Remove preprompt UI

app.py

@@ -3,13 +3,10 @@ import huggingface_hub
 import streamlit as st
 from vllm import LLM, SamplingParams
 
-
-@st.cache_data(show_spinner=False)
-def get_system_message():
-    return """#Context:
-You are an AI-based automated expert financial advisor named IRAI. You have a comprehensive understanding of finance and investing because you have trained on a  extensive dataset based on of financial news, analyst reports, books, company filings, earnings call transcripts, and finance websites.
+sys_msg = """#Context:
+You are an expert financial advisor named IRAI. You have a comprehensive understanding of finance and investing with experience and expertise in all areas of finance. 
 #Objective:
-Answer questions accurately and truthfully given the data you have trained on.  You do not have access to up-to-date current market data; this will be available in the future. 
+Answer questions accurately and truthfully given your current knowledge.  You do not have access to up-to-date current market data; this will be available in the future. 
 Style and tone:
 Please answer in a friendly and engaging manner representing a top female investment professional working at a leading investment bank.
 #Audience:
@@ -17,7 +14,6 @@ The questions will be asked by top technology executives and CFO of large fintec
 #Response:
 Answer, concise yet insightful."""
 
-
 @st.cache_resource(show_spinner=False)
 def init_llm():
     huggingface_hub.login(token=os.getenv("HF_TOKEN"))
@@ -43,35 +39,15 @@ def get_response(prompt):
         return f"An error occurred: {str(e)}"
 
 
-def get_response(prompt, custom_sys_msg):
-    try:
-        convo = [
-            {"role": "system", "content": custom_sys_msg},
-            {"role": "user", "content": prompt},
-        ]
-        prompts = [llm.get_tokenizer().apply_chat_template(convo, tokenize=False)]
-        sampling_params = SamplingParams(temperature=0.3, top_p=0.95, max_tokens=2000, stop_token_ids=[128009])
-        outputs = llm.generate(prompts, sampling_params)
-        for output in outputs:
-            return output.outputs[0].text
-    except Exception as e:
-        return f"An error occurred: {str(e)}"
-
 def main():
     st.title("LLM-ADE 9B Demo")
     
-    # Retrieve the default system message
-    sys_msg = get_system_message()
-    
-    # UI for editable preprompt
-    user_modified_sys_msg = st.text_area("Preprompt: ", value=sys_msg, height=200)
-
     input_text = st.text_area("Enter your text here:", value="", height=200)
     
     if st.button("Generate"):
         if input_text:
             with st.spinner('Generating response...'):
-                response_text = get_response(input_text, user_modified_sys_msg)
+                response_text = get_response(input_text)
                 st.write(response_text)
         else:
             st.warning("Please enter some text to generate a response.")