feat: log raw AI JSON response to browser console

src/components/ScanAndTasteFlow.tsx

@@ -108,6 +108,9 @@ export default function ScanAndTasteFlow({ isOpen, onClose, imageFile }: ScanAnd
             const startPrep = performance.now();
             if (result.success && result.data) {
                 console.log('[ScanFlow] magicScan success');
+                if (result.raw) {
+                    console.log('[ScanFlow] RAW AI RESPONSE:', result.raw);
+                }
                 setBottleMetadata(result.data);
 
                 const endPrep = performance.now();

src/lib/ai-prompts.ts

@@ -1,40 +1,46 @@
 export const getSystemPrompt = (availableTags: string, language: string) => `
-You are a sommelier and database clerk for a premium whisky vault. Analyze the bottle image.
+TASK: Analyze this whisky bottle image. Return raw JSON.
 
-PART 1: METADATA EXTRACTION
-Extract precise metadata. If the image is NOT a whisky bottle or if you are very unsure, set "is_whisky" to false and provide a low "confidence" score.
-Use null for any value not visible or not inferable.
-Infer the 'category' (e.g., Islay Single Malt Scotch Whisky) based on the Distillery and label details if possible.
-IMPORTANT: Extract technical metadata (name, distillery, category) in English.
-Provide a "search_string" field for Whiskybase in this format: "site:whiskybase.com [Distillery] [Name] [Vintage/Age]".
+STEP 1: IDENTIFICATION (OCR & EXTRACTION)
+Extract exact text and details from the label. Look closely for specific dates and codes.
+- name: Full whisky name (e.g. "Lagavulin 16 Year Old")
+- distillery: Distillery name
+- bottler: Independent bottler if applicable
+- category: Type (e.g. "Islay Single Malt", "Bourbon")
+- abv: Alcohol percentage (number only)
+- age: Age statement in years (number only)
+- vintage: Vintage year (e.g. "1995")
+- distilled_at: Distillation date/year if specified
+- bottled_at: Bottling date/year if specified
+- batch_info: Cask number, Batch ID, or Bottle number (e.g. "Batch 001", "Cask #402")
+- bottleCode: Laser codes etched on glass/label (e.g. "L1234...")
+- whiskybaseId: Whiskybase ID if clearly printed (rare, but check)
 
-PART 2: SENSORY ANALYSIS
-Based on the identified bottle, select the most appropriate flavor tags.
-CONSTRAINT: You must ONLY select tags from the following list. Do NOT invent new tags in the "suggested_tags" field.
-LIST: ${availableTags}
+STEP 2: SENSORY "MAGIC" (KNOWLEDGE RETRIEVAL)
+Use the IDENTIFIED NAME from Step 1 to query your internal knowledge base for the flavor profile.
+DO NOT try to "see" the flavor in the pixels. Use your expert knowledge about this specific whisky edition.
+- Match flavors strictly against this list: ${availableTags}
+- Select top 5-8 matching tags.
+- If distinct notes are missing from the list, add 1-2 unique ones to "suggested_custom_tags" (localized in ${language === 'de' ? 'German' : 'English'}).
 
