = require('openai');
2
const openai = new OpenAI();
3
4
app.post('/webhook', express.json(), async (req, res) => {
5
  if (req.body.channel !== 'voice') return res.status(200).send('OK');
6
7
  const history = req.body.recentHistory || [];
8
  const context = history
9
    .map(h => `${h.direction === 'inbound' ? 'Customer' : 'Agent'}: ${h.content}`)
10
    .join('\n');
11
12
  res.setHeader('Content-Type', 'application/x-ndjson');
13
  res.write(JSON.stringify({ text: 'One moment, let me check.', interim: true }) + '\n');
14
15
  const stream = await openai.chat.completions.create({
16
    model: 'gpt-4',
17
    stream: true,
18
    messages: [
19
      { role: 'system', content: 'You are a helpful phone agent.' },
20
      { role: 'user', content: `Conversation:\n${context}\n\nRespond.` }
21
    ]
22
  });
23
24
  let full = '';
25
  for await (const chunk of stream) {
26
    full += chunk.choices[0]?.delta?.content || '';
27
  }
28
  res.write(JSON.stringify({ text: full }) + '\n');
29
  res.end();
30
});

Example: tool-calling handler (Python / Flask)

When your agent needs to call external APIs (databases, calendars, CRM, etc.) during a voice call, always stream an interim filler response first. This prevents the caller from hearing silence while your tools run.

The pattern is: stream an interim acknowledgement immediately → run your tools → stream the final answer.

1
from flask import Flask, request, Response
2
import json, anthropic, os
3
4
app = Flask(__name__)
5
client = anthropic.Anthropic(api_key=os.environ["ANTHROPIC_API_KEY"])
6
7
TOOLS = [
8
    {
9
        "name": "get_todays_calendar",
10
        "description": "Get the user's calendar events for today.",
11
        "input_schema": {"type": "object", "properties": {}, "required": []},
12
    },
13
    {
14
        "name": "search_orders",
15
        "description": "Look up a customer's recent orders.",
16
        "input_schema": {
17
            "type": "object",
18
            "properties": {"query": {"type": "string"}},
19
            "required": ["query"],
20
        },
21
    },
22
]
23
24
TOOL_HANDLERS = {
25
    "get_todays_calendar": lambda args: fetch_calendar_events(),
26
    "search_orders": lambda args: search_order_db(args["query"]),
27
}
28
29
30
def run_tool_call(user_message: str, history: list) -> str:
31
    """Run Claude with tools and return the final text response."""
32
    messages = [{"role": "user", "content": user_message}]
33
34
    for _ in range(5):  # max tool-call iterations
35
        response = client.messages.create(
36
            model="claude-haiku-4-5-20251001",
37
            max_tokens=256,
38
            system="You are a helpful phone assistant. Keep responses to 2-3 sentences.",
39
            tools=TOOLS,
40
            messages=messages,
41
        )
42
43
        if response.stop_reason == "tool_use":
44
            messages.append({"role": "assistant", "content": response.content})
45
            tool_results = []
46
            for block in response.content:
47
                if block.type == "tool_use":
48
                    handler = TOOL_HANDLERS.get(block.name)
49
                    result = handler(block.input) if handler else "Unknown tool"
50
                    tool_results.append({
51
                        "type": "tool_result",
52
                        "tool_use_id": block.id,
53
                        "content": result,
54
                    })
55
            messages.append({"role": "user", "content": tool_results})
56
        else:
57
            return " ".join(b.text for b in response.content if hasattr(b, "text"))
58
59
    return "Sorry, I'm having trouble processing that."
60
61
62
@app.post("/webhook")
63
def webhook():
64
    payload = request.json
65
    if payload.get("channel") != "voice":
66
        return "OK", 200
67
68
    transcript = payload["data"].get("transcript", "")
69
    history = payload.get("recentHistory", [])
70
71
    def generate():
72
        # Immediately tell the caller we're working on it
73
        yield json.dumps({"text": "Let me check on that.", "interim": True}) + "\n"
74
75
        # Now run the slow tool calls (LLM + external APIs)
76
        try:
77
            answer = run_tool_call(transcript, history)
78
        except Exception:
79
            answer = "Sorry, I ran into a problem. Could you try again?"
80
81
        yield json.dumps({"text": answer}) + "\n"
82
83
    return Response(generate(), content_type="application/x-ndjson")

Example: tool-calling handler (Node.js / Express)

1
const express = require("express");
2
const Anthropic = require("@anthropic-ai/sdk");
3
4
const app = express();
5
app.use(express.json());
6
7
const client = new Anthropic();
8
9
const tools = [
10
  {
11
    name: "get_todays_calendar",
12
    description: "Get the user's calendar events for today.",
13
    input_schema: { type: "object", properties: {}, required: [] },
14
  },
15
  {
16
    name: "search_orders",
17
    description: "Look up a customer's recent orders.",
18
    input_schema: {
19
      type: "object",
20
      properties: { query: { type: "string" } },
21
      required: ["query"],
22
    },
23
  },
24
];
25
26
const toolHandlers = {
27
  get_todays_calendar: (args) => fetchCalendarEvents(),
28
  search_orders: (args) => searchOrderDb(args.query),
29
};
30
31
async function runToolCall(userMessage) {
32
  const messages = [{ role: "user", content: userMessage }];
33
34
  for (let i = 0; i < 5; i++) {
35
    const response = await client.messages.create({
36
      model: "claude-haiku-4-5-20251001",
37
      max_tokens: 256,
38
      system: "You are a helpful phone assistant. Keep responses to 2-3 sentences.",
39
      tools,
40
      messages,
41
    });
42
43
    if (response.stop_reason === "tool_use") {
44
      messages.push({ role: "assistant", content: response.content });
45
      const toolResults = [];
46
      for (const block of response.content) {
47
        if (block.type === "tool_use") {
48
          const handler = toolHandlers[block.name];
49
          const result = handler ? await handler(block.input) : "Unknown tool";
50
          toolResults.push({ type: "tool_result", tool_use_id: block.id, content: result });
51
        }
52
      }
53
      messages.push({ role: "user", content: toolResults });
54
    } else {
55
      return response.content
56
        .filter((b) => b.type === "text")
57
        .map((b) => b.text)
58
        .join(" ");
59
    }
60
  }
61
  return "Sorry, I'm having trouble processing that.";
62
}
63
64
app.post("/webhook", async (req, res) => {
65
  if (req.body.channel !== "voice") return res.status(200).send("OK");
66
67
  const transcript = req.body.data?.transcript || "";
68
69
  res.setHeader("Content-Type", "application/x-ndjson");
70
71
  // Immediately tell the caller we're working on it
72
  res.write(JSON.stringify({ text: "Let me check on that.", interim: true }) + "\n");
73
74
  // Now run the slow tool calls (LLM + external APIs)
75
  try {
76
    const answer = await runToolCall(transcript);
77
    res.write(JSON.stringify({ text: answer }) + "\n");
78
  } catch (err) {
79
    res.write(JSON.stringify({ text: "Sorry, I ran into a problem." }) + "\n");
80
  }
81
  res.end();
82
});
83
84
app.listen(3000);

Troubleshooting voice calls

Common issues and how to fix them.

Caller hears silence after speaking

Your webhook is too slow or not responding. Voice webhooks have a 30-second default timeout (configurable per webhook from 5–120 seconds). If your server doesn’t respond in time, the turn is dropped and the caller hears nothing.

Fix: Always stream an interim NDJSON chunk immediately (e.g. {"text": "One moment.", "interim": true}) before doing any slow work. This buys you time while keeping the caller engaged.

Common causes:

• LLM tool calls that take too long (external API latency + LLM processing)
• Cold starts on serverless platforms (Lambda, Cloud Functions)
• Webhook URL is unreachable or returning errors

Caller hears silence after the greeting

Your webhook isn’t configured or isn’t returning a valid JSON object. Voice responses must be a JSON object ({...}). Non-object responses (strings, arrays, numbers) are ignored.

Fix: Verify your webhook is returning {"text": "..."}. Use POST /v1/webhooks/test to confirm your endpoint is reachable and responding correctly.

Response is cut off or sounds garbled

You’re sending the entire response as a single large chunk. Long responses in a single chunk can cause TTS delays.

Fix: Use NDJSON streaming and break responses into natural sentences. Send each sentence as an interim chunk so TTS can start speaking immediately.

Agent speaks XML or code artifacts

Your LLM is including tool-call markup in its response. Some LLMs emit <function_call> or similar tags.

