Update app.py

app.py

@@ -10,17 +10,20 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
 class HybridAgent:
     def __init__(self):
+        # Load LLM for text QA
         self.llm = pipeline("text-generation", model="google/flan-t5-small")
-
+    
     def __call__(self, question: str, task_id: str = None) -> str:
-        print("=== Running on task:", task_id)
+        # Debug logs to inspect behavior
+        print("=== Task ID:", task_id)
         print("Question:", question)
 
+        # Handle file-based questions
         if task_id:
             resp = requests.get(f"{DEFAULT_API_URL}/files/{task_id}")
             if resp.status_code == 200:
                 file_content = resp.text
-                print("File content preview:", file_content[:200])
+                print("File preview:", file_content[:200])
                 try:
                     df = pd.read_csv(StringIO(file_content))
                     q_lower = question.lower()
@@ -30,14 +33,16 @@ class HybridAgent:
                         return str(df.iloc[:, 0].sum())
                     return df.head().to_string(index=False)
                 except Exception as e:
-                    print("Error reading CSV, returning raw:", e)
+                    print("CSV reading error:", e)
                     return file_content.strip()
 
+        # Fallback to LLM for text questions
         prompt = f"Answer this question briefly and only with the final answer:\n{question}"
         result = self.llm(prompt, max_length=50)[0]["generated_text"]
+        # Remove unwanted prefixes
         cleaned = result.replace("Final Answer:", "").replace("Answer:", "").strip()
-        print("Raw LLM response:", result)
-        print("Cleaned answer:", cleaned)
+        print("Raw response:", result)
+        print("Clean answer:", cleaned)
         return cleaned
 
 def run_and_submit_all( profile: gr.OAuthProfile | None):