File size: 2,430 Bytes
866286c 3538cf5 866286c 7b6aaf6 73b1050 7b6aaf6 866286c 7b6aaf6 8bcaf24 7b6aaf6 8bcaf24 7b6aaf6 3538cf5 7b6aaf6 4910ade 7b6aaf6 73b1050 3538cf5 7b6aaf6 4910ade 3538cf5 866286c 0cfa14e 7b6aaf6 866286c 8bcaf24 866286c 7b6aaf6 866286c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 |
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, selected_method):
if not user_message:
return "", history, selected_method
user_message = user_message.strip().lower() # Normalize input
valid_methods = ["bar model", "double number line", "equation"]
# ✅ If user selects a method, store it and provide the method-specific prompt
if user_message in valid_methods:
selected_method = user_message # Store the method
method_prompt = get_prompt_for_method(user_message)
history.append((user_message, method_prompt)) # Ensure tuple format
return method_prompt, history, selected_method
# ✅ If a method has already been selected, provide feedback
if selected_method:
feedback = get_feedback_for_method(selected_method, user_message)
history.append((user_message, feedback)) # Ensure tuple format
return feedback, history, selected_method
error_msg = "❌ Please select a method first (Bar Model, Double Number Line, or Equation)."
history.append((user_message, error_msg)) # Ensure tuple format
return error_msg, history, selected_method
# ✅ 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, "")])
state_selected_method = gr.State(None) # ✅ New state to track selected method
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, state_selected_method],
outputs=[chatbot, state_history, state_selected_method]
)
if __name__ == "__main__":
demo.launch(server_name="0.0.0.0", server_port=7860, share=True)
|