# Information for personality.py ## Classes ### AIPersonality ```python class AIPersonality: def __init__(self, personality_package_path: str | Path, lollms_paths: LollmsPaths, config: LOLLMSConfig, model: LLMBinding = None, app: LoLLMsCom = None, run_scripts = True, selected_language = None, ignore_discussion_documents_rag = False, is_relative_path = True, installation_option: InstallOption = InstallOption.INSTALL_IF_NECESSARY, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any def InfoMessage(self, content, duration: int = 4, client_id = None, verbose: bool = True) -> Any def ShowBlockingMessage(self, content, client_id = None, verbose: bool = True) -> Any def HideBlockingMessage(self, client_id = None, verbose: bool = True) -> Any def info(self, content, duration: int = 4, client_id = None, verbose: bool = True) -> Any def warning(self, content, duration: int = 4, client_id = None, verbose: bool = True) -> Any def success(self, content, duration: int = 4, client_id = None, verbose: bool = True) -> Any def error(self, content, duration: int = 4, client_id = None, verbose: bool = True) -> Any def notify(self, content, notification_type: NotificationType = NotificationType.NOTIF_SUCCESS, duration: int = 4, client_id = None, display_type: NotificationDisplayType = NotificationDisplayType.TOAST, verbose = True) -> Any def new_message(self, message_text: str, message_type: MSG_TYPE = MSG_TYPE.MSG_TYPE_FULL, metadata = [], callback: Callable[([str, int, dict, list, Any], bool)] = None) -> Any def full(self, full_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any def ui(self, ui_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any def full_invisible_to_ai(self, full_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any def full_invisible_to_user(self, full_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any def build_prompt(self, prompt_parts: List[str], sacrifice_id: int = -1, context_size: int = None, minimum_spare_context_size: int = None) -> Any def add_collapsible_entry(self, title, content) -> Any def internet_search_with_vectorization(self, query, quick_search: bool = False, asses_using_llm = True) -> Any def sink(self, s = None, i = None, d = None) -> Any def yes_no(self, question: str, context: str = '', max_answer_length: int = 50, conditionning = '') -> bool def multichoice_question(self, question: str, possible_answers: list, context: str = '', max_answer_length: int = 50, conditionning = '') -> int def multichoice_ranking(self, question: str, possible_answers: list, context: str = '', max_answer_length: int = 50, conditionning = '') -> int def step_start(self, step_text, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any def step_end(self, step_text, status = True, callback: Callable[([str, int, dict, list], bool)] = None) -> Any def step(self, step_text, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any def print_prompt(self, title, prompt) -> Any def fast_gen_with_images(self, prompt: str, images: list, max_generation_size: int = None, placeholders: dict = {}, sacrifice: list = ['previous_discussion'], debug: bool = False, callback = None, show_progress = False) -> str def fast_gen(self, prompt: str, max_generation_size: int = None, placeholders: dict = {}, sacrifice: list = ['previous_discussion'], debug: bool = False, callback = None, show_progress = False, temperature = None, top_k = None, top_p = None, repeat_penalty = None, repeat_last_n = None) -> str def process(self, text: str, message_type: MSG_TYPE, callback = None, show_progress = False) -> Any def generate_with_images(self, prompt, images, max_size, temperature = None, top_k = None, top_p = None, repeat_penalty = None, repeat_last_n = None, callback = None, debug = False, show_progress = False) -> Any def generate(self, prompt, max_size = None, temperature = None, top_k = None, top_p = None, repeat_penalty = None, repeat_last_n = None, callback = None, debug = False, show_progress = False) -> Any def setCallback(self, callback: Callable[([str, MSG_TYPE, dict, list], bool)]) -> Any def __str__(self) -> Any def load_personality(self, package_path = None) -> Any def remove_file(self, file_name, callback = None) -> Any def remove_all_files(self, callback = None) -> Any def add_file(self, path, client: Client, callback = None, process = True) -> Any def save_personality(self, package_path = None) -> Any def as_dict(self) -> Any def conditionning_commands(self) -> Any def logo(self) -> Any def version(self) -> Any def version(self, value) -> Any def author(self) -> Any def author(self, value) -> Any def