adding in entity extraction layer

packages/memory-service/src/entities/extraction.js

@@ -8,16 +8,33 @@ const ENTITY_TYPES = ['person', 'place', 'project', 'technology', 'concept', 'or
 
 function buildExtractionPrompt(userMessage, aiResponse) {
     return [
-        'Extract named entities from the conversation below.',
-        `Valid entity types: ${ENTITY_TYPES.join(', ')}.`,
-        'Return ONLY a JSON array. No explanation, no markdown, no code fences.',
-        'Each item must have exactly these fields: "name" (string), "type" (one of the valid types), "notes" (one sentence fact about this entity from the conversation).',
-        'If no entities are found, return: []',
+        '<|im_start|>system',
+        'You are an entity extraction assistant. You extract named entities from conversations and return them as a JSON array. You never return empty arrays when entities are present. You only output valid JSON.<|im_end|>',
+        '<|im_start|>user',
+        'Extract all named entities from this conversation.',
         '',
+        `Valid types: ${ENTITY_TYPES.join(', ')}`,
+        '',
+        'Examples of entities to extract:',
+        '- People: names of individuals',
+        '- Projects: software projects, systems, tools being built',
+        '- Technologies: databases, frameworks, languages, hardware',
+        '- Organizations: companies, teams',
+        '- Places: locations, servers, infrastructure',
+        '',
+        'Return a JSON array where each item has:',
+        '  "name": the entity name',
+        '  "type": one of the valid types above',
+        '  "notes": one sentence describing this entity based on the conversation',
+        '',
+        '### Conversation:',
         `User: ${userMessage}`,
         `Assistant: ${aiResponse}`,
         '',
-        'JSON array:',
+        '### Extracted entities as JSON array:',
+        '<|im_end|>',
+        '<|im_start|>assistant',
+        '[',
     ].join('\n');
 }