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import gradio as gr
from huggingface_hub import InferenceClient
import os
import time
HF_TOKEN = os.getenv("HF_TOKEN")
client = InferenceClient(
provider="sambanova",
api_key=HF_TOKEN,
)
history_log = []
show_history_flag = False
def chatbot_response(user_input):
messages = [{"role": "user", "content": entry["Pergunta"]} for entry in history_log[-2:]]
messages.append({"role": "user", "content": user_input})
start_time = time.time()
try:
completion = client.chat.completions.create(
model="meta-llama/Llama-3.3-70B-Instruct",
messages=messages,
max_tokens=500,
)
response = completion.choices[0].message['content']
except Exception as e:
response = f"Erro ao gerar resposta: {str(e)}"
end_time = time.time()
history_log.append({
"Pergunta": user_input,
"Resposta": response,
"Tempo de Resposta (s)": round(end_time - start_time, 2)
})
return response
with gr.Blocks(theme=gr.themes.Soft()) as demo:
gr.Markdown("# 🤖 Llama-70B Chatbot - SambaNova")
gr.Markdown("Modelo: meta-llama/Llama-3.3-70B-Instruct")
chatbot = gr.Chatbot(height=500)
msg = gr.Textbox(placeholder="Digite sua mensagem aqui...")
btn = gr.Button("Enviar", variant="primary")
def respond(message, chat_history):
response = chatbot_response(message)
chat_history.append((message, response))
return "", chat_history
btn.click(respond, [msg, chatbot], [msg, chatbot])
def toggle_history():
global show_history_flag
show_history_flag = not show_history_flag
return history_log if show_history_flag else {}
history_btn = gr.Button("Ver/Fechar Histórico", variant="secondary")
history_output = gr.JSON()
history_btn.click(toggle_history, inputs=[], outputs=history_output)
if __name__ == "__main__":
demo.launch()
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