aidio-description/dist/providers/vision/geminiVisionProvider.js

"use strict";
var __importDefault = (this && this.__importDefault) || function (mod) {
    return (mod && mod.__esModule) ? mod : { "default": mod };
};
Object.defineProperty(exports, "__esModule", { value: true });
exports.GeminiVisionProvider = void 0;
const fs_1 = __importDefault(require("fs"));
const generative_ai_1 = require("@google/generative-ai");
/**
 * Google Gemini Vision Provider Implementation
 */
class GeminiVisionProvider {
    constructor(config) {
        this.config = config;
        this.genAI = new generative_ai_1.GoogleGenerativeAI(config.apiKey);
        this.model = this.genAI.getGenerativeModel({ model: config.model });
    }
    /**
     * Describe a single image
     * @param imagePath - Path to the image file
     * @param prompt - Prompt for the AI
     * @returns Description and usage stats
     */
    async describeImage(imagePath, prompt) {
        try {
            const imageData = fs_1.default.readFileSync(imagePath);
            const mimeType = 'image/jpeg'; // Assuming JPEG, could be detected based on file extension
            // Create a file part for the image
            const imagePart = {
                inlineData: {
                    data: imageData.toString('base64'),
                    mimeType
                }
            };
            // Generate content using Gemini
            const result = await this.model.generateContent([prompt, imagePart]);
            const response = await result.response;
            const text = response.text();
            // Gemini doesn't provide token usage information in the same way as OpenAI
            // We'll estimate based on prompt length and response length
            const inputTokens = Math.ceil(prompt.length / 4) + 1000; // rough estimate for image
            const outputTokens = Math.ceil(text.length / 4);
            return {
                description: text,
                usage: {
                    inputTokens,
                    outputTokens,
                    totalTokens: inputTokens + outputTokens
                }
            };
        }
        catch (error) {
            console.error("Error describing image with Gemini:", error);
            return {
                description: "Unable to describe this image.",
                usage: { inputTokens: 0, outputTokens: 0, totalTokens: 0 }
            };
        }
    }
    /**
     * Compare two images and describe the differences
     * @param image1Path - Path to the first image
     * @param image2Path - Path to the second image
     * @param prompt - Prompt for the AI
     * @returns Description and usage stats
     */
    async compareImages(image1Path, image2Path, prompt) {
        try {
            const image1Data = fs_1.default.readFileSync(image1Path);
            const image2Data = fs_1.default.readFileSync(image2Path);
            const mimeType = 'image/jpeg'; // Assuming JPEG, could be detected based on file extension
            // Create file parts for both images
            const image1Part = {
                inlineData: {
                    data: image1Data.toString('base64'),
                    mimeType
                }
            };
            const image2Part = {
                inlineData: {
                    data: image2Data.toString('base64'),
                    mimeType
                }
            };
            // Generate content using Gemini with both images
            const result = await this.model.generateContent([prompt, image1Part, image2Part]);
            const response = await result.response;
            const text = response.text();
            // Estimate token usage
            const inputTokens = Math.ceil(prompt.length / 4) + 2000; // rough estimate for two images
            const outputTokens = Math.ceil(text.length / 4);
            return {
                description: text,
                usage: {
                    inputTokens,
                    outputTokens,
                    totalTokens: inputTokens + outputTokens
                }
            };
        }
        catch (error) {
            console.error("Error comparing images with Gemini:", error);
            return {
                description: "Unable to describe the differences between these images.",
                usage: { inputTokens: 0, outputTokens: 0, totalTokens: 0 }
            };
        }
    }
    /**
     * Describe a batch of images
     * @param imagePaths - Array of paths to the images
     * @param lastBatchContext - Context from the previous batch
     * @param prompt - Prompt for the AI
     * @returns Description and usage stats
     */
    async describeBatch(imagePaths, lastBatchContext, prompt) {
        try {
            // Create a prompt that includes context from the last batch if available
            let contextualPrompt = prompt;
            if (lastBatchContext && lastBatchContext.lastDescription) {
                contextualPrompt = `Previous batch summary: ${lastBatchContext.lastDescription}\n\n${prompt}`;
            }
            // Create content parts array starting with the prompt
            const contentParts = [contextualPrompt];
            // Add all images to the content parts
            for (const imagePath of imagePaths) {
                const imageData = fs_1.default.readFileSync(imagePath);
                const mimeType = 'image/jpeg'; // Assuming JPEG, could be detected based on file extension
                contentParts.push({
                    inlineData: {
                        data: imageData.toString('base64'),
                        mimeType
                    }
                });
            }
            // Generate content using Gemini with all images
            const result = await this.model.generateContent(contentParts);
            const response = await result.response;
            const text = response.text();
            // Estimate token usage
            const inputTokens = Math.ceil(contextualPrompt.length / 4) + (1000 * imagePaths.length); // rough estimate
            const outputTokens = Math.ceil(text.length / 4);
            return {
                description: text,
                usage: {
                    inputTokens,
                    outputTokens,
                    totalTokens: inputTokens + outputTokens
                }
            };
        }
        catch (error) {
            console.error("Error describing batch of images with Gemini:", error);
            return {
                description: "Unable to describe this batch of images.",
                usage: { inputTokens: 0, outputTokens: 0, totalTokens: 0 }
            };
        }
    }
}
exports.GeminiVisionProvider = GeminiVisionProvider;
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