managarten/apps/api/src/modules/nutriphi/routes.ts
Till JS 693d20edd1 refactor(api/nutriphi): split photo flow into /photos/upload + /analysis/photo
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>
2026-04-09 15:13:45 +02:00

174 lines
5.3 KiB
TypeScript

/**
* NutriPhi module — Meal analysis (Gemini) + recommendations
* Ported from apps/nutriphi/apps/server
*
* CRUD for meals, goals, favorites handled by mana-sync.
* This module handles AI analysis and rule-based recommendations.
*/
import { Hono } from 'hono';
import { logger, type AuthVariables } from '@mana/shared-hono';
const LLM_URL = process.env.MANA_LLM_URL || 'http://localhost:3025';
const ANALYSIS_PROMPT = `Du bist ein Ernährungsexperte. Analysiere die Mahlzeit und gib ein JSON zurück mit:
{
"foods": [{"name": "...", "quantity": "...", "calories": 0}],
"totalNutrition": {"calories": 0, "protein": 0, "carbohydrates": 0, "fat": 0, "fiber": 0, "sugar": 0},
"description": "Kurze Beschreibung der Mahlzeit",
"confidence": 0.0-1.0,
"warnings": [],
"suggestions": []
}`;
const routes = new Hono<{ Variables: AuthVariables }>();
// ─── Photo Upload (server-only: S3 storage via mana-media) ───
routes.post('/photos/upload', async (c) => {
const userId = c.get('userId');
const formData = await c.req.formData();
const file = formData.get('file') as File | null;
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 {
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(`${LLM_URL}/api/v1/chat/completions`, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
messages: [
{ role: 'system', content: ANALYSIS_PROMPT },
{
role: 'user',
content: [
{ type: 'text', text: 'Analysiere diese Mahlzeit.' },
{ type: 'image_url', image_url: { url: photoUrl } },
],
},
],
model: process.env.VISION_MODEL || 'gemini-2.0-flash',
response_format: { type: 'json_object' },
temperature: 0.3,
}),
});
if (!res.ok) return c.json({ error: 'AI analysis failed' }, 502);
const data = await res.json();
const content = data.choices?.[0]?.message?.content;
const analysis = typeof content === 'string' ? JSON.parse(content) : content;
return c.json(analysis);
} catch (err) {
logger.error('nutriphi.photo_analysis_failed', {
error: err instanceof Error ? err.message : String(err),
});
return c.json({ error: 'Analysis failed' }, 500);
}
});
// ─── Text Analysis (server-only: Gemini) ─────────────────────
routes.post('/analysis/text', async (c) => {
const { description } = await c.req.json();
if (!description) return c.json({ error: 'description required' }, 400);
try {
const res = await fetch(`${LLM_URL}/api/v1/chat/completions`, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
messages: [
{ role: 'system', content: ANALYSIS_PROMPT },
{ role: 'user', content: `Analysiere diese Mahlzeit: ${description}` },
],
model: process.env.GEMINI_MODEL || 'gemini-2.0-flash',
response_format: { type: 'json_object' },
temperature: 0.3,
}),
});
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;
return c.json(analysis);
} catch (err) {
logger.error('nutriphi.text_analysis_failed', {
error: err instanceof Error ? err.message : String(err),
});
return c.json({ error: 'Analysis failed' }, 500);
}
});
// ─── Recommendations (server-only: rule engine) ──────────────
routes.post('/recommendations/generate', async (c) => {
const { dailyNutrition } = await c.req.json();
const hints: Array<{ type: string; priority: string; message: string; nutrient?: string }> = [];
if (dailyNutrition) {
if (dailyNutrition.protein < 25) {
hints.push({
type: 'hint',
priority: 'medium',
message:
'Deine Proteinzufuhr ist niedrig. Versuche Hülsenfrüchte, Eier oder Joghurt einzubauen.',
nutrient: 'protein',
});
}
if (dailyNutrition.fiber < 10) {
hints.push({
type: 'hint',
priority: 'medium',
message: 'Mehr Ballaststoffe! Vollkornprodukte, Gemüse und Obst helfen.',
nutrient: 'fiber',
});
}
if (dailyNutrition.sugar > 50) {
hints.push({
type: 'hint',
priority: 'high',
message:
'Dein Zuckerkonsum ist hoch. Achte auf versteckten Zucker in Getränken und Fertigprodukten.',
nutrient: 'sugar',
});
}
}
return c.json({ recommendations: hints });
});
export { routes as nutriphiRoutes };