Upload 23 files

app.py

@@ -1,418 +1,408 @@
-from dotenv import load_dotenv
-import streamlit as st
-import os
-import google.generativeai as genai
-import datetime                    
-from streamlit import session_state as state
-
-# Cargar las variables de entorno
-load_dotenv()
-
-# Configurar la API de Google
-genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
-
-# Función para inicializar el modelo
-def initialize_model(temperature=1.0):
-    return genai.GenerativeModel(
-        model_name="gemini-2.0-flash",
-        generation_config={"temperature": temperature}
-    )
-
-# Initialize session state variables at the app level
-session_state_vars = {
-    'headline_content': "", 
-    'problem_content': "", 
-    'solution_content': "",
-    'avatar_details': {}, 
-    'product_details': {},
-    'generated_sections': {},
-    'metadata': {},
-    'avatar_analysis': {}  # Add this new session state variable
-}
-
-for var, default in session_state_vars.items():
-    if var not in st.session_state:
-        st.session_state[var] = default
-
-# Función para generar contenido y procesar el JSON
-def generate_content(prompt, temperature=1.0):
-    model = initialize_model(temperature)
-    
-    response = model.generate_content(prompt)
-    result = response.text
-    
-    # Try to extract JSON metadata if present and remove it from the displayed text
-    try:
-        import json
-        import re
-        
-        # Look for JSON data in the response (both with and without code blocks)
-        json_pattern = r'```json\s*(.*?)\s*```|(\{[\s\S]*"character"[\s\S]*\})'
-        json_match = re.search(json_pattern, result, re.DOTALL)
-        
-        if json_match:
-            # Get the matched JSON string (either from code block or raw JSON)
-            json_str = json_match.group(1) if json_match.group(1) else json_match.group(2)
-            
-            # Parse the JSON data
-            json_data = json.loads(json_str.strip())
-            
-            # Store the JSON data in session state
-            st.session_state.metadata = json_data
-            
-            # Update avatar details and other metadata elements
-            metadata_fields = ['character', 'pain_points', 'emotional_triggers', 'obstacles', 'failed_solutions']
-            for field in metadata_fields:
-                if field in json_data:
-                    if field == 'character' and 'avatar_details' in st.session_state:
-                        st.session_state.avatar_details.update(json_data[field])
-                    else:
-                        st.session_state[field] = json_data[field]
-            
-            # Remove the JSON block from the displayed text
-            result = re.sub(json_pattern, '', result, flags=re.DOTALL).strip()
-    except Exception as e:
-        # Log the error but don't disrupt the user experience
-        print(f"Error processing JSON metadata: {str(e)}")
-    
-    return result
-
-# Modify the display function to preserve content
-def display_generated_content(column, content, key_prefix):
-    """Display generated content in the specified column with download button."""
-    if content:
-        column.markdown("### Contenido generado:")
-        column.markdown(content)
-        
-        # Add download button
-        download_button_key = f"{key_prefix}_download_button"
-        timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
-        section_name = key_prefix.replace("_", "-")
-        filename = f"sales_page_{section_name}_{timestamp}.txt"
-        
-        column.download_button(
-            label="Descargar contenido",
-            data=content,
-            file_name=filename,
-            mime="text/plain",
-            key=f"{key_prefix}_actual_download"
-        )
-
-# Add this function to validate inputs
-def validate_inputs(audience, product):
-    """Validate that required inputs are provided."""
-    return audience.strip() != "" and product.strip() != ""
-
-# Make sure to define your UI elements before using them
-# Add this before the submit button
-st.set_page_config(layout="wide")  # Set the page layout to wide
-st.title("Generador de Páginas de Ventas")
-
-# Load custom CSS from the styles folder
-def load_css(css_file):
-    with open(css_file, 'r') as f:
-        css = f.read()
-    st.markdown(f'<style>{css}</style>', unsafe_allow_html=True)
-
-# Load the CSS file
-css_path = os.path.join(os.path.dirname(__file__), "styles", "styles.css")
-load_css(css_path)
-
-# Create two columns for layout with adjusted widths (40% left, 60% right)
-col1, col2 = st.columns([4, 6])
-
-with col1:
-    st.subheader("Configuración")
-    
-    # Input fields
-    sales_page_audience = st.text_input("Público objetivo:", 
-                                        help="Describe a quién va dirigida tu página de ventas")
-    
-    sales_page_product = st.text_input("Producto/Servicio:", 
-                                       help="Describe el producto o servicio que estás vendiendo")
-    
-    sales_page_offer = st.text_area("Oferta específica (opcional):", 
-                                    help="Detalles específicos de tu oferta, como precio, bonos, etc.")
-    
-    # Add to the section selection list
-    sales_page_section = st.selectbox(
-        "Sección a generar:",
-        [
-            "Above the Fold (Encabezado)",
-            "Problem (Problema)",
-            "Solution & Benefits (Solución y Beneficios)",
-            "Authority (Autoridad)",
-            "Offer & Bonus (Oferta y Bonus)",
-            "Offer Summary (Resumen de Oferta)",  # New section
-            "Social Proof (Prueba Social)",
-            "Guarantees (Garantías)",
-            "Call to Action (Llamada a la Acción)",
-            "P.S. (Post-Data)",
-            "Final Call to Action (Llamada Final)"
-        ]
-    )
-    
-    sales_page_temperature = st.slider(
-        "Creatividad:",
-        min_value=0.0,
-        max_value=1.0,
-        value=0.7,
-        step=0.1,
-        help="Valores más altos = más creatividad, valores más bajos = más consistencia"
-    )
-    
-    # Now create the submit button
-    submit_sales_page = st.button("Generar Sección", key="generate_sales_page")
-
-# Add these section generator functions before the section_functions dictionary
-
-def load_prompt_template(filename):
-    """Load a prompt template from the prompts directory."""
-    prompt_path = os.path.join(os.path.dirname(__file__), "prompts", filename)
-    with open(prompt_path, "r", encoding="utf-8") as file:
-        return file.read()
-
-def generate_above_the_fold(audience, product, temperature=0.7, offer=None):
-    """Generate the Above the Fold (headline) section."""
