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What are Custom Functions?

Custom functions let your Voice AI agent call your own APIs during live conversations. Check order status, update a CRM, book appointments, or integrate with any system - all while on a call.
Bolna custom functions follow the OpenAI function calling specification. If you’ve used OpenAI function calling before, you’ll feel right at home.
Custom function configuration modal showing JSON schema with name, description, parameters, and API endpoint configuration

How Custom Functions Work

1

LLM Reads Function Definition

The LLM sees your function’s name and description to understand what the function does
2

Decides When to Call

Based on conversation context, the LLM decides if this function should be triggered
3

Extracts Parameters

The LLM collects required parameter values from the conversation with the caller
4

Bolna Executes API Call

Bolna makes the HTTP request to your API endpoint with the extracted parameters
5

Response Feeds Back

The API response is returned to the LLM, which continues the conversation naturally
The description is everything. The LLM relies heavily on your description to know when to call the function. A vague description = unreliable triggering.

Complete Schema Structure

Every custom function has two parts: Function Definition (tells LLM what it does) and API Configuration (tells Bolna how to call your API).
{
  "name": "function_name",
  "description": "Detailed description of when to call this function",
  "pre_call_message": "What agent says while the API is being called",
  "parameters": {
    "type": "object",
    "properties": {
      "param_name": {
        "type": "string",
        "description": "What this parameter represents"
      }
    },
    "required": ["param_name"]
  },
  "key": "custom_task",
  "value": {
    "method": "GET",
    "param": {
      "param_name": "%(param_name)s"
    },
    "url": "https://your-api.com/endpoint",
    "api_token": "Bearer your_token",
    "headers": {}
  }
}
Mandatory: The field "key": "custom_task" must be present exactly as shown. Do not modify this value.

Schema Reference

Parts 1-2 follow the OpenAI function calling specification - they define what the function does. Parts 3-5 are Bolna extensions that define how to execute the API call automatically.

1. Function Definition

These fields tell the LLM about your function:
FieldRequiredDescription
nameYesUnique function identifier. Use snake_case (e.g., get_order_status)
descriptionYesTells the LLM when to trigger this function. Be specific and detailed.
parametersYesDefines what information to collect from the caller

2. Parameters Object

The parameters object defines what information the LLM should collect from the caller.
"parameters": {
  "type": "object",
  "properties": {
    "customer_name": {
      "type": "string",
      "description": "The customer's full name"
    },
    "order_id": {
      "type": "string",
      "description": "The order ID, usually starts with ORD-"
    },
    "quantity": {
      "type": "integer",
      "description": "Number of items"
    }
  },
  "required": ["customer_name", "order_id"]
}
Supported Data Types:
TypeUse CaseExample Values
stringText, names, IDs, phone numbers"John Doe", "ORD-12345"
integerWhole numbers5, 100, -10
numberDecimal numbers29.99, 3.14
booleanTrue/false flagstrue, false
Required vs Optional:
In required array?Behavior
YesLLM will keep asking until this value is provided
NoOptional - included if mentioned, skipped otherwise

3. Bolna Extensions

These fields are specific to Bolna:
FieldRequiredDescription
pre_call_messageNoMessage the agent speaks while API is executing (e.g., “One moment please…”)
keyYesMust be "custom_task" - identifies this as a custom function
valueYesAPI configuration object (see below)

4. API Configuration (value object)

This tells Bolna how to make the HTTP request:
FieldRequiredDescription
methodYesHTTP method: GET, POST, PUT, PATCH, DELETE
urlYesYour API endpoint URL
paramYesMaps parameters to API request using format specifiers
api_tokenNoAuthorization header value (e.g., Bearer your_token)
headersNoAdditional HTTP headers as key-value pairs

5. Format Specifiers

The param object maps your parameters to the API request. Use Python-style format specifiers:
Data TypeFormat SpecifierExample
String%(param_name)s"customer_id": "%(customer_id)s"
Integer%(param_name)i"quantity": "%(quantity)i"
Float%(param_name)f"price": "%(price)f"
Parameter names must match exactly. The name in properties must be identical to the name in param mapping (case-sensitive).

Examples

The following examples use illustrative endpoints and credentials to demonstrate the schema structure. Replace the URLs, tokens, and parameter values with your own API details when implementing.

