From a6cbfafa160926d5d724d0eddf64c76b212bda82 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=D9=8A?= Date: Wed, 15 Jan 2025 20:03:00 +0530 Subject: [PATCH] Debacles with AI coding, Reverting breaking changes. --- alwrity.py | 405 ++++++++++++++++++++++++++++++++++------------------- 1 file changed, 259 insertions(+), 146 deletions(-) diff --git a/alwrity.py b/alwrity.py index 8b54000d..5048eafa 100644 --- a/alwrity.py +++ b/alwrity.py @@ -1,111 +1,189 @@ import streamlit as st import os import json -from dotenv import load_dotenv +import base64 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.ui_setup import setup_ui from lib.utils.api_key_manager import check_all_api_keys -from lib.utils.file_processor import read_prompts, write_prompts +from dotenv import load_dotenv +from lib.utils.content_generators import ai_writers, content_planning_tools, blog_from_keyword, story_input_section, essay_writer, ai_news_writer, ai_finance_ta_writer, write_ai_prod_desc, do_web_research, competitor_analysis, ai_agents_content_planner +from lib.utils.seo_tools import ai_seo_tools +from lib.utils.ui_setup import setup_ui, setup_tabs +from lib.utils.alwrity_utils import ai_agents_team, ai_social_writer +from lib.utils.file_processor import load_image, read_prompts, write_prompts +from lib.utils.voice_processing import record_voice -# Constants for various options -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=""): + +def process_folder_for_rag(folder_path): + """Placeholder for the process_folder_for_rag function.""" + st.write(f"This is a placeholder for processing the folder: {folder_path}") + + +def save_config(config): """ - Get custom input from the user. - - Parameters: - - label (str): The label for the input field. - - options (list): List of options for the select box. - - help_text (str): Help text for the select box. - - placeholder (str): Placeholder text for the custom input field. - - Returns: - - str: The selected or custom input value. + Saves the provided configuration dictionary to a JSON file specified by the environment variable. """ - 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 + try: + with open(os.getenv("ALWRITY_CONFIG"), "w") as config_file: + json.dump(config, config_file, indent=4) + except Exception as e: + st.error(f"An error occurred while saving the configuration: {e}") -def content_personalization(sb): - """ - Sidebar content personalization section. - Parameters: - - sb: The Streamlit sidebar object. +# Sidebar configuration +def sidebar_configuration(): + st.sidebar.title("πŸ› οΈ Personalization & Settings πŸ—οΈ") - Returns: - - dict: Dictionary containing personalized content configuration. - """ - with sb.expander("**πŸ‘· Content Personalization**"): - blog_length = sb.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 = sb.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 = sb.selectbox("**Content Output Format**", options=OUTPUT_FORMAT_OPTIONS, help="Select the format for the blog output.") - return { + with st.sidebar.expander("**πŸ‘· Content Personalization**"): + blog_length = st.text_input("**Content Length (words)**", value="2000", + help="Approximate word count for blogs. Note: Actual length may vary based on GPT provider and max token count.") + + blog_tone_options = ["Casual", "Professional", "How-to", "Beginner", "Research", "Programming", "Social Media", "Customize"] + blog_tone = st.selectbox("**Content Tone**", + options=blog_tone_options, + help="Select the desired tone for the blog content.") + + if blog_tone == "Customize": + custom_tone = st.text_input("Enter the tone of your content", help="Specify the tone of your content.") + if custom_tone: + blog_tone = custom_tone + else: + st.warning("Please specify the tone of your content.") + + blog_demographic_options = ["Professional", "Gen-Z", "Tech-savvy", "Student", "Digital Marketing", "Customize"] + + blog_demographic = st.selectbox("**Target Audience**", + options=blog_demographic_options, + help="Select the primary audience for the blog content.") + if blog_demographic == "Customize": + custom_demographic = st.text_input("Enter your target audience", + help="Specify your target audience.", + placeholder="Eg. Domain expert, Content creator, Financial expert etc..") + if custom_demographic: + blog_demographic = custom_demographic + else: + st.warning("Please specify your target audience.") + + blog_type = st.selectbox("**Content Type**", + options=["Informational", "Commercial", "Company", "News", "Finance", "Competitor", "Programming", "Scholar"], + help="Select the category that best describes the blog content.") + + blog_language = st.selectbox("**Content Language**", + options=["English", "Spanish", "German", "Chinese", "Arabic", "Nepali", "Hindi", "Hindustani", "Customize"], + help="Select the language in which the blog will be written.") + if blog_language == "Customize": + custom_lang = st.text_input("Enter the language of your choice", help="Specify the content language.") + if custom_lang: + blog_language = custom_lang + else: + st.warning("Please specify the language of your content.") + + blog_output_format = st.selectbox("**Content Output Format**", + options=["markdown", "HTML", "plaintext"], + help="Select the format for the blog output.") + + with st.sidebar.expander("**🩻 Images Personalization**"): + image_generation_model = st.selectbox("**Image Generation Model**", + options=["stable-diffusion", "dalle2", "dalle3"], + 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 st.sidebar.expander("**πŸ€– LLM Personalization**"): + gpt_provider = st.selectbox("**GPT Provider**", + options=["google", "openai", "minstral"], + 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="""Temperature controls the 'creativity' or randomness of the text generated by GPT. + Greater determinism with higher values indicating more randomness.""" + ) + + top_p = st.slider( + "Top-p", + min_value=0.0, + max_value=1.0, + value=0.9, + step=0.1, + format="%.1f", + help="Top-p sampling controls the level of diversity in the generated text." + ) + + # Selectbox for max tokens + max_tokens_options = [500, 1000, 2000, 4000, 16000, 32000, 64000] + max_tokens = st.selectbox( + "Max Tokens", + options=max_tokens_options, + index=max_tokens_options.index(4000), + help="Max tokens determine the 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 