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from dotenv import load_dotenv | |
import streamlit as st | |
import os | |
import google.generativeai as genai | |
from cta_formulas import cta_formulas | |
from styles import apply_styles | |
from tone_formulas import tone_settings | |
# Cargar variables de entorno | |
load_dotenv() | |
# Configurar API de Google Gemini | |
genai.configure(api_key=os.getenv("GOOGLE_API_KEY")) | |
def get_gemini_response(product_service, target_audience, desired_action, formula_type, tone_type, temperature, postdata_theme=None, cta_count=5): | |
if not product_service or not target_audience or not desired_action: | |
return "Por favor, completa todos los campos requeridos." | |
formula = cta_formulas[formula_type] | |
tone = tone_settings[tone_type] | |
# Lista de fórmulas que ya incluyen P.D. en su estructura | |
formulas_with_pd = ["El Último Aviso (No tan Último)", "Cierra con Corazón", "Gancho Cachondo"] | |
# Preparar información de postdata | |
postdata_instruction = "" | |
if postdata_theme: | |
# Solo aplicar la instrucción de postdata si la fórmula tiene PD en su estructura | |
if formula_type in formulas_with_pd: | |
postdata_instruction = f""" | |
POSTDATA THEME: | |
Use the following theme for the P.S. section: {postdata_theme} | |
IMPORTANT: For formulas with P.S.2 sections, use a DIFFERENT theme or approach than the one used in P.S.1. | |
DO NOT repeat the same urgency factor, benefit, or discount information in both postdatas. | |
Examples: | |
- If P.S.1 mentions "only 2 days left", P.S.2 should NOT mention time limits again | |
- If P.S.1 talks about "limited spots", P.S.2 should focus on a different benefit or feature | |
Make sure each postdata adds unique value and persuasion elements. | |
""" | |
model = genai.GenerativeModel('gemini-2.0-flash') | |
full_prompt = f""" | |
You are an expert copywriter specialized in creating persuasive Calls to Action (CTAs). | |
Analyze (internally, don't include in output) the following information: | |
BUSINESS INFORMATION: | |
Product/Service: {product_service} | |
Target Audience: {target_audience} | |
Desired Action: {desired_action} | |
CTA Type: {formula_type} | |
Tone Style: {tone['style']} | |
Keywords to consider: {', '.join(tone['keywords'])} | |
{formula["description"]} | |
{postdata_instruction} | |
First, analyze (but don't show) these points: | |
1. TARGET AUDIENCE ANALYSIS: | |
- What motivates them to take action? | |
- What obstacles prevent them from acting? | |
- What immediate benefits are they seeking? | |
- What fears or doubts do they have? | |
- What language and tone resonates with them? | |
2. PERSUASION ELEMENTS: | |
- How to make the desired action more appealing? | |
- What emotional triggers will resonate most? | |
- How to create a sense of urgency naturally? | |
- What unique value proposition to emphasize? | |
- How to minimize perceived risk? | |
Based on your internal analysis, create {cta_count} different CTAs following EXACTLY the formula structure: | |
{formula["description"]} | |
CRITICAL INSTRUCTIONS: | |
- Follow the exact formula structure shown in the description above | |
- Create {cta_count} different CTAs using the same formula pattern | |
- ALL CTAs MUST BE IN SPANISH | |
- DO NOT add postdata (P.S.) to formulas that don't include it in their structure | |
- When a formula includes multiple postdatas (P.S.1 and P.S.2), make sure they focus on DIFFERENT themes and don't repeat the same urgency factors or benefits | |
EXAMPLES TO FOLLOW: | |
{formula["examples"]} | |
Output EXACTLY in this format based on {formula_type}: | |
1. Follow format from {formula["examples"]} | |
2. Follow format from {formula["examples"]} | |
3. Follow format from {formula["examples"]} | |
""" | |
response = model.generate_content([full_prompt], generation_config={"temperature": temperature}) | |
return response.parts[0].text if response and response.parts else "Error al generar contenido." | |
# Configurar la aplicación Streamlit | |
st.set_page_config(page_title="CTA Generator", page_icon="🎯", layout="wide") | |
# Leer y mostrar el manual en el sidebar | |
with open("manual.md", "r", encoding="utf-8") as file: | |
manual_content = file.read() | |
st.sidebar.markdown(manual_content) | |
# Aplicar estilos | |
st.markdown(apply_styles(), unsafe_allow_html=True) | |
# Título de la app | |
st.markdown("<h1>Generador de CTAs Persuasivos</h1>", unsafe_allow_html=True) | |
st.markdown("<h3>Crea llamados a la acción que motiven a tu audiencia a dar el siguiente paso.</h3>", unsafe_allow_html=True) | |
# Remove the duplicate manual expander from here | |
# Crear dos columnas | |
col1, col2 = st.columns([0.4, 0.6]) # 40% for left column, 60% for right column | |
# Columna izquierda para inputs | |
with col1: | |
target_audience = st.text_area( | |
"¿Cuál es tu público objetivo?", | |
placeholder="Ejemplo: Emprendedores que buscan automatizar su negocio..." | |
) | |
product_service = st.text_area( | |
"¿Cuál es tu producto o servicio?", | |
placeholder="Ejemplo: Curso de automatización con IA, Software de gestión..." | |
) | |
desired_action = st.text_area( | |
"¿Qué acción quieres que realicen?", | |
placeholder="Ejemplo: Registrarse al webinar, Descargar la guía gratuita..." | |
) | |
# Mover el botón aquí, antes del acordeón | |
generate_button = st.button("Generar CTAs") | |
with st.expander("Opciones avanzadas"): | |
formula_type = st.selectbox( | |
"Tipo de CTA:", | |
options=list(cta_formulas.keys()) | |
) | |
tone_type = st.selectbox( | |
"Tono del CTA:", | |
options=list(tone_settings.keys()), | |
) | |
# Nuevos campos para postdata | |
postdata_theme = st.text_input( | |
"Tema o enfoque para la postdata", | |
placeholder="Ejemplo: urgencia, beneficio, descuento" | |
) | |
cta_count = st.number_input( | |
"Número de llamados a la acción", | |
min_value=1, | |
max_value=5, | |
value=3 | |
) | |
temperature = st.slider( | |
"Nivel de creatividad:", | |
min_value=0.0, | |
max_value=2.0, | |
value=1.0, | |
step=0.1, | |
help="Valores más altos generan CTAs más creativos pero menos predecibles." | |
) | |
# Columna derecha para resultados | |
with col2: | |
if generate_button and (response := get_gemini_response( | |
product_service, | |
target_audience, | |
desired_action, | |
formula_type, | |
tone_type, | |
temperature, | |
postdata_theme, | |
cta_count | |
)): | |
st.markdown("### Tus Llamados a la Acción") | |
st.write(response) |