ALwrity/alwrity.py

import streamlit as st
import os
import json
from dotenv import load_dotenv
from datetime import datetime
from lib.utils.config_manager import save_config
from lib.utils.ui_setup import setup_ui, setup_tabs
from lib.utils.api_key_manager import check_all_api_keys
from lib.utils.file_processor import read_prompts, write_prompts

# Constants
BLOG_TONE_OPTIONS = ["Casual", "Professional", "How-to", "Beginner", "Research", "Programming", "Social Media", "Customize"]
BLOG_DEMOGRAPHIC_OPTIONS = ["Professional", "Gen-Z", "Tech-savvy", "Student", "Digital Marketing", "Customize"]
BLOG_LANGUAGE_OPTIONS = ["English", "Spanish", "German", "Chinese", "Arabic", "Nepali", "Hindi", "Hindustani", "Customize"]
CONTENT_TYPE_OPTIONS = ["Informational", "Commercial", "Company", "News", "Finance", "Competitor", "Programming", "Scholar"]
OUTPUT_FORMAT_OPTIONS = ["markdown", "HTML", "plaintext"]
IMAGE_MODEL_OPTIONS = ["stable-diffusion", "dalle2", "dalle3"]
GPT_PROVIDER_OPTIONS = ["google", "openai", "minstral"]
GEOGRAPHIC_LOCATION_OPTIONS = ["us", "in", "fr", "cn"]
SEARCH_LANGUAGE_OPTIONS = ["en", "zn-cn", "de", "hi"]
TIME_RANGE_OPTIONS = ["anytime", "past day", "past week", "past month", "past year"]

def get_custom_input(label, options, help_text, placeholder=""):
    selection = st.selectbox(f"**{label}**", options=options, help=help_text)
    if selection == "Customize":
        custom_input = st.text_input(f"Enter your {label.lower()}", help=f"Specify your {label.lower()}.", placeholder=placeholder)
        if custom_input:
            selection = custom_input
        else:
            st.warning(f"Please specify your {label.lower()}.")
    return selection

def sidebar_configuration():
    # Alias for sidebar
    sb = st.sidebar

    sb.title("🛠️ Personalization & Settings 🏗️")
    
    with sb.expander("**👷 Content Personalization**"):
        blog_length = st.text_input("**Content Length (words)**", value="2000", help="Approximate word count for blogs.")

        blog_tone = get_custom_input("Content Tone", BLOG_TONE_OPTIONS, "Select the desired tone for the blog content.")
        blog_demographic = get_custom_input("Target Audience", BLOG_DEMOGRAPHIC_OPTIONS, "Select the primary audience for the blog content.", "Eg. Domain expert, Content creator, Financial expert etc..")
        blog_type = st.selectbox("**Content Type**", options=CONTENT_TYPE_OPTIONS, help="Select the category that best describes the blog content.")
        blog_language = get_custom_input("Content Language", BLOG_LANGUAGE_OPTIONS, "Select the language in which the blog will be written.")

        blog_output_format = st.selectbox("**Content Output Format**", options=OUTPUT_FORMAT_OPTIONS, help="Select the format for the blog output.")

    with sb.expander("**🩻 Images Personalization**"):
        image_generation_model = st.selectbox("**Image Generation Model**", options=IMAGE_MODEL_OPTIONS, help="Select the model to generate images for the blog.")
        number_of_blog_images = st.number_input("**Number of Blog Images**", value=1, help="Specify the number of images to include in the blog.")

    with sb.expander("**🤖 LLM Personalization**"):
        gpt_provider = st.selectbox("**GPT Provider**", options=GPT_PROVIDER_OPTIONS, help="Select the provider for the GPT model.")
        model = st.text_input("**Model**", value="gemini-1.5-flash-latest", help="Specify the model version to use from the selected provider.")
        temperature = st.slider("Temperature", min_value=0.1, max_value=1.0, value=0.7, step=0.1, format="%.1f", help="Controls the 'creativity' or randomness of the text generated.")
        top_p = st.slider("Top-p", min_value=0.0, max_value=1.0, value=0.9, step=0.1, format="%.1f", help="Controls the level of diversity in the generated text.")
        max_tokens = st.selectbox("Max Tokens", options=[500, 1000, 2000, 4000, 16000, 32000, 64000], index=3, help="Maximum length of the output sequence generated by a model.")
        n = st.number_input("N", value=1, min_value=1, max_value=10, help="Defines the number of words or characters grouped together in a sequence.")
        frequency_penalty = st.slider("Frequency Penalty", min_value=0.0, max_value=2.0, value=1.0, step=0.1, format="%.1f", help="Promotes diversity with higher values.")
        presence_penalty = st.slider("Presence Penalty", min_value=0.0, max_value=2.0, value=1.0, step=0.1, format="%.1f", help="Encourages the use of diverse words by discouraging repetition.")

    with sb.expander("**🕵️ Search Engine Personalization**"):
        geographic_location = st.selectbox("**Geographic Location**", options=GEOGRAPHIC_LOCATION_OPTIONS, help="Select the geographic location for tailoring search results.")
        search_language = st.selectbox("**Search Language**", options=SEARCH_LANGUAGE_OPTIONS, help="Select the language for the search results.")
        number_of_results = st.number_input("**Number of Results**", value=10, min_value=1, max_value=20, help="Specify the number of search results to retrieve.")
        time_range = st.selectbox("**Time Range**", options=TIME_RANGE_OPTIONS, help="Select the time range for filtering search results.")
        include_domains = st.text_input("**Include Domains**", value="", help="List specific domains to include in search results.")
        similar_url = st.text_input("**Similar URL**", value="", help="Provide a URL to find similar results.")

