إنشاء الصور باستخدام Nano Banana

from google import genai
from PIL import Image
import base64

client = genai.Client()

interaction = client.interactions.create(
    model="gemini-nano-banana-2.1",
    input="Create a picture of a nano banana dish in a fancy restaurant with a Gemini theme",
)

with open("generated_image.png", "wb") as f:
    f.write(base64.b64decode(interaction.output_image.data))

import { GoogleGenAI } from "@google/genai";
import * as fs from "node:fs";

async function main() {

  const ai = new GoogleGenAI({});

  const prompt =
    "Create a picture of a nano banana dish in a fancy restaurant with a Gemini theme";

  const interaction = await ai.interactions.create({
    model: "gemini-nano-banana-2.1",
    input: prompt,
  });
  const generatedImage = interaction.output_image;
  if (generatedImage) {
    const buffer = Buffer.from(generatedImage.data, "base64");
    fs.writeFileSync("gemini-native-image.png", buffer);
    console.log("Image saved as gemini-native-image.png");
  }
}

main();

import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;
import java.nio.file.Files;
import java.nio.file.Paths;
import java.util.Base64;

Client client = new Client();

CreateModelInteraction params =
    CreateModelInteraction.builder()
        .model(Model.of("gemini-nano-banana-2.1"))
        .input(
            InteractionsInput.of(
                "Create a picture of a nano banana dish in a fancy restaurant with a Gemini theme"))
        .build();

Interaction interaction =
    client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();

if (interaction.outputImage().isPresent()
    && interaction.outputImage().get().data().isPresent()) {
  byte[] imageBytes =
      Base64.getDecoder().decode(interaction.outputImage().get().data().get());
  Files.write(Paths.get("generated_image.png"), imageBytes);
}

package main

import (
    "context"
    "encoding/base64"
    "log"
    "os"

    "google.golang.org/genai"
    "google.golang.org/genai/interactions/models/interactions"
    "google.golang.org/genai/interactions/models/operations"
)

func main() {
    ctx := context.Background()
    client, err := genai.NewClient(ctx, nil)
    if err != nil {
        log.Fatal(err)
    }

    res, err := client.Interactions.Create(ctx, operations.CreateInteractionRequest{
        Body: operations.NewCreateInteractionRequestBody(interactions.CreateModelInteraction{
            Model: interactions.Model("gemini-nano-banana-2.1"),
            Input: interactions.NewInteractionsInput("Create a picture of a nano banana dish in a fancy restaurant with a Gemini theme"),
        }),
    })
    if err != nil {
        log.Fatal(err)
    }

    if res.Interaction.OutputImage != nil && res.Interaction.OutputImage.Data != nil {
        imageBytes, err := base64.StdEncoding.DecodeString(*res.Interaction.OutputImage.Data)
        if err != nil {
            log.Fatal(err)
        }
        if err := os.WriteFile("generated_image.png", imageBytes, 0644); err != nil {
            log.Fatal(err)
        }
    }
}

curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-nano-banana-2.1",
    "input": [
      {"type": "text", "text": "Create a picture of a nano banana dish in a fancy restaurant with a Gemini theme"}
    ]
  }'

from google import genai
from PIL import Image
import base64

client = genai.Client()

with open("/path/to/cat_image.png", "rb") as f:
    image_bytes = f.read()

interaction = client.interactions.create(
    model="gemini-nano-banana-2.1",
    input=[
        {
          "type": "text",
          "text": "Create a picture of a nano banana dish in a fancy restaurant with a Gemini theme"
        },
        {
            "type": "image",
            "data": base64.b64encode(image_bytes).decode('utf-8'),
            "mime_type": "image/png"
        }
    ],
)

with open("generated_image.png", "wb") as f:
    f.write(base64.b64decode(interaction.output_image.data))

import { GoogleGenAI } from "@google/genai";
import * as fs from "node:fs";

async function main() {

  const ai = new GoogleGenAI({});

  const imagePath = "path/to/cat_image.png";
  const imageData = fs.readFileSync(imagePath);
  const base64Image = imageData.toString("base64");

  const prompt = [
    { type: "text", text: "Create a picture of my cat eating a nano-banana in a" +
            "fancy restaurant under the Gemini constellation" },
    {
      type: "image",
      mime_type: "image/png",
      data: base64Image
    },
  ];

  const interaction = await ai.interactions.create({
    model: "gemini-nano-banana-2.1",
    input: prompt,
  });
  const generatedImage = interaction.output_image;
  if (generatedImage) {
    const buffer = Buffer.from(generatedImage.data, "base64");
    fs.writeFileSync("gemini-native-image.png", buffer);
    console.log("Image saved as gemini-native-image.png");
  }
}

main();

import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.Content;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.ImageContent;
import com.google.genai.gaos.models.interactions.ImageContentMimeType;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.interactions.TextContent;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;
import java.nio.file.Files;
import java.nio.file.Paths;
import java.util.Arrays;
import java.util.Base64;
import java.util.List;

Client client = new Client();

byte[] inputBytes = Files.readAllBytes(Paths.get("/path/to/cat_image.png"));
String base64Image = Base64.getEncoder().encodeToString(inputBytes);

Content textContent =
    TextContent.builder()
        .text("Create a picture of a nano banana dish in a fancy restaurant with a Gemini theme")
        .build();
Content imageContent =
    ImageContent.builder()
        .data(base64Image)
        .mimeType(ImageContentMimeType.IMAGE_PNG)
        .build();

