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Update app.py
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app.py
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@@ -1,8 +1,17 @@
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from transformers import AutoTokenizer, AutoModelForCausalLM
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import torch
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from pptx import Presentation
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from pptx.util import Inches, Pt
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import os
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def generate_presentation_content(topic, model, tokenizer):
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prompt = f"Crea una presentación de PowerPoint sobre el tema: {topic}. Incluye 5 diapositivas con títulos y contenido."
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@@ -14,7 +23,7 @@ def generate_presentation_content(topic, model, tokenizer):
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slides = generated_text.split("\n\n")
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return slides[:5] # Limitar a 5 diapositivas
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def create_powerpoint(slides
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prs = Presentation()
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for slide_content in slides:
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@@ -30,24 +39,40 @@ def create_powerpoint(slides, output_file):
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title_shape.text = title
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content_shape.text = content
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def main():
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topic = input("Por favor, ingrese el tema de la presentación: ")
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model_name = "meta-llama/Llama-2-7b-chat-hf"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16, device_map="auto")
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print("Generando contenido de la presentación...")
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slides = generate_presentation_content(topic, model, tokenizer)
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print(f"Creando archivo PowerPoint: {output_file}")
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create_powerpoint(slides, output_file)
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if __name__ == "__main__":
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main()
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import streamlit as st
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from transformers import AutoTokenizer, AutoModelForCausalLM
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import torch
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from pptx import Presentation
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from pptx.util import Inches, Pt
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import os
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import io
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@st.cache_resource
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def load_model():
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model_name = "meta-llama/Llama-2-7b-chat-hf"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16, device_map="auto")
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return tokenizer, model
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def generate_presentation_content(topic, model, tokenizer):
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prompt = f"Crea una presentación de PowerPoint sobre el tema: {topic}. Incluye 5 diapositivas con títulos y contenido."
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slides = generated_text.split("\n\n")
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return slides[:5] # Limitar a 5 diapositivas
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def create_powerpoint(slides):
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prs = Presentation()
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for slide_content in slides:
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title_shape.text = title
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content_shape.text = content
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# Guardar la presentación en un buffer de bytes
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pptx_buffer = io.BytesIO()
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prs.save(pptx_buffer)
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pptx_buffer.seek(0)
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return pptx_buffer
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def main():
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st.title("Generador de presentaciones PowerPoint con IA")
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topic = st.text_input("Por favor, ingrese el tema de la presentación:")
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if st.button("Generar Presentación"):
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if topic:
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with st.spinner("Cargando modelo..."):
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tokenizer, model = load_model()
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with st.spinner("Generando contenido de la presentación..."):
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slides = generate_presentation_content(topic, model, tokenizer)
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with st.spinner("Creando archivo PowerPoint..."):
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pptx_buffer = create_powerpoint(slides)
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st.success("Presentación generada con éxito!")
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# Ofrecer la descarga del archivo
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st.download_button(
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label="Descargar Presentación",
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data=pptx_buffer,
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file_name=f"{topic.replace(' ', '_')}_presentacion.pptx",
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mime="application/vnd.openxmlformats-officedocument.presentationml.presentation"
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)
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else:
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st.warning("Por favor, ingrese un tema para la presentación.")
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if __name__ == "__main__":
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main()
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