app.py

# coding=utf8
from gpt_index import SimpleDirectoryReader, GPTListIndex, GPTSimpleVectorIndex, LLMPredictor, PromptHelper
from langchain import OpenAI
import gradio as gr
import random
import time
import sys
import os
from transformers import pipeline
p = pipeline("automatic-speech-recognition")


os.environ["OPENAI_API_KEY"] = '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'

css = """
.gradio-container {
    background-color: #ffffff;
}
    
#component-2 {position: absolute; bottom: 0;    width: 100%;
}

div.float.svelte-1frtwj3 {
    position: absolute;
    opacity: 0;
    height: 100%;
    max-height: 100%;
    overflow-y: auto;




}

div.svelte-1frtwj3 {
    display: inline-flex;
    align-items: center;

div.bot.svelte-6roggh.svelte-6roggh {
    background: #D9A13D;
}

div.bot.svelte-17nzccn.svelte-17nzccn {
    background: #D9A13D;
}

div.user.svelte-6roggh.svelte-6roggh {
    background: #5F0000;
}

div.user.svelte-17nzccn.svelte-17nzccn {
    background: #5F0000;
}    

div.textBoxBot {
    display: flex;
    flex-direction: inherit;
    flex-wrap: wrap;
    gap: var(--form-gap-width);
    box-shadow: var(--block-shadow);
    border: var(--block-border-width) solid #5f0000;
    border-radius: var(--radius-lg);
    background: #ffffff;
    overflow: hidden;
    position: fixed;
    bottom: 0;
    margin-left: -16px;
}

.textarea.svelte-1pie7s6.svelte-1pie7s6 {
    display: flex;
    flex-direction: inherit;
    flex-wrap: wrap;
    gap: var(--form-gap-width);
    box-shadow: var(--block-shadow);
    border: var(--block-border-width) solid #5f0000;
    border-radius: var(--radius-lg);
    background: #ffffff;
    overflow: hidden;
    position: fixed;
    bottom: 0;
    margin-left: -16px;
}

.svelte-1pie7s6.svelte-1pie7s6 {
    display: flex;
    flex-direction: inherit;
    flex-wrap: wrap;
    gap: var(--form-gap-width);
    box-shadow: var(--block-shadow);
    border: 5px solid #5f0000;
    border-radius: var(--radius-lg);
    border-color: #5F0000;
    background: #ffffff;
    color: #5F0000;    
    font-size: 16px;    
    overflow: hidden;
    position: fixed;
    bottom: 20px; /* Ajuste a distância vertical do rodapé */
    margin-left: -5px;
    max-height: 80vh; /* Ajuste a altura máxima da div */
    max-width: 78%; /* Ajuste a largura máxima da div */
}


.img.svelte-ms5bsk {
    width: 100%;
    height: 100%;
    background-color: #ffffff;    
    border: 0px;    
    border-width: 0px;
}
.app.svelte-ac4rv4.svelte-ac4rv4 {
    max-width: none;
}
.app.svelte-ac4rv4.svelte-ac4rv4{max-width:none}
.wrap.svelte-1o68geq.svelte-1o68geq {max-height: none}

.block.svelte-mppz8v {
    position: relative;
    margin: 0;
    return str(response.response)
"""

with gr.Blocks(css=css) as demo:
    realPath = str(os.path.dirname(os.path.realpath(__file__)))
    img1 = gr.Image("images/1024x150_cabeçalho.hippo.png", elem_classes=".img.svelte-ms5bsk", elem_id="img.svelte-ms5bsk").style(container=False)
    gpt = gr.Chatbot(elem_classes=".wrap.svelte-1o68geq.svelte-1o68geq", elem_id="chatbot").style(container=True)
    msg = gr.Textbox(elem_id="div.svelte-awbtu4",elem_classes="textBoxBot", show_label=False,
                placeholder="Bem vindo ao Hippo Supermercados, em que posso ajuda-lo?",
            ).style(container=False)
    #clear = gr.Button("Limpar Conversa")
   # gr.Audio(source="microphone", type="filepath",label="ESTÁ COM DIFICULDADES EM ESCREVER? CLIQUE E ME DIGA O QUE DESEJA")
    def respond(message, chat_history):
        chat_history.append((message, chatbot(message)))
        time.sleep(1)
        vetor = []
        realPath = str(os.path.dirname(os.path.realpath(__file__)))

        if str(message).upper()=="OLA" or str(message).upper()=="OLÁ" or str(message).upper()=="OI":
            vetor = vetor + [((realPath + "\\images\\hippo-apresentacao.mp4",), "")]
        elif str(message).upper() == "VINHO CASA DEL RONCO PINOT GRIGIO" :
                vetor = vetor + [((realPath + "\\images\\casa-del-ronco-branco.png",), "")]
        elif str(message).upper() == "SURVIVOR CHENIN BLANC" :
                vetor = vetor + [((realPath + "\\images\\survivor-branco.png",), "")]
                vetor = vetor + [((realPath + "\\images\\survivor.mp4",), "")]

        elif str(message).upper() == "VINHO PORTO NOVA VERDE" :
                vetor = vetor + [((realPath + "\\images\\porta-nova-branco.jpg",), "")]
                vetor = vetor + [((realPath + "\\images\\porta-nova-verde.mp4",), "")]

        elif str(message).upper() == "VINHO QUINTA DO PINTO ARINTO BRANCO" :
                vetor = vetor + [((realPath + "\\images\\quinta-pinto-arinto-branco.png",), "")]
        elif str(message).upper() == "VINHO 1492 CHARDONNAY" :
                vetor = vetor + [((realPath + "\\images\\chardonay-branco.jpg",), "")]
        elif str(message).upper() == "ME SUGIRA UM VINHO TINTO BOM COM QUEIJO" :
                vetor = vetor + [((realPath + "\\images\\TNT-CABERNET.png",), "")]
                vetor = vetor + [((realPath + "\\images\\vinho-queijo.mp4",), "")]

        elif str(message).upper() == "VINHO BOM COM CHOCOLATE" :
                vetor = vetor + [((realPath + "\\images\\TNT-CABERNET.png",), "")]
        elif str(message).upper() == "VINHO BOM COM PEIXE" :
                vetor = vetor + [((realPath + "\\images\\luson-branco.png",), "")]
                vetor = vetor + [((realPath + "\\images\\vinho-peixe.mp4",), "")]

        elif str(message).upper() == "VINHAS DO LASSO COLHEITA SELECIONADA" :
                vetor = vetor + [((realPath + "\\images\\lasso-colheita-rose.png",), "")]
        elif str(message).upper() == "DOM CAMPOS MOSCATEL" :
                vetor = vetor + [((realPath + "\\images\\dom-campos-rose.png",), "")]
        elif str(message).upper() == "BECAS ROSE MEIO SECO" :
                vetor = vetor + [((realPath + "\\images\\becas-rose.png",), "")]
        elif str(message).upper() == "PORTA DA RAVESSA" :
                vetor = vetor + [((realPath + "\\images\\luson-branco.png",), "")]
               

        return "", chat_history+vetor

   # clear.click(lambda:None, None, gpt, queue=False,)
    msg.submit(respond, [msg, gpt], [msg,gpt])

index = construct_index("docs")
demo.launch()