Updates

app.py

@@ -4,6 +4,7 @@
 
 import streamlit as st
 import json
+import markdown
 
 from langchain.chat_models import ChatOpenAI
 from langchain.schema import (
@@ -17,27 +18,54 @@ from langchain.schema import (
 #App UI starts here
 st.set_page_config(page_title="FRQ Generator", page_icon=":robot:")
 st.header("FRQs using GPT-4")
+header_text=str('''
+                              Paste a JSON file here, with the following information:
+1. The name of the common core standard, 
+2. The student's area of interest. 
+
+E.g. 
+```
+{
+ 'input':'frq-generator',
+ 'entries':[
+	    {'cc-standard': 'CCSS.ELA-LITERACY.W.4.9', 'area-of-interest': 'Baseball' },
+	    {'cc-standard': 'CCSS.ELA-LITERACY.W.5.8', 'area-of-interest': 'Hiking' }
+    ]
+}
+```
+                              ''')
+st.markdown(header_text)
 
 if "sessionMessages" not in st.session_state:
     st.session_state.sessionMessages = [
-        SystemMessage(content = "You are a bot that generates 'free response questions' for assesing school students based on the input of a Common Core Standard, and area of interest.\
-                      If the common core standard involves reading a passage, then also generate a passage of exactly 300 words, and use real world examples. Provide an introduction and clear context for the questions.\
-                      To answer the questions, the student should only need to read the presented text and should not need to refer to external sources.")
+        SystemMessage(content = "You are a bot that generates 'free response questions' for assesing school students based on the input of a Common Core Standard, and area of interest.")
     ]
 
 
 #Function to return the response
 def load_answer(question):
+    ccStandard = question['cc-standard']
     #st.session_state.sessionMessages.append(HumanMessage(content="Common Core standard is: {question[0]}, and the area of interest is: {question[1]}"))
-    st.session_state.sessionMessages.append(HumanMessage(content=str(question)))
+    
+    ## Ask the model to understand the common core standard specified
+    st.session_state.sessionMessages.append(HumanMessage(content="Read the common core standard :"+ccStandard+" and summarize its key requirements for a student in 3 bullet points. what year grade is the above standard applicable to? Answer in simple one word. E.g. '4th grade',' or 'Kindergarten', or 'Nursery'. Also tell if the student needs to read a passage to complete an assessment related to this standard. \
+                                                         Return the result in JSON format, with keys including 'grade-level', 'standard-requirement', 'is-passage-required'."))
     assistant_answer = chat(st.session_state.sessionMessages)
     st.session_state.sessionMessages.append(AIMessage(content=assistant_answer.content))
-    return assistant_answer.content
+
+    # # Identify which grade the standard applies to, and return the grade in one phrase. E.g. '4th grade' or 'kindergarten'
+    # st.session_state.sessionMessages.append(HumanMessage(content="what year grade is the above standard applicable to? Answer in simple one word. E.g. '4th grade',' or 'Kindergarten', or 'Nursery'"))
+    # identifiedGrade = chat(st.session_state.sessionMessages)
+    # st.session_state.sessionMessages.append(AIMessage(content=identifiedGrade.content))
+
+    # output=assistant_answer.content+ " and Identified Grade:"+identifiedGrade.content
+    # print (output)
+    return json.loads(assistant_answer.content)
 
 
 #Gets the user input
 def get_text():
-    input_text = st.text_area("Paste a JSON file here, with the following keys:(1) The name of the common core standard, (2) The student's area of interest. E.g. {\"cc-standard\": \"CCSS.ELA-LITERACY.W.4.9\", \"area-of-interest\": \"Baseball\" }  ", key="input")
+    input_text = st.text_area(label="Paste here")
     return input_text
 
 chat = ChatOpenAI(temperature=0, model_name="gpt-4")

requirements.txt

@@ -3,3 +3,4 @@ Openai
 Streamlit
 streamlit-chat
 python-dotenv
+markdown