Update app.py

app.py

@@ -1,6 +1,5 @@
 import os
 import requests
-from collections import Counter
 from bs4 import BeautifulSoup
 
 api_token = os.environ.get("TOKEN")
@@ -13,7 +12,8 @@ def query(payload):
 
 def analyze_sentiment(pl7_text):
     output = query({
-        "inputs": f'''<s>[INST] <<SYS>>
+        "inputs": 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"
 For posts that talk about image generation models, return "image_generation"
@@ -25,37 +25,40 @@ For posts about tools and libraries, return "tools_libraries"
 For posts containing tutorials and guides, return "tutorials_guides"
 For posts about debugging and problem-solving, return "debugging"
 Respond only with the category name, without any additional explanation or text.
-<</SYS>>
-
-Analyze the following text:
+<|eot_id|>
+<|start_header_id|>user<|end_header_id|>
 {pl7_text}
-[/INST]
+<|eot_id|>
+<|start_header_id|>assistant<|end_header_id|>
 '''
     })
     
+    print("API Response:", output)  # Print the full API response
+    
     if isinstance(output, list) and len(output) > 0:
         generated_text = output[0].get('generated_text', '')
+        print("Generated Text:", generated_text)  # Print the 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:
             return lines[-1]
     return "unknown"
 
+# Fetch a single post
 url = 'https://huggingface.co/posts'
 response = requests.get(url)
 
 if response.status_code == 200:
     soup = BeautifulSoup(response.content, 'html.parser')
-    pl7_elements = soup.find_all(class_='pl-7')
-    pl7_texts = [element.text.strip() for element in pl7_elements]
-
-    sentiment_counter = Counter()
-
-    for text in pl7_texts:
-        sentiment = analyze_sentiment(text)
-        sentiment_counter[sentiment] += 1
-
-    for category, count in sentiment_counter.items():
-        print(f"{category} = {count}")
+    pl7_element = soup.find(class_='pl-7')
+    if pl7_element:
+        pl7_text = pl7_element.text.strip()
+        print("Post content:")
+        print(pl7_text)
+        print("\nAnalyzing sentiment...")
+        sentiment = analyze_sentiment(pl7_text)
+        print(f"\nSentiment category: {sentiment}")
+    else:
+        print("No post found with class 'pl-7'")
 else:
     print(f"Error {response.status_code} when retrieving {url}")