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import gradio as gr
from huggingface_hub import InferenceClient
import os
import time
import re
HF_TOKEN = os.getenv("HF_TOKEN")
client = InferenceClient(
provider="sambanova",
api_key=HF_TOKEN,
)
MODELS = {
"LLaMA 70B": "meta-llama/Llama-3.3-70B-Instruct",
"Qwen 32B": "Qwen/QwQ-32B",
"DeepSeek R1": "deepseek-ai/DeepSeek-R1",
}
history_log = []
show_history_flag = False
def clean_response(text):
text = re.sub(r"</?think>", "", text)
text = re.sub(r"\\boxed\{.*?\}", "", text)
return text.strip()
def chatbot_response(user_input, model_name):
model_id = MODELS[model_name]
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=model_id,
messages=messages,
max_tokens = 8192 if any(m in model_id for m in ["Qwen", "DeepSeek"]) else 800
)
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({
"Modelo": model_name,
"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:
with gr.Row():
gr.Column(scale=0.5, min_width=40)
with gr.Column(scale=4):
with gr.Row():
with gr.Column(scale=1):
gr.Markdown("## ⚙️ Configurações")
model_selector = gr.Dropdown(
choices=list(MODELS.keys()),
label="Escolha o Modelo",
value="LLaMA 70B"
)
with gr.Column(scale=4):
gr.Markdown("# 🤖 Chatbot - API SambaNova")
chatbot = gr.Chatbot(height=500)
msg = gr.Textbox(placeholder="Digite sua mensagem aqui...", label="")
with gr.Row():
btn = gr.Button("Enviar", variant="primary")
history_btn = gr.Button("Histórico", variant="secondary")
with gr.Row():
with gr.Column(scale=4):
history_output = gr.JSON(visible=False)
gr.Column(scale=0.5, min_width=40)
def respond(message, chat_history, model_name):
response = chatbot_response(message, model_name)
response = clean_response(response)
chat_history.append((message, response))
return "", chat_history
btn.click(respond, [msg, chatbot, model_selector], [msg, chatbot])
msg.submit(respond, [msg, chatbot, model_selector], [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.click(toggle_history, inputs=[], outputs=history_output)
if __name__ == "__main__":
demo.launch()
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