-    prompt_template = load_prompt_template("above_the_fold.txt")
-    
-    # Create the prompt with the audience and product information
-    prompt = f"{prompt_template}\n\nAUDIENCE: {audience}\nPRODUCT/SERVICE: {product}"
-    if offer:
-        prompt += f"\nOFFER: {offer}"
-    
-    # Generate the content
-    return generate_content(prompt, temperature)
-
-def generate_problem_section(audience, product, temperature=0.7, offer=None):
-    """Generate the Problem section."""
-    prompt_template = load_prompt_template("problem.txt")
-    
-    # Create context dictionary with any existing session state data
-    context = {}
-    if 'headline_content' in st.session_state:
-        context['headline_content'] = st.session_state.headline_content
-    if 'avatar_details' in st.session_state:
-        context['avatar_details'] = st.session_state.avatar_details
-    if 'product_details' in st.session_state:
-        context['product_details'] = st.session_state.product_details
-    
-    # Create the prompt with the audience and product information
-    prompt = f"{prompt_template}\n\nAUDIENCE: {audience}\nPRODUCT/SERVICE: {product}\nCONTEXT: {context}"
-    if offer:
-        prompt += f"\nOFFER: {offer}"
-    
-    # Generate the content
-    return generate_content(prompt, temperature)
-
-def generate_solution_section(audience, product, temperature=0.7, offer=None):
-    """Generate the Solution & Benefits section."""
-    prompt_template = load_prompt_template("solution_benefits.txt")
-    
-    # Import the avatar analysis function
-    from avatar_analysis import analyze_avatar
-    
-    # Generate avatar analysis if not already in session state
-    if not st.session_state.avatar_analysis:
-        avatar_analysis = analyze_avatar(
-            target_audience=audience,
-            product_service=product,
-            uploaded_content=None,
-            skills=None
-        )
-        st.session_state.avatar_analysis = avatar_analysis
-    
-    # Create context dictionary with any existing session state data
-    context = {}
-    if 'headline_content' in st.session_state:
-        context['headline_content'] = st.session_state.headline_content
-    if 'problem_content' in st.session_state:
-        context['problem_content'] = st.session_state.problem_content
-    if 'avatar_details' in st.session_state:
-        context['avatar_details'] = st.session_state.avatar_details
-    if 'avatar_analysis' in st.session_state:
-        context['avatar_analysis'] = st.session_state.avatar_analysis
-    
-    # Create the prompt with the audience and product information
-    prompt = f"{prompt_template}\n\nAUDIENCE: {audience}\nPRODUCT/SERVICE: {product}\nCONTEXT: {context}"
-    if offer:
-        prompt += f"\nOFFER: {offer}"
-    
-    # Generate the content
-    return generate_content(prompt, temperature)
-
-def generate_authority_section(audience, product, temperature=0.7, offer=None):
-    """Generate the Authority section."""
-    prompt_template = load_prompt_template("authority.txt")
-    
-    # Create the prompt with the audience and product information
-    prompt = f"{prompt_template}\n\nAUDIENCE: {audience}\nPRODUCT/SERVICE: {product}"
-    if offer:
-        prompt += f"\nOFFER: {offer}"
-    
-    # Generate the content
-    return generate_content(prompt, temperature)
-
-def generate_offer_section(audience, product, temperature=0.7, offer=None):
-    """Generate the Offer & Bonus section."""
-    prompt_template = load_prompt_template("offer_bonus.txt")
-    
-    # Create the prompt with the audience and product information
-    prompt = f"{prompt_template}\n\nAUDIENCE: {audience}\nPRODUCT/SERVICE: {product}"
-    if offer:
-        prompt += f"\nOFFER DETAILS: {offer}"
-    else:
-        prompt += "\nOFFER DETAILS: Create a compelling offer based on the product/service and audience."
-    
-    # Generate the content
-    return generate_content(prompt, temperature)
-
-def generate_social_proof_section(audience, product, temperature=0.7, offer=None):
-    """Generate the Social Proof section."""
-    prompt_template = load_prompt_template("social_proof.txt")
-    
-    # Create the prompt with the audience and product information
-    prompt = f"{prompt_template}\n\nAUDIENCE: {audience}\nPRODUCT/SERVICE: {product}"
-    if offer:
-        prompt += f"\nOFFER: {offer}"
-    
-    # Generate the content
-    return generate_content(prompt, temperature)
-
-def generate_guarantees_section(audience, product, temperature=0.7, offer=None):
-    """Generate the Guarantees section."""
-    prompt_template = load_prompt_template("guarantees.txt")
-    
-    # Create the prompt with the audience and product information
-    prompt = f"{prompt_template}\n\nAUDIENCE: {audience}\nPRODUCT/SERVICE: {product}"
-    if offer:
-        prompt += f"\nOFFER: {offer}"
-    
-    # Generate the content
-    return generate_content(prompt, temperature)
-
-def generate_cta_section(audience, product, temperature=0.7, offer=None):
-    """Generate the Call to Action section."""
-    prompt_template = load_prompt_template("cta.txt")
-    
-    # Create the prompt with the audience and product information
-    prompt = f"{prompt_template}\n\nAUDIENCE: {audience}\nPRODUCT/SERVICE: {product}"
-    if offer:
-        prompt += f"\nOFFER: {offer}"
-    
-    # Generate the content
-    return generate_content(prompt, temperature)
-
-def generate_ps_section(audience, product, temperature=0.7, offer=None):
-    """Generate the P.S. (Post-Data) section."""
-    prompt_template = load_prompt_template("ps.txt")
-    
-    # Create the prompt with the audience and product information
-    prompt = f"{prompt_template}\n\nAUDIENCE: {audience}\nPRODUCT/SERVICE: {product}"
-    if offer:
-        prompt += f"\nOFFER: {offer}"
-    
-    # Generate the content
-    return generate_content(prompt, temperature)
-
-def generate_final_cta_section(audience, product, temperature=0.7, offer=None):
-    """Generate the Final Call to Action section."""
