app.py

import os
import openai
import streamlit as st

# Get API key from environment variable
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

def write_sidebar():
    st.sidebar.title("Instructions")
    st.sidebar.markdown("**Step 1: Select the student's grade level.**")
    st.sidebar.markdown("Choose the grade level of the student you want to analyze.")
    st.sidebar.markdown("---")
    st.sidebar.markdown("**Step 2: Select the student's qualifying condition(s).**")
    st.sidebar.markdown("Select one or more qualifying conditions that apply to the student.")
    st.sidebar.markdown("---")
    st.sidebar.markdown("**Step 3: Choose a category and prompt to analyze.**")
    st.sidebar.markdown("Select the category that corresponds to the area you want to analyze (e.g., Reading, Writing). Then choose a specific prompt related to that category.")
    st.sidebar.markdown("---")
    st.sidebar.markdown("**Step 4: Enter your student data.**")
    st.sidebar.markdown("Paste the relevant data about the student that you want to analyze. Provide information such as assessments, performance data, or observations.")
    st.sidebar.markdown("---")
    st.sidebar.markdown("**Step 5: Check the box to generate an IEP goal.**")
    st.sidebar.markdown("If you want the tool to generate an IEP goal based on the analysis, check this box.")
    st.sidebar.markdown("---")
    st.sidebar.markdown("**Step 6: Click the 'Generate' button to generate the selected output.**")
    st.sidebar.markdown("Once you have filled in the necessary information, click the 'Generate' button to generate the analysis or analysis with an IEP goal, depending on your selection.")

    st.sidebar.write("")
    st.sidebar.write("")

    st.sidebar.write("Note: This app uses OpenAI's GPT-3 API to generate the analysis and IEP goal. Please enter data that is relevant and appropriate for generating the output.")

def get_grade_specific_prompts(grade_level):
    # ...

def write_iep_assist():
    st.title("IEP Assist Premium")

    # Select the student's grade level
    st.markdown("<h3>Step 1: Select the student's grade level:</h3>", unsafe_allow_html=True)
    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.markdown("<h3>Step 2: Select the student's qualifying condition(s):</h3>", unsafe_allow_html=True)
    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")

    grade_specific_prompts = get_grade_specific_prompts(grade_level)

    # Choose a category and prompt
    st.markdown("<h3>Step 3: Choose a category and prompt:</h3>", unsafe_allow_html=True)
    selected_category = st.selectbox("Category:", options=list(grade_specific_prompts.keys()), key="category")
    prompts = grade_specific_prompts[selected_category]
    selected_prompt = st.selectbox("Prompt:", options=prompts, key="prompt")

    # Enter student data to be analyzed
    st.markdown("<h3>Step 4: Enter student data to be analyzed:</h3>", unsafe_allow_html=True)
    student_data = st.text_area("Paste student data here", height=250, key="student-data")

    # Checkbox to generate IEP goal
    generate_goal = st.checkbox("Step 5: Generate IEP Goal", key="generate-goal")

    # Add a button to generate the analysis and IEP goal
    generate_button = st.button("Step 6: Generate", key="generate-button", help="Click here to generate the selected output.")

    if generate_button:
        if generate_goal:
            # Call the OpenAI API and generate an effective IEP goal
            response = openai.Completion.create(
                engine="text-davinci-003",
                prompt=f"Generate an effective and measurable IEP goal for a {grade_level} student with qualifying conditions of {', '.join(qualifying_condition)}. The goal should be based on the analysis of their data and meet the following characteristics: Measurable, Specific and Clear, Attainable and Realistic, Relevant and Meaningful, Time-Bound, Individualized, Action-Oriented, Aligned with Standards and Curriculum, Collaboratively Developed, Monitored and Adjusted. Data Analysis: {selected_prompt} {student_data}",
                max_tokens=2000,
                n=1,
                stop=None,
                temperature=0.85,
            )
            goal = response["choices"][0]["text"]

            # Show the generated effective IEP goal
            st.markdown(f"<h3>Effective IEP Goal:</h3>{goal}", unsafe_allow_html=True)
        else:
            # Call the OpenAI API and generate the analysis
            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,
            )
            statement = response["choices"][0]["text"]

            # Show the generated analysis
            st.markdown(f"<h3>Analysis:</h3>{statement}", unsafe_allow_html=True)

if __name__ == "__main__":
    write_sidebar()
    write_iep_assist()