List<Content> contents = Arrays.asList(textContent, imageContent);

CreateModelInteraction params =
    CreateModelInteraction.builder()
        .model(Model.of("gemini-nano-banana-2.1"))
        .input(InteractionsInput.ofContent(contents))
        .build();

Interaction interaction =
    client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();

if (interaction.outputImage().isPresent()
    && interaction.outputImage().get().data().isPresent()) {
  byte[] outputBytes =
      Base64.getDecoder().decode(interaction.outputImage().get().data().get());
  Files.write(Paths.get("generated_image.png"), outputBytes);
}

package main

import (
    "context"
    "encoding/base64"
    "log"
    "os"

    "google.golang.org/genai"
    "google.golang.org/genai/interactions/models/interactions"
    "google.golang.org/genai/interactions/models/operations"
)

func main() {
    ctx := context.Background()
    client, err := genai.NewClient(ctx, nil)
    if err != nil {
        log.Fatal(err)
    }

    inputBytes, err := os.ReadFile("/path/to/cat_image.png")
    if err != nil {
        log.Fatal(err)
    }
    base64Image := base64.StdEncoding.EncodeToString(inputBytes)

    res, err := client.Interactions.Create(ctx, operations.CreateInteractionRequest{
        Body: operations.NewCreateInteractionRequestBody(interactions.CreateModelInteraction{
            Model: interactions.Model("gemini-nano-banana-2.1"),
            Input: interactions.NewInteractionsInput([]interactions.Content{
                interactions.NewContent(interactions.TextContent{
                    Text: "Create a picture of a nano banana dish in a fancy restaurant with a Gemini theme",
                }),
                interactions.NewContent(interactions.ImageContent{
                    Data:     genai.Ptr(base64Image),
                    MimeType: interactions.ImageContentMimeTypeImagePng.ToPointer(),
                }),
            }),
        }),
    })
    if err != nil {
        log.Fatal(err)
    }

    if res.Interaction.OutputImage != nil && res.Interaction.OutputImage.Data != nil {
        outputBytes, err := base64.StdEncoding.DecodeString(*res.Interaction.OutputImage.Data)
        if err != nil {
            log.Fatal(err)
        }
        if err := os.WriteFile("generated_image.png", outputBytes, 0644); err != nil {
            log.Fatal(err)
        }
    }
}

curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/interactions" \
    -H "x-goog-api-key: $GEMINI_API_KEY" \
    -H 'Content-Type: application/json' \
    -d "{
      \"model\": \"gemini-nano-banana-2.1\",
      \"input\": [
        {\"type\": \"text\", \"text\": \"Create a picture of my cat eating a nano-banana in a fancy restaurant under the Gemini constellation\"},
        {
          \"type\": \"image\",
          \"mime_type\": \"image/jpeg\",
          \"data\": \"<BASE64_IMAGE_DATA>\"
        }
      ]
    }"

from google import genai
import base64

client = genai.Client()

interaction = client.interactions.create(
    model="gemini-nano-banana-2.1",
    input="Create a vibrant infographic that explains photosynthesis as if it were a recipe for a plant's favorite food. Show the \"ingredients\" (sunlight, water, CO2) and the \"finished dish\" (sugar/energy). The style should be like a page from a colorful kids' cookbook, suitable for a 4th grader.",
    tools=[{"type": "google_search"}],
)

with open("photosynthesis.png", "wb") as f:
    f.write(base64.b64decode(interaction.output_image.data))

import { GoogleGenAI } from "@google/genai";
import * as fs from "node:fs";

const ai = new GoogleGenAI({});

async function main() {
  const interaction = await ai.interactions.create({
    model: "gemini-nano-banana-2.1",
    input: "Create a vibrant infographic that explains photosynthesis as if it were a recipe for a plant's favorite food. Show the \"ingredients\" (sunlight, water, CO2) and the \"finished dish\" (sugar/energy). The style should be like a page from a colorful kids' cookbook, suitable for a 4th grader.",
    tools: [{"type": "google_search"}],
  });

  const generatedImage = interaction.output_image;
  if (generatedImage) {
    const buffer = Buffer.from(generatedImage.data, "base64");
    fs.writeFileSync("photosynthesis.png", buffer);
    console.log("Image saved as photosynthesis.png");
  }
}

await main();

import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.GoogleSearch;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;
import java.nio.file.Files;
import java.nio.file.Paths;
import java.util.Arrays;
import java.util.Base64;

Client client = new Client();

CreateModelInteraction params =
    CreateModelInteraction.builder()
        .model(Model.of("gemini-nano-banana-2.1"))
        .input(
            InteractionsInput.of(
                "Create a vibrant infographic that explains photosynthesis as if it were a recipe for a plant's favorite food. Show the \"ingredients\" (sunlight, water, CO2) and the \"finished dish\" (sugar/energy). The style should be like a page from a colorful kids' cookbook, suitable for a 4th grader."))
        .tools(Arrays.asList(new GoogleSearch()))
        .build();

Interaction interaction =
    client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();

if (interaction.outputImage().isPresent()
    && interaction.outputImage().get().data().isPresent()) {
  byte[] imageBytes =
      Base64.getDecoder().decode(interaction.outputImage().get().data().get());
  Files.write(Paths.get("photosynthesis.png"), imageBytes);
}

package main

import (
    "context"
    "encoding/base64"
    "log"
    "os"

