app.py

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("""
    <center>
    <h1>
    Uso de AI para un chatbot.
    </h1>
    <img src='data:image/jpg;base64,{}' width=200px>
    <h3>
    Con este espacio podrás hablar en formato conversación con el personaje famoso que quieras, puede ser Albert Einstein, Marie Curie o el/la que quieras!
    </h3>
    </center>
    """.format(encoded_image))
    with gr.Row():
        person1 = gr.Textbox(label="Escribí el nombre del perosnaje famoso:")
        person2 = gr.Textbox(label="Escribí el nombre del perosnaje famoso:")

    with gr.Row():
        chatbot = gr.Chatbot( height=550) #just to fit the notebook
    with gr.Row():
        with gr.Row():
            with gr.Column(scale=4):
                msg = gr.Textbox(label="Texto de entrada")
            with gr.Column(scale=1):
                btn = gr.Button("Enviar")
                clear = gr.ClearButton(components=[msg, chatbot], value="Borrar chat")

   


    btn.click(respond, inputs=[person1,person2, chatbot], outputs=[msg, chatbot])
    #msg.submit(respond, inputs=[msg, person,chatbot], outputs=[msg, chatbot]) #Press enter to submit
    clear.click(clear_chat,inputs=[msg, chatbot], outputs=[msg, chatbot])
demo.queue()
demo.launch()