fix: model 8 inference

app_optimized.py

@@ -137,23 +137,17 @@ def postprocess_binary_output(output, class_names):
     real_prob = 1.0 - fake_prob # Ensure Fake and Real sum to 1
     return {class_names[0]: fake_prob, class_names[1]: real_prob}
 
-# New function to infer using Gradio API for model_8
 def infer_gradio_api(image_path):
     client = Client("aiwithoutborders-xyz/OpenSight-Community-Forensics-Preview")
-    result_str = client.predict(
+    result_dict = client.predict(
         input_image=handle_file(image_path),
         api_name="/simple_predict"
     )
-    logger.info(f"Debug: Raw result_str from Gradio API (model_8): {result_str}, type: {type(result_str)}")
-    try:
-        # Safely evaluate the string as a Python literal
-        result_dict = ast.literal_eval(result_str)
-        fake_probability = result_dict.get('Fake Probability', 0.0)
-        logger.info(f"Debug: Parsed result_dict: {result_dict}, Extracted fake_probability: {fake_probability}")
-        return {"probabilities": np.array([fake_probability])} # Return as a numpy array with one element
-    except Exception as e:
-        logger.error(f"Error parsing Gradio API output: {e}. Raw output: {result_str}")
-        return {"probabilities": np.array([0.0])}
+    logger.info(f"Debug: Raw result_dict from Gradio API (model_8): {result_dict}, type: {type(result_dict)}")
+    # result_dict is already a dictionary, no need for ast.literal_eval
+    fake_probability = result_dict.get('Fake Probability', 0.0)
+    logger.info(f"Debug: Parsed result_dict: {result_dict}, Extracted fake_probability: {fake_probability}")
+    return {"probabilities": np.array([fake_probability])} # Return as a numpy array with one element
 
 # New preprocess function for Gradio API
 def preprocess_gradio_api(image: Image.Image):