Upload app.py

app.py

@@ -52,14 +52,14 @@ def respond(
     study_info = "\n".join(study_summaries)
 
     # Nachrichten vorbereiten
-    messages = [{"role": "system", "content": f"{system_message}\nBitte gib immer am Ende des Chats die Links und Titel zu den Studien aus der Suche an."}]
+    messages = [{"role": "system", "content": f"{system_message}\n"}]
     for val in history:
         if val[0]:
             messages.append({"role": "user", "content": val[0]})
         if val[1]:
             messages.append({"role": "assistant", "content": val[1]})
 
-    messages.append({"role": "user", "content": f"{message}\nStudien-Info:\n{study_info}"})
+    messages.append({"role": "user", "content": f"{message}\nStudies:\n{study_info}"})
 
     # Antwort vom Modell generieren
     response = ""
@@ -84,7 +84,7 @@ def create_intro_text():
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
+        gr.Textbox(value="You are a highly capable assistant specializing in parsing and summarizing study abstracts. Your task is to analyze the provided study data, extract relevant information, and offer concise summaries. Always include the study's title and a direct link, ensuring clarity and accessibility.", label="System message"),
         gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
         gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
         gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),