feat: Refactor result preparation and add contradiction checks

backend/tests/LLMService.refactor.test.ts

@@ -0,0 +1,33 @@
+import { LLMService } from '../src/services/LLMService';
+require('dotenv').config();
+
+describe('LLMService Refactor', () => {
+    let llmService: LLMService;
+
+    beforeAll(() => {
+        const apiKey = process.env.GEMINI_API_KEY;
+        if (!apiKey) {
+            throw new Error('GEMINI_API_KEY is not defined in .env file');
+        }
+        llmService = new LLMService(apiKey);
+    });
+
+    it('should correctly categorize desires based on the rules', async () => {
+        const desireSets = [
+            { participantId: '1', wants: ['Pizza'], accepts: ['Pasta'], noGoes: ['Salad'] },
+            { participantId: '2', wants: ['Pizza'], accepts: ['Pasta'], noGoes: ['Tacos'] },
+        ];
+
+        const result = await llmService.analyzeDesires(desireSets as any);
+
+        expect(result.goTo).toContain('Pizza');
+        expect(result.alsoGood).toContain('Pasta');
+        expect(result.noGoes).toEqual(expect.arrayContaining(['Salad', 'Tacos']));
+    });
+
+    it('should detect inner contradictions in a desire set', async () => {
+        const desireSet = { wants: ['Ice Cream', 'No desserts'], accepts: [], noGoes: [] };
+        const hasContradictions = await llmService.checkForInnerContradictions(desireSet as any);
+        expect(hasContradictions).toBe(true);
+    });
+});

backend/tests/llmService.test.ts

@@ -1,54 +0,0 @@
-import { GoogleGenerativeAI } from '@google/generative-ai';
-import { LLMService } from '../src/services/LLMService';
-
-// Mock the GoogleGenerativeAI class and its methods
-jest.mock('@google/generative-ai', () => ({
-    GoogleGenerativeAI: jest.fn().mockImplementation(() => ({
-        getGenerativeModel: jest.fn().mockReturnValue({
-            generateContent: jest.fn().mockResolvedValue({
-                response: {
-                    text: jest.fn().mockReturnValue(
-                        JSON.stringify({
-                            "item1": "Concept A",
-                            "item2": "Concept A",
-                            "item3": "Concept B"
-                        })
-                    ),
-                },
-            }),
-        }),
-    })),
-}));
-
-describe('LLMService', () => {
-    let llmService: LLMService;
-    const mockApiKey = 'test-api-key';
-
-    beforeEach(() => {
-        llmService = new LLMService(mockApiKey);
-    });
-
-    it('should call the Gemini API with the correct prompt and return parsed content', async () => {
-        const desires = [
-            { wants: ['item1'], accepts: [], noGoes: [] },
-            { wants: ['item2'], accepts: [], noGoes: [] },
-            { wants: [], accepts: ['item3'], noGoes: [] },
-        ];
-
-        const result = await llmService.analyzeDesires(desires);
-
-        expect(GoogleGenerativeAI).toHaveBeenCalledWith(mockApiKey);
-        expect(llmService['model'].generateContent).toHaveBeenCalled();
-        expect(result).toEqual({
-            "item1": "Concept A",
-            "item2": "Concept A",
-            "item3": "Concept B"
-        });
-    });
-
-    it('should handle API errors gracefully', async () => {
-        llmService['model'].generateContent.mockRejectedValueOnce(new Error('API Error'));
-
-        await expect(llmService.analyzeDesires([])).rejects.toThrow('API Error');
-    });
-});