when analyzing text.") + frequency_penalty = st.slider( + "Frequency Penalty", + min_value=0.0, + max_value=2.0, + value=1.0, + step=0.1, + format="%.1f", + help="Influences word selection during text generation, promoting 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 st.sidebar.expander("**πŸ•΅οΈ Search Engine Personalization**"): + geographic_location = st.selectbox("**Geographic Location**", + options=["us", "in", "fr", "cn"], + help="Select the geographic location for tailoring search results.") + search_language = st.selectbox("**Search Language**", + options=["en", "zn-cn", "de", "hi"], + help="Select the language for the search results.") + number_of_results = st.number_input("**Number of Results**", + value=10, + max_value=20, + min_value=1, + help="Specify the number of search results to retrieve.") + time_range = st.selectbox("**Time Range**", + options=["anytime", "past day", "past week", "past month", "past year"], + 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. Leave blank to include all domains.") + similar_url = st.text_input("**Similar URL**", value="", help="Provide a URL to find similar results. Leave blank if not needed.") + + # 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 - } - -def images_personalization(sb): - """ - Sidebar images personalization section. - - Parameters: - - sb: The Streamlit sidebar object. - - Returns: - - dict: Dictionary containing personalized images configuration. - """ - with sb.expander("**🩻 Images Personalization**"): - image_generation_model = sb.selectbox("**Image Generation Model**", options=IMAGE_MODEL_OPTIONS, help="Select the model to generate images for the blog.") - number_of_blog_images = sb.number_input("**Number of Blog Images**", value=1, help="Specify the number of images to include in the blog.") - return { + }, + "Blog Images Details": { "Image Generation Model": image_generation_model, "Number of Blog Images": number_of_blog_images - } - -def llm_personalization(sb): - """ - Sidebar LLM personalization section. - - Parameters: - - sb: The Streamlit sidebar object. - - Returns: - - dict: Dictionary containing personalized LLM configuration. - """ - with sb.expander("**πŸ€– LLM Personalization**"): - gpt_provider = sb.selectbox("**GPT Provider**", options=GPT_PROVIDER_OPTIONS, help="Select the provider for the GPT model.") - model = sb.text_input("**Model**", value="gemini-1.5-flash-latest", help="Specify the model version to use from the selected provider.") - temperature = sb.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 = sb.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 = sb.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 = sb.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 = sb.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 = sb.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.") - return { + }, + "LLM Options": { "GPT Provider": gpt_provider, "Model": model, "Temperature": temperature, @@ -114,26 +192,8 @@ def llm_personalization(sb): "N": n, "Frequency Penalty": frequency_penalty, "Presence Penalty": presence_penalty - } - -def search_engine_personalization(sb): - """ - Sidebar search engine personalization section. - - Parameters: - - sb: The Streamlit sidebar object. - - Returns: - - dict: Dictionary containing personalized search engine configuration. - """ - with sb.expander("**πŸ•΅οΈ Search Engine Personalization**"): - geographic_location = sb.selectbox("**Geographic Location**", options=GEOGRAPHIC_LOCATION_OPTIONS, help="Select the geographic location for tailoring search results.") - search_language = sb.selectbox("**Search Language**", options=SEARCH_LANGUAGE_OPTIONS, help="Select the language for the search results.") - number_of_results = sb.number_input("**Number of Results**", value=10, min_value=1, max_value=20, help="Specify the number of search results to retrieve.") - time_range = sb.selectbox("**Time Range**", options=TIME_RANGE_OPTIONS, help="Select the time range for filtering search results.") - include_domains = sb.text_input("**Include Domains**", value="", help="List specific domains to include in search results.") - similar_url = sb.text_input("**Similar URL**", value="", help="Provide a URL to find similar results.") - return { + }, + "Search Engine Parameters": { "Geographic Location": geographic_location, "Search Language": search_language, "Number of Results": number_of_results, @@ -141,34 +201,27 @@ def search_engine_personalization(sb): "Include Domains": include_domains, "Similar URL": similar_url } - -def sidebar_configuration(): - """ - Sidebar configuration for personalization and settings. - This function consolidates various personalization settings into the sidebar. - """ - sb = st.sidebar - sb.title("πŸ› οΈ Personalization & Settings πŸ—οΈ") - - content_config = content_personalization(sb) - images_config = images_personalization(sb) - llm_config = llm_personalization(sb) - search_config = search_engine_personalization(sb) - - config = { - "Blog Content Characteristics": content_config, - "Blog Images Details": images_config, - "LLM Options": llm_config, - "Search Engine Parameters": search_config } - # Save the configuration to a file whenever a change is made + # 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. - """ + """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") @@ -176,10 +229,9 @@ def setup_environment_paths(): 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. - """ + """Provides a sidebar for modifying prompts.""" st.sidebar.title("πŸ“ Modify Prompts") prompts = read_prompts() @@ -195,20 +247,81 @@ def modify_prompts_sidebar(): else: st.sidebar.warning("No prompts found in the file.") -def main(): - """ - Main function to run the Streamlit app. - Initializes the environment, checks API keys, sets up paths, and configures the UI. - """ - load_dotenv() - setup_ui() - if check_all_api_keys(): - setup_environment_paths() - sidebar_configuration() - setup_tabs() - modify_prompts_sidebar() +# 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("**πŸ‘‡Select a content creation type:**", options, index=0, format_func=lambda x: f"πŸ“ {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 πŸ₯ΉπŸ₯Ή") + + +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"πŸ” {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() -