Update app.py

app.py

@@ -1,51 +1,43 @@
-import os 
+import os
 import requests
-import gradio as gr 
+import gradio as gr
 
 api_token = os.environ.get("TOKEN")
-
 API_URL = "https://api-inference.huggingface.co/models/meta-llama/Meta-Llama-3-8B-Instruct"
 headers = {"Authorization": f"Bearer {api_token}"}
 
 def query(payload):
-     response = requests.post(API_URL, headers=headers, json=payload)
+    response = requests.post(API_URL, headers=headers, json=payload)
     return response.json()
 
-
-
-
 def analyze_sentiment(text):
     output = query({
-    "inputs":   f'''<|begin_of_text|>
-    <|start_header_id|>system<|end_header_id|>
-you are a feeling analyser and you'll say only "positive" if i'm feeling positive and "negativ" if i'm feeling sad   <|eot_id|>
-    <|start_header_id|>user<|end_header_id|>
-    {text}
-    <|eot_id|>
-    <|start_header_id|>assistant<|end_header_id|>
-    '''
-})
+        "inputs": f'''<|begin_of_text|>
+<|start_header_id|>system<|end_header_id|>
+You are a feeling analyser and you'll say only "positive" if I'm feeling positive and "negative" if I'm feeling sad
+<|eot_id|>
+<|start_header_id|>user<|end_header_id|>
+{text}
+<|eot_id|>
+<|start_header_id|>assistant<|end_header_id|>
+'''
+    })
 
-    # Assurez-vous de gérer correctement la sortie de l'API
-    if isinstance(output, list) and len(output) > 0:
-        return output[0].get('generated_text', 'Erreur: Réponse inattendue')
     if isinstance(output, list) and len(output) > 0:
         response = output[0].get('generated_text', '').strip().lower()
-    if 'positive' in response:
-       return 'positive'
-    elif 'negative' in response:
-       return 'negativ'
+        if 'positive' in response:
+            return 'positive'
+        elif 'negative' in response:
+            return 'negative'
+        else:
+            return "Erreur: Réponse inattendue"
     else:
-       return "Erreur: Réponse inattendue"
-
-
-
-
+        return "Erreur: Réponse inattendue de l'API"
 
 demo = gr.Interface(
-    fn = query,
-    inputs=["text"],
-    outputs=["text"]
+    fn=analyze_sentiment,
+    inputs="text",
+    outputs="text"
 )
 
 demo.launch()