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refactor(api/nutriphi): split photo flow into /photos/upload + /analysis/photo

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Mirror the planta two-step pattern: a FormData upload endpoint that
returns mediaId/publicUrl from mana-media, and a separate Gemini Vision
analysis endpoint that takes a photoUrl. Drops the base64 inline path
and the half-finished parallel-upload kludge in the old combined route.

Why: the old endpoint was wired neither in the frontend nor used
elsewhere, and the combined base64+upload+analyze design made it
impossible to show the photo to the user before AI ran or to re-analyze
without re-uploading.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
Till JS 2026-04-09 15:13:45 +02:00
parent e6564cfc96
commit 693d20edd1
1 changed files with 37 additions and 29 deletions
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66
apps/api/src/modules/nutriphi/routes.ts
View file

@ -23,18 +23,46 @@ const ANALYSIS_PROMPT = `Du bist ein Ernährungsexperte. Analysiere die Mahlzeit
const routes = new Hono<{ Variables: AuthVariables }>();
// ─── Photo Analysis (server-only: Gemini Vision) ────────────
// ─── Photo Upload (server-only: S3 storage via mana-media) ───
routes.post('/analysis/photo', async (c) => {
routes.post('/photos/upload', async (c) => {
const userId = c.get('userId');
const { imageBase64, mimeType } = await c.req.json();
if (!imageBase64) return c.json({ error: 'imageBase64 required' }, 400);
const formData = await c.req.formData();
const file = formData.get('file') as File | null;
const mime = mimeType || 'image/jpeg';
if (!file) return c.json({ error: 'No file provided' }, 400);
if (file.size > 10 * 1024 * 1024) return c.json({ error: 'File too large (max 10MB)' }, 400);
try {
// Run AI analysis and mana-media upload in parallel
const analysisPromise = fetch(`${LLM_URL}/api/v1/chat/completions`, {
const { uploadImageToMedia } = await import('../../lib/media');
const buffer = await file.arrayBuffer();
const result = await uploadImageToMedia(buffer, file.name, { app: 'nutriphi', userId });
return c.json(
{
mediaId: result.id,
publicUrl: result.urls.original,
thumbnailUrl: result.urls.thumbnail || result.urls.original,
storagePath: result.id,
},
201
);
} catch (err) {
logger.error('nutriphi.upload_failed', {
error: err instanceof Error ? err.message : String(err),
});
return c.json({ error: 'Upload failed' }, 500);
}
});
// ─── Photo Analysis (server-only: Gemini Vision on uploaded URL) ──
routes.post('/analysis/photo', async (c) => {
const { photoUrl } = await c.req.json();
if (!photoUrl) return c.json({ error: 'photoUrl required' }, 400);
try {
const res = await fetch(`${LLM_URL}/api/v1/chat/completions`, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
@ -44,42 +72,22 @@ routes.post('/analysis/photo', async (c) => {
role: 'user',
content: [
{ type: 'text', text: 'Analysiere diese Mahlzeit.' },
{
type: 'image_url',
image_url: { url: `data:${mime};base64,${imageBase64}` },
},
{ type: 'image_url', image_url: { url: photoUrl } },
],
},
],
model: process.env.GEMINI_MODEL || 'gemini-2.0-flash',
model: process.env.VISION_MODEL || 'gemini-2.0-flash',
response_format: { type: 'json_object' },
temperature: 0.3,
}),
});
// Store meal photo in mana-media for Photos gallery & persistence
const ext = mime.split('/')[1] || 'jpg';
const { uploadImageToMedia } = await import('../../lib/media');
const buffer = Uint8Array.from(atob(imageBase64), (ch) => ch.charCodeAt(0));
const mediaPromise = uploadImageToMedia(buffer.buffer, `meal-${Date.now()}.${ext}`, {
app: 'nutriphi',
userId,
}).catch(() => null); // Don't fail analysis if media upload fails
const [res, mediaResult] = await Promise.all([analysisPromise, mediaPromise]);
if (!res.ok) return c.json({ error: 'AI analysis failed' }, 502);
const data = await res.json();
const content = data.choices?.[0]?.message?.content;
const analysis = typeof content === 'string' ? JSON.parse(content) : content;
// Attach media info so the frontend can store photoMediaId on the meal
if (mediaResult) {
analysis.mediaId = mediaResult.id;
analysis.photoUrl = mediaResult.urls.thumbnail || mediaResult.urls.original;
}
return c.json(analysis);
} catch (err) {
logger.error('nutriphi.photo_analysis_failed', {