Oracle weight assigning update

Oracle/deepfundingoracle.py

@@ -231,6 +231,8 @@ def timeout_handler(signum, frame):
 #     logging.info(f"[INFO] Base weights assigned successfully in {end_time - start_time:.2f} seconds.")
 #     return df
 
+import json
+
 def assign_base_weight(df, max_workers=32):
     """
     Assign base weights using a single LLM call to determine feature weights,
@@ -257,12 +259,22 @@ def assign_base_weight(df, max_workers=32):
     )
     try:
         response = llama.predict(prompt)
-        feature_weights = eval(response)  # Convert JSON string to dictionary
+        feature_weights = json.loads(response)  # Safely parse JSON
         print(f"[INFO] Feature weights from LLM: {feature_weights}", flush=True)
-    except Exception as e:
+    except (json.JSONDecodeError, Exception) as e:
         print(f"[ERROR] Failed to fetch feature weights from LLM: {e}", flush=True)
         logging.error(f"[ERROR] Failed to fetch feature weights from LLM: {e}")
-        return df
+        # Fallback to default weights
+        feature_weights = {
+            "stars": 0.3,
+            "forks": 0.2,
+            "watchers": 0.2,
+            "open_issues": 0.1,
+            "pulls": 0.1,
+            "activity": 0.05,
+            "contributors": 0.05
+        }
+        print(f"[INFO] Using default feature weights: {feature_weights}", flush=True)
 
     # Step 2: Programmatically calculate weights for each repository
     def calculate_weight(row):