-    prompt_template = load_prompt_template("final_cta.txt")
-    
-    # Create the prompt with the audience and product information
-    prompt = f"{prompt_template}\n\nAUDIENCE: {audience}\nPRODUCT/SERVICE: {product}"
-    if offer:
-        prompt += f"\nOFFER: {offer}"
-    
-    # Generate the content
-    return generate_content(prompt, temperature)
-
-# Define section functions mapping once
-section_functions = {
-    "Above the Fold (Encabezado)": generate_above_the_fold,
-    "Problem (Problema)": generate_problem_section,
-    "Solution & Benefits (Solución y Beneficios)": generate_solution_section,
-    "Authority (Autoridad)": generate_authority_section,
-    "Offer & Bonus (Oferta y Bonus)": generate_offer_section,
-    "Social Proof (Prueba Social)": generate_social_proof_section,
-    "Guarantees (Garantías)": generate_guarantees_section,
-    "Call to Action (Llamada a la Acción)": generate_cta_section,
-    "P.S. (Post-Data)": generate_ps_section,
-    "Final Call to Action (Llamada Final)": generate_final_cta_section
-        }
-        
-# Add new function for offer summary generation
-def generate_offer_summary_section(audience, product, temperature=0.7, offer=None):
-    """Generate the Offer Summary section."""
-    prompt_template = load_prompt_template("offer_summary.txt")
-    
-    # Create context dictionary with offer details if available
-    context = {}
-    if 'generated_sections' in st.session_state:
-        if 'offer_&_bonus' in st.session_state.generated_sections:
-            context['offer_content'] = st.session_state.generated_sections['offer_&_bonus']
-    
-    # Create the prompt with all available information
-    prompt = f"{prompt_template}\n\nAUDIENCE: {audience}\nPRODUCT/SERVICE: {product}"
-    if offer:
-        prompt += f"\nOFFER DETAILS: {offer}"
-    if context:
-        prompt += f"\nCONTEXT: {context}"
-    
-    return generate_content(prompt, temperature)
-
-# Update section functions mapping
-section_functions = {
-    "Above the Fold (Encabezado)": generate_above_the_fold,
-    "Problem (Problema)": generate_problem_section,
-    "Solution & Benefits (Solución y Beneficios)": generate_solution_section,
-    "Authority (Autoridad)": generate_authority_section,
-    "Offer & Bonus (Oferta y Bonus)": generate_offer_section,
-    "Offer Summary (Resumen de Oferta)": generate_offer_summary_section,  # Add new section
-    "Social Proof (Prueba Social)": generate_social_proof_section,
-    "Guarantees (Garantías)": generate_guarantees_section,
-    "Call to Action (Llamada a la Acción)": generate_cta_section,
-    "P.S. (Post-Data)": generate_ps_section,
-    "Final Call to Action (Llamada Final)": generate_final_cta_section
-}
-
-# Then use it in the conditional
-if submit_sales_page:
-    # Validar entradas
-    if validate_inputs(sales_page_audience, sales_page_product):
-        try:
-            # Store current inputs in session state
-            st.session_state.last_audience = sales_page_audience
-            st.session_state.last_product = sales_page_product
-            st.session_state.last_offer = sales_page_offer
-            
-            # Crear un contenedor para el spinner en la columna 2
-            with col2:
-                with st.spinner("Generando sección de página de ventas...", show_time=True):
-                    # Obtener la función correspondiente
-                    generator_func = section_functions[sales_page_section]
-                    
-                    # Generar el contenido
-                    generated_content = generator_func(
-                        audience=sales_page_audience,
-                        product=sales_page_product,
-                        temperature=sales_page_temperature,
-                        offer=sales_page_offer if sales_page_offer.strip() else None
-                    )
-                    
-                    # Store the generated content in session state with a key based on the section
-                    section_key = sales_page_section.replace(" ", "_").lower()
-                    st.session_state.generated_sections[section_key] = generated_content
-                
-            # Mostrar el contenido generado fuera del bloque del spinner
-            display_generated_content(col2, generated_content, "sales_page_section")
-                
-        except Exception as e:
-            st.error(f"Error al generar la sección: {str(e)}")
-    else:
-        st.warning("Por favor, completa los campos de público objetivo y producto/servicio.")
-else:
-    # Display previously generated content if available for the selected section
-    section_key = sales_page_section.replace(" ", "_").lower()
-    if section_key in st.session_state.generated_sections and st.session_state.generated_sections[section_key]:
+from dotenv import load_dotenv
+import streamlit as st
+import os
+import google.generativeai as genai
+import datetime                    
+from streamlit import session_state as state
+
+# Cargar las variables de entorno
+load_dotenv()
+
+# Configurar la API de Google
+genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
+
+# Función para inicializar el modelo
+def initialize_model(temperature=1.0):
+    return genai.GenerativeModel(
+        model_name="gemini-2.0-flash",
+        generation_config={"temperature": temperature}
+    )
+
+# Initialize session state variables at the app level
+session_state_vars = {
+    'headline_content': "", 
+    'problem_content': "", 
+    'solution_content': "",
+    'avatar_details': {}, 
+    'product_details': {},
+    'generated_sections': {},
+    'metadata': {},
+    'avatar_analysis': {}  # Add this new session state variable
+}
+
+for var, default in session_state_vars.items():
+    if var not in st.session_state:
+        st.session_state[var] = default
+
+# Función para generar contenido y procesar el JSON
+def generate_content(prompt, temperature=1.0):
+    model = initialize_model(temperature)
+    
+    response = model.generate_content(prompt)
+    result = response.text
+    
+    # Try to extract JSON metadata if present and remove it from the displayed text
+    try:
+        import json
+        import re
+        
+        # Look for JSON data in the response (both with and without code blocks)
+        json_pattern = r'```json\s*(.*?)\s*```|(\{[\s\S]*"character"[\s\S]*\})'
+        json_match = re.search(json_pattern, result, re.DOTALL)
+        
+        if json_match:
+            # Get the matched JSON string (either from code block or raw JSON)
+            json_str = json_match.group(1) if json_match.group(1) else json_match.group(2)
+            
+            # Parse the JSON data
+            json_data = json.loads(json_str.strip())
+            
+            # Store the JSON data in session state
+            st.session_state.metadata = json_data
+            
+            # Update avatar details and other metadata elements
+            metadata_fields = ['character', 'pain_points', 'emotional_triggers', 'obstacles', 'failed_solutions']
+            for field in metadata_fields:
+                if field in json_data:
+                    if field == 'character' and 'avatar_details' in st.session_state:
+                        st.session_state.avatar_details.update(json_data[field])
+                    else:
+                        st.session_state[field] = json_data[field]
+            
+            # Remove the JSON block from the displayed text
+            result = re.sub(json_pattern, '', result, flags=re.DOTALL).strip()
+    except Exception as e:
+        # Log the error but don't disrupt the user experience
+        print(f"Error processing JSON metadata: {str(e)}")
+    
+    return result
+
+# Modify the display function to preserve content
+def display_generated_content(column, content, key_prefix):
+    """Display generated content in the specified column with download button."""
