import gradio as gr import json, openai, os, time from openai import OpenAI _client, _assistant, _thread = None, None, None def show_json(str, obj): print(f"=> {str}\n{json.loads(obj.model_dump_json())}") def init_client(): global _client, _assistant, _thread _client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY")) _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", _assistant) _thread = _client.beta.threads.create() #show_json("thread", _thread) def wait_on_run(run): global _client, _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(0.25) return run def extract_content_values(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, openai_api_key): global _client, _assistant, _thread if _client == None: init_client() message = _client.beta.threads.messages.create( role="user", thread_id=_thread.id, content=message, ) #show_json("message", message) run = _client.beta.threads.runs.create( assistant_id=_assistant.id, thread_id=_thread.id, ) #show_json("run", run) run = wait_on_run(run) show_json("run", run) messages = _client.beta.threads.messages.list( thread_id=_thread.id ) show_json("messages", messages) return extract_content_values(messages)[0] gr.ChatInterface( chat, chatbot=gr.Chatbot(), textbox=gr.Textbox(placeholder="Question", container=False, scale=7), title="Multi-Assistant Demo", description="Ask AAA Assistant, BBB Assistant, and CCC Assistant any question", retry_btn=None, undo_btn=None, clear_btn="Clear", examples=[["I need to solve the equation '2x + 10 = 20'. Can you help me?", "sk-"]], cache_examples=False, additional_inputs=[ gr.Textbox("sk-", label="OpenAI API Key", type = "password"), ], ).launch()