diff --git a/alwrity.py b/alwrity.py index 5048eafa..2e6bd090 100644 --- a/alwrity.py +++ b/alwrity.py @@ -15,6 +15,18 @@ 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 hardcoded values +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_TYPE_OPTIONS = ["Informational", "Commercial", "Company", "News", "Finance", "Competitor", "Programming", "Scholar"] +BLOG_LANGUAGE_OPTIONS = ["English", "Spanish", "German", "Chinese", "Arabic", "Nepali", "Hindi", "Hindustani", "Customize"] +BLOG_OUTPUT_FORMAT_OPTIONS = ["markdown", "HTML", "plaintext"] +IMAGE_GENERATION_MODEL_OPTIONS = ["stable-diffusion", "dalle2", "dalle3"] +GPT_PROVIDER_OPTIONS = ["google", "openai", "minstral"] +MAX_TOKENS_OPTIONS = [500, 1000, 2000, 4000, 16000, 32000, 64000] +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 process_folder_for_rag(folder_path): @@ -33,179 +45,151 @@ def save_config(config): st.error(f"An error occurred while saving the configuration: {e}") -# Sidebar configuration -def sidebar_configuration(): - st.sidebar.title("🛠️ Personalization & Settings 🏗️") +def handle_custom_input(label, default_options, help_text): + """ + Handles custom user input for selectbox options. + + Args: + label (str): The label for the selectbox. + default_options (list): The default options for the selectbox. + help_text (str): The help text for the selectbox. - with st.sidebar.expander("**👷 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.") + Returns: + str: The selected or custom input value. + """ + selected_option = st.selectbox(f"**{label}**", options=default_options, help=help_text) + if selected_option == "Customize": + custom_option = st.text_input(f"Enter your {label.lower()}", help=f"Specify your {label.lower()}.") + if custom_option: + return custom_option + else: + st.warning(f"Please specify your {label.lower()}.") + return selected_option - 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("**🤖 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("**🕵️ 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 - }, - "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 - } +def configure_content_personalization(): + """ + Configures the content personalization settings in the sidebar. + + Returns: + dict: A dictionary containing the blog content characteristics. + """ + st.sidebar.expander("**👷 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 = handle_custom_input("Content Tone", BLOG_TONE_OPTIONS, "Select the desired tone for the blog content.") + blog_demographic = handle_custom_input("Target Audience", BLOG_DEMOGRAPHIC_OPTIONS, "Select the primary audience for the blog content.") + blog_type = st.selectbox("**Content Type**", options=BLOG_TYPE_OPTIONS, help="Select the category that best describes the blog content.") + blog_language = handle_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=BLOG_OUTPUT_FORMAT_OPTIONS, help="Select the format for the blog output.") + return { + "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 } - # Writing the configuration to a file whenever a change is made - save_config(config) +def configure_images_personalization(): + """ + Configures the image personalization settings in the sidebar. + + Returns: + dict: A dictionary containing the blog image details. + """ + st.sidebar.expander("**🩻 Images Personalization**") + image_generation_model = st.selectbox("**Image Generation Model**", options=IMAGE_GENERATION_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.") + return { + "Image Generation Model": image_generation_model, + "Number of Blog Images": number_of_blog_images + } +def configure_llm_personalization(): + """ + Configures the LLM (Language Learning Model) personalization settings in the sidebar. + + Returns: + dict: A dictionary containing the LLM options. + """ + st.sidebar.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="Temperature controls the 'creativity' or randomness of the text generated by GPT.") + 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.") + 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.") + return { + "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 + } + +def configure_search_engine_personalization(): + """ + Configures the search engine personalization settings in the sidebar. + + Returns: + dict: A dictionary containing the search engine parameters. + """ + st.sidebar.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, max_value=20, min_value=1, 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. 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.") + return { + "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 + } + +def sidebar_configuration(): + """ + Configures the sidebar with various personalization and settings options for the AI Writer application. + + The function includes configurations for: + - Content Personalization + - Images Personalization + - LLM Personalization + - Search Engine Personalization + + The collected inputs are stored in a dictionary and saved to a configuration file. + """ + st.sidebar.title("🛠️ Personalization & Settings 🏗️") + + # Configure content personalization settings + blog_content_config = configure_content_personalization() + + # Configure image personalization settings + blog_images_config = configure_images_personalization() + + # Configure LLM personalization settings + llm_config = configure_llm_personalization() + + # Configure search engine personalization settings + search_engine_config = configure_search_engine_personalization() + + # Combine all configurations into a dictionary + config = { + "Blog Content Characteristics": blog_content_config, + "Blog Images Details": blog_images_config, + "LLM Options": llm_config, + "Search Engine Parameters": search_engine_config + } + + # Save the configuration whenever a change is made + save_config(config) def main():