+    if content:
+        column.markdown("### Contenido generado:")
+        column.markdown(content)
+        
+        # Add download button
+        download_button_key = f"{key_prefix}_download_button"
+        timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
+        section_name = key_prefix.replace("_", "-")
+        filename = f"sales_page_{section_name}_{timestamp}.txt"
+        
+        column.download_button(
+            label="Descargar contenido",
+            data=content,
+            file_name=filename,
+            mime="text/plain",
+            key=f"{key_prefix}_actual_download"
+        )
+
+# Add this function to validate inputs
+def validate_inputs(audience, product):
+    """Validate that required inputs are provided."""
+    return audience.strip() != "" and product.strip() != ""
+
+# Make sure to define your UI elements before using them
+# Add this before the submit button
+st.set_page_config(layout="wide")  # Set the page layout to wide
+st.title("Generador de Páginas de Ventas")
+
+# Load custom CSS from the styles folder
+def load_css(css_file):
+    with open(css_file, 'r') as f:
+        css = f.read()
+    st.markdown(f'<style>{css}</style>', unsafe_allow_html=True)
+
+# Load the CSS file
+css_path = os.path.join(os.path.dirname(__file__), "styles", "styles.css")
+load_css(css_path)
+
+# Create two columns for layout with adjusted widths (40% left, 60% right)
+col1, col2 = st.columns([4, 6])
+
+with col1:
+    st.subheader("Configuración")
+    
+    # Input fields
+    sales_page_audience = st.text_input("Público objetivo:", 
+                                        help="Describe a quién va dirigida tu página de ventas")
+    
+    sales_page_product = st.text_input("Producto/Servicio:", 
+                                       help="Describe el producto o servicio que estás vendiendo")
+    
+    sales_page_offer = st.text_area("Oferta específica (opcional):", 
+                                    help="Detalles específicos de tu oferta, como precio, bonos, etc.")
+    
+    # Add to the section selection list
+    sales_page_section = st.selectbox(
+        "Sección a generar:",
+        [
+            "Above the Fold (Encabezado)",
+            "Problem (Problema)",
+            "Solution & Benefits (Solución y Beneficios)",
+            "Authority (Autoridad)",
+            "Offer & Bonus (Oferta y Bonus)",
+            "Social Proof (Prueba Social)",
+            "Guarantees (Garantías)",
+            "FAQ (Preguntas Frecuentes)",
+            "Closing (Cierre)",
+            "P.S. (Post-Data)"
+        ]
+    )
+    
+    sales_page_temperature = st.slider(
+        "Creatividad:",
+        min_value=0.0,
+        max_value=1.0,
+        value=0.7,
+        step=0.1,
+        help="Valores más altos = más creatividad, valores más bajos = más consistencia"
+    )
+    
+    # Now create the submit button
+    submit_sales_page = st.button("Generar Sección", key="generate_sales_page")
+
+# Add these section generator functions before the section_functions dictionary
+
+def load_prompt_template(filename):
+    """Load a prompt template from the prompts directory."""
+    prompt_path = os.path.join(os.path.dirname(__file__), "prompts", filename)
+    with open(prompt_path, "r", encoding="utf-8") as file:
+        return file.read()
+
+def generate_above_the_fold(audience, product, temperature=0.7, offer=None):
+    """Generate the Above the Fold (headline) section."""
+    prompt_template = load_prompt_template("above_the_fold.txt")
+    
+    # Create the prompt with the audience and product information
+    prompt = f"{prompt_template}\n\nAUDIENCE: {audience}\nPRODUCT/SERVICE: {product}"
+    if offer:
+        prompt += f"\nOFFER: {offer}"
+    
+    # Generate the content
+    return generate_content(prompt, temperature)
+
+def generate_problem_section(audience, product, temperature=0.7, offer=None):
+    """Generate the Problem section."""
+    prompt_template = load_prompt_template("problem.txt")
+    
+    # Create context dictionary with any existing session state data
+    context = {}
+    if 'headline_content' in st.session_state:
+        context['headline_content'] = st.session_state.headline_content
+    if 'avatar_details' in st.session_state:
+        context['avatar_details'] = st.session_state.avatar_details
+    if 'product_details' in st.session_state:
+        context['product_details'] = st.session_state.product_details
+    
+    # Create the prompt with the audience and product information
+    prompt = f"{prompt_template}\n\nAUDIENCE: {audience}\nPRODUCT/SERVICE: {product}\nCONTEXT: {context}"
+    if offer:
+        prompt += f"\nOFFER: {offer}"
+    
+    # Generate the content
+    return generate_content(prompt, temperature)
+
+def generate_solution_section(audience, product, temperature=0.7, offer=None):
+    """Generate the Solution & Benefits section."""
+    prompt_template = load_prompt_template("solution_benefits.txt")
+    
+    # Import the avatar analysis function
+    from avatar_analysis import analyze_avatar
+    
+    # Generate avatar analysis if not already in session state
+    if not st.session_state.avatar_analysis:
+        avatar_analysis = analyze_avatar(
+            target_audience=audience,
+            product_service=product,
+            uploaded_content=None,
+            skills=None
+        )
+        st.session_state.avatar_analysis = avatar_analysis
+    
+    # Create context dictionary with any existing session state data
+    context = {}
+    if 'headline_content' in st.session_state:
+        context['headline_content'] = st.session_state.headline_content
+    if 'problem_content' in st.session_state:
+        context['problem_content'] = st.session_state.problem_content
+    if 'avatar_details' in st.session_state:
+        context['avatar_details'] = st.session_state.avatar_details
+    if 'avatar_analysis' in st.session_state:
+        context['avatar_analysis'] = st.session_state.avatar_analysis
+    
+    # Create the prompt with the audience and product information
+    prompt = f"{prompt_template}\n\nAUDIENCE: {audience}\nPRODUCT/SERVICE: {product}\nCONTEXT: {context}"
+    if offer:
+        prompt += f"\nOFFER: {offer}"
+    
+    # Generate the content
+    return generate_content(prompt, temperature)
+
+def generate_authority_section(audience, product, temperature=0.7, offer=None):
+    """Generate the Authority section."""
