ai-pp3/dist/agent.js

CLI tool combining multimodal AI analysis with RawTherapee's engine to generate optimized PP3 profiles for RAW photography

import path from "node:path";
import { PREVIEW_SETTINGS } from "./constants.js";
// Re-export section parsing functionality
export { splitContentBySections, splitPP3ContentBySections, splitContentIntoSections, } from "./pp3-sections/section-parser.js";
// Re-export section manipulation functionality
export { createSectionMap, applySectionChanges, applyParameterChanges, reconstructContent, reconstructPP3Content, applyDirectSectionChanges, } from "./pp3-sections/section-manipulation.js";
// Re-export file operations
export { readImageData, readBasePP3Content, createPreviewImage, setupPreviewAndValidation, cleanupPreviewFiles, } from "./file-operations/file-handlers.js";
// Re-export AI processing functionality
export { generateAIResponse, processAIGeneration, prepareImageContents, parseBestGenerationIndex, evaluateGenerations, } from "./ai-generation/ai-processor.js";
// Re-export generation helpers
export { logGenerationProgress, generateSinglePP3Profile, logMultiGenerationAnalysis, logSingleGenerationAnalysis, generateMultiplePP3Profiles, } from "./ai-generation/generation-helpers.js";
// Import search/replace functionality
import { processAIGeneration } from "./ai-generation/ai-processor.js";
import { setupPreviewAndValidation, cleanupPreviewFiles, } from "./file-operations/file-handlers.js";
import { generateMultiplePP3Profiles, logSingleGenerationAnalysis, logMultiGenerationAnalysis, } from "./ai-generation/generation-helpers.js";
/**
 * Generates multiple PP3 profiles from a RAW image and selects the best one
 */
export async function generateMultiPP3FromRawImage({ inputPath, basePP3Path, providerName = "openai", visionModel = "gpt-4-vision-preview", verbose = false, keepPreview = false, prompt, preset = "aggressive", sections = [
    "Exposure",
    "Retinex",
    "Local Contrast",
    "Wavlet",
    "Vibrance",
    "White Balance",
    "Color appearance",
    "Shadows & Highlights",
    "RGB Curves",
    "ColorToning",
    "ToneEqualizer",
    "Sharpening",
    "Defringing",
    "Dehaze",
    "Directional Pyramid Denoising",
], previewQuality = PREVIEW_SETTINGS.quality, previewFormat = "jpeg", maxRetries = 2, generations = 3, outputFormat = "jpeg", outputQuality = 100, tiffCompression, bitDepth = 16, }) {
    const extension = inputPath.slice(inputPath.lastIndexOf("."));
    const previewExtension = previewFormat === "png" ? "png" : "jpg";
    const previewPath = path.join(path.dirname(inputPath), `${path.basename(inputPath, extension)}_preview.${previewExtension}`);
    // Handle multiple models
    const models = Array.isArray(visionModel) ? visionModel : [visionModel];
    const actualGenerations = Array.isArray(visionModel)
        ? models.length
        : generations;
    // Log analysis information
    logMultiGenerationAnalysis(verbose, inputPath, providerName, visionModel, models, generations);
    let previewCreated = false;
    try {
        const setup = await setupPreviewAndValidation(inputPath, previewPath, basePP3Path, previewQuality, previewFormat, verbose);
        previewCreated = setup.previewCreated;
        return await generateMultiplePP3Profiles(inputPath, setup.finalBasePP3Path, sections, providerName, visionModel, prompt, preset, maxRetries, verbose, actualGenerations, previewPath, previewFormat, previewQuality, outputFormat, outputQuality, tiffCompression, bitDepth);
    }
    catch (error) {
        if (error instanceof Error) {
            if (verbose) {
                console.error("Error during multi-generation PP3 creation:");
                console.error(error.message);
                if (error.stack)
                    console.error(error.stack);
            }
            throw error;
        }
        throw new Error(`Unknown error during multi-generation PP3 creation: ${String(error)}`);
    }
    finally {
        await cleanupPreviewFiles(previewPath, previewCreated, keepPreview, verbose);
    }
}
/**
 * Generates a single PP3 profile from a RAW image
 */
export async function generatePP3FromRawImage({ inputPath, basePP3Path, providerName = "openai", visionModel = "gpt-4-vision-preview", verbose = false, keepPreview = false, prompt, preset = "aggressive", sections = [
    "Exposure",
    "Retinex",
    "Local Contrast",
    "Wavlet",
    "Vibrance",
    "White Balance",
    "Color appearance",
    "Shadows & Highlights",
    "RGB Curves",
    "ColorToning",
    "ToneEqualizer",
    "Sharpening",
    "Defringing",
    "Dehaze",
    "Directional Pyramid Denoising",
], previewQuality = PREVIEW_SETTINGS.quality, previewFormat = "jpeg", maxRetries = 2, }) {
    const extension = inputPath.slice(inputPath.lastIndexOf("."));
    const previewExtension = previewFormat === "png" ? "png" : "jpg";
    const previewPath = path.join(path.dirname(inputPath), `${path.basename(inputPath, extension)}_preview.${previewExtension}`);
    // Log analysis information
    logSingleGenerationAnalysis(verbose, inputPath, providerName, visionModel);
    let previewCreated = false;
    try {
        const setup = await setupPreviewAndValidation(inputPath, previewPath, basePP3Path, previewQuality, previewFormat, verbose);
        previewCreated = setup.previewCreated;
        return await processAIGeneration(previewPath, setup.finalBasePP3Path, sections, providerName, visionModel, prompt, preset, maxRetries, verbose);
    }
    catch (error) {
        if (error instanceof Error) {
            if (verbose) {
                console.error("Error during PP3 generation:");
                console.error(error.message);
                if (error.stack)
                    console.error(error.stack);
            }
            throw error;
        }
        throw new Error(`Unknown error during PP3 generation: ${String(error)}`);
    }
    finally {
        await cleanupPreviewFiles(previewPath, previewCreated, keepPreview, verbose);
    }
}
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