تولید تصاویر

const { GoogleGenerativeAI } = require("@google/generative-ai");
const fs = require("fs");

const genAI = new GoogleGenerativeAI(process.env.GEMINI_API_KEY);

async function generateImage() {
  const contents = "Hi, can you create a 3d rendered image of a pig " +
                  "with wings and a top hat flying over a happy " +
                  "futuristic scifi city with lots of greenery?";

  // Set responseModalities to include "Image" so the model can generate  an image
  const model = genAI.getGenerativeModel({
    model: "gemini-2.0-flash-exp-image-generation",
    generationConfig: {
        responseModalities: ['Text', 'Image']
    },
  });

  try {
    const response = await model.generateContent(contents);
    for (const part of  response.response.candidates[0].content.parts) {
      // Based on the part type, either show the text or save the image
      if (part.text) {
        console.log(part.text);
      } else if (part.inlineData) {
        const imageData = part.inlineData.data;
        const buffer = Buffer.from(imageData, 'base64');
        fs.writeFileSync('gemini-native-image.png', buffer);
        console.log('Image saved as gemini-native-image.png');
      }
    }
  } catch (error) {
    console.error("Error generating content:", error);
  }
}

generateImage();

curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-exp-image-generation:generateContent?key=$GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "contents": [{
      "parts": [
        {"text": "Hi, can you create a 3d rendered image of a pig with wings and a top hat flying over a happy futuristic scifi city with lots of greenery?"}
      ]
    }],
    "generationConfig":{"responseModalities":["Text","Image"]}
  }' \
  | grep -o '"data": "[^"]*"' \
  | cut -d'"' -f4 \
  | base64 --decode > gemini-native-image.png

const { GoogleGenerativeAI } = require("@google/generative-ai");
const fs = require("fs");

const genAI = new GoogleGenerativeAI(process.env.GEMINI_API_KEY);

async function generateImage() {
    // Load the image from the local file system
    const imagePath = '/path/to/image.png';
    const imageData = fs.readFileSync(imagePath);
    const base64Image = imageData.toString('base64');

    // Prepare the content parts
    const contents = [
        { text: "Hi, This is a picture of me. Can you add a llama next to me?" },
        {
          inlineData: {
            mimeType: 'image/png',
            data: base64Image
          }
        }
      ];

  // Set responseModalities to include "Image" so the model can generate an image
  const model = genAI.getGenerativeModel({
    model: "gemini-2.0-flash-exp-image-generation",
    generationConfig: {
        responseModalities: ['Text', 'Image']
    },
  });

  try {
    const response = await model.generateContent(contents);
    for (const part of  response.response.candidates[0].content.parts) {
      // Based on the part type, either show the text or save the image
      if (part.text) {
        console.log(part.text);
      } else if (part.inlineData) {
        const imageData = part.inlineData.data;
        const buffer = Buffer.from(imageData, 'base64');
        fs.writeFileSync('gemini-native-image.png', buffer);
        console.log('Image saved as gemini-native-image.png');
      }
    }
  } catch (error) {
    console.error("Error generating content:", error);
  }
}

generateImage();

IMG_PATH=/path/to/your/image1.jpeg

if [[ "$(base64 --version 2>&1)" = *"FreeBSD"* ]]; then
  B64FLAGS="--input"
else
  B64FLAGS="-w0"
fi

IMG_BASE64=$(base64 "$B64FLAGS" "$IMG_PATH" 2>&1)

curl -X POST \
  "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-exp-image-generation:generateContent?key=$GEMINI_API_KEY" \
    -H 'Content-Type: application/json' \
    -d "{
      \"contents\": [{
        \"parts\":[
            {\"text\": \"'Hi, This is a picture of me. Can you add a llama next to me\"},
            {
              \"inline_data\": {
                \"mime_type\":\"image/jpeg\",
                \"data\": \"$IMG_BASE64\"
              }
            }
        ]
      }],
      \"generationConfig\": {\"responseModalities\": [\"Text\", \"Image\"]}
    }"  \
  | grep -o '"data": "[^"]*"' \
  | cut -d'"' -f4 \
  | base64 --decode > gemini-edited-image.png

curl -X POST \
    "https://generativelanguage.googleapis.com/v1beta/models/imagen-3.0-generate-002:predict?key=GEMINI_API_KEY" \
    -H "Content-Type: application/json" \
    -d '{
        "instances": [
          {
            "prompt": "Fuzzy bunnies in my kitchen"
          }
        ],
        "parameters": {
          "sampleCount": 4
        }
      }'