Update newapp.py

newapp.py

@@ -45,70 +45,47 @@ logger = logging.getLogger(__name__)
 # Initialize geocoder
 geocoder = Nominatim(user_agent="indian_property_verifier", timeout=10)
 
-# Configure memory optimization
-quantization_config = BitsAndBytesConfig(
-    load_in_4bit=True,
-    bnb_4bit_compute_dtype=torch.float16,
-    bnb_4bit_quant_type="nf4",
-    bnb_4bit_use_double_quant=True,
-)
+# Add memory monitoring function
+def monitor_memory():
+    while True:
+        process = psutil.Process()
+        memory_info = process.memory_info()
+        logger.info(f"Memory usage: {memory_info.rss / 1024 / 1024:.2f} MB")
+        if memory_info.rss > 1 * 1024 * 1024 * 1024:  # If using more than 1GB
+            logger.warning("High memory usage detected, clearing cache")
+            clear_model_cache()
+        time.sleep(300)  # Check every 5 minutes
 
-# Initialize CLIP model with memory optimization
+# Start memory monitoring in a separate thread
+memory_monitor_thread = threading.Thread(target=monitor_memory, daemon=True)
+memory_monitor_thread.start()
+
+# Initialize CLIP model
 try:
     clip_processor = CLIPProcessor.from_pretrained("openai/clip-vit-base-patch32")
-    clip_model = CLIPModel.from_pretrained(
-        "openai/clip-vit-base-patch32",
-        quantization_config=quantization_config,
-        device_map="auto"
-    )
+    clip_model = CLIPModel.from_pretrained("openai/clip-vit-base-patch32")
     has_clip_model = True
-    logger.info("CLIP model loaded successfully with 4-bit quantization")
+    logger.info("CLIP model loaded successfully")
 except Exception as e:
     logger.error(f"Error loading CLIP model: {str(e)}")
     has_clip_model = False
 
-# Initialize sentence transformer with memory optimization
+# Initialize sentence transformer
 try:
-    sentence_model = SentenceTransformer(
-        'paraphrase-MiniLM-L6-v2',
-        device='cpu',
-        cache_folder='./model_cache'
-    )
+    sentence_model = SentenceTransformer('paraphrase-MiniLM-L6-v2')
     logger.info("Sentence transformer loaded successfully")
 except Exception as e:
     logger.error(f"Error loading sentence transformer: {str(e)}")
     sentence_model = None
 
-# Initialize spaCy with memory optimization
+# Initialize spaCy
 try:
-    nlp = spacy.load('en_core_web_sm')  # Using smaller model
+    nlp = spacy.load('en_core_web_md')
     logger.info("spaCy model loaded successfully")
 except Exception as e:
     logger.error(f"Error loading spaCy model: {str(e)}")
     nlp = None
 
-# Add memory monitoring function
-def monitor_memory():
-    while True:
-        process = psutil.Process()
-        memory_info = process.memory_info()
-        logger.info(f"Memory usage: {memory_info.rss / 1024 / 1024:.2f} MB")
-        if memory_info.rss > 8 * 1024 * 1024 * 1024:  # If using more than 8GB
-            logger.warning("High memory usage detected, clearing cache")
-            clear_model_cache()
-        time.sleep(300)  # Check every 5 minutes
-
-# Start memory monitoring in a separate thread
-memory_monitor_thread = threading.Thread(target=monitor_memory, daemon=True)
-memory_monitor_thread.start()
-
-def clear_model_cache():
-    """Clear model cache and free up memory"""
-    gc.collect()
-    if torch.cuda.is_available():
-        torch.cuda.empty_cache()
-    logger.info("Model cache cleared and memory freed")
-
 def make_json_serializable(obj):
     try:
         if isinstance(obj, (bool, int, float, str, type(None))):