Gjenerimi i imazhit Nano Banana

from google import genai
from PIL import Image
import base64

client = genai.Client()

interaction = client.interactions.create(
    model="gemini-3.1-flash-image",
    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-3.1-flash-image",
    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();

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-3.1-flash-image",
    "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-3.1-flash-image",
    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-3.1-flash-image",
    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();

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-3.1-flash-image\",
      \"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-3.1-flash-image",
    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-3.1-flash-image",
    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();

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-3.1-flash-image",
    "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-3.1-flash-image",
    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-3.1-flash-image",
  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);
}

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-3.1-flash-image",
    "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-3.1-flash-image",
    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