+    prompt_template = load_prompt_template("authority.txt")
+    
+    # Create the prompt with the audience and product information
+    prompt = f"{prompt_template}\n\nAUDIENCE: {audience}\nPRODUCT/SERVICE: {product}"
+    if offer:
+        prompt += f"\nOFFER: {offer}"
+    
+    # Generate the content
+    return generate_content(prompt, temperature)
+
+def generate_offer_section(audience, product, temperature=0.7, offer=None):
+    """Generate the Offer & Bonus section."""
+    prompt_template = load_prompt_template("offer_bonus.txt")
+    
+    # Create the prompt with the audience and product information
+    prompt = f"{prompt_template}\n\nAUDIENCE: {audience}\nPRODUCT/SERVICE: {product}"
+    if offer:
+        prompt += f"\nOFFER DETAILS: {offer}"
+    else:
+        prompt += "\nOFFER DETAILS: Create a compelling offer based on the product/service and audience."
+    
+    # Generate the content
+    return generate_content(prompt, temperature)
+
+def generate_social_proof_section(audience, product, temperature=0.7, offer=None):
+    """Generate the Social Proof section."""
+    prompt_template = load_prompt_template("social_proof.txt")
+    
+    # Create the prompt with the audience and product information
+    prompt = f"{prompt_template}\n\nAUDIENCE: {audience}\nPRODUCT/SERVICE: {product}"
+    if offer:
+        prompt += f"\nOFFER: {offer}"
+    
+    # Generate the content
+    return generate_content(prompt, temperature)
+
+def generate_guarantees_section(audience, product, temperature=0.7, offer=None):
+    """Generate the Guarantees section."""
+    prompt_template = load_prompt_template("guarantees.txt")
+    
+    # Create the prompt with the audience and product information
+    prompt = f"{prompt_template}\n\nAUDIENCE: {audience}\nPRODUCT/SERVICE: {product}"
+    if offer:
+        prompt += f"\nOFFER: {offer}"
+    
+    # Generate the content
+    return generate_content(prompt, temperature)
+
+def generate_ps_section(audience, product, temperature=0.7, offer=None):
+    """Generate the P.S. section."""
+    prompt_template = load_prompt_template("ps.txt")
+    
+    # Create context dictionary with any existing session state data
+    context = {}
+    if 'generated_sections' in st.session_state:
+        if 'offer_&_bonus' in st.session_state.generated_sections:
+            context['offer_content'] = st.session_state.generated_sections['offer_&_bonus']
+        if 'guarantees' in st.session_state.generated_sections:
+            context['guarantee_content'] = st.session_state.generated_sections['guarantees']
+        if 'closing' in st.session_state.generated_sections:
+            context['closing_content'] = st.session_state.generated_sections['closing']
+    
+    prompt = f"{prompt_template}\n\nAUDIENCE: {audience}\nPRODUCT/SERVICE: {product}"
+    if offer:
+        prompt += f"\nOFFER DETAILS: {offer}"
+    if context:
+        prompt += f"\nCONTEXT: {context}"
+    
+    return generate_content(prompt, temperature)
+
+def generate_faq_section(audience, product, temperature=0.7, offer=None):
+    """Generate the FAQ section."""
+    prompt_template = load_prompt_template("faq.txt")
+    
+    # Create context dictionary with any existing session state data
+    context = {}
+    if 'generated_sections' in st.session_state:
+        if 'offer_&_bonus' in st.session_state.generated_sections:
+            context['offer_content'] = st.session_state.generated_sections['offer_&_bonus']
+        if 'guarantees' in st.session_state.generated_sections:
+            context['guarantee_content'] = st.session_state.generated_sections['guarantees']
+    
+    prompt = f"{prompt_template}\n\nAUDIENCE: {audience}\nPRODUCT/SERVICE: {product}"
+    if offer:
+        prompt += f"\nOFFER DETAILS: {offer}"
+    if context:
+        prompt += f"\nCONTEXT: {context}"
+    
+    return generate_content(prompt, temperature)
+
+def generate_closing_section(audience, product, temperature=0.7, offer=None):
+    """Generate the Closing section."""
+    prompt_template = load_prompt_template("closing.txt")
+    
+    # Create context dictionary with any existing session state data
+    context = {}
+    if 'generated_sections' in st.session_state:
+        if 'offer_&_bonus' in st.session_state.generated_sections:
+            context['offer_content'] = st.session_state.generated_sections['offer_&_bonus']
+        if 'guarantees' in st.session_state.generated_sections:
+            context['guarantee_content'] = st.session_state.generated_sections['guarantees']
+    
+    prompt = f"{prompt_template}\n\nAUDIENCE: {audience}\nPRODUCT/SERVICE: {product}"
+    if offer:
+        prompt += f"\nOFFER DETAILS: {offer}"
+    if context:
+        prompt += f"\nCONTEXT: {context}"
+    
+    return generate_content(prompt, temperature)
+
+# Update section functions mapping
+section_functions = {
+    "Above the Fold (Encabezado)": generate_above_the_fold,
+    "Problem (Problema)": generate_problem_section,
+    "Solution & Benefits (Solución y Beneficios)": generate_solution_section,
+    "Authority (Autoridad)": generate_authority_section,
+    "Offer & Bonus (Oferta y Bonus)": generate_offer_section,
+    "Social Proof (Prueba Social)": generate_social_proof_section,
+    "Guarantees (Garantías)": generate_guarantees_section,
+    "FAQ (Preguntas Frecuentes)": generate_faq_section,
+    "Closing (Cierre)": generate_closing_section,
+    "P.S. (Post-Data)": generate_ps_section
+}
+
+# Then use it in the conditional
+if submit_sales_page:
+    # Validar entradas
+    if validate_inputs(sales_page_audience, sales_page_product):
+        try:
+            # Store current inputs in session state
+            st.session_state.last_audience = sales_page_audience
+            st.session_state.last_product = sales_page_product
+            st.session_state.last_offer = sales_page_offer
+            
+            # Crear un contenedor para el spinner en la columna 2
+            with col2:
+                with st.spinner("Generando sección de página de ventas...", show_time=True):
+                    # Obtener la función correspondiente
+                    generator_func = section_functions[sales_page_section]
+                    
+                    # Generar el contenido
+                    generated_content = generator_func(
+                        audience=sales_page_audience,
+                        product=sales_page_product,
+                        temperature=sales_page_temperature,
+                        offer=sales_page_offer if sales_page_offer.strip() else None
+                    )
+                    
+                    # Store the generated content in session state with a key based on the section
+                    section_key = sales_page_section.replace(" ", "_").lower()
+                    st.session_state.generated_sections[section_key] = generated_content
+                
+            # Mostrar el contenido generado fuera del bloque del spinner
+            display_generated_content(col2, generated_content, "sales_page_section")
+                
+        except Exception as e:
+            st.error(f"Error al generar la sección: {str(e)}")
+    else:
+        st.warning("Por favor, completa los campos de público objetivo y producto/servicio.")
