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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, otherwise show an error
if not OPENAI_API_KEY:
raise ValueError("🚨 OpenAI API key is missing! Set it in the .env file or hardcode it in app.py.")
client = OpenAI(api_key=OPENAI_API_KEY)
# ✅ Chatbot Response Function
def respond(user_message, history):
if not user_message:
return "", history
# ✅ Handle method selection
if user_message.lower() in ["bar model", "double number line", "equation"]:
response = get_prompt_for_method(user_message)
history.append((user_message, response))
return "", history
# ✅ Handle teacher response to method
last_method = history[-1][0] if history else None
if last_method and last_method.lower() in ["bar model", "double number line", "equation"]:
response = get_feedback_for_method(last_method, user_message)
history.append((user_message, response))
return "", history
# ✅ Default response if input is unclear
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) # ✅ Ensures AI starts with INITIAL_PROMPT
state_history = gr.State([(INITIAL_PROMPT, "")]) # ✅ Sets initial prompt as the first message
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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