    # Storing collected inputs in a dictionary
    config = {
        "Blog Content Characteristics": {
            "Blog Length": blog_length,
            "Blog Tone": blog_tone,
            "Blog Demographic": blog_demographic,
            "Blog Type": blog_type,
            "Blog Language": blog_language,
            "Blog Output Format": blog_output_format
        },
        "Blog Images Details": {
            "Image Generation Model": image_generation_model,
            "Number of Blog Images": number_of_blog_images
        },
        "LLM Options": {
            "GPT Provider": gpt_provider,
            "Model": model,
            "Temperature": temperature,
            "Top-p": top_p,
            "Max Tokens": max_tokens,
            "N": n,
            "Frequency Penalty": frequency_penalty,
            "Presence Penalty": presence_penalty
        },
        "Search Engine Parameters": {
            "Geographic Location": geographic_location,
            "Search Language": search_language,
            "Number of Results": number_of_results,
            "Time Range": time_range,
            "Include Domains": include_domains,
            "Similar URL": similar_url
        }
    }

    # Writing the configuration to a file whenever a change is made
    save_config(config)

def main():
    #load_environment
    load_dotenv()
    setup_ui()

    if check_all_api_keys():
        setup_environment_paths()
        sidebar_configuration()
        setup_tabs()
        modify_prompts_sidebar()


def setup_environment_paths():
    """Sets up environment paths for saving files and configurations."""
    os.environ["SEARCH_SAVE_FILE"] = os.path.join(os.getcwd(), "lib", "workspace", "alwrity_web_research",
                                                  f"web_research_report_{datetime.now().strftime('%Y-%m-%d_%H-%M-%S')}")
    os.environ["IMG_SAVE_DIR"] = os.path.join(os.getcwd(), "lib", "workspace", "alwrity_content")
    os.environ["CONTENT_SAVE_DIR"] = os.path.join(os.getcwd(), "lib", "workspace", "alwrity_content")
    os.environ["PROMPTS_DIR"] = os.path.join(os.getcwd(), "lib", "workspace", "alwrity_prompts")
    os.environ["ALWRITY_CONFIG"] = os.path.join(os.getcwd(), "lib", "workspace", "alwrity_config", "main_config.json")


def modify_prompts_sidebar():
    """Provides a sidebar for modifying prompts."""
    st.sidebar.title("📝 Modify Prompts")
    prompts = read_prompts()

    if prompts:
        edited_prompts = []
        for i, prompt in enumerate(prompts):
            edited_prompt = st.sidebar.text_area(f"Prompt {i+1}", prompt)
            edited_prompts.append(edited_prompt)

        if st.sidebar.button("Save Prompts"):
            write_prompts(edited_prompts)
            st.sidebar.success("Prompts saved successfully!")
    else:
        st.sidebar.warning("No prompts found in the file.")


# Functions for the main options
def ai_writers():
    options = [
        "AI Blog Writer",
        "Story Writer",
        "Essay writer",
        "Write News reports",
        "Write Financial TA report",
        "AI Product Description Writer",
        "AI Copywriter",
        "Quit"
    ]
    choice = st.selectbox("**👇Select a content creation type:**", options, index=0, format_func=lambda x: f"📝 {x}")

    if choice == "AI Blog Writer":
        blog_from_keyword()
    elif choice == "Story Writer":
        story_input_section()
    elif choice == "Essay writer":
        essay_writer()
    elif choice == "Write News reports":
        ai_news_writer()
    elif choice == "Write Financial TA report":
        ai_finance_ta_writer()
    elif choice == "AI Product Description Writer":
        write_ai_prod_desc()
    elif choice == "Quit":
        st.subheader("Exiting, Getting Lost. But.... I have nowhere to go 🥹🥹")


def content_planning_tools():
    st.markdown("""**Alwrity content Ideation & Planning** : Provide few keywords to do comprehensive web research.
             Provide few keywords to get Google, Neural, pytrends analysis. Know keywords, blog titles to target.
             Generate months long content calendar around given keywords.""")
    
    options = [
        "Keywords Researcher",
        "Competitor Analysis",
        "Content Calender Ideator"
    ]
    choice = st.radio("Select a content planning tool:", options, index=0, format_func=lambda x: f"🔍 {x}")
    
    if choice == "Keywords Researcher":
        do_web_research()
    elif choice == "Competitor Analysis":
        competitor_analysis()
    elif choice == "Content Calender Ideator":
        plan_keywords = st.text_input(
            "**Enter Your main Keywords to get 2 months content calendar:**",
            placeholder="Enter 2-3 main keywords to generate AI content calendar with keyword researched blog titles",
            help="The keywords are the ones where you would want to generate 50-60 blogs/articles on."
        )
        if st.button("**Ideate Content Calender**"):
            if plan_keywords:
                ai_agents_content_planner(plan_keywords)
            else:
                st.error("Come on, really, Enter some keywords to plan on..")


def alwrity_brain():
    st.title("🧠 Alwrity Brain, Better than yours!")
    st.write("Choose a folder to write content on. Alwrity will do RAG on these documents. The documents can of any type, pdf, pptx, docs, txt, cs etc. Video files and Audio files are also permitted.")

    folder_path = st.text_input("**Enter folder path:**")
    if st.button("**Process Folder**"):
        if folder_path:
            try:
                process_folder_for_rag(folder_path)
                st.success("Folder processed successfully!")
            except Exception as e:
                st.error(f"Error processing folder: {e}")
        else:
            st.warning("Please enter a valid folder path.")


if __name__ == "__main__":
    main()