feat: initialize project with docker-compose infrastructure and server application logic

greenlns-landing/docker-compose.yml

@@ -41,7 +41,8 @@ services:
       MINIO_PUBLIC_URL: ${MINIO_PUBLIC_URL:-https://greenlenspro.com/storage}
       OPENAI_API_KEY: ${OPENAI_API_KEY:-}
       OPENAI_SCAN_MODEL: ${OPENAI_SCAN_MODEL:-gpt-5-mini}
-      OPENAI_HEALTH_MODEL: ${OPENAI_HEALTH_MODEL:-gpt-5-mini}
+      OPENAI_SCAN_MODEL_PRO: ${OPENAI_SCAN_MODEL_PRO:-gpt-5.4}
+      OPENAI_HEALTH_MODEL: ${OPENAI_HEALTH_MODEL:-gpt-4o-mini}
       REVENUECAT_WEBHOOK_SECRET: ${REVENUECAT_WEBHOOK_SECRET:-}
       REVENUECAT_PRO_ENTITLEMENT_ID: ${REVENUECAT_PRO_ENTITLEMENT_ID:-pro}
       JWT_SECRET: ${JWT_SECRET:?JWT_SECRET is required}

server/index.js

@@ -180,7 +180,7 @@ const toPlantResult = (entry, confidence) => {
   };
 };
 
-const pickCatalogFallback = (entries, imageUri, preferHighConfidence = false) => {
+const pickCatalogFallback = (entries, imageUri, preferHighConfidence = false, { silent = false } = {}) => {
   if (!Array.isArray(entries) || entries.length === 0) return null;
   const baseHash = hashString(`${imageUri || ''}|${entries.length}`);
   const index = baseHash % entries.length;
@@ -188,11 +188,13 @@ const pickCatalogFallback = (entries, imageUri, preferHighConfidence = false) =>
   const confidence = preferHighConfidence
     ? 0.22 + ((baseHash % 3) / 100)
     : 0.18 + ((baseHash % 7) / 100);
-  console.warn('Using hash-based catalog fallback — OpenAI is unavailable or returned null.', {
+  if (!silent) {
-    plant: entries[index]?.name,
+    console.warn('Using hash-based catalog fallback — OpenAI is unavailable or returned null.', {
-    confidence,
+      plant: entries[index]?.name,
-    imageHint: (imageUri || '').slice(0, 80),
+      confidence,
-  });
+      imageHint: (imageUri || '').slice(0, 80),
+    });
+  }
   return toPlantResult(entries[index], confidence);
 };
 
@@ -637,7 +639,7 @@ app.post('/v1/scan', async (request, response) => {
     const accountSnapshot = await getAccountSnapshot(db, userId);
     const scanPlan = accountSnapshot.plan === 'pro' ? 'pro' : 'free';
     const catalogEntries = await getPlants(db, { limit: 500 });
-    let result = pickCatalogFallback(catalogEntries, imageUri, false);
+    let result = pickCatalogFallback(catalogEntries, imageUri, false, { silent: true });
     let usedOpenAi = false;
 
