Update app.py

app.py

@@ -52,8 +52,53 @@ def load_model():
         trust_remote_code=True
     )
 
-    # Load LoRA adapter
-    model = PeftModel.from_pretrained(base_model, MODEL_REPO)
+    # Load LoRA adapter with error handling for unsupported parameters
+    try:
+        model = PeftModel.from_pretrained(base_model, MODEL_REPO)
+    except TypeError as e:
+        if "unexpected keyword argument" in str(e):
+            print(f"⚠️ Warning: {e}")
+            print("Attempting to load with filtered config...")
+
+            # Download and modify config
+            from huggingface_hub import hf_hub_download
+            import tempfile
+            import shutil
+
+            config_path = hf_hub_download(repo_id=MODEL_REPO, filename="adapter_config.json")
+            with open(config_path, 'r') as f:
+                config = json.load(f)
+
+            # Remove unsupported parameters
+            unsupported_params = ['alora_invocation_tokens', 'alora_invocation_token_ids']
+            for param in unsupported_params:
+                if param in config:
+                    print(f"Removing unsupported parameter: {param}")
+                    del config[param]
+
+            # Save modified config to temp directory
+            temp_dir = tempfile.mkdtemp()
+            temp_config_path = f"{temp_dir}/adapter_config.json"
+            with open(temp_config_path, 'w') as f:
+                json.dump(config, f, indent=2)
+
+            # Copy other adapter files
+            for filename in ['adapter_model.safetensors', 'adapter_model.bin']:
+                try:
+                    src = hf_hub_download(repo_id=MODEL_REPO, filename=filename)
+                    shutil.copy(src, f"{temp_dir}/{filename}")
+                    break
+                except:
+                    continue
+
+            # Load from temp directory
+            model = PeftModel.from_pretrained(base_model, temp_dir)
+
+            # Cleanup
+            shutil.rmtree(temp_dir)
+        else:
+            raise
+
     tokenizer = AutoTokenizer.from_pretrained(MODEL_REPO)
 
     print("Model loaded successfully!")
@@ -139,6 +184,31 @@ def extract_code(text):
 # N8N JSON CONVERSION
 # ==============================================================================
 
+def parse_js_object(js_obj_str):
+    """Convert JavaScript object notation to Python dict"""
+    if not js_obj_str or js_obj_str.strip() == "{}":
+        return {}
+
+    try:
+        # First try direct JSON parsing
+        return json.loads(js_obj_str)
+    except:
+        pass
+
+    try:
+        # Convert JS object notation to JSON
+        # Replace single quotes with double quotes
+        json_str = js_obj_str.replace("'", '"')
+
+        # Add quotes around unquoted keys (e.g., {path: "data"} -> {"path": "data"})
+        json_str = re.sub(r'(\w+):', r'"\1":', json_str)
+
+        # Parse the JSON
+        return json.loads(json_str)
+    except Exception as e:
+        print(f"Warning: Could not parse parameters '{js_obj_str}': {e}")
+        return {}
+
 def convert_to_n8n_json(typescript_code):
     """Convert TypeScript DSL to n8n JSON format"""
 
@@ -151,8 +221,8 @@ def convert_to_n8n_json(typescript_code):
     if name_match:
         workflow_name = name_match.group(1)
 
-    # Extract node definitions
-    node_pattern = r'const\s+(\w+)\s*=\s*workflow\.add\([\'"]([^\'\"]+)[\'"](?:,\s*({[^}]+}))?\)'
+    # Extract node definitions with improved parameter parsing
+    node_pattern = r'const\s+(\w+)\s*=\s*workflow\.add\([\'"]([^\'\"]+)[\'"](?:,\s*(\{[^}]*\}))?\)'
     node_matches = re.finditer(node_pattern, typescript_code)
 
     node_map = {}  # variable name -> node id
@@ -164,11 +234,8 @@ def convert_to_n8n_json(typescript_code):
         node_type = match.group(2)
         params_str = match.group(3) if match.group(3) else "{}"
 
-        # Parse parameters (basic JSON parsing)
-        try:
-            parameters = json.loads(params_str)
-        except:
-            parameters = {}
+        # Convert JavaScript object notation to valid JSON
+        parameters = parse_js_object(params_str)
 
         node_id = str(i)
         node_map[var_name] = node_id