    "google.golang.org/genai"
    "google.golang.org/genai/interactions/models/interactions"
    "google.golang.org/genai/interactions/models/operations"
)

func main() {
    ctx := context.Background()
    client, err := genai.NewClient(ctx, nil)
    if err != nil {
        log.Fatal(err)
    }

    res, err := client.Interactions.Create(ctx, operations.CreateInteractionRequest{
        Body: operations.NewCreateInteractionRequestBody(interactions.CreateModelInteraction{
            Model: interactions.Model("gemini-nano-banana-2.1"),
            Input: interactions.NewInteractionsInput(`Create a vibrant infographic that explains photosynthesis as if it were a recipe for a plant's favorite food. Show the "ingredients" (sunlight, water, CO2) and the "finished dish" (sugar/energy). The style should be like a page from a colorful kids' cookbook, suitable for a 4th grader.`),
            Tools: []interactions.Tool{
                interactions.NewTool(interactions.GoogleSearch{}),
            },
        }),
    })
    if err != nil {
        log.Fatal(err)
    }

    if res.Interaction.OutputImage != nil && res.Interaction.OutputImage.Data != nil {
        imageBytes, err := base64.StdEncoding.DecodeString(*res.Interaction.OutputImage.Data)
        if err != nil {
            log.Fatal(err)
        }
        if err := os.WriteFile("photosynthesis.png", imageBytes, 0644); err != nil {
            log.Fatal(err)
        }
    }
}

curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-nano-banana-2.1",
    "input": [
      {"type": "text", "text": "Create a vibrant infographic that explains photosynthesis as if it were a recipe for a plants favorite food. Show the \"ingredients\" (sunlight, water, CO2) and the \"finished dish\" (sugar/energy). The style should be like a page from a colorful kids cookbook, suitable for a 4th grader."}
    ],
    "tools": [{"type": "google_search"}]
  }'

interaction_2 = client.interactions.create(
    model="gemini-nano-banana-2.1",
    input="Update this infographic to be in Spanish. Do not change any other elements of the image.",
    previous_interaction_id=interaction.id,
    response_format={
        "type": "image",
        "mime_type": "image/jpeg",
        "aspect_ratio": "16:9",
        "image_size": "2K"
    },
)

generated_image = interaction_2.output_image
if generated_image:
    with open("photosynthesis_spanish.png", "wb") as f:
        f.write(base64.b64decode(generated_image.data))

const interaction2 = await ai.interactions.create({
  model: "gemini-nano-banana-2.1",
  input: "Update this infographic to be in Spanish. Do not change any other elements of the image.",
  previous_interaction_id: interaction.id,
  response_format: {
    type: "image",
    mime_type: "image/png",
    aspect_ratio: "16:9",
    image_size: "2K"
  },
});

const generatedImage = interaction2.output_image;
if (generatedImage) {
  const buffer = Buffer.from(generatedImage.data, "base64");
  fs.writeFileSync("photosynthesis_spanish.png", buffer);
}

import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.CreateModelInteractionResponseFormat;
import com.google.genai.gaos.models.interactions.GoogleSearch;
import com.google.genai.gaos.models.interactions.ImageResponseFormat;
import com.google.genai.gaos.models.interactions.ImageResponseFormatAspectRatio;
import com.google.genai.gaos.models.interactions.ImageResponseFormatImageSize;
import com.google.genai.gaos.models.interactions.ImageResponseFormatMimeType;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.interactions.ResponseFormat;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;
import java.nio.file.Files;
import java.nio.file.Paths;
import java.util.Arrays;
import java.util.Base64;

Client client = new Client();

CreateModelInteraction turn1Params =
    CreateModelInteraction.builder()
        .model(Model.of("gemini-nano-banana-2.1"))
        .input(
            InteractionsInput.of(
                "Create a vibrant infographic that explains photosynthesis as if it were a recipe for a plant's favorite food."))
        .tools(Arrays.asList(new GoogleSearch()))
        .build();

Interaction interaction =
    client.interactions.create(CreateInteractionRequestBody.of(turn1Params)).interaction().get();

CreateModelInteractionResponseFormat format =
    CreateModelInteractionResponseFormat.of(
        ResponseFormat.of(
            ImageResponseFormat.builder()
                .mimeType(ImageResponseFormatMimeType.IMAGE_JPEG)
                .aspectRatio(ImageResponseFormatAspectRatio.of("16:9"))
                .imageSize(ImageResponseFormatImageSize.TWO_K)
                .build()));

CreateModelInteraction turn2Params =
    CreateModelInteraction.builder()
        .model(Model.of("gemini-nano-banana-2.1"))
        .input(
            InteractionsInput.of(
                "Update this infographic to be in Spanish. Do not change any other elements of the image."))
        .previousInteractionId(interaction.id().orElse(""))
        .responseFormat(format)
        .build();

Interaction interaction2 =
    client.interactions.create(CreateInteractionRequestBody.of(turn2Params)).interaction().get();

if (interaction2.outputImage().isPresent()
    && interaction2.outputImage().get().data().isPresent()) {
  byte[] imageBytes =
      Base64.getDecoder().decode(interaction2.outputImage().get().data().get());
  Files.write(Paths.get("photosynthesis_spanish.png"), imageBytes);
}

package main

import (
    "context"
    "encoding/base64"
    "log"
    "os"

    "google.golang.org/genai"
    "google.golang.org/genai/interactions/models/interactions"
    "google.golang.org/genai/interactions/models/operations"
)

func main() {
    ctx := context.Background()
    client, err := genai.NewClient(ctx, nil)
    if err != nil {
        log.Fatal(err)
    }

    res1, err := client.Interactions.Create(ctx, operations.CreateInteractionRequest{
        Body: operations.NewCreateInteractionRequestBody(interactions.CreateModelInteraction{
            Model: interactions.Model("gemini-nano-banana-2.1"),
            Input: interactions.NewInteractionsInput("Create a vibrant infographic that explains photosynthesis as if it were a recipe for a plant's favorite food."),
            Tools: []interactions.Tool{
                interactions.NewTool(interactions.GoogleSearch{}),
            },
        }),
    })
    if err != nil {
        log.Fatal(err)
    }

    format := interactions.NewCreateModelInteractionResponseFormat(
        interactions.NewResponseFormat(interactions.ImageResponseFormat{
            MimeType:    interactions.ImageResponseFormatMimeTypeImageJpeg.ToPointer(),
            AspectRatio: interactions.ImageResponseFormatAspectRatio("16:9").ToPointer(),
            ImageSize:   interactions.ImageResponseFormatImageSizeTwoK.ToPointer(),
        }),
    )

    res2, err := client.Interactions.Create(ctx, operations.CreateInteractionRequest{
        Body: operations.NewCreateInteractionRequestBody(interactions.CreateModelInteraction{
            Model:                 interactions.Model("gemini-nano-banana-2.1"),
            Input:                 interactions.NewInteractionsInput("Update this infographic to be in Spanish. Do not change any other elements of the image."),
            PreviousInteractionID: res1.Interaction.ID,
            ResponseFormat:        genai.Ptr(format),
        }),
    })
    if err != nil {
        log.Fatal(err)
    }

    if res2.Interaction.OutputImage != nil && res2.Interaction.OutputImage.Data != nil {
        imageBytes, err := base64.StdEncoding.DecodeString(*res2.Interaction.OutputImage.Data)
        if err != nil {
            log.Fatal(err)
        }
        if err := os.WriteFile("photosynthesis_spanish.png", imageBytes, 0644); err != nil {
            log.Fatal(err)
        }
    }
}

curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "gemini-nano-banana-2.1",
    "input": "Update this infographic to be in Spanish. Do not change any other elements of the image.",
    "previous_interaction_id": "<PREVIOUS_INTERACTION_ID>",
    "response_format": {
      "type": "image",
      "mime_type": "image/jpeg",
      "aspect_ratio": "16:9",
      "image_size": "2K"
    }
  }'

from google import genai
from google.genai import types
from PIL import Image
import base64

prompt = "An office group photo of these people, they are making funny faces."

client = genai.Client()

interaction = client.interactions.create(
    model="gemini-nano-banana-2.1",
    input=[
        {
            "type": "text",
            "text": prompt,
        },
        {
            "type": "image",
            "data": base64.b64encode(image_bytes).decode('utf-8'),
            "mime_type": "image/png"
        },
        {
            "type": "image",
            "data": base64.b64encode(image_bytes).decode('utf-8'),
            "mime_type": "image/png"
        },
        {
            "type": "image",
            "data": base64.b64encode(image_bytes).decode('utf-8'),
            "mime_type": "image/png"
        },
        {
            "type": "image",
            "data": base64.b64encode(image_bytes).decode('utf-8'),
            "mime_type": "image/png"
        },
        {
            "type": "image",
            "data": base64.b64encode(image_bytes).decode('utf-8'),
            "mime_type": "image/png"
        },
    ],
    response_format={
        "type": "image",
        "aspect_ratio": "5:4",
        "image_size": "2K"
    },
)

with open("office.png", "wb") as f:
    f.write(base64.b64decode(interaction.output_image.data))

import { GoogleGenAI } from "@google/genai";
import * as fs from "node:fs";

async function main() {
  const ai = new GoogleGenAI({});

  const input = [
    {
      type: "text",
      text: "An office group photo of these people, they are making funny faces.",
    },
    { type: "image", mime_type: "image/jpeg", data: base64ImageFile1 },
    { type: "image", mime_type: "image/jpeg", data: base64ImageFile2 },
    { type: "image", mime_type: "image/jpeg", data: base64ImageFile3 },
    { type: "image", mime_type: "image/jpeg", data: base64ImageFile4 },
    { type: "image", mime_type: "image/jpeg", data: base64ImageFile5 },
  ];

  const interaction = await ai.interactions.create({
    model: "gemini-nano-banana-2.1",
    input: input,
    response_format: {
      type: "image",
      aspect_ratio: "5:4",
      image_size: "2K",
    },
  });

  const buffer = Buffer.from(interaction.output_image.data, 'base64');

  fs.writeFileSync('office.png', buffer);
}

main();

import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.Content;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.CreateModelInteractionResponseFormat;
import com.google.genai.gaos.models.interactions.ImageContent;
import com.google.genai.gaos.models.interactions.ImageContentMimeType;
import com.google.genai.gaos.models.interactions.ImageResponseFormat;
import com.google.genai.gaos.models.interactions.ImageResponseFormatAspectRatio;
import com.google.genai.gaos.models.interactions.ImageResponseFormatImageSize;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.interactions.ResponseFormat;
import com.google.genai.gaos.models.interactions.TextContent;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;
import java.nio.file.Files;
import java.nio.file.Paths;
import java.util.Arrays;
import java.util.Base64;
import java.util.List;

