Update app.py

app.py

@@ -1,6 +1,7 @@
 import os
 import requests
 from collections import Counter
+from bs4 import BeautifulSoup
 
 api_token = os.environ.get("TOKEN")
 API_URL = "https://api-inference.huggingface.co/models/meta-llama/Llama-2-7b-chat-hf"
@@ -10,10 +11,10 @@ def query(payload):
     response = requests.post(API_URL, headers=headers, json=payload)
     return response.json()
 
-def analyze_sentiment(pl7_texts):
+def analyze_sentiment(pl7_text):
     output = query({
         "inputs": f'''<s>[INST] <<SYS>>
-You're going to deeply analyze the texts I'm going to give you and you're only going to tell me which category they belong to by answering only the words that correspond to the following categories:
+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"
 For texts that ask for information from the community, return "questions"
@@ -27,20 +28,23 @@ Respond only with the category name, without any additional explanation or text.
 <</SYS>>
 
 Analyze the following text:
-{pl7_texts}
+{pl7_text}
 [/INST]
 '''
     })
     
-    if isinstance(output, list) and len(output) > 0 and 'generated_text' in output[0]:
-        return output[0]['generated_text'].strip().lower()
+    if isinstance(output, list) and len(output) > 0:
+        generated_text = output[0].get('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"
 
 url = 'https://huggingface.co/posts'
 response = requests.get(url)
 
 if response.status_code == 200:
-    from bs4 import BeautifulSoup
     soup = BeautifulSoup(response.content, 'html.parser')
     pl7_elements = soup.find_all(class_='pl-7')
     pl7_texts = [element.text.strip() for element in pl7_elements]