Update app.py

app.py

@@ -1,65 +1,23 @@
-import os
-import gradio as gr
-from dotenv import load_dotenv
-from openai import OpenAI
-from prompts.main_prompt import MAIN_PROMPT  # Ensure this file exists and is fixed
-
-# Load API key from .env file
-if os.path.exists(".env"):
-    load_dotenv(".env")
-
-OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
-
-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
-
-    try:
-        assistant_reply = client.chat.completions.create(
-            model="gpt-4o",
-            messages=[
-                {"role": "system", "content": MAIN_PROMPT},
-                *[
-                    {"role": "user", "content": u} if i % 2 == 0 else {"role": "assistant", "content": a}
-                    for i, (u, a) in enumerate(history)
-                ],
-                {"role": "user", "content": user_message}
-            ],
-            max_tokens=512,
-            temperature=0.7,
-        ).choices[0].message.content
-
-        history.append((user_message, assistant_reply))
-
-        return "", history
-
-    except Exception as e:
-        return f"An error occurred: {str(e)}", history
-
-# Gradio UI Setup
-with gr.Blocks() as demo:
-    gr.Markdown("## AI-Guided Math PD Chatbot")
-
-    chatbot = gr.Chatbot(value=[(MAIN_PROMPT, "")], height=500) 
-    state_history = gr.State([(MAIN_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)
+    """
+    Handles user input and determines how the chatbot responds.
+    - If the teacher selects a method, AI will **first ask them to explain their approach**.
+    - AI will not provide a full solution immediately.
+    - If the teacher already explained, AI will provide feedback and hints.
+    """
+    user_message = user_message.strip().lower()
+
+    # If the user selects a method, prompt them to explain their approach first
+    if user_message in ["bar model", "double number line", "equation"]:
+        return get_prompt_for_method(user_message), history
+    
+    # If AI is expecting an explanation, process teacher's response
+    elif len(history) > 0 and history[-1] in [
+        get_prompt_for_method("bar model"),
+        get_prompt_for_method("double number line"),
+        get_prompt_for_method("equation")
+    ]:
+        last_method = history[-1].split("**")[1].split(" ")[0].lower()  # Extract method name from the last message
+        return get_feedback_for_method(last_method, user_message), history
+    
+    return "I didn’t quite understand that. Please select a method first (Bar Model, Double Number Line, or Equation).", history