String prompt = "An office group photo of these people, they are making funny faces.";

byte[] imageBytes = Files.readAllBytes(Paths.get("/path/to/person.png"));
String base64Image = Base64.getEncoder().encodeToString(imageBytes);

Content textContent = TextContent.builder().text(prompt).build();
Content imageContent =
    ImageContent.builder()
        .data(base64Image)
        .mimeType(ImageContentMimeType.IMAGE_PNG)
        .build();

List<Content> contents =
    Arrays.asList(
        textContent,
        imageContent,
        imageContent,
        imageContent,
        imageContent,
        imageContent);

CreateModelInteractionResponseFormat format =
    CreateModelInteractionResponseFormat.of(
        ResponseFormat.of(
            ImageResponseFormat.builder()
                .aspectRatio(ImageResponseFormatAspectRatio.of("5:4"))
                .imageSize(ImageResponseFormatImageSize.TWO_K)
                .build()));

Client client = new Client();

CreateModelInteraction params =
    CreateModelInteraction.builder()
        .model(Model.of("gemini-nano-banana-2.1"))
        .input(InteractionsInput.ofContent(contents))
        .responseFormat(format)
        .build();

Interaction interaction =
    client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();

if (interaction.outputImage().isPresent()
    && interaction.outputImage().get().data().isPresent()) {
  byte[] outBytes =
      Base64.getDecoder().decode(interaction.outputImage().get().data().get());
  Files.write(Paths.get("office.png"), outBytes);
}

package main

import (
    "context"
    "encoding/base64"
    "log"
    "os"

    "google.golang.org/genai"
    "google.golang.org/genai/interactions/models/interactions"
    "google.golang.org/genai/interactions/models/operations"
)

func main() {
    ctx := context.Background()
    client, err := genai.NewClient(ctx, nil)
    if err != nil {
        log.Fatal(err)
    }

    prompt := "An office group photo of these people, they are making funny faces."

    imageBytes, err := os.ReadFile("/path/to/person.png")
    if err != nil {
        log.Fatal(err)
    }
    base64Image := base64.StdEncoding.EncodeToString(imageBytes)

    textContent := interactions.NewContent(interactions.TextContent{
        Text: prompt,
    })
    imageContent := interactions.NewContent(interactions.ImageContent{
        Data:     genai.Ptr(base64Image),
        MimeType: interactions.ImageContentMimeTypeImagePng.ToPointer(),
    })

    contents := []interactions.Content{
        textContent,
        imageContent,
        imageContent,
        imageContent,
        imageContent,
        imageContent,
    }

    format := interactions.NewCreateModelInteractionResponseFormat(
        interactions.NewResponseFormat(interactions.ImageResponseFormat{
            AspectRatio: interactions.ImageResponseFormatAspectRatio("5:4").ToPointer(),
            ImageSize:   interactions.ImageResponseFormatImageSizeTwoK.ToPointer(),
        }),
    )

    res, err := client.Interactions.Create(ctx, operations.CreateInteractionRequest{
        Body: operations.NewCreateInteractionRequestBody(interactions.CreateModelInteraction{
            Model:          interactions.Model("gemini-nano-banana-2.1"),
            Input:          interactions.NewInteractionsInput(contents),
            ResponseFormat: genai.Ptr(format),
        }),
    })
    if err != nil {
        log.Fatal(err)
    }

    if res.Interaction.OutputImage != nil && res.Interaction.OutputImage.Data != nil {
        outBytes, err := base64.StdEncoding.DecodeString(*res.Interaction.OutputImage.Data)
        if err != nil {
            log.Fatal(err)
        }
        if err := os.WriteFile("office.png", outBytes, 0644); err != nil {
            log.Fatal(err)
        }
    }
}

curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/interactions" \
    -H "x-goog-api-key: $GEMINI_API_KEY" \
    -H 'Content-Type: application/json' \
    -d "{
      \"model\": \"gemini-nano-banana-2.1\",
      \"input\": [
        {\"type\": \"text\", \"text\": \"An office group photo of these people, they are making funny faces.\"},
        {\"type\": \"image\", \"mime_type\": \"image/png\", \"data\": \"<BASE64_DATA_IMG_1>\"},
        {\"type\": \"image\", \"mime_type\": \"image/png\", \"data\": \"<BASE64_DATA_IMG_2>\"},
        {\"type\": \"image\", \"mime_type\": \"image/png\", \"data\": \"<BASE64_DATA_IMG_3>\"},
        {\"type\": \"image\", \"mime_type\": \"image/png\", \"data\": \"<BASE64_DATA_IMG_4>\"},
        {\"type\": \"image\", \"mime_type\": \"image/png\", \"data\": \"<BASE64_DATA_IMG_5>\"}
      ],
      \"response_format\": {
        \"type\": \"image\",
        \"aspect_ratio\": \"5:4\",
        \"image_size\": \"2K\"
      }
    }"

