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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
# ✅ 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):
"""
Handles user input for the chatbot.
- If a method is selected, AI asks for teacher's reasoning first.
- AI only provides feedback after hearing the teacher's approach.
"""
user_message = user_message.strip().lower()
# ✅ Check if the last message in history was a method selection prompt
if history and history[-1][1] in [
get_prompt_for_method("bar model"),
get_prompt_for_method("double number line"),
get_prompt_for_method("equation")
]:
# ✅ Retrieve the last selected method
last_method = history[-1][1].split("**")[1].split(" ")[0].lower()
response = get_feedback_for_method(last_method, user_message)
history.append((user_message, response))
return "", history
# ✅ If user selects a method, ask them to explain their reasoning
if user_message in ["bar model", "double number line", "equation"]:
response = get_prompt_for_method(user_message)
history.append((user_message, response))
return "", history
# ✅ Default response if input is unclear and no method has been selected
if not history or history[-1][0] not in ["bar model", "double number line", "equation"]:
return "I didn’t understand that. Please select a method first (Bar Model, Double Number Line, or Equation).", history
return "", history # ✅ Keep the conversation flowing without errors
# ✅ 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")
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)
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