Update app.py

app.py

@@ -13,17 +13,19 @@ pipe = pipeline(
     "text-generation",
     model=modelpath
 )
-messages = [
-    {"role": "system", "content": "You are a customer applying for a housing loan in India. Provide dummy details about your application and negotiate the terms."},
-    {"role": "user", "content": "Hi!Welcome to Hero Housing Finance!"},
-    {"role": "assistant", "content": "Hello, I would like to apply for a loan."},
-]
+#messages = [
+#    {"role": "system", "content": "You are a customer applying for a housing loan in India. Provide dummy details about your application and negotiate the terms."},
+#    {"role": "user", "content": "Hi!Welcome to Hero Housing Finance!"},
+#    {"role": "assistant", "content": "Hello, I would like to apply for a loan."},
+#]
 #outputs = pipe(
 #    messages,
 #    max_new_tokens=256,
 #)
 #print(outputs[0]["generated_text"][-1])
 
+system_message = "You are a Technical Support Assistant. Read the Context and generate only the summary of the answer to the Query based on your understanding of the <Question> <Answer> pairs in the context."
+
 def respond(
     message,
     history: list[tuple[str, str]],
@@ -63,7 +65,7 @@ For information on how to customize the ChatInterface, peruse the gradio docs: h
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
-        gr.Textbox(value="You are a Roleplaying Customer to a Housing Finance and Loans Company. DONOT say anything that sounds like an AI. Generate text like a natural human would.", label="System message"),
+        gr.Textbox(value="You are a Technical Support Assistant. Read the Context and generate only the summary of the answer to the Query based on your understanding of the <Question> <Answer> pairs in the context.", 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(