Update app.py

app.py

@@ -11,8 +11,7 @@ def query(payload):
     return response.json()
 
 def analyze_sentiment(pl7_text):
-    output = query({
-        "inputs": f'''<|begin_of_text|>
+    prompt = f'''<|begin_of_text|>
 <|start_header_id|>system<|end_header_id|>
 You're going to deeply analyze the text I'm going to give you and you're only going to tell me which category it belongs to by answering only the words that correspond to the following categories:
 For posts that talk about chat models/LLM, return "Chatmodel/LLM"
@@ -31,10 +30,19 @@ Respond only with the category name, without any additional explanation or text.
 <|eot_id|>
 <|start_header_id|>assistant<|end_header_id|>
 '''
-    })
+    
+    print("Sending the following prompt to the API:")
+    print(prompt)
+    
+    output = query({"inputs": prompt})
+    
+    print("\nAPI Response:")
+    print(output)
     
     if isinstance(output, list) and len(output) > 0:
         generated_text = output[0].get('generated_text', '')
+        print("\nGenerated Text:")
+        print(generated_text)
         # Extract the last non-empty line as the category
         lines = [line.strip().lower() for line in generated_text.split('\n') if line.strip()]
         if lines:
@@ -50,9 +58,11 @@ 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...")
         sentiment = analyze_sentiment(pl7_text)
-        print(f"Sentiment category: {sentiment}")
+        print(f"\nSentiment category: {sentiment}")
     else:
         print("No post found with class 'pl-7'")
 else: