app.py

# - Modified based on given code with corrections and improvements
# - Fixed Gemini API integration by using google.generativeai instead of manual API requests
# - Added support for multiple responses (though Gemini API requires handling this differently)
# - Improved error handling for better reliability
# - Refined creative mode and fact-checking integration into the prompt
# - Optimized token handling for better text generation performance
# - Added support for multiple languages (English and Tagalog)
# - Added Streamlit Secrets for secure API key storage
# - Added Streamlit Session State for persistent model initialization
# - Added Streamlit Sidebar for configuration settings
# - Added Streamlit Warnings and Errors for better user feedback
# - Added Streamlit Markdown for better text formatting
# - Added Streamlit Title and Header for better UI design
# - Added Streamlit Selectbox, Slider, Number Input, Text Area, Button, and Checkbox for user input

import streamlit as st  # Import Streamlit for building the web app
import google.generativeai as genai  # Import Google Generative AI SDK for text generation

# Load Gemini API key from Streamlit Secrets configuration
api_key = st.secrets["gemini"]["api_key"]

# Configure the generative AI model with API key
genai.configure(api_key=api_key)

# Define the model ID for the AI-powered text generation
MODEL_ID = "gemini-1.5-flash"  

# Initialize the model if it is not already in session state
if "model" not in st.session_state:
    st.session_state.model = genai.GenerativeModel(MODEL_ID)

# Retrieve the AI model instance
model = st.session_state.model

# Page title
st.title("LemmaTeks: AI-Powered Text Generator")

# Sidebar for settings
with st.sidebar:
    st.header("Configuration")
    
    # Dropdown menu for selecting output format (e.g., Story, Poem, Article, Code)
    output_format = st.selectbox("Choose Output Format:", ["Story", "Poem", "Article", "Code"])
    
    # Dropdown menu for selecting tone/style of generated text
    tone_style = st.selectbox("Select Tone/Style:", ["Formal", "Informal", "Humorous", "Technical"])
    
    # Dropdown menu for selecting the language of the generated text
    language = st.selectbox("Select Language:", ["English", "Tagalog"])

    # Slider for specifying text length in words
    text_length = st.slider("Text Length (words):", min_value=50, max_value=1000, step=50)
    
    # Slider for adjusting creativity level of AI-generated response
    creativity_level = st.slider("Creativity Level:", min_value=0.0, max_value=1.0, step=0.1)
    
    # Input box to set the number of responses to generate
    num_responses = st.number_input("Number of Responses:", min_value=1, max_value=5, step=1)
    
    # Checkbox to enable creative mode, which enhances creativity in AI responses
    creative_mode = st.checkbox("Enable Creative Mode")
    
    # Checkbox to enable fact-checking, ensuring responses are supported by evidence
    fact_checking = st.checkbox("Enable Fact-Checking")

# Text input field for user prompt
user_prompt = st.text_area("Enter Your Prompt Here:")

# Modify the prompt based on selected settings
if creative_mode:
    user_prompt += " Optimize the creativity of your response."
if fact_checking:
    user_prompt += " Support your answer with evidence."

# Adjust prompt for language selection
if language != "English":
    user_prompt = f"Write in {language}: {user_prompt}"
if language != "Tagalog":
    user_prompt = f"Sumulat sa {language}: {user_prompt}"
    
# Submit button to generate AI-powered text
if st.button("Generate"):
    # Check if prompt is empty
    if user_prompt.strip() == "":
        st.warning("Please enter a prompt before generating!")
    else:
        st.write("Generating responses...")
        
        try:
            # Generate AI content based on user settings
            response = model.generate_content(
                f"Format: {output_format}\nTone: {tone_style}\nPrompt: {user_prompt}",
                generation_config=genai.GenerationConfig(
                    max_output_tokens=text_length * 2,  # Convert word count to token estimate
                    temperature=creativity_level  # Control randomness of response
                )
            )
            
            # Display generated text
            st.markdown(response.text)
        
        except Exception as e:
            # Handle errors gracefully
            st.error(f"An unexpected error occurred: {e}")