import gradio as gr import json, openai, os, time from openai import OpenAI client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY")) def show_json(obj): print("###") print(json.loads(obj.model_dump_json())) print("###") def wait_on_run(run, thread): while run.status == "queued" or run.status == "in_progress": run = client.beta.threads.runs.retrieve( thread_id=thread.id, run_id=run.id, ) time.sleep(0.5) return run def extract_content_value(data): content_values = [] for item in data['data']: for content in item['content']: if content['type'] == 'text': content_values.append(content['text']['value']) return content_values def chat(message, history): assistant = client.beta.assistants.create( name="Math Tutor", instructions="You are a personal math tutor. Answer questions briefly, in a sentence or less.", model="gpt-4-1106-preview", ) show_json(assistant) thread = client.beta.threads.create() show_json(thread) message = client.beta.threads.messages.create( thread_id=thread.id, role="user", content="I need to solve the equation `3x + 11 = 14`. Can you help me?", ) show_json(message) run = client.beta.threads.runs.create( thread_id=thread.id, assistant_id=assistant.id, ) show_json(run) run = wait_on_run(run, thread) show_json(run) messages = client.beta.threads.messages.list(thread_id=thread.id) show_json(messages) return extract_content_value(messages)[0] gr.ChatInterface( chat, chatbot=gr.Chatbot(height=300), textbox=gr.Textbox(placeholder="Ask me a yes or no question", container=False, scale=7), title="Math Tutor", description="Ask Math Tutor any question", theme="soft", examples=["I need to solve the equation `3x + 11 = 14`. Can you help me?"], cache_examples=True, retry_btn=None, undo_btn=None, clear_btn="Clear", ).launch()