app.py

import os
import gradio as gr
from dotenv import load_dotenv
from openai import OpenAI
from prompts.initial_prompt import INITIAL_PROMPT
from prompts.main_prompt import MAIN_PROMPT, get_prompt_for_method, get_feedback_for_method

# ✅ Load API key from .env file
if os.path.exists(".env"):
    load_dotenv(".env")

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")

# ✅ Ensure API Key is available
if not OPENAI_API_KEY:
    raise ValueError("🚨 OpenAI API key is missing! Set it in the .env file.")

client = OpenAI(api_key=OPENAI_API_KEY)

# ✅ Chatbot Response Function
def respond(user_message, history):
    if not user_message:
        return "", history

    user_message = user_message.strip().lower()  # Normalize input for better handling

    # ✅ Extract previous user input
    last_user_input = history[-1][0].strip().lower() if history else ""

    # ✅ Check if user selected a method
    valid_methods = ["bar model", "double number line", "equation"]

    if user_message in valid_methods:
        prompt = get_prompt_for_method(user_message)
        history.append((user_message, prompt))  # Update history
        return prompt, history

    # ✅ Ensure the user has selected a method before receiving feedback
    if last_user_input in valid_methods:
        selected_method = last_user_input  # Keep track of last selected method
        feedback = get_feedback_for_method(selected_method, user_message)
        history.append((user_message, feedback))  # Update history
        return feedback, history

    return "❌ I didn’t understand that. Please select a method first (Bar Model, Double Number Line, or Equation).", history

# ✅ Gradio UI Setup
with gr.Blocks() as demo:
    gr.Markdown("## 🤖 AI-Guided Math PD Chatbot")

    chatbot = gr.Chatbot(value=[(INITIAL_PROMPT, "")], height=500)
    state_history = gr.State([(INITIAL_PROMPT, "")])

    user_input = gr.Textbox(placeholder="Type your message here...", label="Your Input")

    # ✅ Handling user input and response logic
    user_input.submit(
        respond,
        inputs=[user_input, state_history],
        outputs=[user_input, chatbot]
    ).then(
        fn=lambda _, h: h,
        inputs=[user_input, chatbot],
        outputs=[state_history]
    )

if __name__ == "__main__":
    demo.launch(server_name="0.0.0.0", server_port=7860, share=True)