     if (isOpenAiConfigured()) {
@@ -662,7 +664,10 @@ app.post('/v1/scan', async (request, response) => {
         modelPath.push('openai-primary');
         if (grounded.grounded) modelPath.push('catalog-grounded-primary');
       } else {
-        console.warn(`OpenAI primary identification returned null for user ${userId}`);
+        console.warn(`OpenAI primary identification returned null for user ${userId} — using catalog fallback.`, {
+          attemptedModels: openAiPrimary?.attemptedModels,
+          plant: result?.name,
+        });
         modelPath.push('openai-primary-failed');
         modelPath.push('catalog-primary-fallback');
       }
@@ -711,11 +716,13 @@ app.post('/v1/scan', async (request, response) => {
             modelPath.push('openai-review');
             if (grounded.grounded) modelPath.push('catalog-grounded-review');
           } else {
-            console.warn(`OpenAI review identification returned null for user ${userId}`);
+            console.warn(`OpenAI review identification returned null for user ${userId}.`, {
+              attemptedModels: openAiReview?.attemptedModels,
+            });
             modelPath.push('openai-review-failed');
           }
         } else {
-          const reviewFallback = pickCatalogFallback(catalogEntries, `${imageUri}|review`, true);
+          const reviewFallback = pickCatalogFallback(catalogEntries, `${imageUri}|review`, true, { silent: true });
           if (reviewFallback) {
             result = reviewFallback;
           }
@@ -827,7 +834,13 @@ app.post('/v1/health-check', async (request, response) => {
     });
     const analysis = analysisResponse?.analysis;
     if (!analysis) {
-      const error = new Error('OpenAI health check failed. Please verify API key, model, and network access.');
+      console.warn('Health check analysis was null — all models returned unusable output.', {
+        attemptedModels: analysisResponse?.attemptedModels,
+        modelUsed: analysisResponse?.modelUsed,
+      });
+      const error = new Error(
+        `Health check AI failed. Tried: ${(analysisResponse?.attemptedModels || []).join(', ')}. Verify API key, model access, and network.`
+      );
       error.code = 'PROVIDER_ERROR';
       throw error;
     }

server/lib/openai.js

@@ -137,15 +137,16 @@ const normalizeHealthAnalysis = (raw, language) => {
   const actionsNowRaw = getStringArray(raw.actionsNow).slice(0, 8);
   const plan7DaysRaw = getStringArray(raw.plan7Days).slice(0, 10);
 
-  if (scoreRaw == null || !statusRaw || !Array.isArray(issuesRaw)) {
+  // Use safe defaults instead of returning null — bad/partial JSON falls through
-    return null;
+  // to the graceful "Uncertain analysis" fallback at line 164 rather than
-  }
+  // propagating null → PROVIDER_ERROR to the caller.
-
+  const score = scoreRaw ?? 50;
-  const status = statusRaw === 'healthy' || statusRaw === 'watch' || statusRaw === 'critical'
+  const status = (statusRaw === 'healthy' || statusRaw === 'watch' || statusRaw === 'critical')
     ? statusRaw
     : 'watch';
+  const issuesInput = Array.isArray(issuesRaw) ? issuesRaw : [];
 
-  const likelyIssues = issuesRaw
+  const likelyIssues = issuesInput
     .map((entry) => {
       if (!entry || typeof entry !== 'object' || Array.isArray(entry)) return null;
       const title = getString(entry.title);
@@ -168,7 +169,7 @@ const normalizeHealthAnalysis = (raw, language) => {
         ? 'La IA no pudo extraer senales de salud estables.'
         : 'AI could not extract stable health signals.';
     return {
-      overallHealthScore: Math.round(clamp(scoreRaw, 0, 100)),
+      overallHealthScore: Math.round(clamp(score, 0, 100)),
       status,
       likelyIssues: [
         {
@@ -191,7 +192,7 @@ const normalizeHealthAnalysis = (raw, language) => {
   }
 
   return {
-    overallHealthScore: Math.round(clamp(scoreRaw, 0, 100)),
+    overallHealthScore: Math.round(clamp(score, 0, 100)),
     status,
     likelyIssues,
     actionsNow: actionsNowRaw,
@@ -305,10 +306,14 @@ const postChatCompletion = async ({ modelChain, messages, imageUri, temperature
 
       if (!response.ok) {
         const body = await response.text();
+        let parsedError = {};
+        try { parsedError = JSON.parse(body); } catch {}
         console.warn('OpenAI request HTTP error.', {
           status: response.status,
           model,
           endpoint: OPENAI_CHAT_COMPLETIONS_URL,
+          openAiCode: parsedError?.error?.code,
+          openAiMessage: parsedError?.error?.message,
           image: summarizeImageUri(imageUri),
           bodyPreview: body.slice(0, 300),
         });