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Create app.py
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app.py
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import gradio as gr
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from transformers import pipeline, Conversation
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# Modelo de Hugging Face para conversaci贸n
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model_name = "microsoft/DialoGPT-large"
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conversation_model = pipeline("conversational", model=model_name)
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# Historial de la conversaci贸n, se mantendr谩 dentro del contexto de la aplicaci贸n
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conversation = Conversation()
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# Funci贸n para procesar la entrada del usuario y generar la respuesta
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def chatbot_response(user_input):
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# Agregar la respuesta del usuario al historial de la conversaci贸n
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conversation.add_user_input(user_input)
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# Generar la respuesta del bot
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bot_response = conversation_model(user_input, conversation=conversation)["generated_text"]
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# Agregar la respuesta del bot al historial de la conversaci贸n
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conversation.add_system_output(bot_response)
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# Retornar la respuesta del bot para mostrarla en la interfaz
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return bot_response
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# Ejecuci贸n de la aplicaci贸n
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if __name__ == "__main__":
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# Interfaz de Gradio para la aplicaci贸n web
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iface = gr.Interface(
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fn=chatbot_response,
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inputs=gr.Textbox(lines=2, placeholder="Escribe tu mensaje aqu铆..."),
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outputs=gr.Textbox(lines=2, placeholder="Respuesta del bot..."),
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title="Entrevista de Programaci贸n - ChatBot",
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theme="compact",
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live=True
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)
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# Lanzar la interfaz de Gradio
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iface.launch()
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