Custom Functions

import json

from perplexity import Perplexity

MODEL = "openai/gpt-5.6-sol"
QUESTION = "What's the status of order ORD-10042?"

client = Perplexity()

tools = [
    {
        "type": "function",
        "name": "get_order_status",
        "description": "Look up the current status of an order by its order ID.",
        "parameters": {
            "type": "object",
            "properties": {"order_id": {"type": "string"}},
            "required": ["order_id"],
            "additionalProperties": False,
        },
        "strict": True,
    }
]


def get_order_status(order_id: str) -> dict[str, str]:
    """Replace this sample data with a database or API call."""
    orders = {
        "ORD-10042": {
            "status": "in_transit",
            "carrier": "DHL",
            "estimated_delivery": "2026-08-08",
        }
    }
    return orders.get(order_id, {"error": "Order not found."})


# 1. Send the question and available tools to the model.
response = client.responses.create(
    model=MODEL,
    input=QUESTION,
    tools=tools,
)

# 2. Add the model's output items to the conversation.
next_input = [
    {"type": "message", "role": "user", "content": QUESTION},
    *[item.model_dump(exclude_none=True) for item in response.output],
]

# 3. Run every function the model requested, then append its result.
for item in response.output:
    if item.type != "function_call":
        continue
    if item.name != "get_order_status":
        raise ValueError(f"Unknown function: {item.name}")

    arguments = json.loads(item.arguments)
    result = get_order_status(**arguments)
    next_input.append(
        {
            "type": "function_call_output",
            "call_id": item.call_id,
            "output": json.dumps(result),
        }
    )

# 4. Send the updated conversation back so the model can answer.
final_response = client.responses.create(
    model=MODEL,
    input=next_input,
    tools=tools,
)

print(final_response.output_text)

import Perplexity from '@perplexity-ai/perplexity_ai';
import type { InputItem } from '@perplexity-ai/perplexity_ai/resources/responses/responses';

const MODEL = 'openai/gpt-5.6-sol';
const QUESTION = "What's the status of order ORD-10042?";

const client = new Perplexity();

const tools = [
  {
    type: 'function' as const,
    name: 'get_order_status',
    description: 'Look up the current status of an order by its order ID.',
    parameters: {
      type: 'object',
      properties: { order_id: { type: 'string' } },
      required: ['order_id'],
      additionalProperties: false,
    },
    strict: true,
  },
];

function getOrderStatus(orderId: string): Record<string, string> {
  // Replace this sample data with a database or API call.
  const orders: Record<string, Record<string, string>> = {
    'ORD-10042': {
      status: 'in_transit',
      carrier: 'DHL',
      estimated_delivery: '2026-08-08',
    },
  };
  return orders[orderId] ?? { error: 'Order not found.' };
}

// 1. Send the question and available tools to the model.
const response = await client.responses.create({
  model: MODEL,
  input: QUESTION,
  tools,
});

// 2. Start the continuation with the original question.
const nextInput: InputItem[] = [
  { type: 'message', role: 'user', content: QUESTION },
];

// 3. Replay each function call, run it locally, and append its result.
for (const item of response.output) {
  if (item.type !== 'function_call') continue;
  nextInput.push({
    type: 'function_call',
    call_id: item.call_id,
    name: item.name,
    arguments: item.arguments,
    ...(item.thought_signature
      ? { thought_signature: item.thought_signature }
      : {}),
  });

  if (item.name !== 'get_order_status') {
    throw new Error(`Unknown function: ${item.name}`);
  }
  const args = JSON.parse(item.arguments) as { order_id: string };
  const result = getOrderStatus(args.order_id);
  nextInput.push({
    type: 'function_call_output',
    call_id: item.call_id,
    output: JSON.stringify(result),
  });
}

// 4. Send the updated conversation back so the model can answer.
const finalResponse = await client.responses.create({
  model: MODEL,
  input: nextInput,
  tools,
});

console.log(finalResponse.output_text);

python custom_function.py

npm install @perplexity-ai/perplexity_ai tsx
npx tsx custom-function.ts