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Update app.py
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app.py
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@@ -8,20 +8,21 @@ load_dotenv()
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genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
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# Funci贸n para obtener respuesta del modelo Gemini
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def get_gemini_response(target_audience, product, text_type, length,
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model = genai.GenerativeModel(model_choice)
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# Crear
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mention_instruction = ""
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if product_mention == "
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mention_instruction = f"
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elif product_mention == "
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mention_instruction = f"Ensure that subtle and realistic references to the product '{product}' are included without explicitly mentioning it."
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elif product_mention == "
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mention_instruction = f"Refer to the product '{product}' through a metaphor
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full_prompt = f"""
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"""
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response = model.generate_content([full_prompt])
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@@ -69,16 +70,18 @@ with col1:
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# Entradas del usuario
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target_audience = st.text_input("P煤blico objetivo:", placeholder="Especifica tu p煤blico aqu铆...")
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product = st.text_input("Producto:", placeholder="Especifica el producto aqu铆...")
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text_type = st.selectbox("Tipo de texto:", ["Historia", "Shayari", "Sher", "Poema", "Cita"])
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length = st.selectbox("Longitud del texto:", ["Corto", "Largo"])
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# Nueva opci贸n para c贸mo se debe mencionar el producto
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product_mention = st.selectbox("Menci贸n del producto:", ["Direct", "Subtle", "Metaphor"])
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mood = st.selectbox("Tono del Texto:", ["Emocional", "Triste", "Feliz", "Horror", "Comedia", "Rom谩ntico"])
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#
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# Bot贸n para generar contenido
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submit = st.button("Escribir mi historia")
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@@ -87,7 +90,7 @@ with col1:
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if submit:
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if target_audience and product: # Verificar que se haya proporcionado el p煤blico objetivo y el producto
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try:
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response = get_gemini_response(target_audience, product, text_type, length,
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col2.subheader("Contenido generado:")
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col2.write(response)
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except ValueError as e:
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genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
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# Funci贸n para obtener respuesta del modelo Gemini
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def get_gemini_response(target_audience, product, product_mention, text_type, length, mood, model_choice):
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model = genai.GenerativeModel(model_choice)
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# Crear la instrucci贸n de menci贸n basada en la opci贸n seleccionada
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mention_instruction = ""
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if product_mention == "Directa":
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mention_instruction = f"Mention the product '{product}' directly in the text."
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elif product_mention == "Indirecta":
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mention_instruction = f"Ensure that subtle and realistic references to the product '{product}' are included without explicitly mentioning it."
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elif product_mention == "Metaf贸rica":
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mention_instruction = f"Refer to the product '{product}' through a metaphor without explicitly mentioning it."
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# Crear el prompt completo basado en los campos del frontend
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full_prompt = f"""
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You are a creative writer skilled in the art of persuasion. Write a {length} {text_type} in Spanish. The tone of the {text_type} should be {mood} and carefully crafted to emotionally resonate with a {target_audience}. {mention_instruction} Use persuasive techniques to guide the reader towards an intuitive understanding of the product's benefits, focusing on creating a strong emotional connection with the audience.
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"""
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response = model.generate_content([full_prompt])
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# Entradas del usuario
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target_audience = st.text_input("P煤blico objetivo:", placeholder="Especifica tu p煤blico aqu铆...")
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product = st.text_input("Producto:", placeholder="Especifica el producto aqu铆...")
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# Agrupar todas las opciones en una acorde贸n
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with st.expander("Personaliza tu texto"):
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# Variable para c贸mo se debe mencionar el producto
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product_mention = st.selectbox("Menci贸n del producto:", ["Directa", "Indirecta", "Metaf贸rica"])
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text_type = st.selectbox("Tipo de texto:", ["Historia", "Shayari", "Sher", "Poema", "Cita"])
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length = st.selectbox("Longitud del texto:", ["Corto", "Largo"])
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mood = st.selectbox("Tono del Texto:", ["Emocional", "Triste", "Feliz", "Horror", "Comedia", "Rom谩ntico"])
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# Opci贸n para seleccionar el modelo
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model_choice = st.selectbox("Selecciona el modelo:", ["gemini-1.5-flash", "gemini-1.5-pro"], index=0)
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# Bot贸n para generar contenido
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submit = st.button("Escribir mi historia")
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if submit:
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if target_audience and product: # Verificar que se haya proporcionado el p煤blico objetivo y el producto
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try:
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response = get_gemini_response(target_audience, product, product_mention, text_type, length, mood, model_choice)
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col2.subheader("Contenido generado:")
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col2.write(response)
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except ValueError as e:
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