refactor: make generateText model return ExtractedFact

tests/ingestion.test.ts

@@ -53,7 +53,7 @@ describe('IdentityDB ingestion', () => {
     expect(topic?.facts).toHaveLength(1);
   });
 
-  it('ships an LLM extractor adapter that turns structured JSON responses into facts', async () => {
+  it('ships an LLM extractor adapter that returns structured facts from the model', async () => {
     let prompt = '';
 
     const extractor = new LlmFactExtractor({
@@ -61,7 +61,7 @@ describe('IdentityDB ingestion', () => {
         async generateText(input) {
           prompt = input;
 
-          return JSON.stringify({
+          return {
             statement: 'I have worked with Bun and TypeScript since 2025.',
             summary: 'The speaker has Bun and TypeScript experience.',
             source: 'chat',
@@ -73,7 +73,7 @@ describe('IdentityDB ingestion', () => {
               { name: 'TypeScript', category: 'entity', granularity: 'concrete', role: 'object' },
               { name: '2025', category: 'temporal', granularity: 'concrete', role: 'time' },
             ],
-          });
+          };
         },
       },
       instructions: 'Prefer technology and time topics.',
@@ -91,47 +91,4 @@ describe('IdentityDB ingestion', () => {
     expect(fact.metadata).toEqual({ channel: 'telegram' });
     expect(fact.topics.map((topic) => topic.name)).toEqual(['I', 'Bun', 'TypeScript', '2025']);
   });
-
-  it('parses JSON responses wrapped in markdown code fences', async () => {
-    const extractor = new LlmFactExtractor({
-      model: {
-        async generateText() {
-          return [
-            'Here is the extracted fact:',
-            '```json',
-            JSON.stringify({
-              statement: 'Bun powers TypeScript tooling.',
-              topics: [
-                { name: 'Bun', category: 'entity', granularity: 'concrete' },
-                { name: 'TypeScript', category: 'entity', granularity: 'concrete' },
-              ],
-            }),
-            '```',
-          ].join('\n');
-        },
-      },
-    });
-
-    const fact = await db.ingestStatement('Bun powers TypeScript tooling.', {
-      extractor,
-    });
-
-    expect(fact.topics.map((topic) => topic.name)).toEqual(['Bun', 'TypeScript']);
-  });
-
-  it('rejects invalid LLM responses before writing facts', async () => {
-    const extractor = new LlmFactExtractor({
-      model: {
-        async generateText() {
-          return 'not json at all';
-        },
-      },
-    });
-
-    await expect(
-      db.ingestStatement('Bun powers TypeScript tooling.', {
-        extractor,
-      }),
-    ).rejects.toThrow('LLM extractor returned invalid JSON.');
-  });
 });