Update app.py

app.py

@@ -3,7 +3,9 @@ import openai
 import streamlit as st
 
 # Get API key from environment variable
-api_key = os.environ["API_KEY"]
+api_key = os.environ.get("API_KEY")
+if api_key is None:
+    raise ValueError("API_KEY environment variable not set")
 
 # Set API key for OpenAI
 openai.api_key = api_key
@@ -12,23 +14,27 @@ st.title("IEP Assist Premium")
 
 # Add a sidebar with instructions
 st.sidebar.title("Instructions")
-st.sidebar.markdown("""
-1. Select the student's grade level.
-2. Select the student's qualifying condition(s).
-3. Choose a prompt to communicate with the AI how you want your data analyzed.
-4. Enter your student data.
-5. Click the 'Analyze Student Data' button to generate a summary of your data.
-**Note**: This app uses OpenAI's GPT-3 API to generate the PLAAFP statement. Please enter data that is relevant and appropriate for generating the statement.
-""")
+st.sidebar.write("1. Select the student's grade level.")
+st.sidebar.write("2. Select the student's qualifying condition(s).")
+st.sidebar.write("3. Choose a prompt based to communicate with the AI how you want your data analyzed.")
+st.sidebar.write("4. Enter your student data.")
+st.sidebar.write("5. Click the 'Analyze Student Data' button to generate a summary of your data.")
+
+st.sidebar.write("")
+st.sidebar.write("")
+
+st.sidebar.write("Note: This app uses OpenAI's GPT-3 API to generate the PLAAFP statement. Please enter data that is relevant and appropriate for generating the statement.")
+
+# Add a horizontal line for separation
+st.write("---")
 
 # Select the student's grade level
-st.subheader("Student Information")
 st.write("Select the student's grade level:")
 grade_level = st.selectbox("Grade:", ["Pre-K", "K", "1st", "2nd", "3rd", "4th", "5th", "6th", "7th", "8th", "9th", "10th", "11th", "12th"], key="grade-level")
 
 # Select the student's qualifying condition
 st.write("Select the student's qualifying condition(s):")
-qualifying_condition = st.multiselect( ["Specific Learning Disability", "Emotional Disturbance", "Autism", "Intellectual Disability", "Speech/Language Impairment", "Other Health Impairment", "Orthopedic Impairment", "Auditory Impairment", "Traumatic Brain Injury", "Deafness", "Blindness", "Developmental Delay"], key="qualifying-condition")
+qualifying_condition = st.multiselect("Qualifying Condition(s):", ["Specific Learning Disability", "Emotional Disturbance", "Autism", "Intellectual Disability", "Speech/Language Impairment", "Other Health Impairment", "Orthopedic Impairment", "Auditory Impairment", "Traumatic Brain Injury", "Deafness", "Blindness", "Developmental Delay"], key="qualifying-condition")
 
 # Choose a prompt
 st.write("Choose a prompt:(This tells the AI how you want your data analyzed)")
@@ -46,35 +52,26 @@ prompts = [    "Analyze the data provided on the student and provide a summary o
 
 selected_prompt = st.selectbox("Prompt:", options=prompts, key="prompt")
 
-# Enter student data
-st.subheader("Student Data")
 st.write("Enter student data to be analyzed:")
-student_data = st.text_area(height=300, key="student-data")
+student_data = st.text_area("Paste student data here", height=250, key="student-data")
 
 # Add a button to generate the PLAAFP statement
 if st.button("Analyze Student Data", key="analyze-button"):
-    if not student_data:
-        st.error('Please enter student data before analyzing.')
-    elif not grade_level or not qualifying_condition:
-        st.error('Please select grade level and qualifying condition before analyzing.')
-    else:
-        with st.spinner('Analyzing student data...'):
-            # Set OpenAI API key
-            openai.api_key = api_key
-
-            # Call the OpenAI API and generate a response
-            response = openai.Completion.create(
-                engine="text-davinci-003",
-                prompt=f"{selected_prompt} {student_data} {grade_level} {qualifying_condition}",
-                max_tokens=2000,
-                n=1,
-                stop=None,
-                temperature=0.9,
-            )
-
-            # Extract the generated statement from the API response
-            statement = response["choices"][0]["text"]
-
-            # Show the generated statement
-            st.subheader("Analysis Result")
-            st.write("Summary of Data entered:", statement)
+    # Set OpenAI API key
+    openai.api_key = api_key
+
+    # Call the OpenAI API and generate a response
+    response = openai.Completion.create(
+        engine="text-davinci-003",
+        prompt=f"{selected_prompt} {student_data} {grade_level} {qualifying_condition}",
+        max_tokens=2000,
+        n=1,
+        stop=None,
+        temperature=0.9,
+    )
+
+    # Extract the generated statement from the API response
+    statement = response["choices"][0]["text"]
+
+    # Show the generated statement
+    st.write("Summary of Data entered:", statement)