from google import genai
from google.genai import types
import base64
prompt = "Visualize the current weather forecast for the next 5 days in San Francisco as a clean, modern weather chart. Add a visual on what I should wear each day"

client = genai.Client()

interaction = client.interactions.create(
    model="gemini-nano-banana-2.1",
    input=prompt,
    tools=[{"type": "google_search"}],
    response_format={
        "type": "image",
        "mime_type": "image/jpeg",
        "aspect_ratio": "16:9"
    },
)

with open("weather.png", "wb") as f:
    f.write(base64.b64decode(interaction.output_image.data))

import { GoogleGenAI } from "@google/genai";
import * as fs from "node:fs";

async function main() {
  const ai = new GoogleGenAI({});

  const interaction = await ai.interactions.create({
    model: "gemini-nano-banana-2.1",
    input: "Visualize the current weather forecast for the next 5 days in San Francisco as a clean, modern weather chart. Add a visual on what I should wear each day",
    tools: [{"type": "google_search"}],
    response_format: {
      type: "image",
      mime_type: "image/png",
      aspect_ratio: "16:9",
      image_size: "2K"
    },
  });

  const buffer = Buffer.from(interaction.output_image.data, 'base64');

  fs.writeFileSync('weather.png', buffer);
}

main();

import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.CreateModelInteractionResponseFormat;
import com.google.genai.gaos.models.interactions.GoogleSearch;
import com.google.genai.gaos.models.interactions.ImageResponseFormat;
import com.google.genai.gaos.models.interactions.ImageResponseFormatAspectRatio;
import com.google.genai.gaos.models.interactions.ImageResponseFormatMimeType;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.interactions.ResponseFormat;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;
import java.nio.file.Files;
import java.nio.file.Paths;
import java.util.Arrays;
import java.util.Base64;

String prompt =
    "Visualize the current weather forecast for the next 5 days in San Francisco as a clean, modern weather chart. Add a visual on what I should wear each day";

Client client = new Client();

CreateModelInteractionResponseFormat format =
    CreateModelInteractionResponseFormat.of(
        ResponseFormat.of(
            ImageResponseFormat.builder()
                .mimeType(ImageResponseFormatMimeType.IMAGE_JPEG)
                .aspectRatio(ImageResponseFormatAspectRatio.of("16:9"))
                .build()));

CreateModelInteraction params =
    CreateModelInteraction.builder()
        .model(Model.of("gemini-nano-banana-2.1"))
        .input(InteractionsInput.of(prompt))
        .tools(Arrays.asList(new GoogleSearch()))
        .responseFormat(format)
        .build();

Interaction interaction =
    client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();

if (interaction.outputImage().isPresent()
    && interaction.outputImage().get().data().isPresent()) {
  byte[] imageBytes =
      Base64.getDecoder().decode(interaction.outputImage().get().data().get());
  Files.write(Paths.get("weather.png"), imageBytes);
}

package main

import (
    "context"
    "encoding/base64"
    "log"
    "os"

    "google.golang.org/genai"
    "google.golang.org/genai/interactions/models/interactions"
    "google.golang.org/genai/interactions/models/operations"
)

func main() {
    ctx := context.Background()
    client, err := genai.NewClient(ctx, nil)
    if err != nil {
        log.Fatal(err)
    }

    prompt := "Visualize the current weather forecast for the next 5 days in San Francisco as a clean, modern weather chart. Add a visual on what I should wear each day"

    format := interactions.NewCreateModelInteractionResponseFormat(
        interactions.NewResponseFormat(interactions.ImageResponseFormat{
            MimeType:    interactions.ImageResponseFormatMimeTypeImageJpeg.ToPointer(),
            AspectRatio: interactions.ImageResponseFormatAspectRatio("16:9").ToPointer(),
        }),
    )

    res, err := client.Interactions.Create(ctx, operations.CreateInteractionRequest{
        Body: operations.NewCreateInteractionRequestBody(interactions.CreateModelInteraction{
            Model: interactions.Model("gemini-nano-banana-2.1"),
            Input: interactions.NewInteractionsInput(prompt),
            Tools: []interactions.Tool{
                interactions.NewTool(interactions.GoogleSearch{}),
            },
            ResponseFormat: genai.Ptr(format),
        }),
    })
    if err != nil {
        log.Fatal(err)
    }

    if res.Interaction.OutputImage != nil && res.Interaction.OutputImage.Data != nil {
        imageBytes, err := base64.StdEncoding.DecodeString(*res.Interaction.OutputImage.Data)
        if err != nil {
            log.Fatal(err)
        }
        if err := os.WriteFile("weather.png", imageBytes, 0644); err != nil {
            log.Fatal(err)
        }
    }
}

curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-nano-banana-2.1",
    "input": [
      {"type": "text", "text": "Visualize the current weather forecast for the next 5 days in San Francisco as a clean, modern weather chart. Add a visual on what I should wear each day"}
    ],
    "tools": [{"type": "google_search"}],
    "response_format": {
      "type": "image",
      "mime_type": "image/jpeg",
      "aspect_ratio": "16:9"
    }
  }'

from google import genai

client = genai.Client()

interaction = client.interactions.create(
    model="gemini-nano-banana-2.1",
    input="A detailed painting of a Timareta butterfly resting on a flower",
    tools=[{
      "type": "google_search",
      "search_types": ["web_search", "image_search"]
    }]
)

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

async function main() {
  const ai = new GoogleGenAI({});

  const interaction = await ai.interactions.create({
    model: "gemini-nano-banana-2.1",
    input: "A detailed painting of a Timareta butterfly resting on a flower",
    tools: [{
      "type": "google_search",
      "search_types": ["web_search", "image_search"]
    }]
  });
}

main();

import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.GoogleSearch;
import com.google.genai.gaos.models.interactions.GoogleSearchSearchType;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;
import java.util.Arrays;

Client client = new Client();

GoogleSearch searchTool =
    GoogleSearch.builder()
        .searchTypes(
            Arrays.asList(
                GoogleSearchSearchType.WEB_SEARCH, GoogleSearchSearchType.IMAGE_SEARCH))
        .build();

CreateModelInteraction params =
    CreateModelInteraction.builder()
        .model(Model.of("gemini-nano-banana-2.1"))
        .input(
            InteractionsInput.of(
                "A detailed painting of a Timareta butterfly resting on a flower"))
        .tools(Arrays.asList(searchTool))
        .build();

Interaction interaction =
    client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();

package main

import (
    "context"
    "log"

    "google.golang.org/genai"
    "google.golang.org/genai/interactions/models/interactions"
    "google.golang.org/genai/interactions/models/operations"
)

func main() {
    ctx := context.Background()
    client, err := genai.NewClient(ctx, nil)
    if err != nil {
        log.Fatal(err)
    }

    searchTool := interactions.GoogleSearch{
        SearchTypes: []interactions.GoogleSearchSearchType{
            interactions.GoogleSearchSearchTypeWebSearch,
            interactions.GoogleSearchSearchTypeImageSearch,
        },
    }

    res, err := client.Interactions.Create(ctx, operations.CreateInteractionRequest{
        Body: operations.NewCreateInteractionRequestBody(interactions.CreateModelInteraction{
            Model: interactions.Model("gemini-nano-banana-2.1"),
            Input: interactions.NewInteractionsInput("A detailed painting of a Timareta butterfly resting on a flower"),
            Tools: []interactions.Tool{
                interactions.NewTool(searchTool),
            },
        }),
    })
    if err != nil {
        log.Fatal(err)
    }
    _ = res
}

curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-nano-banana-2.1",
    "input": "A detailed painting of a Timareta butterfly resting on a flower",
    "tools": [{"type": "google_search", "search_types": ["web_search", "image_search"]}]
  }'

from google import genai
from google.genai import types
import base64

client = genai.Client()

interaction = client.interactions.create(
    model="gemini-nano-banana-2.1",
    input=[
        {
            "type": "video",
            "uri": "https://www.youtube.com/watch?v=UTdfxFyOQTI",
            "mime_type": "video/mp4"
        },
        {"type": "text", "text": "Generate a poster image that captures the key themes of this video."}
    ],
    response_format={"type": "image", "aspect_ratio": "16:9"}
)

# Save the generated image part
for step in interaction.steps:
    if step.type == "model_output":
        for content_block in step.content:
            if content_block.type == "text":
                print(content_block.text)
            elif content_block.type == "image":
                with open("video_poster.png", "wb") as f:
                    f.write(base64.b64decode(content_block.data))
                print("Image saved as video_poster.png")

import { GoogleGenAI } from "@google/genai";
import * as fs from "node:fs";

async function main() {
  const ai = new GoogleGenAI({});

  const interaction = await ai.interactions.create({
    model: "gemini-nano-banana-2.1",
    input: [
      {
        type: "video",
        uri: "https://www.youtube.com/watch?v=UTdfxFyOQTI",
        mime_type: "video/mp4"
      },
      { type: "text", text: "Generate a poster image that captures the key themes of this video." }
    ],
    response_format: {
      type: "image",
      aspect_ratio: "16:9"
    }
  });

  for (const step of interaction.steps) {
    if (step.type === "model_output") {
      for (const contentBlock of step.content) {
        if (contentBlock.type === "text") {
          console.log(contentBlock.text);
        } else if (contentBlock.type === "image") {
          const buffer = Buffer.from(contentBlock.data, "base64");
          fs.writeFileSync("video_poster.png", buffer);
          console.log("Image saved as video_poster.png");
        }
      }
    }
  }
}

main();

import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.Content;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.CreateModelInteractionResponseFormat;
import com.google.genai.gaos.models.interactions.ImageContent;
import com.google.genai.gaos.models.interactions.ImageResponseFormat;
import com.google.genai.gaos.models.interactions.ImageResponseFormatAspectRatio;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.interactions.ModelOutputStep;
import com.google.genai.gaos.models.interactions.ResponseFormat;
import com.google.genai.gaos.models.interactions.Step;
import com.google.genai.gaos.models.interactions.TextContent;
import com.google.genai.gaos.models.interactions.VideoContent;
import com.google.genai.gaos.models.interactions.VideoContentMimeType;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;
import java.nio.file.Files;
import java.nio.file.Paths;
import java.util.Arrays;
import java.util.Base64;
import java.util.List;

Client client = new Client();

Content videoContent =
    VideoContent.builder()
        .uri("https://www.youtube.com/watch?v=UTdfxFyOQTI")
        .mimeType(VideoContentMimeType.VIDEO_MP4)
        .build();
Content textContent =
    TextContent.builder()
        .text("Generate a poster image that captures the key themes of this video.")
        .build();

