Update app.py

app.py

@@ -16,19 +16,24 @@ bg = st.text_area("Background information",
 
 if 'ft' in st.session_state or st.button('Next step'):
     if 'ft' not in st.session_state:
+        rf = os.environ.get("DESIGN_PROMPT")
         messages = [
             {
                 "role": "user",
                 "content": f"""Generate possible factors related to the goal
-                based on the information provided. List the factors in markdown list.\n\n
+                based on the information provided. List the factors in markdown list.
+                You can give advice to human to edit their goal if you cannot define
+                more than 3 factors.\n\n
                 goals:\n\n{gl}\n\n
-                background:\n\n{bg}\n\n""",
+                background:\n\n{bg}\n\n
+                some design principles for your reference:\n\n
+                reference:\n\n```markdown\n{rf}\n\n```\n\n""",
             }
         ]
         
         chat_completion = client.chat.completions.create(
             messages=messages,
-            model="llama3-8b-8192",
+            model="llama3-70b-8192",
         )
     
     ft = st.text_area("Factors to be considered in questions",
@@ -36,7 +41,28 @@ if 'ft' in st.session_state or st.button('Next step'):
     st.session_state['ft'] = ft
     st.write('Edit above factors, add or remove if needed')
 
+    rf = os.environ.get("DESIGN_PROMPT")
+
     if st.button('Generate questions'):
-        pass # for each factor generate 5 questions
-        # suggest the number of sample to collect for the polling = 7 * total question number
+        rf += f'''\n\n---\n\n{os.environ.get("DESIGN_PROMPT_SIXPOINT")}'''
+        messages = [
+            {
+                "role": "user",
+                "content": f"""Extract all factors from the text to create context.
+                Generate 5 question based on the text and context.
+                Write the questionnaire form in markdown\n\n
+                text:\n\n{ft}\n\n
+                some design principles for your reference:\n\n
+                reference:\n\n```markdown\n{rf}\n```\n\n""",
+            }
+        ]
+        
+        chat_completion = client.chat.completions.create(
+            messages=messages,
+            model="llama3-70b-8192",
+        )
+
+        md = chat_completion.choices[0].message.content
+        suggested_sampling = 5 * len(md.split("\n"))
+        st.markdown(f"{md}\n\n**suggested number of sampling**: {suggested_sampling}")
         # dump questions into excel and allow download