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import os
import gradio as gr
from dotenv import load_dotenv
from openai import OpenAI
from prompts.main_prompt import MAIN_PROMPT, get_prompt_for_method, get_feedback_for_method
from prompts.initial_prompt import INITIAL_PROMPT
# βœ… Load API key from .env file
if os.path.exists(".env"):
load_dotenv(".env")
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
# βœ… 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)
# βœ… Track the selected method
selected_method = None # This will store which method the teacher selects
# βœ… Chatbot Response Function
def respond(user_message, history):
"""
Handles user input for the chatbot.
- Step 1: Teacher selects a method (Bar Model, Double Number Line, or Equation).
- Step 2: AI asks teacher to explain their reasoning before giving guidance.
- Step 3: AI listens to teacher's explanation and provides feedback.
"""
global selected_method # Store the selected method so AI remembers it
user_message = user_message.strip().lower()
# βœ… Step 1: Check if user selected a method (but hasn't explained yet)
if user_message in ["bar model", "double number line", "equation"]:
selected_method = user_message # Store selected method
response = get_prompt_for_method(user_message) # Ask for reasoning
history.append((user_message, response))
return "", history
# βœ… Step 2: If a method was selected, process teacher's explanation
if selected_method:
response = get_feedback_for_method(selected_method, user_message) # Give feedback
history.append((user_message, response))
return "", history
# βœ… If no method is selected yet, ask the user to select one
if not selected_method:
return "I didn’t understand that. Please select a method first (Bar Model, Double Number Line, or Equation).", history
return "", history # βœ… Maintain conversation flow
# βœ… Gradio UI Setup
with gr.Blocks() as demo:
gr.Markdown("## πŸ€– 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")
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)