Update app.py

app.py

@@ -2,10 +2,9 @@ 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, PROBLEM_SOLUTIONS_PROMPT  # Ensure both are imported
+from prompts.main_prompt import MAIN_PROMPT
 
-# Load the API key from the .env file if available
+# Load API key
 if os.path.exists(".env"):
     load_dotenv(".env")
 
@@ -13,97 +12,36 @@ OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
 
 client = OpenAI(api_key=OPENAI_API_KEY)
 
-
-def gpt_call(history, user_message,
-             model="gpt-4o",
-             max_tokens=3000,  # Increased to 3000 to prevent truncation
-             temperature=0.7,
-             top_p=0.95):
-    """
-    Calls the OpenAI API to generate a response.
-    - history: [(user_text, assistant_text), ...]
-    - user_message: The latest user message
-    """
-    # 1) Start with the system message (MAIN_PROMPT) for context
-    messages = [{"role": "system", "content": MAIN_PROMPT}]
-
-    # 2) Append conversation history
-    for user_text, assistant_text in history:
-        if user_text:
-            messages.append({"role": "user", "content": user_text})
-        if assistant_text:
-            messages.append({"role": "assistant", "content": assistant_text})
-
-    # 3) Add the user's new message
-    messages.append({"role": "user", "content": user_message})
-
-    # 4) Call OpenAI API (with continuation handling)
-    full_response = ""
-    while True:
-        completion = client.chat.completions.create(
-            model=model,
-            messages=messages,
-            max_tokens=max_tokens,  # Increased to allow longer responses
-            temperature=temperature,
-            top_p=top_p
-        )
-        
-        response_part = completion.choices[0].message.content.strip()
-        full_response += " " + response_part
-
-        # If the response looks incomplete, force the AI to continue
-        if len(response_part) < max_tokens - 50:  # Ensures near full completion
-            break  # Stop loop if response is complete
-
-        # Add last response back into conversation history to continue it
-        messages.append({"role": "assistant", "content": response_part})
-
-    return full_response.strip()
-
-
 def respond(user_message, history):
-    """
-    Handles user input and gets GPT-generated response.
-    - user_message: The message from the user
-    - history: List of (user, assistant) conversation history
-    """
     if not user_message:
         return "", history
 
-    # If the user asks for a solution, inject PROBLEM_SOLUTIONS_PROMPT
-    if "solution" in user_message.lower():
-        assistant_reply = gpt_call(history, PROBLEM_SOLUTIONS_PROMPT)
-    else:
-        assistant_reply = gpt_call(history, user_message)
+    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
 
-    # Add conversation turn to history
     history.append((user_message, assistant_reply))
 
     return "", history
 
-
-##############################
-#  Gradio Blocks UI
-##############################
 with gr.Blocks() as demo:
     gr.Markdown("## AI-Guided Math PD Chatbot")
+    chatbot = gr.Chatbot(height=500)
 
-    # Chatbot initialization with the first AI message
-    chatbot = gr.Chatbot(
-        value=[("", INITIAL_PROMPT)],  # Initial system prompt
-        height=500
-    )
+    state_history = gr.State([("", MAIN_PROMPT)])
 
-    # Stores the chat history
-    state_history = gr.State([("", INITIAL_PROMPT)])
+    user_input = gr.Textbox(placeholder="Type your message here...", label="Your Input")
 
-    # User input field
-    user_input = gr.Textbox(
-        placeholder="Type your message here...",
-        label="Your Input"
-    )
-
-    # Submit action
     user_input.submit(
         respond,
         inputs=[user_input, state_history],
@@ -114,6 +52,16 @@ with gr.Blocks() as demo:
         outputs=[state_history]
     )
 
-# Run the Gradio app
+# ✅ **Explicitly tell Gradio to use MathJax for LaTeX rendering**
+gr.Markdown(
+    r"""
+    <script type="text/javascript">
+        MathJax = {
+            tex: { inlineMath: [['$', '$'], ['\\(', '\\)']] }
+        };
+    </script>
+    """
+)
+
 if __name__ == "__main__":
     demo.launch(server_name="0.0.0.0", server_port=7860, share=True)