app.py

import streamlit as st
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM

# Initialize tokenizer and model for Microsoft's Phi-2
tokenizer = AutoTokenizer.from_pretrained("microsoft/phi-2", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("microsoft/phi-2", torch_dtype="auto", device_map="auto", trust_remote_code=True)

# Function to generate text using Phi-2 model
def generate_text(prompt):
    with torch.no_grad():
        token_ids = tokenizer.encode(prompt, add_special_tokens=False, return_tensors="pt")
        output_ids = model.generate(
            token_ids.to(model.device),
            max_new_tokens=512,
            do_sample=True,
            temperature=0.4
        )
    return tokenizer.decode(output_ids[0][token_ids.size(1):])

# Streamlit app interface
st.title("Lesson Plan Generator")

# User input for subject and education level
subject = st.text_input("Subject:", "Mathematics")
level = st.text_input("Education Level:", "High School")

# Streamlit Session State for storing learning objectives
if 'learning_objectives' not in st.session_state:
    st.session_state.learning_objectives = ""

# Generate Learning Objectives Button
if st.button("Generate Learning Objectives"):
    # Prompt for generating learning objectives
    objectives_prompt = f"Generate learning objectives for a {level} level {subject} lesson."
    learning_objectives = generate_text(objectives_prompt)

    # Save and display generated objectives
    st.session_state.learning_objectives = learning_objectives.strip()
    st.write(f"### Learning Objectives:\n{learning_objectives.strip()}")

# Generate Lesson Plan Button
if st.button("Generate Lesson Plan"):
    # Construct the prompt for lesson plan
    lesson_plan_prompt = f"""
    Generate a lesson plan for a {level} grade teacher planning to teach their class about {subject}. Include objectives, activities, assessment methods, procedure, resources, and notes. Use the following objectives: {st.session_state.learning_objectives}
    """

    # Generate lesson plan
    lesson_plan = generate_text(lesson_plan_prompt)
    st.write(f"### Lesson Plan:\n{lesson_plan.strip()}")