name(self) -> str def name(self, value: str) -> Any def user_name(self) -> str def user_name(self, value: str) -> Any def language(self) -> str def category(self) -> str def category_desc(self) -> str def language(self, value: str) -> Any def category(self, value: str) -> Any def category_desc(self, value: str) -> Any def supported_languages(self) -> str def supported_languages(self, value: str) -> Any def selected_language(self) -> str def selected_language(self, value: str) -> Any def ignore_discussion_documents_rag(self) -> str def ignore_discussion_documents_rag(self, value: str) -> Any def personality_description(self) -> str def personality_description(self, description: str) -> Any def personality_conditioning(self) -> str def personality_conditioning(self, conditioning: str) -> Any def prompts_list(self) -> str def prompts_list(self, prompts: str) -> Any def welcome_message(self) -> str def welcome_message(self, message: str) -> Any def include_welcome_message_in_discussion(self) -> bool def include_welcome_message_in_discussion(self, message: bool) -> Any def user_message_prefix(self) -> str def user_message_prefix(self, prefix: str) -> Any def link_text(self) -> str def link_text(self, text: str) -> Any def ai_message_prefix(self) -> Any def ai_message_prefix(self, prefix) -> Any def dependencies(self) -> List[str] def dependencies(self, dependencies: List[str]) -> Any def disclaimer(self) -> str def disclaimer(self, disclaimer: str) -> Any def help(self) -> str def help(self, help: str) -> Any def commands(self) -> str def commands(self, commands: str) -> Any def model_temperature(self) -> float def model_temperature(self, value: float) -> Any def model_top_k(self) -> int def model_top_k(self, value: int) -> Any def model_top_p(self) -> float def model_top_p(self, value: float) -> Any def model_repeat_penalty(self) -> float def model_repeat_penalty(self, value: float) -> Any def model_repeat_last_n(self) -> int def model_repeat_last_n(self, value: int) -> Any def assets_list(self) -> list def assets_list(self, value: list) -> Any def processor(self) -> APScript def processor(self, value: APScript) -> Any def processor_cfg(self) -> list def processor_cfg(self, value: dict) -> Any def start_header_id_template(self) -> str def end_header_id_template(self) -> str def system_message_template(self) -> str def separator_template(self) -> str def start_user_header_id_template(self) -> str def end_user_header_id_template(self) -> str def end_user_message_id_template(self) -> str def start_ai_header_id_template(self) -> str def end_ai_header_id_template(self) -> str def end_ai_message_id_template(self) -> str def system_full_header(self) -> str def user_full_header(self) -> str def ai_full_header(self) -> str def system_custom_header(self, ai_name) -> str def ai_custom_header(self, ai_name) -> str def detect_antiprompt(self, text: str) -> bool def replace_keys(input_string, replacements) -> Any def verify_rag_entry(self, query, rag_entry) -> Any def translate(self, text_chunk, output_language = 'french', max_generation_size = 3000) -> Any def summarize_text(self, text, summary_instruction = 'summarize', doc_name = 'chunk', answer_start = '', max_generation_size = 3000, max_summary_size = 512, callback = None, chunk_summary_post_processing = None, summary_mode = SUMMARY_MODE.SUMMARY_MODE_SEQUENCIAL) -> Any def smart_data_extraction(self, text, data_extraction_instruction = f'summarize the current chunk.', final_task_instruction = 'reformulate with better wording', doc_name = 'chunk', answer_start = '', max_generation_size = 3000, max_summary_size = 512, callback = None, chunk_summary_post_processing = None, summary_mode = SUMMARY_MODE.SUMMARY_MODE_SEQUENCIAL) -> Any def summarize_chunks(self, chunks, summary_instruction = f'summarize the current chunk.', doc_name = 'chunk', answer_start = '', max_generation_size = 3000, callback = None, chunk_summary_post_processing = None, summary_mode = SUMMARY_MODE.SUMMARY_MODE_SEQUENCIAL) -> Any def sequencial_chunks_summary(self, chunks, summary_instruction = 'summarize', doc_name = 'chunk', answer_start = '', max_generation_size = 3000, callback = None, chunk_summary_post_processing = None) -> Any ``` ### StateMachine ```python class StateMachine: def __init__(self, states_list) -> Any def goto_state(self, state) -> Any def process_state(self, command, full_context, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None, context_state: dict = None, client: Client = None) -> Any ``` ### LoLLMsActionParameters ```python class LoLLMsActionParameters: def __init__(self, name: