Update app.py

app.py

@@ -48,12 +48,17 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
 # --- Agent Tools ---
 def wikipedia_lookup(query):
-    wiki_wiki = wikipediaapi.Wikipedia('en')
-    page = wiki_wiki.page(query)
-    if not page.exists():
-        return f"Wikipedia page for '{query}' not found."
-    return page.summary[:1024]
-
+    try:
+        wiki_wiki = wikipediaapi.Wikipedia('en')
+        page = wiki_wiki.page(query)
+        if not page.exists():
+            return f"Wikipedia page for '{query}' not found."
+        return page.summary[:1024]
+    except StopIteration:
+        return "ERROR: YouTube transcript tool raised StopIteration."
+    except Exception as e:
+        return f"Failed to retrieve transcript: {str(e)}"
+        
 wiki_tool = Tool(
     name="WikipediaTool",
     func=wikipedia_lookup,
@@ -65,6 +70,8 @@ def get_youtube_transcript(url):
         yt = YouTube(url)
         caption = yt.captions.get_by_language_code('en')
         return caption.generate_srt_captions()[:2048]
+    except StopIteration:
+        return "ERROR: YouTube transcript tool raised StopIteration."
     except Exception as e:
         return f"Failed to retrieve transcript: {str(e)}"
 
@@ -75,9 +82,14 @@ youtube_tool = Tool(
 )
 
 def transcribe_audio(file_path):
-    model = whisper.load_model("base")
-    result = model.transcribe(file_path)
-    return result['text'][:2048]
+    try:
+        model = whisper.load_model("base")
+        result = model.transcribe(file_path)
+        return result['text'][:2048]
+    except StopIteration:
+        return "ERROR: YouTube transcript tool raised StopIteration."
+    except Exception as e:
+        return f"Failed to retrieve transcript: {str(e)}"        
 
 audio_tool = Tool(
     name="AudioTranscriber",
@@ -86,15 +98,20 @@ audio_tool = Tool(
 )
 
 def extract_food_sales(filepath):
-    wb = openpyxl.load_workbook(filepath)
-    sheet = wb.active
-    total = 0
-    for row in sheet.iter_rows(min_row=2, values_only=True):
-        item, category, sales = row
-        if category.lower() == 'food':
-            total += float(sales)
-    return f"Total food sales: ${total:.2f}"
-
+    try:
+        wb = openpyxl.load_workbook(filepath)
+        sheet = wb.active
+        total = 0
+        for row in sheet.iter_rows(min_row=2, values_only=True):
+            item, category, sales = row
+            if category.lower() == 'food':
+                total += float(sales)
+        return f"Total food sales: ${total:.2f}"
+    except StopIteration:
+        return "ERROR: YouTube transcript tool raised StopIteration."
+    except Exception as e:
+        return f"Failed to retrieve transcript: {str(e)}"
+        
 excel_tool = Tool(
     name="ExcelFoodSales",
     func=extract_food_sales,
@@ -102,14 +119,19 @@ excel_tool = Tool(
 )
 
 def describe_image(image_path):
-    processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
-    model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base")
-    raw_image = Image.open(image_path).convert('RGB')
-    inputs = processor(raw_image, return_tensors="pt")
-    out = model.generate(**inputs)
-    caption = processor.decode(out[0], skip_special_tokens=True)
-    return caption
-
+    try:
+        processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
+        model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base")
+        raw_image = Image.open(image_path).convert('RGB')
+        inputs = processor(raw_image, return_tensors="pt")
+        out = model.generate(**inputs)
+        caption = processor.decode(out[0], skip_special_tokens=True)
+        return caption
+    except StopIteration:
+        return "ERROR: YouTube transcript tool raised StopIteration."
+    except Exception as e:
+        return f"Failed to retrieve transcript: {str(e)}"
+        
 image_tool = Tool(
     name="ImageDescriber",
     func=describe_image,