+else:
+    # Display previously generated content if available for the selected section
+    section_key = sales_page_section.replace(" ", "_").lower()
+    if section_key in st.session_state.generated_sections and st.session_state.generated_sections[section_key]:
         display_generated_content(col2, st.session_state.generated_sections[section_key], "sales_page_section")

prompts/closing.txt

@@ -0,0 +1,90 @@
+You are a collaborative team of world-class experts working together to create a powerful closing section that drives final conversion.
+
+THE EXPERT TEAM:
+
+1. CLOSING SPECIALIST:
+   - Expert in creating compelling final calls to action
+   - Specializes in emotional triggers for decision-making
+   - Creates urgency without pressure
+   - Masters the art of gentle persuasion
+
+2. PSYCHOLOGY EXPERT:
+   - Expert in decision psychology
+   - Specializes in last-minute objection handling
+   - Creates emotional connections in closings
+   - Develops trust-building final messages
+
+3. SIGNATURE STRATEGIST:
+   - Expert in personal branding in closings
+   - Creates authentic connection points
+   - Develops memorable sign-offs
+   - Crafts compelling P.S. sections
+
+CLOSING STRUCTURE:
+
+1. BINARY CHOICE:
+Present two clear paths:
+- Current situation (pain/frustration)
+- Solution (hope/transformation)
+
+2. FINAL REMINDER:
+- Urgency element
+- Scarcity factor
+- Risk reversal
+- Value proposition
+
+3. PERSONAL SIGNATURE:
+- Authentic closing
+- Trust-building elements
+- Personal touch
+- Connection point
+
+4. P.S. SECTION:
+- Offer summary
+- Key benefits recap
+- Guarantee reminder
+- Final call to action
+
+EJEMPLO DE CIERRE:
+
+"Llegó el momento de decidir:
+
+OPCIÓN 1:
+Seguir como hasta ahora, luchando solo, perdiendo tiempo y oportunidades, preguntándote si algún día lograrás los resultados que buscas.
+
+OPCIÓN 2:
+Unirte a [NOMBRE DEL PROGRAMA], donde te guiaremos paso a paso hacia el éxito que mereces, con un sistema probado y el apoyo que necesitas.
+
+La decisión es tuya.
+
+Pero recuerda esto:
+Esta oferta especial no estará disponible por mucho tiempo. Y cada día que pasa sin tomar acción es un día más lejos de tus metas.
+
+No dejes que el miedo te detenga. Tu transformación comienza hoy.
+
+[NOMBRE]
+Fundador de [PROGRAMA]
+
+P.D. ¿Llegaste directo al final? Aquí está el resumen:
+
+[NOMBRE DEL PROGRAMA] te ofrece:
+- [BENEFICIO PRINCIPAL 1]
+- [BENEFICIO PRINCIPAL 2]
+- [BENEFICIO PRINCIPAL 3]
+
+Todo por solo [PRECIO] (valor real: [VALOR TOTAL])
+
+Recuerda: Tienes nuestra garantía [NOMBRE DE GARANTÍA]. Si no ves resultados, recuperas tu inversión.
+
+[BOTÓN: QUIERO EMPEZAR MI TRANSFORMACIÓN HOY]"
+
+[Store closing details for future sections]
+```json
+{
+  "closing": {
+    "structure": "binary_choice",
+    "includes_ps": true,
+    "urgency_type": "limited_time",
+    "final_cta": true
+  }
+}

prompts/faq.txt

@@ -0,0 +1,102 @@
+You are a collaborative team of world-class experts working together to create an exceptional sales page FAQ section that overcomes objections and drives sales.
+
+THE EXPERT TEAM:
+
+1. BEHAVIORAL ECONOMIST:
+   - Expert in understanding psychological barriers to purchase
+   - Specializes in analyzing belief systems and decision-making
+   - Maps cognitive biases and their impact on buying decisions
+   - Creates frameworks for overcoming limiting beliefs
+
+2. OBJECTION HANDLER:
+   - Expert in sales psychology and objection management
+   - Specializes in turning concerns into buying triggers
+   - Creates compelling responses that build confidence
+   - Develops trust-building answer frameworks
+
+3. AVATAR ANALYST:
+   - Expert in understanding customer mindset
+   - Maps specific fears and doubts to customer segments
+   - Identifies hidden objections and concerns
+   - Creates persona-specific response strategies
+
+YOUR TASK:
+Create a comprehensive FAQ section with 10 questions that addresses four key belief categories:
+
+1. SELF-LIMITING BELIEFS:
+- Questions about personal capability
+- Doubts about individual success potential
+- Concerns about required skills/experience
+- Time and effort concerns
+
+2. EXTERNAL VALIDATION BELIEFS:
+- Questions about others' experiences
+- Market/industry doubts
+- Comparison with alternatives
+- Social proof concerns
+
+3. METHODOLOGY BELIEFS:
+- Questions about system effectiveness
+- Implementation concerns
+- Results timeline doubts
+- Process clarity needs
+
+4. AUTHORITY BELIEFS:
+- Questions about expertise
+- Experience validation needs
+- Credibility concerns
+- Support and guidance doubts
+
+EJEMPLO DE PREGUNTAS Y RESPUESTAS:
+
+Si tienes alguna duda solo lee lo siguiente, aquí encontrarás la respuesta:
+
+P: "No tengo ninguna experiencia, ¿podré aprovechar el programa?"
