Upload app.py

app.py

@@ -6,7 +6,9 @@ import gradio as gr
 class CollegePerformanceAnalyzer:
     def __init__(self):
         try:
-            hf_token = os.environ.get('HF_TOKEN')
+            # Preprocess the token to remove any whitespace or newline characters
+            hf_token = os.environ.get('HF_TOKEN', '').strip()
+            
             if not hf_token:
                 raise ValueError("No Hugging Face token found. Please set it as a Space secret.")
             
@@ -15,7 +17,7 @@ class CollegePerformanceAnalyzer:
                 token=hf_token
             )
         except Exception as e:
-            print(f"Inference Client Error: {e}")
+            print(f"Inference Client Initialization Error: {e}")
             self.client = None
         
         self.parameters = self._define_performance_parameters()
@@ -63,13 +65,15 @@ class CollegePerformanceAnalyzer:
 
     def generate_ai_feedback(self, analysis_results):
         if not self.client:
-            return "AI feedback could not be generated as no client is configured."
+            return "AI feedback could not be generated. Client not initialized."
         
         feedback_prompt = self._construct_feedback_prompt(analysis_results)
         
         try:
+            # Use requests library for more explicit error handling if needed
+            import requests
+            
             completion = self.client.text_generation(
-                model="mistralai/Mistral-7B-Instruct-v0.1",
                 prompt=feedback_prompt,
                 max_new_tokens=500,
                 temperature=0.7,
@@ -78,7 +82,8 @@ class CollegePerformanceAnalyzer:
             )
             return completion
         except Exception as e:
-            return f"AI Feedback Generation Error: {e}"
+            print(f"Detailed AI Feedback Generation Error: {e}")
+            return f"AI Feedback Generation Error: {str(e)}"
 
     def _construct_feedback_prompt(self, analysis_results):
         parameters = analysis_results["parameters"]
@@ -105,6 +110,13 @@ def chatbot_responses(message, history, seed=None, use_ai_insights=True):
 
     # Create analyzer and generate performance analysis
     analyzer = CollegePerformanceAnalyzer()
+    
+    # Check if client is initialized
+    if analyzer.client is None:
+        response = "Error: Unable to initialize AI client. Please check your Hugging Face token."
+        history.append([message, response])
+        return history, response
+
     parameters = analyzer.generate_performance_scores(seed)
     analysis_results = analyzer.calculate_weighted_metrics(parameters)