import streamlit as st import google.generativeai as genai import os import time from dotenv import load_dotenv from styles import get_custom_css, get_response_html_wrapper from formulas import offer_formulas from prompts import create_offer_instruction import PyPDF2 import docx from PIL import Image import io # Set page to wide mode to use full width st.set_page_config(layout="wide") # Load environment variables load_dotenv() # Configure Google Gemini API genai.configure(api_key=os.getenv('GOOGLE_API_KEY')) model = genai.GenerativeModel('gemini-2.0-flash') # Remove duplicate import # from formulas import create_offer_instruction, offer_formulas # Initialize session state variables if they don't exist if 'submitted' not in st.session_state: st.session_state.submitted = False if 'offer_result' not in st.session_state: st.session_state.offer_result = "" if 'generated' not in st.session_state: st.session_state.generated = False # Hide Streamlit menu and footer st.markdown(""" """, unsafe_allow_html=True) # Custom CSS st.markdown(get_custom_css(), unsafe_allow_html=True) # App title and description st.markdown('

Great Offer Generator

', unsafe_allow_html=True) st.markdown('

Transform your skills into compelling offers!

', unsafe_allow_html=True) # Create two columns for layout - left column 40%, right column 60% col1, col2 = st.columns([4, 6]) # Main input section in left column with col1: # Define the generate_offer function first def handle_generate_button(): # Renamed to avoid conflict has_manual_input = bool(skills or product_service) has_file_input = bool(uploaded_file is not None and not is_image) has_image_input = bool(uploaded_file is not None and is_image) # Simple validation - check if we have at least one input type if not (has_manual_input or has_file_input or has_image_input): st.error('Por favor ingresa texto o sube un archivo/imagen') return st.session_state.submitted = True st.session_state.generated = False # Reset generated flag # Store inputs based on what's available if has_manual_input: st.session_state.skills = skills if skills else "" st.session_state.product_service = product_service if product_service else "" if has_file_input: st.session_state.file_content = file_content if has_image_input: st.session_state.image_parts = image_parts # Set input type based on what's available if has_image_input: if has_manual_input: st.session_state.input_type = "manual_image" else: st.session_state.input_type = "image" else: if has_manual_input and has_file_input: st.session_state.input_type = "both" elif has_file_input: st.session_state.input_type = "file" elif has_manual_input: st.session_state.input_type = "manual" # Store common settings st.session_state.target_audience = target_audience st.session_state.temperature = temperature st.session_state.formula_type = formula_type # Keep only the manual input tab with st.container(): skills = st.text_area('💪 Tus Habilidades', height=70, help='Lista tus habilidades y experiencia clave') product_service = st.text_area('🎯 Producto/Servicio', height=70, help='Describe tu producto o servicio') # Generate button moved here - right after product/service st.button('Generar Oferta 🎉', on_click=handle_generate_button) # Updated function name # Accordion for additional settings with st.expander('⚙️ Configuración Avanzada'): target_audience = st.text_area('👥 Público Objetivo', height=70, help='Describe tu cliente o público ideal') # Add file/image uploader here uploaded_file = st.file_uploader("📄 Sube un archivo o imagen", type=['txt', 'pdf', 'docx', 'jpg', 'jpeg', 'png']) if uploaded_file is not None: file_type = uploaded_file.name.split('.')[-1].lower() # Handle text files if file_type in ['txt', 'pdf', 'docx']: if file_type == 'txt': try: file_content = uploaded_file.read().decode('utf-8') except Exception as e: st.error(f"Error al leer el archivo TXT: {str(e)}") file_content = "" elif file_type == 'pdf': try: import PyPDF2 pdf_reader = PyPDF2.PdfReader(uploaded_file) file_content = "" for page in pdf_reader.pages: file_content += page.extract_text() + "\n" except Exception as e: st.error(f"Error al leer el archivo PDF: {str(e)}") file_content = "" elif file_type == 'docx': try: import docx doc = docx.Document(uploaded_file) file_content = "\n".join([para.text for para in doc.paragraphs]) except Exception as e: st.error(f"Error al leer el archivo DOCX: {str(e)}") file_content = "" # Remove success message - no notification shown # Set file type flag is_image = False # Handle image files elif file_type in ['jpg', 'jpeg', 'png']: try: image = Image.open(uploaded_file) st.image(image, caption="Imagen cargada", use_container_width=True) image_bytes = uploaded_file.getvalue() image_parts = [ { "mime_type": uploaded_file.type, "data": image_bytes } ] # Set file type flag is_image = True except Exception as e: st.error(f"Error al procesar la imagen: {str(e)}") is_image = False # Selector de fórmula formula_type = st.selectbox( '📋 Tipo de Fórmula', options=list(offer_formulas.keys()), help='Selecciona el tipo de fórmula para tu oferta' ) temperature = st.slider('🌡️ Nivel de Creatividad', min_value=0.0, max_value=2.0, value=0.7, help='Valores más altos hacen que el resultado sea más creativo pero menos enfocado') # Results column with col2: if st.session_state.submitted and not st.session_state.generated: with st.spinner('Creando tu oferta perfecta...'): # Use the create_offer_instruction function to generate the prompt avatar_description = st.session_state.target_audience if hasattr(st.session_state, 'target_audience') and st.session_state.target_audience else 'General audience' # Determine product name based on input type if hasattr(st.session_state, 'product_service') and st.session_state.product_service: product_name = st.session_state.product_service else: product_name = "Producto/Servicio" # Get the instruction using the formula instruction = create_offer_instruction( avatar_description=avatar_description, product_name=product_name, selected_formula_name=st.session_state.formula_type, offer_formulas=offer_formulas # Pass the offer_formulas dictionary ) # Add additional context based on input type if st.session_state.input_type == "manual": additional_context = f""" Additional information: Skills: {st.session_state.skills} """ instruction += additional_context elif st.session_state.input_type == "file": additional_context = f""" Additional information from file: {st.session_state.file_content} """ instruction += additional_context elif st.session_state.input_type == "both": additional_context = f""" Additional information: Skills: {st.session_state.skills} File content: {st.session_state.file_content} """ instruction += additional_context try: generation_config = genai.GenerationConfig(temperature=st.session_state.temperature) if "image" in st.session_state.input_type: response = model.generate_content([instruction, st.session_state.image_parts[0]], generation_config=generation_config) else: response = model.generate_content(instruction, generation_config=generation_config) st.session_state.offer_result = response.text st.session_state.generated = True # Mark as generated except Exception as e: st.error(f'Ocurrió un error: {str(e)}') st.session_state.submitted = False # Display results if we have an offer result if st.session_state.generated: # With this line that uses the wrapper: st.markdown(get_response_html_wrapper(st.session_state.offer_result), unsafe_allow_html=True) # Add a small space st.markdown('
', unsafe_allow_html=True) # Apply the custom button style before rendering the download button st.markdown('', unsafe_allow_html=True) st.download_button( label="Descargar Oferta", data=st.session_state.offer_result, file_name="oferta_generada.txt", mime="text/plain" ) # Footer st.markdown('---') st.markdown('Made with ❤️ by Jesús Cabrera') # Remove the duplicate functions at the bottom