str, parameter_type: Type, range: Optional[List] = None, options: Optional[List] = None, value: Any = None) -> None def __str__(self) -> str def from_str(string: str) -> LoLLMsActionParameters def from_dict(parameter_dict: dict) -> LoLLMsActionParameters ``` ### LoLLMsActionParametersEncoder ```python class LoLLMsActionParametersEncoder: def default(self, obj) -> Any ``` ### LoLLMsAction ```python class LoLLMsAction: def __init__(self, name, parameters: List[LoLLMsActionParameters], callback: Callable, description: str = '') -> None def __str__(self) -> str def from_str(string: str) -> LoLLMsAction def from_dict(action_dict: dict) -> LoLLMsAction def run(self) -> None ``` ### APScript ```python class APScript: def __init__(self, personality: AIPersonality, personality_config: TypedConfig, states_list: dict = {}, callback = None) -> None def sink(self, s = None, i = None, d = None) -> Any def settings_updated(self) -> Any def mounted(self) -> Any def get_welcome(self, welcome_message: str, client: Client) -> Any def selected(self) -> Any def execute_command(self, command: str, parameters: list = [], client: Client = None) -> Any def load_personality_config(self) -> Any def install(self) -> Any def uninstall(self) -> Any def add_file(self, path, client: Client, callback = None, process = True) -> Any def remove_file(self, path) -> Any def load_config_file(self, path, default_config = None) -> Any def save_config_file(self, path, data) -> Any def generate_with_images(self, prompt, images, max_size = None, temperature = None, top_k = None, top_p = None, repeat_penalty = None, repeat_last_n = None, callback = None, debug = False) -> Any def generate(self, prompt, max_size = None, temperature = None, top_k = None, top_p = None, repeat_penalty = None, repeat_last_n = None, callback = None, debug = False) -> Any def run_workflow(self, prompt: str, previous_discussion_text: str = '', callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None, context_details: dict = None, client: Client = None) -> Any def compile_latex(self, file_path, pdf_latex_path = None) -> Any def find_numeric_value(self, text) -> Any def remove_backticks(self, text) -> Any def search_duckduckgo(self, query: str, max_results: int = 10, instant_answers: bool = True, regular_search_queries: bool = True, get_webpage_content: bool = False) -> List[Dict[(str, Union[str, None])]] def translate(self, text_chunk, output_language = 'french', max_generation_size = 3000) -> Any def summarize_text(self, text, summary_instruction = 'summarize', doc_name = 'chunk', answer_start = '', max_generation_size = 3000, max_summary_size = 512, callback = None, chunk_summary_post_processing = None, summary_mode = SUMMARY_MODE.SUMMARY_MODE_SEQUENCIAL) -> Any def smart_data_extraction(self, text, data_extraction_instruction = 'summarize', final_task_instruction = 'reformulate with better wording', doc_name = 'chunk', answer_start = '', max_generation_size = 3000, max_summary_size = 512, callback = None, chunk_summary_post_processing = None, summary_mode = SUMMARY_MODE.SUMMARY_MODE_SEQUENCIAL) -> Any def summarize_chunks(self, chunks, summary_instruction = 'summarize', doc_name = 'chunk', answer_start = '', max_generation_size = 3000, callback = None, chunk_summary_post_processing = None, summary_mode = SUMMARY_MODE.SUMMARY_MODE_SEQUENCIAL) -> Any def sequencial_chunks_summary(self, chunks, summary_instruction = 'summarize', doc_name = 'chunk', answer_start = '', max_generation_size = 3000, callback = None, chunk_summary_post_processing = None) -> Any def build_prompt_from_context_details(self, context_details: dict, custom_entries = '', suppress = []) -> Any def build_prompt(self, prompt_parts: List[str], sacrifice_id: int = -1, context_size: int = None, minimum_spare_context_size: int = None) -> Any def add_collapsible_entry(self, title, content, subtitle = '') -> Any def internet_search_with_vectorization(self, query, quick_search: bool = False) -> Any def vectorize_and_query(self, title, url, text, query, max_chunk_size = 512, overlap_size = 20, internet_vectorization_nb_chunks = 3) -> Any def step_start(self, step_text, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any def step_end(self, step_text, status = True, callback: Callable[([str, int, dict, list], bool)] = None) -> Any def step(self, step_text, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any def exception(self, ex, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any def warning(self, warning: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any def json(self, title: str, json_infos: dict, callback: Callable[([str, int, dict, list], bool)] = None, indent = 4) -> Any def ui(self, html_ui: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any def ui_in_iframe(self, html_ui: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any def code(self, code: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any def chunk(self, full_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any def full(self, full_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None, msg_type: MSG_TYPE = MSG_TYPE.MSG_TYPE_FULL) -> Any def full_invisible_to_ai(self, full_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any def full_invisible_to_user(self, full_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any def execute_python(self, code, code_folder = None, code_file_name = None) -> Any def build_python_code(self, prompt, max_title_length = 4096) -> Any def make_title(self, prompt, max_title_length: int = 50) -> Any def plan_with_images(self, request: str, images: list, actions_list: list = [LoLLMsAction], context: str = '', max_answer_length: int = 512) -> List[LoLLMsAction] def plan(self, request: str, actions_list: list = [LoLLMsAction], context: str = '', max_answer_length: int = 512) -> List[LoLLMsAction] def parse_directory_structure(self, structure) -> Any def extract_code_blocks(self, text: str) -> List[dict] def build_and_execute_python_code(self, context, instructions, execution_function_signature, extra_imports = '') -> Any def yes_no(self, question: str, context: str = '', max_answer_length: int = 50, conditionning = '') -> bool def multichoice_question(self, question: str, possible_answers: list, context: str = '', max_answer_length: int = 50, conditionning = '') -> int def multichoice_ranking(self, question: str, possible_answers: list, context: str = '', max_answer_length: int = 50, conditionning = '') -> int def build_html5_integration(self, html, ifram_name = 'unnamed') -> Any def InfoMessage(self, content, client_id = None, verbose: bool = None) -> Any def info(self, info_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any def step_progress(self, step_text: str, progress: float, callback: Callable[([str, MSG_TYPE, dict, list, AIPersonality], bool)] = None) -> Any def new_message(self, message_text: str, message_type: MSG_TYPE = MSG_TYPE.MSG_TYPE_FULL, metadata = [], callback: Callable[([str, int, dict, list, AIPersonality], bool)] = None) -> Any def finished_message(self, message_text: str = '', callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any def print_prompt(self, title, prompt) -> Any def fast_gen_with_images(self, prompt: str, images: list, max_generation_size: int = None, placeholders: dict = {}, sacrifice: list = ['previous_discussion'], debug: bool = False, callback = None, show_progress = False) -> str def fast_gen(self, prompt: str, max_generation_size: int = None, placeholders: dict = {}, sacrifice: list = ['previous_discussion'], debug: bool = False, callback = None, show_progress = False) -> str def mix_it_up(self, prompt: str, models, master_model, nb_rounds = 2, max_generation_size: int = None, placeholders: dict = {}, sacrifice: list = ['previous_discussion'], debug: bool = False, callback = None, show_progress = False) -> dict def generate_with_function_calls(self, context_details: dict, functions: List[Dict[(str, Any)]], max_answer_length: Optional[int] = None, callback = None) -> List[Dict[(str, Any)]] def generate_with_function_calls_and_images(self, context_details: dict, images: list, functions: List[Dict[(str, Any)]], max_answer_length: Optional[int] = None, callback = None) -> List[Dict[(str, Any)]] def execute_function(self, code, function_definitions = None) -> Any def execute_function_calls(self, function_calls: List[Dict[(str, Any)]], function_definitions: List[Dict[(str, Any)]]) -> List[Any] def transform_functions_to_text(self, functions) -> Any def transform_functions(self, functions) -> Any def _upgrade_prompt_with_function_info(self, context_details: dict, functions: List[Dict[(str, Any)]]) -> str def extract_function_calls_as_json(self, text: str) -> List[Dict[(str, Any)]] def interact(self, context_details, callback = None) -> Any def interact_with_function_call(self, context_details, function_definitions, prompt_after_execution = True, callback = None, hide_function_call = False, separate_output = False, max_nested_function_calls = 10) -> Any def path2url(file) -> Any def build_a_document_block(self, title = 'Title', link = '', content = 'content') -> Any def build_a_folder_link(self, folder_path, link_text = 'Open Folder') -> Any