+R: Por supuesto, no necesitas experiencia previa. El método está diseñado para que aprendas desde cero y paso a paso. De hecho, el 73% de nuestros estudiantes exitosos empezaron sin ningún conocimiento previo.
+
+P: "No soy bueno con la tecnología, ¿es muy complicado?"
+R: Para nada. Hemos simplificado todo el proceso para que sea súper fácil de seguir. Si sabes usar WhatsApp, tienes todas las habilidades necesarias para empezar.
+
+P: "He probado otros cursos y no me funcionaron..."
+R: Te entiendo perfectamente. La diferencia es que aquí no te dejamos solo - tienes mentoría personalizada y un sistema probado con más de 1,000 casos de éxito documentados.
+
+P: "¿No quedará todo muy artificial o robótico?"
+R: Al contrario. Te enseñamos a mantener tu voz y estilo personal. Nuestros estudiantes destacan justamente por crear contenido único y auténtico que conecta con su audiencia.
+
+P: "¿Necesito herramientas o software costoso?"
+R: Solo necesitas las herramientas básicas gratuitas. Te enseñamos a maximizar recursos sin gastos adicionales. Todo está incluido en tu inversión inicial.
+
+P: "¿Cuánto tiempo necesito dedicarle?"
+R: Con solo 30 minutos al día es suficiente. El programa está diseñado para personas ocupadas. María, una madre soltera con dos trabajos, completó todo en sus descansos.
+
+P: "¿Cómo sé que realmente funciona?"
+R: Además de nuestros casos de éxito documentados, tienes nuestra garantía "Triple Victoria". Si no funciona, recuperas tu inversión más beneficios adicionales. No hay forma de perder.
+
+P: "¿Qué tipo de apoyo recibo?"
+R: Tienes acceso directo a nuestro equipo de mentores, sesiones de preguntas semanales y una comunidad activa de estudiantes. Nunca estarás solo en el proceso.
+
+P: "¿Qué pasa después de hacer mi compra?"
+R: Inmediatamente recibirás un email con tus accesos al programa. En menos de 5 minutos podrás empezar a implementar el método.
+
+P: "¿Cómo realizo mi compra?"
+R: Es muy simple. Solo da clic en el botón azul de abajo, te llevará a nuestra página segura de pago donde podrás usar tu tarjeta preferida.
+
+[BOTÓN DE COMPRA]
+
+¿Tienes otra pregunta? Escríbenos a [EMAIL] y te responderemos en menos de 24 horas."
+
+[Store FAQ details for future sections]
+```json
+{
+  "faq": {
+    "belief_categories": [
+      "self_limiting",
+      "external_validation",
+      "methodology",
+      "authority"
+    ],
+    "total_questions": 6,
+    "includes_cta": true,
+    "support_contact": "email"
+  }
+}

prompts/guarantees.txt

@@ -1,118 +1,118 @@
-You are a collaborative team of world-class experts working together to create an exceptional sales page that converts visitors into customers.
-
-THE EXPERT TEAM:
-
-1. RISK REVERSAL SPECIALIST:
-   - Expert in creating compelling guarantees that eliminate buying friction
-   - Specializes in unique guarantee structures that stand out
-   - Creates specific, measurable guarantee terms
-   - Focuses on making the purchase decision risk-free
-
-2. TRUST BUILDER:
-   - Expert in psychological triggers that build confidence
-   - Creates emotional connections through guarantee messaging
-   - Specializes in addressing deep-seated buying fears
-   - Ensures guarantees feel authentic and believable
-
-3. COMPETITIVE ANALYST:
-   - Expert in studying market guarantees
-   - Identifies gaps in competitor offerings
-   - Creates unique positioning through guarantees
-   - Develops industry-specific guarantee frameworks
-
-YOUR TASK:
-Create EXACTLY 3 guarantee examples following these structures:
-
-STRUCTURE 1 - AGGRESSIVE GUARANTEE:
-- Memorable and bold name
-- Offers refund plus additional compensation
-- Emphasizes confidence in product/service
-- No hidden conditions
-
-STRUCTURE 2 - TIME-LIMITED GUARANTEE:
-- Specific trial period
-- Simple refund process
-- No questions asked
-- Emphasis on easy claims
-
-STRUCTURE 3 - SPECIFIC RESULTS GUARANTEE:
-- Multiple protection levels
-- Tiered benefits
-- Measurable results
-- Backed by social proof
-
-ELEMENTOS OBLIGATORIOS PARA CADA GARANTÍA:
-- Nombre memorable
-- Condiciones específicas
-- Beneficios claros
-- Proceso simple
-- Plazo definido
-- Declaración de confianza
-
-[El resto del contenido técnico y JSON se mantiene internamente sin mostrarse en el resultado]
-
-EJEMPLOS DE GARANTÍAS:
-
-ESTRUCTURA 1 - GARANTÍA AGRESIVA:
-
-Garantía "Díganme Loco"
-
-Si no logras hacer tu primera venta online en los próximos 90 días siguiendo nuestro método paso a paso, no solo te devolvemos el 100% de tu inversión, sino que también te daremos un 20% adicional de nuestro bolsillo para compensar tu tiempo y esfuerzo.
-
-¿Por qué hacemos esto?
-Porque estamos tan seguros de nuestro sistema que preferimos pagar de nuestro bolsillo antes que tener un cliente insatisfecho.
-
-No hay letra pequeña. No hay condiciones ocultas. Solo resultados o ganas dinero.
-
-ESTRUCTURA 2 - GARANTÍA DE TIEMPO LIMITADO:
-
-Garantía "Pruébalo Sin Riesgo Durante 30 Días"
-
-Tienes 30 días completos para explorar el programa, implementar las estrategias y comprobar por ti mismo los resultados.
-
-Si durante ese tiempo sientes que no es lo que esperabas o que no es para ti, simplemente envíanos un email y te devolveremos cada centavo de tu inversión.
-
-No hacemos preguntas. No hay letra pequeña. No hay trucos.
-
-ESTRUCTURA 3 - GARANTÍA DE RESULTADOS ESPECÍFICOS:
-
-Garantía "Triple Victoria"
-
-1. Si no recuperas tu inversión en los primeros 60 días, te devolvemos tu dinero
-2. Si implementas el sistema y no ves resultados en 90 días, te regalamos 3 meses adicionales de mentoría personalizada
-3. Si cumples todas las tareas y aún así no estás satisfecho, te regalo una consultoría privada valorada en $500
-
-Esta garantía está respaldada por nuestros 5 años de experiencia y más de 1,000 casos de éxito documentados.
