fixed problems

.gitignore

@@ -1,4 +1,4 @@
 venv/
 .venv/
 __pycache__
-models/
+.cache/

src/app.py

@@ -82,31 +82,45 @@ BASE_DIR = os.path.dirname(os.path.dirname(__file__))
 MODEL_DIR = os.path.join(BASE_DIR, "models")
 MODEL_PATH = os.path.join(MODEL_DIR, MODEL_NAME)
 
-def ensure_model():
-    """Download specific model file if not exists."""
-    # Create models/ directory if missing
-    os.makedirs(MODEL_DIR, exist_ok=True)
+from typing import Optional
+
+def ensure_model(model_name: Optional[str] = None, repo_id: Optional[str] = None) -> str:
+    """Ensures model is available, downloading only if needed."""
     
-    model_path = os.path.join(MODEL_DIR, MODEL_NAME)
-    if not os.path.isfile(model_path):
-        print(f"Downloading model {MODEL_NAME} from {REPO_ID}...")
-        
-        # Download specific file instead of whole repo
-        from huggingface_hub import hf_hub_download
-        try:
-            hf_hub_download(
-                repo_id=REPO_ID,
-                filename=MODEL_NAME,
-                local_dir=MODEL_DIR,
-                local_dir_use_symlinks=False
-            )
-            print(f"Successfully downloaded model to {model_path}")
-        except Exception as e:
-            raise RuntimeError(f"Failed to download model: {str(e)}")
-    else:
-        print(f"Model already exists at {model_path}")
+    # Use HF Spaces cache directory
+    cache_dir = "/home/user/.cache/models"
+    os.makedirs(cache_dir, exist_ok=True)
+    
+    # Get model details
+    if not model_name or not repo_id:
+        model_option = MODEL_OPTIONS["small"]  # default to small model
+        model_name = model_option["name"]
+        repo_id = model_option["repo"]
     
-    return model_path
+    # Ensure model_name and repo_id are not None
+    if model_name is None:
+        raise ValueError("model_name cannot be None")
+    if repo_id is None:
+        raise ValueError("repo_id cannot be None")
+    # Check if model already exists in cache
+    model_path = os.path.join(cache_dir, model_name)
+    if os.path.exists(model_path):
+        print(f"\nUsing cached model: {model_path}")
+        return model_path
+        
+    print(f"\nDownloading model {model_name} from {repo_id}...")
+    try:
+        model_path = hf_hub_download(
+            repo_id=repo_id,
+            filename=model_name,
+            cache_dir=cache_dir,
+            local_dir=cache_dir
+        )
+        print(f"Model downloaded successfully to {model_path}")
+        return model_path
+    except Exception as e:
+        print(f"Error downloading model: {str(e)}")
+        raise
 
 # Ensure model is downloaded
 model_path = ensure_model()
@@ -225,7 +239,7 @@ def format_response_for_user(response_dict):
     return message
 
 # Build enhanced Gradio interface
-with gr.Blocks(theme=gr.themes.Soft()) as demo:
+with gr.Blocks() as demo:
     gr.Markdown("""
     # 🏥 Medical Symptom to ICD-10 Code Assistant
     
@@ -248,8 +262,7 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
             chatbot = gr.Chatbot(
                 label="Medical Consultation",
                 height=500,
-                container=True,
-                bubble=True
+                container=True
             )
             
             with gr.Row():