Generate Content using Function Calling

This sample demonstrates how to use Function declarations to influence the content generated by the Gemini Multimodal.

Explore further

For detailed documentation that includes this code sample, see the following:

• Function calling reference
• Introduction to function calling

Code sample

Go

Before trying this sample, follow the Go setup instructions in the Vertex AI quickstart using client libraries. For more information, see the Vertex AI Go API reference documentation.

To authenticate to Vertex AI, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

import (
	"context"
	"fmt"
	"io"

	genai "google.golang.org/genai"
)

// generateWithFuncCall shows how to submit a prompt and a function declaration to the model,
// allowing it to suggest a call to the function to fetch external data. Returning this data
// enables the model to generate a text response that incorporates the data.
func generateWithFuncCall(w io.Writer) error {
	ctx := context.Background()

	client, err := genai.NewClient(ctx, &genai.ClientConfig{
		HTTPOptions: genai.HTTPOptions{APIVersion: "v1"},
	})
	if err != nil {
		return fmt.Errorf("failed to create genai client: %w", err)
	}

	weatherFunc := &genai.FunctionDeclaration{
		Description: "Returns the current weather in a location.",
		Name:        "getCurrentWeather",
		Parameters: &genai.Schema{
			Type: "object",
			Properties: map[string]*genai.Schema{
				"location": {Type: "string"},
			},
			Required: []string{"location"},
		},
	}
	config := &genai.GenerateContentConfig{
		Tools: []*genai.Tool{
			{FunctionDeclarations: []*genai.FunctionDeclaration{weatherFunc}},
		},
		Temperature: genai.Ptr(float32(0.0)),
	}

	modelName := "gemini-2.5-flash"
	contents := []*genai.Content{
		{Parts: []*genai.Part{
			{Text: "What is the weather like in Boston?"},
		},
			Role: "user"},
	}

	resp, err := client.Models.GenerateContent(ctx, modelName, contents, config)
	if err != nil {
		return fmt.Errorf("failed to generate content: %w", err)
	}

	var funcCall *genai.FunctionCall
	for _, p := range resp.Candidates[0].Content.Parts {
		if p.FunctionCall != nil {
			funcCall = p.FunctionCall
			fmt.Fprint(w, "The model suggests to call the function ")
			fmt.Fprintf(w, "%q with args: %v\n", funcCall.Name, funcCall.Args)
			// Example response:
			// The model suggests to call the function "getCurrentWeather" with args: map[location:Boston]
		}
	}
	if funcCall == nil {
		return fmt.Errorf("model did not suggest a function call")
	}

	// Use synthetic data to simulate a response from the external API.
	// In a real application, this would come from an actual weather API.
	funcResp := &genai.FunctionResponse{
		Name: "getCurrentWeather",
		Response: map[string]any{
			"location":         "Boston",
			"temperature":      "38",
			"temperature_unit": "F",
			"description":      "Cold and cloudy",
			"humidity":         "65",
			"wind":             `{"speed": "10", "direction": "NW"}`,
		},
	}

	// Return conversation turns and API response to complete the model's response.
	contents = []*genai.Content{
		{Parts: []*genai.Part{
			{Text: "What is the weather like in Boston?"},
		},
			Role: "user"},
		{Parts: []*genai.Part{
			{FunctionCall: funcCall},
		}},
		{Parts: []*genai.Part{
			{FunctionResponse: funcResp},
		}},
	}

	resp, err = client.Models.GenerateContent(ctx, modelName, contents, config)
	if err != nil {
		return fmt.Errorf("failed to generate content: %w", err)
	}

	respText := resp.Text()

	fmt.Fprintln(w, respText)

	// Example response:
	// The weather in Boston is cold and cloudy with a temperature of 38 degrees Fahrenheit. The humidity is ...

	return nil
}

Java

Before trying this sample, follow the Java setup instructions in the Vertex AI quickstart using client libraries. For more information, see the Vertex AI Java API reference documentation.