Fix: Strip non-speech content from your LLM output before returning it. AgentPhone removes common patterns automatically, but your webhook should clean responses to be safe.

Webhook works for SMS but not voice

You’re returning a 200 OK with no body, or a non-JSON response for voice. SMS webhooks only need a 200 status — voice webhooks must return a JSON object with a text field.

Fix: Check the channel field in the webhook payload. For "voice", always return {"text": "..."}. For "sms", a 200 OK is sufficient.

Call recording

Call recording is an optional add-on that saves audio recordings of your voice calls. When enabled, completed calls include a recordingUrl field with a link to the audio file.

Enable recording from the Billing page in the dashboard. See Usage & Billing for pricing.

List calls

List all calls for this project.

GET /v1/calls

Query parameters

Example

$
curl -X GET "https://api.agentphone.ai/v1/calls?limit=10&offset=0" \
>
  -H "Authorization: Bearer YOUR_API_KEY"

1
{
2
  "data": [
3
    {
4
      "id": "call_ghi012",
5
      "agentId": "agt_abc123",
6
      "phoneNumberId": "num_xyz789",
7
      "phoneNumber": "+15551234567",
8
      "fromNumber": "+15559876543",
9
      "toNumber": "+15551234567",
10
      "direction": "inbound",
11
      "status": "completed",
12
      "startedAt": "2025-01-15T14:00:00Z",
13
      "endedAt": "2025-01-15T14:05:30Z",
14
      "durationSeconds": 330,
15
      "lastTranscriptSnippet": "Thank you for calling, goodbye!",
16
      "recordingUrl": "https://api.twilio.com/2010-04-01/.../Recordings/RE...",
17
      "recordingAvailable": true
18
    }
19
  ],
20
  "hasMore": false,
21
  "total": 1
22
}

Get call

Get details of a specific call, including its full transcript.

GET /v1/calls/{call_id}

Example

$
curl -X GET "https://api.agentphone.ai/v1/calls/call_ghi012" \
>
  -H "Authorization: Bearer YOUR_API_KEY"

1
{
2
  "id": "call_ghi012",
3
  "agentId": "agt_abc123",
4
  "phoneNumberId": "num_xyz789",
5
  "phoneNumber": "+15551234567",
6
  "fromNumber": "+15559876543",
7
  "toNumber": "+15551234567",
8
  "direction": "inbound",
9
  "status": "completed",
10
  "startedAt": "2025-01-15T14:00:00Z",
11
  "endedAt": "2025-01-15T14:05:30Z",
12
  "durationSeconds": 330,
13
  "recordingUrl": "https://api.twilio.com/2010-04-01/.../Recordings/RE...",
14
  "recordingAvailable": true,
15
  "transcripts": [
16
    {
17
      "id": "tr_001",
18
      "transcript": "Hello! Thanks for calling Acme Corp. How can I help you today?",
19
      "confidence": 0.95,
20
      "response": "Sure! Could you please provide your order number?",
21
      "createdAt": "2025-01-15T14:00:05Z"
22
    },
23
    {
24
      "id": "tr_002",
25
      "transcript": "Hi, I'd like to check the status of my order.",
26
      "confidence": 0.92,
27
      "response": "Of course! Let me look that up for you.",
28
      "createdAt": "2025-01-15T14:00:15Z"
29
    }
30
  ]
31
}

Stream transcript (SSE)

Stream a call’s transcript in real time via Server-Sent Events. On connect the server replays all existing transcript turns from the database, then streams new turns as they arrive from the voice engine. Works for both live and completed calls — same URL either way.

GET /v1/calls/{call_id}/transcript/stream

The response is an SSE stream (Content-Type: text/event-stream) with the following event types:

A : heartbeat comment is sent every 15 seconds to keep proxies and load balancers from closing the connection.