List<Content> contents = Arrays.asList(videoContent, textContent);

CreateModelInteractionResponseFormat format =
    CreateModelInteractionResponseFormat.of(
        ResponseFormat.of(
            ImageResponseFormat.builder()
                .aspectRatio(ImageResponseFormatAspectRatio.of("16:9"))
                .build()));

CreateModelInteraction params =
    CreateModelInteraction.builder()
        .model(Model.of("gemini-nano-banana-2.1"))
        .input(InteractionsInput.ofContent(contents))
        .responseFormat(format)
        .build();

Interaction interaction =
    client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();

if (interaction.steps().isPresent()) {
  for (Step step : interaction.steps().get()) {
    if (step instanceof ModelOutputStep) {
      ModelOutputStep outputStep = (ModelOutputStep) step;
      if (outputStep.content().isPresent()) {
        for (Content block : outputStep.content().get()) {
          if (block instanceof TextContent) {
            System.out.println(((TextContent) block).text().orElse(""));
          } else if (block instanceof ImageContent) {
            ImageContent img = (ImageContent) block;
            if (img.data().isPresent()) {
              byte[] imgBytes = Base64.getDecoder().decode(img.data().get());
              Files.write(Paths.get("video_poster.png"), imgBytes);
              System.out.println("Image saved as video_poster.png");
            }
          }
        }
      }
    }
  }
}

package main

import (
    "context"
    "encoding/base64"
    "fmt"
    "log"
    "os"

    "google.golang.org/genai"
    "google.golang.org/genai/interactions/models/interactions"
    "google.golang.org/genai/interactions/models/operations"
)

func main() {
    ctx := context.Background()
    client, err := genai.NewClient(ctx, nil)
    if err != nil {
        log.Fatal(err)
    }

    contents := []interactions.Content{
        interactions.NewContent(interactions.VideoContent{
            URI:      genai.Ptr("https://www.youtube.com/watch?v=UTdfxFyOQTI"),
            MimeType: interactions.VideoContentMimeTypeVideoMp4.ToPointer(),
        }),
        interactions.NewContent(interactions.TextContent{
            Text: "Generate a poster image that captures the key themes of this video.",
        }),
    }

    format := interactions.NewCreateModelInteractionResponseFormat(
        interactions.NewResponseFormat(interactions.ImageResponseFormat{
            AspectRatio: interactions.ImageResponseFormatAspectRatio("16:9").ToPointer(),
        }),
    )

    res, err := client.Interactions.Create(ctx, operations.CreateInteractionRequest{
        Body: operations.NewCreateInteractionRequestBody(interactions.CreateModelInteraction{
            Model:          interactions.Model("gemini-nano-banana-2.1"),
            Input:          interactions.NewInteractionsInput(contents),
            ResponseFormat: genai.Ptr(format),
        }),
    })
    if err != nil {
        log.Fatal(err)
    }

    for _, step := range res.Interaction.Steps {
        if step.ModelOutputStep != nil {
            for _, block := range step.ModelOutputStep.Content {
                if block.TextContent != nil {
                    fmt.Println(block.TextContent.Text)
                } else if block.ImageContent != nil && block.ImageContent.Data != nil {
                    imgBytes, err := base64.StdEncoding.DecodeString(*block.ImageContent.Data)
                    if err != nil {
                        log.Fatal(err)
                    }
                    if err := os.WriteFile("video_poster.png", imgBytes, 0644); err != nil {
                        log.Fatal(err)
                    }
                    fmt.Println("Image saved as video_poster.png")
                }
            }
        }
    }
}

curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "gemini-nano-banana-2.1",
    "input": [
      {
        "type": "video",
        "uri": "https://www.youtube.com/watch?v=UTdfxFyOQTI",
        "mime_type": "video/mp4"
      },
      {
        "type": "text",
        "text": "Generate a poster image that captures the key themes of this video."
      }
    ],
    "response_format": {
      "type": "image",
      "aspect_ratio": "16:9"
    }
  }'

from google import genai
from google.genai import types
import base64

prompt = "Da Vinci style anatomical sketch of a dissected Monarch butterfly. Detailed drawings of the head, wings, and legs on textured parchment with notes in English."

client = genai.Client()

interaction = client.interactions.create(
    model="gemini-nano-banana-2.1",
    input=prompt,
    response_format={
        "type": "image",
        "mime_type": "image/jpeg",
        "aspect_ratio": "1:1",
        "image_size": "1K"
    },
)

print(interaction.output_text)

with open("butterfly.png", "wb") as f:
    f.write(base64.b64decode(interaction.output_image.data))

import { GoogleGenAI } from "@google/genai";
import * as fs from "node:fs";

async function main() {
  const ai = new GoogleGenAI({});

  const interaction = await ai.interactions.create({
    model: "gemini-nano-banana-2.1",
    input: "Da Vinci style anatomical sketch of a dissected Monarch butterfly. Detailed drawings of the head, wings, and legs on textured parchment with notes in English.",
    response_format: {
      type: "image",
      mime_type: "image/png",
      aspect_ratio: "1:1",
      image_size: "1K",
    },
  });

  console.log(interaction.output_text);

  const buffer = Buffer.from(interaction.output_image.data, 'base64');

  fs.writeFileSync('butterfly.png', buffer);
}

main();