To authenticate to Vertex AI, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

import com.google.genai.Client;
import com.google.genai.types.FunctionDeclaration;
import com.google.genai.types.GenerateContentConfig;
import com.google.genai.types.GenerateContentResponse;
import com.google.genai.types.HttpOptions;
import com.google.genai.types.Schema;
import com.google.genai.types.Tool;
import com.google.genai.types.Type;
import java.util.Map;

public class ToolFunctionDescriptionWithText {

  public static void main(String[] args) {
    // TODO(developer): Replace these variables before running the sample.
    String modelId = "gemini-2.5-flash";
    String contents =
        "At Stellar Sounds, a music label, 2024 was a rollercoaster. \"Echoes of the Night,\""
            + " a debut synth-pop album, \n surprisingly sold 350,000 copies, while veteran"
            + " rock band \"Crimson Tide's\" latest, \"Reckless Hearts,\" \n lagged at"
            + " 120,000. Their up-and-coming indie artist, \"Luna Bloom's\" EP, \"Whispers "
            + "of Dawn,\" \n secured 75,000 sales. The biggest disappointment was the "
            + "highly-anticipated rap album \"Street Symphony\" \n only reaching 100,000"
            + " units. Overall, Stellar Sounds moved over 645,000 units this year, revealing"
            + " unexpected \n trends in music consumption.";

    generateContent(modelId, contents);
  }

  // Generates content with text input and function declaration that
  // the model may use to retrieve external data for the response
  public static String generateContent(String modelId, String contents) {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests.
    try (Client client =
        Client.builder()
            .location("global")
            .vertexAI(true)
            .httpOptions(HttpOptions.builder().apiVersion("v1").build())
            .build()) {

      FunctionDeclaration getAlbumSales =
          FunctionDeclaration.builder()
              .name("get_album_sales")
              .description("Gets the number of albums sold")
              // Function parameters are specified in schema format
              .parameters(
                  Schema.builder()
                      .type(Type.Known.OBJECT)
                      .properties(
                          Map.of(
                              "albums",
                              Schema.builder()
                                  .type(Type.Known.ARRAY)
                                  .description("List of albums")
                                  .items(
                                      Schema.builder()
                                          .description("Album and its sales")
                                          .type(Type.Known.OBJECT)
                                          .properties(
                                              Map.of(
                                                  "album_name",
                                                      Schema.builder()
                                                          .type(Type.Known.STRING)
                                                          .description("Name of the music album")
                                                          .build(),
                                                  "copies_sold",
                                                      Schema.builder()
                                                          .type(Type.Known.INTEGER)
                                                          .description("Number of copies sold")
                                                          .build()))
                                          .build()) // End items schema for albums
                                  .build() // End "albums" property schema
                              ))
                      .build()) // End parameters schema
              .build(); // End function declaration

      Tool salesTool = Tool.builder().functionDeclarations(getAlbumSales).build();

      GenerateContentConfig config =
          GenerateContentConfig.builder().tools(salesTool).temperature(0.0f).build();

      GenerateContentResponse response = client.models.generateContent(modelId, contents, config);

      // response.functionCalls() returns an Immutable<FunctionCall>.
      System.out.println(response.functionCalls().get(0));

      return response.functionCalls().toString();
      // Example response:
      // FunctionCall{id=Optional.empty, args=Optional[{albums=[{copies_sold=350000,
      // album_name=Echoes of the Night},
      // {copies_sold=120000, album_name=Reckless Hearts}, {copies_sold=75000, album_name=Whispers
      // of Dawn},
      // {album_name=Street Symphony, copies_sold=100000}]}], name=Optional[get_album_sales]}
    }
  }
}

Node.js

Before trying this sample, follow the Node.js setup instructions in the Vertex AI quickstart using client libraries. For more information, see the Vertex AI Node.js API reference documentation.

