clean up code

app/enrichment/llm_client.py

@@ -1,54 +1,70 @@
 import requests
 import json
-from typing import Dict, Optional
+import logging
+from typing import Dict, Optional, List
+
+logger = logging.getLogger(__name__)
 
 class LLMClient:
-    def __init__(self, endpoint: str = 'http://192.168.1.74:1234', model: str = 'local'):
+    def __init__(self, endpoint: str = 'http://localhost:11434', model: str = 'llama3', use_local: bool = True):
         self.endpoint = endpoint
         self.model = model
-        self.local_ollama = 'http://localhost:11434'
+        self.use_local = use_local
+        self.lm_studio_endpoint = 'http://192.168.1.74:1234'
+        self.lm_studio_model = 'openai/gpt-oss-20b'
 
     def summarize(self, text: str, max_length: int = 200) -> Dict:
-        prompt = f"Summarize the following in {max_length} chars or less:\n\n{text[:2000]}"
+        prompt = f"Summarize this concisely in under {max_length} characters:\n\n{text[:3000]}"
         return self._query(prompt)
 
     def extract_topics(self, text: str) -> Dict:
-        prompt = f"Extract 5-10 key topics/tags from this text. Return as comma-separated list:\n\n{text[:2000]}"
+        prompt = f"Extract 5-10 key topics/tags. Return ONLY comma-separated words:\n\n{text[:3000]}"
+        result = self._query(prompt)
+        if result.get('success'):
+            topics = [t.strip() for t in result['text'].split(',')]
+            result['topics'] = topics[:10]
+        return result
+
+    def extract_intent(self, text: str) -> Dict:
+        prompt = f"What is the main purpose/intent of this code/document? Answer in 1-2 sentences:\n\n{text[:3000]}"
         return self._query(prompt)
 
-    def classify_content(self, text: str) -> Dict:
-        prompt = f"Classify this content. Return: category, topics, has_pii (yes/no), quality (high/medium/low):\n\n{text[:1000]}"
+    def detect_project_type(self, text: str, file_list: List[str]) -> Dict:
+        files_str = ', '.join(file_list[:20])
+        prompt = f"Based on these files: {files_str}\nAnd this content:\n{text[:2000]}\n\nWhat type of project is this? (e.g. web app, ml/ai, transcription, data processing, etc.)"
         return self._query(prompt)
 
-    def _query(self, prompt: str, use_local: bool = False) -> Dict:
+    def _query(self, prompt: str, timeout: int = 30) -> Dict:
         try:
-            endpoint = self.local_ollama if use_local else self.endpoint
-
-            if use_local:
+            if self.use_local:
                 response = requests.post(
-                    f'{endpoint}/api/generate',
-                    json={'model': 'llama3.2', 'prompt': prompt, 'stream': False},
-                    timeout=30
+                    f'{self.endpoint}/api/generate',
+                    json={'model': self.model, 'prompt': prompt, 'stream': False},
+                    timeout=timeout
                 )
+                if response.status_code == 200:
+                    data = response.json()
+                    return {'success': True, 'text': data.get('response', '').strip()}
             else:
                 response = requests.post(
-                    f'{endpoint}/v1/chat/completions',
+                    f'{self.lm_studio_endpoint}/v1/chat/completions',
                     json={
-                        'model': self.model,
+                        'model': self.lm_studio_model,
                         'messages': [{'role': 'user', 'content': prompt}],
-                        'max_tokens': 500
+                        'max_tokens': 500,
+                        'temperature': 0.7
                     },
-                    timeout=30
+                    timeout=timeout
                 )
+                if response.status_code == 200:
+                    data = response.json()
+                    return {'success': True, 'text': data['choices'][0]['message']['content'].strip()}
 
-            if response.status_code == 200:
-                data = response.json()
-                if use_local:
-                    return {'success': True, 'text': data.get('response', '')}
-                else:
-                    return {'success': True, 'text': data['choices'][0]['message']['content']}
-            else:
-                return {'success': False, 'error': f'HTTP {response.status_code}'}
+            return {'success': False, 'error': f'HTTP {response.status_code}'}
 
+        except requests.Timeout:
+            logger.warning(f'LLM request timeout after {timeout}s')
+            return {'success': False, 'error': 'timeout'}
         except Exception as e:
+            logger.error(f'LLM query failed: {e}')
             return {'success': False, 'error': str(e)}