Update app.py

app.py

@@ -19,10 +19,7 @@ def call_zephyr_api(prompt, hf_token=HF_TOKEN):
         response.raise_for_status()
         return response.json()[0]["generated_text"]
     except Exception as e:
-        error_msg = f"❌ Erreur d'appel API Hugging Face : {str(e)}"
-        if isinstance(e, requests.exceptions.RequestException):
-            error_msg += f" (Code de statut : {e.response.status_code if e.response else 'N/A'})"
-        raise gr.Error(error_msg)
+        raise gr.Error(f"❌ Erreur d'appel API Hugging Face : {str(e)}")
 
 # Chargement du modèle de sentiment
 classifier = pipeline("sentiment-analysis", model="mrm8488/distilroberta-finetuned-financial-news-sentiment-analysis")
@@ -57,20 +54,22 @@ def full_analysis(text, mode, detail_mode, count, history):
     result = classifier(text)[0]
     sentiment_output = f"Sentiment : {result['label']} (Score: {result['score']:.2f})"
 
-    prompt = f"""
-    You are a professional financial analyst AI.
+    prompt = f"""<|system|>
+You are a professional financial analyst AI.
+</s>
+<|user|>
+Analyze the following financial news carefully:
+"{text}"
 
-    Analyze the following financial news carefully:
-    "{text}"
+The detected sentiment for this news is: {result['label'].lower()}.
 
-    The detected sentiment for this news is: {result['label'].lower()}.
-
-    Now, explain why the sentiment is {result['label'].lower()} using a logical, fact-based explanation.
-    Base your reasoning only on the given news text.
-    Do not repeat the news text or the prompt.
-    Respond only with your financial analysis in one clear paragraph.
-    Write in a clear and professional tone.
-    """
+Now, explain why the sentiment is {result['label'].lower()} using a logical, fact-based explanation.
+Base your reasoning only on the given news text.
+Do not repeat the news text or the prompt.
+Respond only with your financial analysis in one clear paragraph.
+Write in a clear and professional tone.
+</s>
+<|assistant|>"""
 
     explanation_en = call_zephyr_api(prompt)
     explanation_fr = translator_to_fr(explanation_en, max_length=512)[0]['translation_text']
@@ -143,7 +142,6 @@ def launch_app():
             outputs=[sentiment_output, explanation_output_en, explanation_output_fr, count, history]
         )
 
-
         download_btn.click(
             download_history,
             inputs=[history],
@@ -153,4 +151,4 @@ def launch_app():
     iface.launch()
 
 if __name__ == "__main__":
-    launch_app()
+    launch_app()