To authenticate to Vertex AI, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

const {GoogleGenAI, Type} = require('@google/genai');

const GOOGLE_CLOUD_PROJECT = process.env.GOOGLE_CLOUD_PROJECT;
const GOOGLE_CLOUD_LOCATION = process.env.GOOGLE_CLOUD_LOCATION || 'global';

async function generateContent(
  projectId = GOOGLE_CLOUD_PROJECT,
  location = GOOGLE_CLOUD_LOCATION
) {
  const ai = new GoogleGenAI({
    vertexai: true,
    project: projectId,
    location: location,
  });

  const get_album_sales = {
    name: 'get_album_sales',
    description: 'Gets the number of albums sold',
    parameters: {
      type: Type.OBJECT,
      properties: {
        albums: {
          type: Type.ARRAY,
          description: 'List of albums',
          items: {
            description: 'Album and its sales',
            type: Type.OBJECT,
            properties: {
              album_name: {
                type: Type.STRING,
                description: 'Name of the music album',
              },
              copies_sold: {
                type: Type.INTEGER,
                description: 'Number of copies sold',
              },
            },
          },
        },
      },
    },
  };

  const sales_tool = {
    functionDeclarations: [get_album_sales],
  };

  const prompt = `
    At Stellar Sounds, a music label, 2024 was a rollercoaster. "Echoes of the Night", a debut synth-pop album, 
    surprisingly sold 350,000 copies, while veteran rock band "Crimson Tide's" latest, "Reckless Hearts",
    lagged at 120,000. Their up-and-coming indie artist, "Luna Bloom's" EP, "Whispers of Dawn",
    secured 75,000 sales. The biggest disappointment was the highly-anticipated rap album "Street Symphony" 
    only reaching 100,000 units. Overall, Stellar Sounds moved over 645,000 units this year, revealing unexpected
    trends in music consumption.
  `;

  const MODEL_NAME = 'gemini-2.5-flash';

  const response = await ai.models.generateContent({
    model: MODEL_NAME,
    contents: prompt,
    config: {
      tools: [sales_tool],
      temperature: 0,
    },
  });

  console.log(response.functionCalls);

  return response.functionCalls;
}

Python

Before trying this sample, follow the Python setup instructions in the Vertex AI quickstart using client libraries. For more information, see the Vertex AI Python API reference documentation.

To authenticate to Vertex AI, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

from google import genai
from google.genai.types import (
    FunctionDeclaration,
    GenerateContentConfig,
    HttpOptions,
    Tool,
)

client = genai.Client(http_options=HttpOptions(api_version="v1"))
model_id = "gemini-2.5-flash"

get_album_sales = FunctionDeclaration(
    name="get_album_sales",
    description="Gets the number of albums sold",
    # Function parameters are specified in JSON schema format
    parameters={
        "type": "OBJECT",
        "properties": {
            "albums": {
                "type": "ARRAY",
                "description": "List of albums",
                "items": {
                    "description": "Album and its sales",
                    "type": "OBJECT",
                    "properties": {
                        "album_name": {
                            "type": "STRING",
                            "description": "Name of the music album",
                        },
                        "copies_sold": {
                            "type": "INTEGER",
                            "description": "Number of copies sold",
                        },
                    },
                },
            },
        },
    },
)

sales_tool = Tool(
    function_declarations=[get_album_sales],
)

response = client.models.generate_content(
    model=model_id,
    contents='At Stellar Sounds, a music label, 2024 was a rollercoaster. "Echoes of the Night," a debut synth-pop album, '
    'surprisingly sold 350,000 copies, while veteran rock band "Crimson Tide\'s" latest, "Reckless Hearts," '
    'lagged at 120,000. Their up-and-coming indie artist, "Luna Bloom\'s" EP, "Whispers of Dawn," '
    'secured 75,000 sales. The biggest disappointment was the highly-anticipated rap album "Street Symphony" '
    "only reaching 100,000 units. Overall, Stellar Sounds moved over 645,000 units this year, revealing unexpected "
    "trends in music consumption.",
    config=GenerateContentConfig(
        tools=[sales_tool],
        temperature=0,
    ),
)

print(response.function_calls)
# Example response:
# [FunctionCall(
#     id=None,
#     name="get_album_sales",
#     args={
#         "albums": [
#             {"album_name": "Echoes of the Night", "copies_sold": 350000},
#             {"copies_sold": 120000, "album_name": "Reckless Hearts"},
#             {"copies_sold": 75000, "album_name": "Whispers of Dawn"},
#             {"copies_sold": 100000, "album_name": "Street Symphony"},
#         ]
#     },
# )]

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