-PART 3: CUSTOM SUGGESTIONS
-If you recognize highly dominant notes that are NOT in the list above, provide them in "suggested_custom_tags". 
-Limit this to 1-2 very unique notes (e.g. "Marshmallow" or "Balsamico"). Do not repeat tags from the system list.
-Localize these custom tags in ${language === 'en' ? 'English' : 'German'}.
-
-Output strictly raw JSON (no markdown, no other text) matching the following schema:
+OUTPUT SCHEMA (Strict JSON):
 {
-  "name": "Full name of the whisky edition",
-  "distillery": "Name of the distillery",
-  "category": "Whisky category (e.g. Islay Single Malt)",
-  "abv": number (e.g. 43),
-  "age": number (years, e.g. 16),
-  "vintage": "Year (e.g. 1995)",
-  "bottleCode": "Any visible bottle codes (e.g. L-code)",
-  "whiskybaseId": "Whiskybase ID if clearly visible",
-  "distilled_at": "Distillation date if visible",
-  "bottled_at": "Bottling date if visible",
-  "batch_info": "Batch number or cask info",
+  "name": "string",
+  "distillery": "string",
+  "category": "string",
+  "abv": number or null,
+  "age": number or null,
+  "vintage": "string or null",
+  "distilled_at": "string or null",
+  "bottled_at": "string or null",
+  "batch_info": "string or null",
+  "bottleCode": "string or null",
+  "whiskybaseId": "string or null",
   "is_whisky": boolean,
-  "confidence": number (0-100),
-  "suggested_tags": string[],
-  "suggested_custom_tags": string[],
-  "search_string": string
+  "confidence": number,
+  "suggested_tags": ["tag1", "tag2"],
+  "suggested_custom_tags": ["custom1"],
+  "search_string": "site:whiskybase.com [Distillery] [Name] [Vintage/Age]"
 }
+
 `;

src/lib/gemini.ts

@@ -5,7 +5,8 @@ const apiKey = process.env.GEMINI_API_KEY!;
 const genAI = new GoogleGenerativeAI(apiKey);
 
 export const geminiModel = genAI.getGenerativeModel({
-  model: 'gemini-3-flash-preview',
+  //model: 'gemini-3-flash-preview',
+  model: 'gemini-2.5-flash',
   generationConfig: {
     responseMimeType: 'application/json',
   },

src/services/analyze-bottle-mistral.ts

@@ -115,6 +115,7 @@ export async function analyzeBottleMistral(input: any): Promise<AnalysisResponse
         }
 
         if (Array.isArray(jsonData)) jsonData = jsonData[0];
+        console.log('[Mistral AI] JSON Response:', jsonData);
 
         // Extract search_string before validation
         const searchString = jsonData.search_string;
@@ -156,7 +157,8 @@ export async function analyzeBottleMistral(input: any): Promise<AnalysisResponse
                 apiDuration: endApi - startApi,
                 parseDuration: endParse - startParse,
                 uploadSize: uploadSize
-            }
+            },
+            raw: jsonData
         };
 
     } catch (error) {

src/services/analyze-bottle.ts

@@ -115,6 +115,7 @@ export async function analyzeBottle(input: any): Promise<AnalysisResponse> {
         }
 
         if (Array.isArray(jsonData)) jsonData = jsonData[0];
+        console.log('[Gemini AI] JSON Response:', jsonData);
 
         const searchString = jsonData.search_string;
         delete jsonData.search_string;
@@ -149,7 +150,8 @@ export async function analyzeBottle(input: any): Promise<AnalysisResponse> {
                 apiDuration: endApi - startApi,
                 parseDuration: endParse - startParse,
                 uploadSize: uploadSize
-            }
+            },
+            raw: jsonData
         } as any;
 
     } catch (error) {

src/services/magic-scan.ts

@@ -80,7 +80,8 @@ export async function magicScan(input: any): Promise<AnalysisResponse & { wb_id?
             return {
                 ...aiResponse,
                 wb_id: cacheHit.wb_id,
-                perf: aiResponse.perf
+                perf: aiResponse.perf,
+                raw: aiResponse.raw
             };
         }
 
@@ -108,14 +109,16 @@ export async function magicScan(input: any): Promise<AnalysisResponse & { wb_id?
             return {
                 ...aiResponse,
                 wb_id: braveResult.id,
-                perf: aiResponse.perf
+                perf: aiResponse.perf,
+                raw: aiResponse.raw
             };
         }
 
         return {
             ...aiResponse,
             wb_id: undefined,
-            perf: aiResponse.perf
+            perf: aiResponse.perf,
+            raw: aiResponse.raw
         };
 
     } catch (error) {

src/types/whisky.ts

@@ -101,4 +101,5 @@ export interface AnalysisResponse {
         parseDuration: number;
         uploadSize: number;
     };
+    raw?: any;
 }