GET Request Examples

A customer calls and asks “Where is my order?” The agent collects the order ID and fetches the status from your backend.What the agent says: “Let me check the status of your order.”What Bolna sends:
curl --location 'https://api.yourstore.com/orders?order_id=ORD-78234' \
--header 'Authorization: Bearer sk_live_abc123'
Function schema:
{
  "name": "check_order_status",
  "description": "Use this function when the customer asks about their order status, delivery update, shipping progress, or tracking information. The customer must provide their order ID.",
  "pre_call_message": "Let me check the status of your order.",
  "parameters": {
    "type": "object",
    "properties": {
      "order_id": {
        "type": "string",
        "description": "The customer's order ID. Usually starts with ORD- followed by numbers, e.g., ORD-78234."
      }
    },
    "required": ["order_id"]
  },
  "key": "custom_task",
  "value": {
    "method": "GET",
    "param": {
      "order_id": "%(order_id)s"
    },
    "url": "https://api.yourstore.com/orders",
    "api_token": "Bearer sk_live_abc123",
    "headers": {}
  }
}
Example API response the LLM receives:
{
  "order_id": "ORD-78234",
  "status": "shipped",
  "estimated_delivery": "March 15, 2026",
  "tracking_number": "1Z999AA10123456784"
}
The agent would then say something like: “Your order ORD-78234 has been shipped and is expected to arrive by March 15th. Your tracking number is 1Z999AA10123456784.”
A customer calls and asks “What’s my current balance?” The agent verifies their identity using their registered phone number and account ID, then fetches the balance.What the agent says: “Let me pull up your account details.”What Bolna sends:
curl --location 'https://api.yourbank.com/accounts/balance?account_id=ACC-991042&phone=%2B919876543210' \
--header 'Authorization: Bearer fin_api_key_001' \
--header 'X-Request-Source: voice-agent'
Function schema:
{
  "name": "get_account_balance",
  "description": "Use this function when the customer asks about their account balance, available credit, remaining amount, or account summary. Requires the customer's account ID and phone number for verification.",
  "pre_call_message": "Let me pull up your account details.",
  "parameters": {
    "type": "object",
    "properties": {
      "account_id": {
        "type": "string",
        "description": "The customer's account ID, usually starts with ACC- followed by numbers."
      },
      "phone": {
        "type": "string",
        "description": "The customer's registered phone number for identity verification."
      }
    },
    "required": ["account_id", "phone"]
  },
  "key": "custom_task",
  "value": {
    "method": "GET",
    "param": {
      "account_id": "%(account_id)s",
      "phone": "%(phone)s"
    },
    "url": "https://api.yourbank.com/accounts/balance",
    "api_token": "Bearer fin_api_key_001",
    "headers": {
      "X-Request-Source": "voice-agent"
    }
  }
}
Example API response the LLM receives:
{
  "account_id": "ACC-991042",
  "name": "Rahul Verma",
  "current_balance": 24500.75,
  "currency": "INR",
  "last_transaction": "2026-03-12"
}
The agent would then say something like: “Your current account balance is Rs. 24,500.75. Your last transaction was on March 12th.”
The phone parameter can be auto-injected using the {from_number} context variable, so the caller does not need to repeat their number.

