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Create app.py
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app.py
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import streamlit as st
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from PIL import Image
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from transformers import pipeline
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import google.generativeai as genai
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# Configura tu API de Gemini
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genai.configure(api_key='TU_API_KEY_GEMINI')
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gemini_model = genai.GenerativeModel('gemini-pro')
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# Carga el modelo de Hugging Face BLIP (captioning)
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captioner = pipeline("image-to-text", model="Salesforce/blip-image-captioning-base")
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# Interfaz Streamlit
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st.title("🗺️ Asistente Turístico Visual Inteligente")
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uploaded_file = st.file_uploader("Carga la imagen de un lugar turístico", type=['jpg', 'png', 'jpeg'])
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if uploaded_file is not None:
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image = Image.open(uploaded_file)
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st.image(image, caption='Imagen subida', use_column_width=True)
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if st.button("Generar información turística"):
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with st.spinner('🖼️ Identificando lugar...'):
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descripcion = captioner(image)[0]['generated_text']
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st.markdown(f"**Descripción visual generada:** _{descripcion}_")
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with st.spinner('📚 Generando información turística con Gemini...'):
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prompt = f"""Genera información turística detallada sobre el siguiente lugar: {descripcion}.
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Incluye breve historia, datos curiosos, y recomendaciones para visitarlo."""
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info = gemini_model.generate_content(prompt)
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st.markdown("### 📝 Información Turística:")
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st.write(info.text)
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