import os from openai import OpenAI import gradio as gr import json from dotenv import load_dotenv # Load environment variables from the .env file de forma local load_dotenv() import base64 with open("Iso_Logotipo_Ceibal.png", "rb") as image_file: encoded_image = base64.b64encode(image_file.read()).decode() client1= OpenAI(api_key=os.environ['OPENAI_API_KEY']) client2= OpenAI(api_key=os.environ['OPENAI_API_KEY']) def clear_chat(message, chat_history): return "", [] def add_new_message_client1(message,person, chat_history): new_chat = [] new_chat.append({"role": "system", "content": 'Sos {} y tendrás que responder preguntas, las respuestas tienen que ser cómo si las hubiera dicho {} '.format(person,person)}) for turn in chat_history: user, bot = turn new_chat.append({"role": "user", "content": user}) new_chat.append({"role": "assistant","content":bot}) new_chat.append({"role": "user","content":message}) return new_chat def add_new_message_client2(message,person, chat_history): new_chat = [] new_chat.append({"role": "system", "content": 'Sos {} y tendrás que responder preguntas, las respuestas tienen que ser cómo si las hubiera dicho {} '.format(person,person)}) for turn in chat_history: user, bot = turn new_chat.append({"role": "user", "content": user}) new_chat.append({"role": "assistant","content":bot}) new_chat.append({"role": "user","content":message}) return new_chat counter2 =1 def respond(person1,person2, chat_history): print(chat_history) global counter2 if(len(chat_history)<1): message="Hola" prompt = add_new_message_client1(message, person1, chat_history) response = client1.chat.completions.create( model="gpt-3.5-turbo", messages= prompt, temperature=0.5, max_tokens=1000, stream=False, ) chat_history.append((message, response.choices[0].message.content)) else: counter2 +=1 if(counter2 % 2==0): prompt = add_new_message_client1(chat_history[-1][1], person1, chat_history) response = client1.chat.completions.create( model="gpt-3.5-turbo", messages= prompt, temperature=0.5, max_tokens=1000, stream=False, ) chat_history.append((response.choices[0].message.content, "" )) else: prompt =add_new_message_client2(chat_history[-1][1], person2, chat_history) response = client2.chat.completions.create( model="gpt-3.5-turbo", messages= prompt, temperature=0.5, max_tokens=1000, stream=False, ) chat_history[-1][1]=response.choices[0].message.content #.append([chat_history[-1][1], response.choices[0].message.content]) print(chat_history) token_counter = 0 partial_words = "" counter=0 partial_message = "" print(chat_history) return "", chat_history # for chunk in response: # if len(chunk.choices[0].delta.content) != 0: # partial_message = partial_message + chunk.choices[0].delta.content # yield partial_message # for chunk in response: # print(chunk) # print( "text",chunk.choices[0].delta.content) # chunk_message = chunk.choices[0].delta # if(len(chat_history))<1: # # print("entró acaá") # partial_words += chunk_message.content # chat_history.append([message,chunk_message.content]) # else: # # print("antes", chat_history) # if(len(chunk_message.content)!=0): # if(len(chunk_message.content)==2): # partial_words += chunk_message.content # chat_history.append([message,chunk_message.content]) # else: # partial_words += chunk_message.content # chat_history[-1] =([message,partial_words]) # yield "",chat_history with gr.Blocks() as demo: gr.Markdown("""