Initial commit for Greenlens

services/plantRecognitionService.ts

@@ -1,85 +1,24 @@
-
 import { IdentificationResult, Language } from '../types';
-import { GoogleGenAI, Type } from "@google/genai";
-import { PlantDatabaseService } from './plantDatabaseService';
+import { backendApiClient } from './backend/backendApiClient';
+import { createIdempotencyKey } from '../utils/idempotency';
 
-// Helper to convert base64 data URL to raw base64 string
-const cleanBase64 = (dataUrl: string) => {
-  return dataUrl.split(',')[1];
-};
+interface IdentifyOptions {
+  idempotencyKey?: string;
+}
 
 export const PlantRecognitionService = {
-  identify: async (imageUri: string, lang: Language = 'de'): Promise<IdentificationResult> => {
-    // 1. Check if we have an API Key. If so, use Gemini
-    if (process.env.API_KEY) {
-      try {
-        const ai = new GoogleGenAI({ apiKey: process.env.API_KEY });
-        
-        // Dynamic prompt based on language
-        const promptLang = lang === 'de' ? 'German' : lang === 'es' ? 'Spanish' : 'English';
-        const promptText = `Identify this plant. Provide the common ${promptLang} name, the botanical name, a description (2 sentences) in ${promptLang}, an estimated confidence (0-1), and care info (water interval in days, light in ${promptLang}, temp). Response must be JSON.`;
-
-        const response = await ai.models.generateContent({
-          model: 'gemini-3-pro-preview',
-          contents: {
-            parts: [
-              {
-                inlineData: {
-                  mimeType: 'image/jpeg',
-                  data: cleanBase64(imageUri),
-                },
-              },
-              {
-                text: promptText
-              }
-            ],
-          },
-          config: {
-            responseMimeType: "application/json",
-            responseSchema: {
-              type: Type.OBJECT,
-              properties: {
-                name: { type: Type.STRING },
-                botanicalName: { type: Type.STRING },
-                description: { type: Type.STRING },
-                confidence: { type: Type.NUMBER },
-                careInfo: {
-                  type: Type.OBJECT,
-                  properties: {
-                    waterIntervalDays: { type: Type.NUMBER },
-                    light: { type: Type.STRING },
-                    temp: { type: Type.STRING },
-                  },
-                  required: ["waterIntervalDays", "light", "temp"]
-                }
-              },
-              required: ["name", "botanicalName", "confidence", "careInfo", "description"]
-            }
-          }
-        });
-
-        if (response.text) {
-          return JSON.parse(response.text) as IdentificationResult;
-        }
-      } catch (error) {
-        console.error("Gemini analysis failed, falling back to mock.", error);
-      }
-    }
-
-    // 2. Mock Process (Fallback)
-    return new Promise((resolve) => {
-      setTimeout(() => {
-        // Use the centralized database service for consistent mock results
-        const randomResult = PlantDatabaseService.getRandomPlant(lang);
-        
-        // Create a clean IdentificationResult without categories/imageUri if we want to strictly adhere to that type, 
-        // though Typescript allows extra props.
-        // We simulate that the recognition might not be 100% like the db
-        resolve({
-            ...randomResult,
-            confidence: 0.85 + Math.random() * 0.14
-        });
-      }, 2500);
+  identify: async (
+    imageUri: string,
+    lang: Language = 'de',
+    options: IdentifyOptions = {},
+  ): Promise<IdentificationResult> => {
+    const idempotencyKey = options.idempotencyKey || createIdempotencyKey('scan');
+    const response = await backendApiClient.scanPlant({
+      idempotencyKey,
+      imageUri,
+      language: lang,
     });
-  }
+
+    return response.result;
+  },
 };