Event payloads

connected

1
{
2
  "callId": "call_ghi012",
3
  "status": "in-progress",
4
  "agentId": "agt_abc123",
5
  "agentName": "Support Bot",
6
  "direction": "inbound",
7
  "fromNumber": "+15559876543",
8
  "toNumber": "+15551234567",
9
  "startedAt": "2025-01-15T14:00:00Z"
10
}

turn

1
{
2
  "role": "user",
3
  "content": "I need help with my order.",
4
  "createdAt": "2025-01-15T14:00:10Z"
5
}

ended

1
{
2
  "callId": "call_ghi012",
3
  "status": "completed",
4
  "endedAt": "2025-01-15T14:05:30Z",
5
  "durationSeconds": 330
6
}

Example: curl

$
curl -N "https://api.agentphone.ai/v1/calls/call_ghi012/transcript/stream" \
>
  -H "Authorization: Bearer YOUR_API_KEY"

Example: JavaScript (Node.js / fetch stream)

1
const API_KEY = "YOUR_API_KEY";
2
const callId = "call_ghi012";
3
const response = await fetch(
4
  `https://api.agentphone.ai/v1/calls/${callId}/transcript/stream`,
5
  { headers: { Authorization: `Bearer ${API_KEY}` } }
6
);
7
8
if (!response.ok) {
9
  throw new Error(`Failed to stream transcript: ${response.status}`);
10
}
11
12
const reader = response.body.getReader();
13
const decoder = new TextDecoder();
14
let buffer = "";
15
let eventType = null;
16
17
while (true) {
18
  const { done, value } = await reader.read();
19
  if (done) break;
20
21
  buffer += decoder.decode(value, { stream: true });
22
  const lines = buffer.split("\n");
23
  buffer = lines.pop();
24
25
  for (const line of lines) {
26
    if (line.startsWith("event:")) {
27
      eventType = line.slice(6).trim();
28
    } else if (line.startsWith("data:")) {
29
      const data = JSON.parse(line.slice(5).trim());
30
      if (eventType === "connected") {
31
        console.log(`Connected to call ${data.callId} (${data.status})`);
32
      } else if (eventType === "turn") {
33
        console.log(`[${data.role}] ${data.content}`);
34
      } else if (eventType === "ended") {
35
        console.log(`Call ended - ${data.durationSeconds}s`);
36
      }
37
    }
38
  }
39
}

Example: Python

1
import requests
2
3
API_KEY = "YOUR_API_KEY"
4
call_id = "call_ghi012"
5
6
url = f"https://api.agentphone.ai/v1/calls/{call_id}/transcript/stream"
7
headers = {"Authorization": f"Bearer {API_KEY}"}
8
9
with requests.get(url, headers=headers, stream=True) as resp:
10
    event_type = None
11
    for line in resp.iter_lines(decode_unicode=True):
12
        if line.startswith("event:"):
13
            event_type = line[len("event:"):].strip()
14
        elif line.startswith("data:"):
15
            import json
16
            data = json.loads(line[len("data:"):].strip())
17
            if event_type == "turn":
18
                print(f"[{data['role']}] {data['content']}")
19
            elif event_type == "ended":
20
                print(f"Call ended — {data['durationSeconds']}s")
21
                break

Create outbound call

Initiate an outbound voice call from one of your agent’s phone numbers. The agent’s first assigned phone number is used as the caller ID.

POST /v1/calls

Request body

Example

$
curl -X POST "https://api.agentphone.ai/v1/calls" \
>
  -H "Authorization: Bearer YOUR_API_KEY" \
>
  -H "Content-Type: application/json" \
>
  -d '{
>
    "agentId": "agt_abc123",
>
    "toNumber": "+15559876543",
>
    "initialGreeting": "Hi, this is Acme Corp calling about your recent order.",
>
    "systemPrompt": "You are a friendly support agent from Acme Corp."
>
  }'

Web calls

Web calls let users talk to your agent directly from a browser, no phone number needed. Use the agentphone-web-sdk npm package on the frontend and mint access tokens from your backend.

How it works:

1. Your backend calls POST /v1/calls/web with agentId to get an access token
2. The token is valid for 30 seconds. Pass it to the frontend immediately.
3. The frontend uses agentphone-web-sdk to start the call with the token

POST /v1/calls/web

Request body

Response

Example

$
curl -X POST "https://api.agentphone.ai/v1/calls/web" \
>
  -H "Authorization: Bearer YOUR_API_KEY" \
>
  -H "Content-Type: application/json" \
>
  -d '{"agentId": "agt_abc123"}'

The call direction will be web (in addition to inbound and outbound).

List calls for number

List all calls associated with a specific phone number.

GET /v1/numbers/{number_id}/calls

Example

$
curl -X GET "https://api.agentphone.ai/v1/numbers/num_xyz789/calls?limit=10" \
>
  -H "Authorization: Bearer YOUR_API_KEY"