Update app.py

app.py

@@ -7,8 +7,13 @@ API_URL = "https://api-inference.huggingface.co/models/meta-llama/Llama-2-7b-cha
 headers = {"Authorization": f"Bearer {api_token}"}
 
 def query(payload):
-    response = requests.post(API_URL, headers=headers, json=payload)
-    return response.json()
+    try:
+        response = requests.post(API_URL, headers=headers, json=payload)
+        response.raise_for_status()  # Raise an exception for bad status codes
+        return response.json()
+    except requests.exceptions.RequestException as e:
+        print(f"Error making request to API: {e}")
+        return None
 
 def analyze_sentiment(pl7_text):
     prompt = f'''<|begin_of_text|>
@@ -31,12 +36,20 @@ Respond only with the category name, without any additional explanation or text.
 <|start_header_id|>assistant<|end_header_id|>
 '''
     
+    print("Sending request to API...")
     output = query({"inputs": prompt})
     
+    if output is None:
+        return "Error: Failed to get response from API"
+    
+    print("Raw API response:")
+    print(output)
+    
     if isinstance(output, list) and len(output) > 0:
         generated_text = output[0].get('generated_text', '')
         return generated_text.strip()
-    return "Error: No response from the model"
+    else:
+        return "Error: Unexpected response format from API"
 
 # Fetch a single post
 url = 'https://huggingface.co/posts'
@@ -47,7 +60,9 @@ if response.status_code == 200:
     pl7_element = soup.find(class_='pl-7')
     if pl7_element:
         pl7_text = pl7_element.text.strip()
-        print("Analyzing post...")
+        print("Post content (first 100 characters):")
+        print(pl7_text[:100] + "..." if len(pl7_text) > 100 else pl7_text)
+        print("\nAnalyzing post...")
         llm_response = analyze_sentiment(pl7_text)
         print(f"\nLLM Response:\n{llm_response}")
     else: