Update app.py
Browse files
app.py
CHANGED
@@ -7,16 +7,16 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
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model_id = "somosnlp-hackathon-2025/leia_preference_model_social_norms"
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device = "cuda" if torch.cuda.is_available() else "cpu"
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# Obtener el token
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hf_token = os.environ.get("SSNZHY_TOKEN")
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# Cargar modelo y tokenizer con autenticaci贸n
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tokenizer = AutoTokenizer.from_pretrained(model_id, token=hf_token)
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model = AutoModelForCausalLM.from_pretrained(model_id, token=hf_token).to(device)
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# Funci贸n para responder
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def respond(message, history, system_message, max_tokens, temperature, top_p):
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prompt = system_message + "\n"
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for user, assistant in history:
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@@ -39,6 +39,7 @@ def respond(message, history, system_message, max_tokens, temperature, top_p):
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# Descripci贸n del proyecto
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descripcion = """
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@@ -100,20 +101,32 @@ En **LeIA GO**, somos conscientes de que los modelos de lenguaje pueden reflejar
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- Dataset: [https://huggingface.co/datasets/somosnlp-hackathon-2025/dataset-preferencias-v0]
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"""
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# Interfaz Gradio
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with gr.Blocks() as demo:
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with gr.Tab("Descripci贸n del Proyecto"):
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gr.Markdown(descripcion)
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with gr.Tab("Chatbot LeIA GO"):
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gr.ChatInterface(
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respond,
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additional_inputs=[
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gr.Textbox(
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gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
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gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
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gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
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],
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)
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if __name__ == "__main__":
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demo.launch(
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model_id = "somosnlp-hackathon-2025/leia_preference_model_social_norms"
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device = "cuda" if torch.cuda.is_available() else "cpu"
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# Obtener el token desde variable de entorno
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hf_token = os.environ.get("SSNZHY_TOKEN")
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if not hf_token:
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raise ValueError("El token de Hugging Face no est谩 definido. Configura la variable de entorno 'SSNZHY_TOKEN'.")
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# Cargar modelo y tokenizer con autenticaci贸n
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tokenizer = AutoTokenizer.from_pretrained(model_id, token=hf_token)
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model = AutoModelForCausalLM.from_pretrained(model_id, token=hf_token).to(device)
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# Funci贸n de respuesta del chatbot
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def respond(message, history, system_message, max_tokens, temperature, top_p):
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prompt = system_message + "\n"
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for user, assistant in history:
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# Descripci贸n del proyecto
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descripcion = """
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- Dataset: [https://huggingface.co/datasets/somosnlp-hackathon-2025/dataset-preferencias-v0]
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"""
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# Interfaz con Gradio
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with gr.Blocks() as demo:
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with gr.Tab("Descripci贸n del Proyecto"):
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gr.Markdown(descripcion)
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with gr.Tab("Chatbot LeIA GO"):
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gr.Markdown("### 馃憢 Bienvenida a LeIA GO\nChatea con una IA especializada en normas sociales y variantes del espa帽ol.")
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gr.ChatInterface(
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respond,
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additional_inputs=[
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gr.Textbox(
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value="Eres una asistente ling眉铆stica especializada en espa帽ol regional.",
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label="Mensaje del sistema"
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),
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gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
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gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
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gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
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],
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)
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# Lanzamiento
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if __name__ == "__main__":
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demo.launch(
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show_api=False,
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share=False,
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title="LeIA GO - Chat de Normas Sociales",
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theme=gr.themes.Base()
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)
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