Update app.py

app.py

@@ -4,7 +4,6 @@ from langchain.prompts import PromptTemplate
 from langchain_core.prompts import FewShotPromptTemplate 
 from langchain.prompts.example_selector import LengthBasedExampleSelector
 
-
 def getLLMResponse(query,age_option,tasktype_option,numberOfWords):
     llm = OpenAI(model="gpt-3.5-turbo-instruct", temperature=.9)
 
@@ -64,13 +63,15 @@ def getLLMResponse(query,age_option,tasktype_option,numberOfWords):
     )
 
 
-    prefix = """You need to {template_tasktype_option} for a {template_ageoption} in not more than {template_numberOfWords} words: 
-    Here are some examples of how you should tailor your response for this person: 
+    prefix = """You need to {template_tasktype_option} for a {template_ageoption}: 
+    Here are some set of questions and expected responses for a person like this. these examples are to familarize yourself. The last question does not have a response. you need to generate it: 
     """
 
     suffix = """
     Question: {template_userInput}
-    Response: """
+    Response: ?
+    The final response should not be more than {template_numberOfWords} words
+    """
 
     example_selector = LengthBasedExampleSelector(
         examples=examples,
@@ -119,3 +120,4 @@ submit = st.button("Generate")
 
 if submit:
     st.write(getLLMResponse(form_input,age_option,tasktype_option,numberOfWords))
+