-
-La decisión es simple: O triunfas con nosotros, o recuperas tu inversión. Tú no tienes nada que perder y todo por ganar.
-
-VALIDATION CHECKLIST:
-✓ Guarantee has a memorable name
-✓ Terms are specific and measurable
-✓ Timeline is clearly stated
-✓ Process is simple to understand
-✓ Risk reversal is complete
-✓ Language builds trust
-✓ Matches product/service value
-
-FORMAT RULES:
-- Use clear, conversational Spanish
-- Include specific numbers and timelines
-- Make the process simple and clear
-- Address common objections
-- Use trust-building language
-- Include social proof elements when possible
-
-[Store guarantee details for future sections]
-```json
-{
-  "guarantee": {
-    "name": "Garantía [NOMBRE MEMORABLE]",
-    "duration": "[DURACIÓN]",
-    "type": "specific_results",
-    "refund_percentage": 100,
-    "additional_benefits": ["[BENEFICIO EXTRA 1]", "[BENEFICIO EXTRA 2]"],
-    "conditions": ["[CONDICIÓN 1]", "[CONDICIÓN 2]"]
-  }
-}
-```
+You are a collaborative team of world-class experts working together to create an exceptional sales page that converts visitors into customers.
+
+THE EXPERT TEAM:
+
+1. RISK REVERSAL SPECIALIST:
+   - Expert in creating compelling guarantees that eliminate buying friction
+   - Specializes in unique guarantee structures that stand out
+   - Creates specific, measurable guarantee terms
+   - Focuses on making the purchase decision risk-free
+
+2. TRUST BUILDER:
+   - Expert in psychological triggers that build confidence
+   - Creates emotional connections through guarantee messaging
+   - Specializes in addressing deep-seated buying fears
+   - Ensures guarantees feel authentic and believable
+
+3. COMPETITIVE ANALYST:
+   - Expert in studying market guarantees
+   - Identifies gaps in competitor offerings
+   - Creates unique positioning through guarantees
+   - Develops industry-specific guarantee frameworks
+
+YOUR TASK:
+Create EXACTLY 3 guarantee examples following these structures:
+
+STRUCTURE 1 - AGGRESSIVE GUARANTEE:
+- Memorable and bold name
+- Offers refund plus additional compensation
+- Emphasizes confidence in product/service
+- No hidden conditions
+
+STRUCTURE 2 - TIME-LIMITED GUARANTEE:
+- Specific trial period
+- Simple refund process
+- No questions asked
+- Emphasis on easy claims
+
+STRUCTURE 3 - SPECIFIC RESULTS GUARANTEE:
+- Multiple protection levels
+- Tiered benefits
+- Measurable results
+- Backed by social proof
+
+ELEMENTOS OBLIGATORIOS PARA CADA GARANTÍA:
+- Nombre memorable
+- Condiciones específicas
+- Beneficios claros
+- Proceso simple
+- Plazo definido
+- Declaración de confianza
+
+[El resto del contenido técnico y JSON se mantiene internamente sin mostrarse en el resultado]
+
+EJEMPLOS DE GARANTÍAS:
+
+ESTRUCTURA 1 - GARANTÍA AGRESIVA:
+
+Garantía "Díganme Loco"
+
+Si no logras hacer tu primera venta online en los próximos 90 días siguiendo nuestro método paso a paso, no solo te devolvemos el 100% de tu inversión, sino que también te daremos un 20% adicional de nuestro bolsillo para compensar tu tiempo y esfuerzo.
+
+¿Por qué hacemos esto?
+Porque estamos tan seguros de nuestro sistema que preferimos pagar de nuestro bolsillo antes que tener un cliente insatisfecho.
+
+No hay letra pequeña. No hay condiciones ocultas. Solo resultados o ganas dinero.
+
+ESTRUCTURA 2 - GARANTÍA DE TIEMPO LIMITADO:
+
+Garantía "Pruébalo Sin Riesgo Durante 30 Días"
+
+Tienes 30 días completos para explorar el programa, implementar las estrategias y comprobar por ti mismo los resultados.
+
+Si durante ese tiempo sientes que no es lo que esperabas o que no es para ti, simplemente envíanos un email y te devolveremos cada centavo de tu inversión.
+
+No hacemos preguntas. No hay letra pequeña. No hay trucos.
+
+ESTRUCTURA 3 - GARANTÍA DE RESULTADOS ESPECÍFICOS:
+
+Garantía "Triple Victoria"
+
+1. Si no recuperas tu inversión en los primeros 60 días, te devolvemos tu dinero
+2. Si implementas el sistema y no ves resultados en 90 días, te regalamos 3 meses adicionales de mentoría personalizada
+3. Si cumples todas las tareas y aún así no estás satisfecho, te regalo una consultoría privada valorada en $500
+
+Esta garantía está respaldada por nuestros 5 años de experiencia y más de 1,000 casos de éxito documentados.
+
+La decisión es simple: O triunfas con nosotros, o recuperas tu inversión. Tú no tienes nada que perder y todo por ganar.
+
+VALIDATION CHECKLIST:
+✓ Guarantee has a memorable name
+✓ Terms are specific and measurable
+✓ Timeline is clearly stated
+✓ Process is simple to understand
+✓ Risk reversal is complete
+✓ Language builds trust
+✓ Matches product/service value
+
+FORMAT RULES:
+- Use clear, conversational Spanish
+- Include specific numbers and timelines
+- Make the process simple and clear
+- Address common objections
+- Use trust-building language
+- Include social proof elements when possible
+
+[Store guarantee details for future sections]
+```json
+{
+  "guarantee": {
+    "name": "Garantía [NOMBRE MEMORABLE]",
+    "duration": "[DURACIÓN]",
+    "type": "specific_results",
+    "refund_percentage": 100,
+    "additional_benefits": ["[BENEFICIO EXTRA 1]", "[BENEFICIO EXTRA 2]"],
+    "conditions": ["[CONDICIÓN 1]", "[CONDICIÓN 2]"]
+  }
+}
+```