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Function Calling#

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Docs API reference

The Interactions API is now generally available. We recommend using this API for access to all the latest features and models.

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Function calling with the Gemini API#

Function calling lets you connect models to external tools and APIs. Instead of generating text responses, the model determines when to call specific functions and provides the necessary parameters to execute real-world actions. This allows the model to act as a bridge between natural language and real-world actions and data. Function calling has 3 primary use cases:

  • Take Actions: Interact with external systems using APIs, such as scheduling appointments, creating invoices, sending emails, or controlling smart home devices.
  • Augment Knowledge: Access information from external sources like databases, APIs, and knowledge bases.
  • Extend Capabilities: Use external tools to perform computations and extend the limitations of the model, such as using a calculator or creating charts.

You can browse examples of these use cases below:

Schedule Meeting#

This example shows how to define a function that schedules a meeting with attendees at a specific time, allowing the model to parse user requests and return structured arguments to trigger actions in external systems.

Python#

from google import genai

schedule_meeting_function = {
    "type": "function",
    "name": "schedule_meeting",
    "description": "Schedules a meeting with specified attendees at a given time and date.",
    "parameters": {
        "type": "object",
        "properties": {
            "attendees": {"type": "array", "items": {"type": "string"}},
            "date": {"type": "string", "description": "Date (e.g., '2024-07-29')"},
            "time": {"type": "string", "description": "Time (e.g., '15:00')"},
            "topic": {"type": "string", "description": "The meeting topic."},
        },
        "required": ["attendees", "date", "time", "topic"],
    },
}

client = genai.Client()

interaction = client.interactions.create(
    model="gemini-3.6-flash",
    input="Schedule a meeting with Bob and Alice for 03/14/2025 at 10:00 AM about Q3 planning.",
    tools=[{"type": "function", **schedule_meeting_function}],
)

for step in interaction.steps:
    if step.type == "function_call":
        print(f"Function to call: {step.name}")
        print(f"Arguments: {step.arguments}")

JavaScript#

import { GoogleGenAI } from '@google/genai';

const client = new GoogleGenAI({});

const scheduleMeetingFunction = {
  type: 'function',
  name: 'schedule_meeting',
  description: 'Schedules a meeting with specified attendees at a given time and date.',
  parameters: {
    type: 'object',
    properties: {
      attendees: { type: 'array', items: { type: 'string' } },
      date: { type: 'string', description: 'Date (e.g., "2024-07-29")' },
      time: { type: 'string', description: 'Time (e.g., "15:00")' },
      topic: { type: 'string', description: 'The meeting topic.' },
    },
    required: ['attendees', 'date', 'time', 'topic'],
  },
};

const interaction = await client.interactions.create({
  model: 'gemini-3.6-flash',
  input: 'Schedule a meeting with Bob and Alice for 03/27/2025 at 10:00 AM about Q3 planning.',
  tools: [scheduleMeetingFunction],
});

for (const step of interaction.steps) {
  if (step.type === 'function_call') {
    console.log(`Function to call: ${step.name}`);
    console.log(`Arguments: ${JSON.stringify(step.arguments)}`);
  }
}

REST#

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "gemini-3.6-flash",
    "input": "Schedule a meeting with Bob and Alice for 03/27/2025 at 10:00 AM about Q3 planning.",
    "tools": [{
        "type": "function",
        "name": "schedule_meeting",
        "description": "Schedules a meeting with specified attendees at a given time and date.",
        "parameters": {
          "type": "object",
          "properties": {
            "attendees": {"type": "array", "items": {"type": "string"}},
            "date": {"type": "string"},
            "time": {"type": "string"},
            "topic": {"type": "string"}
          },
          "required": ["attendees", "date", "time", "topic"]
        }
    }]
  }'

Get Weather#

This example shows how to define a function that retrieves temperature data for a location, enabling the model to call external APIs to answer queries requiring real-time or external information.

Python#

from google import genai

weather_function = {
    "type": "function",
    "name": "get_current_temperature",
    "description": "Gets the current temperature for a given location.",
    "parameters": {
        "type": "object",
        "properties": {
            "location": {
                "type": "string",
                "description": "The city name, e.g. San Francisco",
            },
        },
        "required": ["location"],
    },
}

client = genai.Client()

interaction = client.interactions.create(
    model="gemini-3.6-flash",
    input="What's the temperature in London?",
    tools=[weather_function],
)

for step in interaction.steps:
    if step.type == "function_call":
        print(f"Function to call: {step.name}")
        print(f"Arguments: {step.arguments}")

JavaScript#

import { GoogleGenAI } from '@google/genai';

const client = new GoogleGenAI({});

const weatherFunctionDeclaration = {
  type: 'function',
  name: 'get_current_temperature',
  description: 'Gets the current temperature for a given location.',
  parameters: {
    type: 'object',
    properties: {
      location: {
        type: 'string',
        description: 'The city name, e.g. San Francisco',
      },
    },
    required: ['location'],
  },
};

const interaction = await client.interactions.create({
  model: 'gemini-3.6-flash',
  input: "What's the temperature in London?",
  tools: [weatherFunctionDeclaration],
});

for (const step of interaction.steps) {
  if (step.type === 'function_call') {
    console.log(`Function to call: ${step.name}`);
    console.log(`Arguments: ${JSON.stringify(step.arguments)}`);
  }
}

REST#

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "gemini-3.6-flash",
    "input": "What'\''s the temperature in London?",
    "tools": [{
      "type": "function",
      "nam