Create app.py

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM, AutoModelForSequenceClassification, pipeline
+import torch
+import numpy as np
+
+# === CARREGAR OS MODELOS GERADORES ===
+generator_1_name = "pierreguillou/gpt2-small-portuguese"
+generator_2_name = "pierreguillou/gpt2-small-portuguese"  # Usando o mesmo por simplicidade/teste
+
+tokenizer_1 = AutoTokenizer.from_pretrained(generator_1_name)
+model_1 = AutoModelForCausalLM.from_pretrained(generator_1_name)
+
+tokenizer_2 = AutoTokenizer.from_pretrained(generator_2_name)
+model_2 = AutoModelForCausalLM.from_pretrained(generator_2_name)
+
+# === CARREGAR MODELO ÁRBITRO (BERT) ===
+judge_model_name = "neuralmind/bert-base-portuguese-cased"
+judge_tokenizer = AutoTokenizer.from_pretrained(judge_model_name)
+judge_model = AutoModelForSequenceClassification.from_pretrained(judge_model_name, num_labels=2)
+
+# Classificador de similaridade (baseado em relevância para o prompt)
+def score_response(prompt, response):
+    inputs = judge_tokenizer(prompt, response, return_tensors="pt", truncation=True, padding=True)
+    with torch.no_grad():
+        outputs = judge_model(**inputs)
+    score = torch.softmax(outputs.logits, dim=1)[0][1].item()  # Probabilidade da classe "boa"
+    return score
+
+# Gerar resposta com modelo
+def generate_response(model, tokenizer, prompt):
+    input_ids = tokenizer.encode(prompt, return_tensors="pt")
+    output_ids = model.generate(input_ids, max_new_tokens=60, num_return_sequences=1, do_sample=True)
+    return tokenizer.decode(output_ids[0], skip_special_tokens=True)
+
+# Função principal
+def chatbot(prompt):
+    response_1 = generate_response(model_1, tokenizer_1, prompt)
+    response_2 = generate_response(model_2, tokenizer_2, prompt)
+
+    score_1 = score_response(prompt, response_1)
+    score_2 = score_response(prompt, response_2)
+
+    if score_1 > score_2:
+        final = response_1
+        chosen = "Resposta 1"
+    else:
+        final = response_2
+        chosen = "Resposta 2"
+
+    return (
+        prompt,
+        response_1,
+        response_2,
+        chosen,
+        final
+    )
+
+# === INTERFACE GRADIO ===
+iface = gr.Interface(
+    fn=chatbot,
+    inputs=gr.Textbox(label="Digite sua pergunta"),
+    outputs=[
+        gr.Textbox(label="Prompt"),
+        gr.Textbox(label="Resposta 1"),
+        gr.Textbox(label="Resposta 2"),
+        gr.Textbox(label="Resposta escolhida pelo árbitro"),
+        gr.Textbox(label="Resposta final exibida")
+    ],
+    title="Chatbot em Cascata (Português)",
+    description="Dois modelos geram respostas e um árbitro (BERT) escolhe a melhor."
+)
+
+if __name__ == "__main__":
+    iface.launch()