POST Request Examples

A caller wants to schedule a consultation. The agent collects their name, preferred date, and time, then creates the booking.What the agent says: “I’m booking that appointment for you now.”What Bolna sends:
curl --location 'https://api.yourclinic.com/v1/appointments' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer clinic_token_xyz' \
--data '{
    "patient_name": "Priya Sharma",
    "preferred_date": "2026-03-20",
    "preferred_time": "10:30 AM",
    "reason": "General consultation"
}'
Function schema:
{
  "name": "book_appointment",
  "description": "Use this function when the caller wants to book, schedule, or set up an appointment, consultation, or visit. Collect the patient's name, their preferred date and time, and the reason for the visit.",
  "pre_call_message": "I'm booking that appointment for you now.",
  "parameters": {
    "type": "object",
    "properties": {
      "patient_name": {
        "type": "string",
        "description": "Full name of the patient"
      },
      "preferred_date": {
        "type": "string",
        "description": "Preferred appointment date in YYYY-MM-DD format"
      },
      "preferred_time": {
        "type": "string",
        "description": "Preferred time, e.g., '10:30 AM' or '2:00 PM'"
      },
      "reason": {
        "type": "string",
        "description": "Brief reason for the appointment, e.g., 'General consultation' or 'Follow-up'"
      }
    },
    "required": ["patient_name", "preferred_date", "preferred_time"]
  },
  "key": "custom_task",
  "value": {
    "method": "POST",
    "param": {
      "patient_name": "%(patient_name)s",
      "preferred_date": "%(preferred_date)s",
      "preferred_time": "%(preferred_time)s",
      "reason": "%(reason)s"
    },
    "url": "https://api.yourclinic.com/v1/appointments",
    "api_token": "Bearer clinic_token_xyz",
    "headers": {
      "Content-Type": "application/json"
    }
  }
}
The reason field is optional (not in the required array). If the caller mentions a reason, the LLM includes it. If not, it is skipped without asking.
A customer calls with a complaint or issue. The agent collects the details and creates a support ticket in your helpdesk system.What the agent says: “I’m creating a support ticket for this issue right away.”What Bolna sends:
curl --location 'https://api.yourhelpdesk.com/tickets' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer helpdesk_key_789' \
--data '{
    "caller_phone": "+919876543210",
    "issue_category": "billing",
    "description": "Customer was charged twice for their February subscription",
    "priority": "high"
}'
Function schema:
{
  "name": "create_support_ticket",
  "description": "Use this function when the customer reports a problem, complaint, issue, or bug. Create a support ticket with the issue category, a summary of the problem, and priority level. The caller's phone number is automatically available.",
  "pre_call_message": "I'm creating a support ticket for this issue right away.",
  "parameters": {
    "type": "object",
    "properties": {
      "caller_phone": {
        "type": "string",
        "description": "The customer's phone number"
      },
      "issue_category": {
        "type": "string",
        "description": "Category of the issue: billing, technical, account, shipping, or other"
      },
      "description": {
        "type": "string",
        "description": "A brief summary of the customer's issue in 1-2 sentences"
      },
      "priority": {
        "type": "string",
        "description": "Priority level: low, medium, or high. Set to high if the customer is upset or the issue is time-sensitive."
      }
    },
    "required": ["caller_phone", "issue_category", "description"]
  },
  "key": "custom_task",
  "value": {
    "method": "POST",
    "param": {
      "caller_phone": "%(caller_phone)s",
      "issue_category": "%(issue_category)s",
      "description": "%(description)s",
      "priority": "%(priority)s"
    },
    "url": "https://api.yourhelpdesk.com/tickets",
    "api_token": "Bearer helpdesk_key_789",
    "headers": {
      "Content-Type": "application/json"
    }
  }
}
The caller_phone can be auto-injected using context variables. Add {from_number} to your agent prompt, and the LLM will use it automatically instead of asking the caller for their number.

Using Variables and Dynamic Context

Context variables defined in your agent prompt are automatically substituted into custom functions. The LLM won’t ask the caller for these values - they’re already available.

Auto-Injected System Variables

VariableDescription
{agent_id}The id of the agent
{call_sid}Unique id of the phone call (from Twilio, Plivo, etc.)
{from_number}Phone number that initiated the call
{to_number}Phone number that received the call

How Variable Substitution Works

You are agent Sam speaking to {customer_name}.
The agent ID is "{agent_id}".
The call ID is "{call_sid}".
The customer's phone is "{to_number}".
ParameterDefined in Prompt?Result
to_numberYes (system)Auto-substituted
agent_idYes (system)Auto-substituted
customer_nameYes (passed via call)Auto-substituted
customer_addressNoLLM will collect from caller

Best Practices

Write Detailed Descriptions

Include synonyms and variations: “Use when customer asks about order status, shipping, delivery, or tracking”

Always Add Pre-call Message

Set a friendly message like “Let me check that for you” so callers know to wait

Use Required Fields Wisely

Only mark parameters as required if the function truly cannot work without them

Test APIs First

Verify your API works with tools like curl or Postman before adding to Bolna

Leverage Auto-Injection

Put known data in the agent prompt to avoid asking callers for information you already have

Match Names Exactly

Parameter names in properties and param must be identical (case-sensitive)

Troubleshooting

Cause: Description doesn’t match what the caller is saying.Fix: Make your description more comprehensive. Include synonyms and example phrases.
Cause: Incorrect URL, authentication, or headers.Fix: Test your API with curl or Postman first. Verify api_token format and required headers.
Cause: Typo or format specifier mismatch.Fix: Ensure parameter names match exactly between properties and param. Use %(name)s format.
Cause: Variable not defined in agent prompt.Fix: Add the variable to your agent prompt using {variable_name} syntax.

Next Steps

Context Variables

Learn about dynamic variable injection

Transfer Calls

Route calls to human agents

Calendar Integration

Book appointments via Cal.com

Agent API

Programmatic function configuration