frontend/api/generate-3d.js

export default async function handler(req, res) {
    const startTime = Date.now();
    const logTrace = [];

    function addLog(stage, message, data = null) {
        const entry = {
            timestamp: new Date().toISOString(),
            elapsedMs: Date.now() - startTime,
            stage: stage,
            message: message,
            data: data
        };
        logTrace.push(entry);
        console.log(`[3D-DIAGNOSTIC] [${stage}] ${message}`, data ? JSON.stringify(data).slice(0, 300) : '');
    }

    if (req.method !== 'POST') {
        return res.status(405).json({ error: 'Método no permitido', logs: logTrace });
    }

    try {
        const body = req.body || {};
        const {
            image,
            seed = Math.floor(Math.random() * 100000),
            resolution = '1024',
            ss_guidance = 7.5,
            ss_steps = 12,
            slat_guidance = 3.0,
            slat_steps = 12,
            texture_size = 1024,
            decimation_target = 300000
        } = body;

        const seedNum = parseInt(seed) || Math.floor(Math.random() * 100000);
        const resolutionStr = String(resolution || '1024');
        const ssGuidanceNum = parseFloat(ss_guidance) || 7.5;
        const ssStepsNum = parseInt(ss_steps) || 12;
        const slatGuidanceNum = parseFloat(slat_guidance) || 3.0;
        const slatStepsNum = parseInt(slat_steps) || 12;
        const textureSizeNum = parseInt(texture_size) || 1024;
        const decimationNum = parseInt(decimation_target) || 300000;

        const sessionHash = Math.random().toString(36).substring(2, 13) + Math.random().toString(36).substring(2, 13);

        addLog('INIT', 'Iniciando Carga de Imagen y Generación Gradio 4 v3', {
            hasImage: Boolean(image),
            imageLength: image ? image.length : 0,
            seed: seedNum,
            resolution: resolutionStr,
            sessionHash
        });

        if (!image) {
            return res.status(400).json({ error: 'La imagen 2D es requerida para la generación 3D.', logs: logTrace });
        }

        const hfToken = process.env.HF_TOKEN;
        const spaceUrl = 'https://logicaltrue-trellis-2.hf.space';
        const headers = {
            ...(hfToken ? { 'Authorization': `Bearer ${hfToken}` } : {})
        };

        let remoteFilePath = null;
        const base64Data = image.replace(/^data:image\/\w+;base64,/, '');
        const imgBuffer = Buffer.from(base64Data, 'base64');

        const boundary = '----WebKitFormBoundary' + Math.random().toString(36).substring(2);
        let formDataParts = [];
        formDataParts.push(`--${boundary}\r\nContent-Disposition: form-data; name="files"; filename="input.png"\r\nContent-Type: image/png\r\n\r\n`);
        const headerBuf = Buffer.from(formDataParts.join(''));
        const footerBuf = Buffer.from(`\r\n--${boundary}--\r\n`);
        const fullBody = Buffer.concat([headerBuf, imgBuffer, footerBuf]);

        const uploadEndpoints = [
            `${spaceUrl}/gradio_api/upload`,
            `${spaceUrl}/upload`
        ];

        for (const uUrl of uploadEndpoints) {
            addLog('UPLOAD_TRY', `Subiendo imagen 2D a ${uUrl}...`);
            try {
                const uploadRes = await fetch(uUrl, {
                    method: 'POST',
                    headers: {
                        ...headers,
                        'Content-Type': `multipart/form-data; boundary=${boundary}`
                    },
                    body: fullBody,
                    signal: AbortSignal.timeout(12000)
                }).catch(e => ({ ok: false, statusText: e.message }));

                if (uploadRes && uploadRes.ok) {
                    const uploadJson = await uploadRes.json().catch(() => []);
                    if (Array.isArray(uploadJson) && uploadJson.length > 0) {
                        remoteFilePath = uploadJson[0];
                        addLog('UPLOAD_SUCCESS', `Imagen cargada con éxito en ${uUrl}`, { remotePath: remoteFilePath });
                        break;
                    }
                } else if (uploadRes) {
                    const errTxt = await uploadRes.text().catch(() => '');
                    addLog('UPLOAD_WARN', `Status ${uploadRes.status} en ${uUrl}`, { error: errTxt.slice(0, 200) });
                }
            } catch (e) {
                addLog('UPLOAD_EXCEPT', `Excepción en ${uUrl}`, { error: e.message });
            }
        }

        const gradioImageObj = remoteFilePath ? {
            path: remoteFilePath,
            url: `${spaceUrl}/file=${remoteFilePath}`,
            orig_name: 'input.png',
            mime_type: 'image/png',
            meta: { _type: 'gradio.FileData' }
        } : (typeof image === 'string' && (image.startsWith('data:') || image.startsWith('http')) ? {
            path: image,
            url: image,
            orig_name: 'input.png',
            meta: { _type: 'gradio.FileData' }
        } : image);

        const gradioData3D = [
            gradioImageObj,
            seedNum,
            resolutionStr,
            ssGuidanceNum,
            0.7,
            ssStepsNum,
            5.0,
            slatGuidanceNum,
            0.5,
            slatStepsNum,
            3.0,
            1.0,
            0.0,
            12,
            3.0
        ];

        addLog('PASO1_SUBMIT', 'Enviando FileData verificado a /image_to_3d...', { remotePath: remoteFilePath });
        let step1EventId = null;

        const step1Targets = [
            `${spaceUrl}/gradio_api/call/image_to_3d`,
            `${spaceUrl}/call/image_to_3d`
        ];

        for (const targetUrl of step1Targets) {
            try {
                const sRes = await fetch(targetUrl, {
                    method: 'POST',
                    headers: {
                        'Content-Type': 'application/json',
                        ...headers
                    },
                    body: JSON.stringify({
                        data: gradioData3D,
                        fn_index: 0,
                        session_hash: sessionHash
                    }),
                    signal: AbortSignal.timeout(12000)
                }).catch(() => null);

                if (sRes && sRes.ok) {
                    const sJson = await sRes.json().catch(() => ({}));
                    if (sJson.event_id) {
                        step1EventId = sJson.event_id;
                        addLog('PASO1_SUCCESS', 'Paso 1 (/image_to_3d) ejecutándose en la GPU A100', { event_id: step1EventId });
                        break;
                    }
                }
            } catch (e) {
                addLog('PASO1_ERROR', `Error llamando ${targetUrl}`, { error: e.message });
            }
        }

        if (step1EventId) {
            const jobId = `hf:logicaltrue-trellis-2:${sessionHash}:${step1EventId}:${decimationNum}:${textureSizeNum}`;
            return res.status(202).json({
                success: true,
                job_id: jobId,
                status: 'pending',
                provider: 'Hugging Face Space (LogicalTrue/TRELLIS.2)',
                credits: 999,
                diagnostics: logTrace
            });
        }

        addLog('FATAL_END', 'No se pudo iniciar /image_to_3d en Trellis 2.');
        return res.status(500).json({
            error: 'No se pudo iniciar el proceso 3D en Hugging Face Space.',
            diagnostics: logTrace
        });

    } catch (err) {
        addLog('FATAL_EXCEPT', 'Excepción general', { error: err.message, stack: err.stack });
        return res.status(500).json({
            error: err.message || 'Error en la generación 3D.',
            diagnostics: logTrace
        });
    }
}