| 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 |
| from prompts.initial_prompt import INITIAL_PROMPT |
|
|
| |
| if os.path.exists(".env"): |
| load_dotenv(".env") |
|
|
| OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") |
|
|
| if not OPENAI_API_KEY: |
| raise ValueError("π¨ OpenAI API key is missing! Set it in your .env file.") |
|
|
| |
| client = OpenAI() |
|
|
| def respond(user_message, history): |
| if not user_message: |
| return "", history |
|
|
| |
| try: |
| messages = [{"role": "system", "content": INITIAL_PROMPT}] |
|
|
| 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}) |
|
|
| |
| method_selection = user_message.lower().strip() |
| method_prompt = get_prompt_for_method(method_selection) |
| |
| if method_prompt != "I didnβt understand your choice. Please type 'Bar Model,' 'Double Number Line,' or 'Equation' to proceed.": |
| messages.append({"role": "assistant", "content": method_prompt}) |
| history.append((user_message, method_prompt)) |
| return "", history |
|
|
| messages.append({"role": "user", "content": user_message}) |
|
|
| |
| completion = client.chat.completions.create( |
| model="gpt-4o", |
| messages=messages, |
| max_tokens=512, |
| temperature=0.7 |
| ) |
|
|
| assistant_reply = completion.choices[0].message.content |
| history.append((user_message, assistant_reply)) |
|
|
| return "", history |
|
|
| except Exception as e: |
| return f"β οΈ An error occurred: {str(e)}", history |
|
|
| |
| with gr.Blocks() as demo: |
| gr.Markdown("## π€ 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) |
|
|