def build_a_file_link(self, file_path, link_text = 'Open Folder') -> Any def compress_js(self, code) -> Any def compress_python(self, code) -> Any def compress_html(self, code) -> Any def select_model(self, binding_name, model_name) -> Any def verify_rag_entry(self, query, rag_entry) -> Any def start_header_id_template(self) -> str def end_header_id_template(self) -> str def system_message_template(self) -> str def separator_template(self) -> str def start_user_header_id_template(self) -> str def end_user_header_id_template(self) -> str def end_user_message_id_template(self) -> str def start_ai_header_id_template(self) -> str def end_ai_header_id_template(self) -> str def end_ai_message_id_template(self) -> str def system_full_header(self) -> str def user_full_header(self) -> str def ai_full_header(self) -> str def system_custom_header(self, ai_name) -> str def ai_custom_header(self, ai_name) -> str ``` ### AIPersonalityInstaller ```python class AIPersonalityInstaller: def __init__(self, personality: AIPersonality) -> None ``` ### PersonalityBuilder ```python class PersonalityBuilder: def __init__(self, lollms_paths: LollmsPaths, config: LOLLMSConfig, model: LLMBinding, app = None, installation_option: InstallOption = InstallOption.INSTALL_IF_NECESSARY, callback = None) -> Any def build_personality(self, id: int = None) -> Any def get_personality(self) -> Any def extract_function_call(self, query) -> Any ``` ## Functions ### get_element_id ```python def get_element_id(url, text) -> Any ``` ### craft_a_tag_to_specific_text ```python def craft_a_tag_to_specific_text(url, text, caption) -> Any ``` ### is_package_installed ```python def is_package_installed(package_name) -> Any ``` ### install_package ```python def install_package(package_name) -> Any ``` ### fix_json ```python def fix_json(json_text) -> Any ``` ### generate_actions ```python def generate_actions(potential_actions: List[LoLLMsAction], parsed_text: dict) -> List[LoLLMsAction] ``` ### __init__ ```python def __init__(self, personality_package_path: str | Path, lollms_paths: LollmsPaths, config: LOLLMSConfig, model: LLMBinding = None, app: LoLLMsCom = None, run_scripts = True, selected_language = None, ignore_discussion_documents_rag = False, is_relative_path = True, installation_option: InstallOption = InstallOption.INSTALL_IF_NECESSARY, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any ``` ### InfoMessage ```python def InfoMessage(self, content, duration: int = 4, client_id = None, verbose: bool = True) -> Any ``` ### ShowBlockingMessage ```python def ShowBlockingMessage(self, content, client_id = None, verbose: bool = True) -> Any ``` ### HideBlockingMessage ```python def HideBlockingMessage(self, client_id = None, verbose: bool = True) -> Any ``` ### info ```python def info(self, content, duration: int = 4, client_id = None, verbose: bool = True) -> Any ``` ### warning ```python def warning(self, content, duration: int = 4, client_id = None, verbose: bool = True) -> Any ``` ### success ```python def success(self, content, duration: int = 4, client_id = None, verbose: bool = True) -> Any ``` ### error ```python def error(self, content, duration: int = 4, client_id = None, verbose: bool = True) -> Any ``` ### notify ```python def notify(self, content, notification_type: NotificationType = NotificationType.NOTIF_SUCCESS, duration: int = 4, client_id = None, display_type: NotificationDisplayType = NotificationDisplayType.TOAST, verbose = True) -> Any ``` ### new_message ```python def new_message(self, message_text: str, message_type: MSG_TYPE = MSG_TYPE.MSG_TYPE_FULL, metadata = [], callback: Callable[([str, int, dict, list, Any], bool)] = None) -> Any ``` ### full ```python def full(self, full_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any ``` ### ui ```python def ui(self, ui_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any ``` ### full_invisible_to_ai ```python def full_invisible_to_ai(self, full_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any ``` ### full_invisible_to_user ```python def full_invisible_to_user(self, full_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any ``` ### build_prompt ```python def build_prompt(self, prompt_parts: List[str], sacrifice_id: int = -1, context_size: int = None, minimum_spare_context_size: int = None) -> Any ``` ### add_collapsible_entry ```python def add_collapsible_entry(self, title, content) -> Any ``` ### internet_search_with_vectorization ```python def internet_search_with_vectorization(self, query, quick_search: bool = False, asses_using_llm = True) -> Any ``` ### sink ```python def sink(self, s = None, i = None, d = None) -> Any ``` ### yes_no ```python def yes_no(self, question: str, context: str = '', max_answer_length: int = 50, conditionning = '') -> bool ``` ### multichoice_question ```python def multichoice_question(self, question: str, possible_answers: list, context: str = '', max_answer_length: int = 50, conditionning = '') -> int ``` ### multichoice_ranking ```python def multichoice_ranking(self, question: str, possible_answers: list, context: str = '', max_answer_length: int = 50, conditionning = '') -> int ``` ### step_start ```python def step_start(self, step_text, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any ``` ### step_end ```python def step_end(self, step_text, status = True, callback: Callable[([str, int, dict, list], bool)] = None) -> Any ``` ### step ```python def step(self, step_text, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any ``` ### print_prompt ```python def print_prompt(self, title, prompt) -> Any ``` ### fast_gen_with_images ```python def fast_gen_with_images(self, prompt: str, images: list, max_generation_size: int = None, placeholders: dict = {}, sacrifice: list = ['previous_discussion'], debug: bool = False, callback = None, show_progress = False) -> str ``` ### fast_gen ```python def fast_gen(self, prompt: str, max_generation_size: int = None, placeholders: dict = {}, sacrifice: list = ['previous_discussion'], debug: bool = False, callback = None, show_progress = False, temperature = None, top_k = None, top_p = None, repeat_penalty = None, repeat_last_n = None) -> str ``` ### process ```python def process(self, text: str, message_type: MSG_TYPE, callback = None, show_progress = False) -> Any ``` ### generate_with_images ```python def generate_with_images(self, prompt, images, max_size, temperature = None, top_k = None, top_p = None, repeat_penalty = None, repeat_last_n = None, callback = None, debug = False, show_progress = False) -> Any ``` ### generate ```python def generate(self, prompt, max_size = None, temperature = None, top_k = None, top_p = None, repeat_penalty = None, repeat_last_n = None, callback = None, debug = False, show_progress = False) -> Any ``` ### setCallback ```python def setCallback(self, callback: Callable[([str, MSG_TYPE, dict, list], bool)]) -> Any ``` ### __str__ ```python def __str__(self) -> Any ``` ### load_personality ```python def load_personality(self, package_path = None) -> Any ``` ### remove_file ```python def remove_file(self, file_name, callback = None) -> Any ``` ### remove_all_files ```python def remove_all_files(self, callback = None) -> Any ``` ### add_file ```python def add_file(self, path, client: Client, callback = None, process = True) -> Any ``` ### save_personality ```python def save_personality(self, package_path = None) -> Any ``` ### as_dict ```python def as_dict(self) -> Any ``` ### conditionning_commands ```python def conditionning_commands(self) -> Any ``` ### logo ```python def logo(self) -> Any ``` ### version ```python def version(self) -> Any ``` ### version ```python def version(self, value) -> Any ``` ### author ```python def author(self) -> Any ``` ### author ```python def author(self, value) -> Any ``` ### name ```python def name(self) -> str ``` ### name ```python def name(self, value: str) -> Any ``` ### user_name ```python def user_name(self) -> str ``` ### user_name ```python def user_name(self, value: str) -> Any ``` ### language ```python def language(self) -> str ``` ### category ```python def category(self) -> str ``` ### category_desc ```python def category_desc(self) -> str ``` ### language ```python def language(self, value: str) -> Any ``` ### category ```python def category(self, value: str) -> Any ``` ### category_desc ```python def category_desc(self, value: str) -> Any ``` ### supported_languages ```python def supported_languages(self) -> str ``` ### supported_languages ```python def supported_languages(self, value: str) -> Any ``` ### selected_language ```python def selected_language(self) -> str ``` ### selected_language ```python def selected_language(self, value: str) -> Any ``` ### ignore_discussion_documents_rag ```python def ignore_discussion_documents_rag(self) -> str ``` ### ignore_discussion_documents_rag ```python def ignore_discussion_documents_rag(self, value: str) -> Any ``` ### personality_description ```python def personality_description(self) -> str ``` ### personality_description ```python def personality_description(self, description: str) -> Any ``` ### personality_conditioning ```python def personality_conditioning(self) -> str ``` ### personality_conditioning ```python def personality_conditioning(self, conditioning: str) -> Any ``` ### prompts_list ```python def prompts_list(self) -> str ``` ### prompts_list ```python def prompts_list(self, prompts: str) -> Any ``` ### welcome_message ```python def welcome_message(self) -> str ``` ### welcome_message ```python def welcome_message(self, message: str) -> Any ``` ### include_welcome_message_in_discussion ```python def include_welcome_message_in_discussion(self) -> bool ``` ### include_welcome_message_in_discussion ```python def include_welcome_message_in_discussion(self, message: bool) -> Any ``` ### user_message_prefix ```python def user_message_prefix(self) -> str ``` ### user_message_prefix ```python def user_message_prefix(self, prefix: str) -> Any ``` ### link_text ```python def link_text(self) -> str ``` ### link_text ```python def link_text(self, text: str) -> Any ``` ### ai_message_prefix ```python def ai_message_prefix(self) -> Any ``` ### ai_message_prefix ```python def ai_message_prefix(self, prefix) -> Any ``` ### dependencies ```python def dependencies(self) -> List[str] ``` ### dependencies ```python def dependencies(self, dependencies: List[str]) -> Any ``` ### disclaimer ```python def disclaimer(self) -> str ``` ### disclaimer ```python def disclaimer(self, disclaimer: str) -> Any ``` ### help ```python def help(self) -> str ``` ### help ```python def help(self, help: str) -> Any ``` ### commands ```python def commands(self) -> str ``` ### commands ```python def commands(self, commands: str) -> Any ``` ### model_temperature ```python def model_temperature(self) -> float ``` ### model_temperature ```python def model_temperature(self, value: float) -> Any ``` ### model_top_k ```python def model_top_k(self) -> int ``` ### model_top_k ```python def model_top_k(self, value: int) -> Any ``` ### model_top_p ```python def model_top_p(self) -> float ``` ### model_top_p ```python def model_top_p(self, value: float) -> Any ``` ### model_repeat_penalty ```python def model_repeat_penalty(self) -> float ``` ### model_repeat_penalty ```python def model_repeat_penalty(self, value: float) -> Any ``` ### model_repeat_last_n ```python def model_repeat_last_n(self) -> int ``` ### model_repeat_last_n ```python def model_repeat_last_n(self, value: int) -> Any ``` ### assets_list ```python def assets_list(self) -> list ``` ### assets_list ```python def assets_list(self, value: list) -> Any ``` ### processor ```python def processor(self) -> APScript ``` ### processor ```python def processor(self, value: APScript) -> Any ``` ### processor_cfg ```python def processor_cfg(self) -> list ``` ### processor_cfg ```python def processor_cfg(self, value: dict) -> Any ``` ### start_header_id_template ```python def start_header_id_template(self) -> str ``` ### end_header_id_template ```python def end_header_id_template(self) -> str ``` ### system_message_template ```python def system_message_template(self) -> str ``` ### separator_template ```python def separator_template(self) -> str ``` ### start_user_header_id_template ```python def start_user_header_id_template(self) -> str ``` ### end_user_header_id_template ```python def end_user_header_id_template(self) -> str ``` ### end_user_message_id_template ```python def end_user_message_id_template(self) -> str ``` ### start_ai_header_id_template ```python def start_ai_header_id_template(self) -> str ``` ### end_ai_header_id_template ```python def end_ai_header_id_template(self) -> str ``` ### end_ai_message_id_template ```python def end_ai_message_id_template(self) -> str ``` ### system_full_header ```python def system_full_header(self) -> str ``` ### user_full_header ```python def user_full_header(self) -> str ``` ### ai_full_header ```python def ai_full_header(self) -> str ``` ### system_custom_header ```python def system_custom_header(self, ai_name) -> str ``` ### ai_custom_header ```python def ai_custom_header(self, ai_name) -> str ``` ### detect_antiprompt ```python def detect_antiprompt(self, text: str) -> bool ``` ### replace_keys ```python def replace_keys(input_string, replacements) -> Any ``` ### verify_rag_entry ```python def verify_rag_entry(self, query, rag_entry) -> Any ``` ### translate ```python def translate(self, text_chunk, output_language = 'french', max_generation_size = 3000) -> Any ``` ### summarize_text ```python def summarize_text(self, text, summary_instruction = 'summarize', doc_name = 'chunk', answer_start = '', max_generation_size = 3000, max_summary_size = 512, callback = None, chunk_summary_post_processing = None, summary_mode = SUMMARY_MODE.SUMMARY_MODE_SEQUENCIAL) -> Any ``` ### smart_data_extraction ```python def smart_data_extraction(self, text, data_extraction_instruction = f'summarize the current chunk.', final_task_instruction = 'reformulate with better wording', doc_name = 'chunk', answer_start = '', max_generation_size = 3000, max_summary_size = 512, callback = None, chunk_summary_post_processing = None, summary_mode = SUMMARY_MODE.SUMMARY_MODE_SEQUENCIAL) -> Any ``` ### summarize_chunks ```python def summarize_chunks(self, chunks, summary_instruction = f'summarize the current chunk.', doc_name = 'chunk', answer_start = '', max_generation_size = 3000, callback = None, chunk_summary_post_processing = None, summary_mode = SUMMARY_MODE.SUMMARY_MODE_SEQUENCIAL) -> Any ``` ### sequencial_chunks_summary ```python def sequencial_chunks_summary(self, chunks, summary_instruction = 'summarize', doc_name = 'chunk', answer_start = '', max_generation_size = 3000, callback = None, chunk_summary_post_processing = None) -> Any ``` ### __init__ ```python def __init__(self, states_list) -> Any ``` ### goto_state ```python def goto_state(self, state) -> Any ``` ### process_state ```python def process_state(self, command, full_context, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None, context_state: dict = None, client: Client = None) -> Any ``` ### __init__ ```python def __init__(self, name: str, parameter_type: Type, range: Optional[List] = None, options: Optional[List] = None, value: Any = None) -> None ``` ### __str__ ```python def __str__(self) -> str ``` ### from_str ```python def from_str(string: str) -> LoLLMsActionParameters ``` ### from_dict ```python def from_dict(parameter_dict: dict) -> LoLLMsActionParameters ``` ### default ```python def default(self, obj) -> Any ``` ### __init__ ```python def __init__(self, name, parameters: List[LoLLMsActionParameters], callback: Callable, description: str = '') -> None ``` ### __str__ ```python def __str__(self) -> str ``` ### from_str ```python def from_str(string: str) -> LoLLMsAction ``` ### from_dict ```python def from_dict(action_dict: dict) -> LoLLMsAction ``` ### run ```python def run(self) -> None ``` ### __init__ ```python def __init__(self, personality: AIPersonality, personality_config: TypedConfig, states_list: dict = {}, callback = None) -> None ``` ### sink ```python def sink(self, s = None, i = None, d = None) -> Any ``` ### settings_updated ```python def settings_updated(self) -> Any ``` ### mounted ```python def mounted(self) -> Any ``` ### get_welcome ```python def get_welcome(self, welcome_message: str, client: Client) -> Any ``` ### selected ```python def selected(self) -> Any ``` ### execute_command ```python def execute_command(self, command: str, parameters: list = [], client: Client = None) -> Any ``` ### load_personality_config ```python def load_personality_config(self) -> Any ``` ### install ```python def install(self) -> Any ``` ### uninstall ```python def uninstall(self) -> Any ``` ### add_file ```python def add_file(self, path, client: Client, callback = None, process = True) -> Any ``` ### remove_file ```python def remove_file(self, path) -> Any ``` ### load_config_file ```python def load_config_file(self, path, default_config = None) -> Any ``` ### save_config_file ```python def save_config_file(self, path, data) -> Any ``` ### generate_with_images ```python def generate_with_images(self, prompt, images, max_size = None, temperature = None, top_k = None, top_p = None, repeat_penalty = None, repeat_last_n = None, callback = None, debug = False) -> Any ``` ### generate ```python def generate(self, prompt, max_size = None, temperature = None, top_k = None, top_p = None, repeat_penalty = None, repeat_last_n = None, callback = None, debug = False) -> Any ``` ### run_workflow ```python def run_workflow(self, prompt: str, previous_discussion_text: str = '', callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None, context_details: dict = None, client: Client = None) -> Any ``` ### compile_latex ```python def compile_latex(self, file_path, pdf_latex_path = None) -> Any ``` ### find_numeric_value ```python def find_numeric_value(self, text) -> Any ``` ### remove_backticks ```python def remove_backticks(self, text) -> Any ``` ### search_duckduckgo ```python def search_duckduckgo(self, query: str, max_results: int = 10, instant_answers: bool = True, regular_search_queries: bool = True, get_webpage_content: bool = False) -> List[Dict[(str, Union[str, None])]] ``` ### translate ```python def translate(self, text_chunk, output_language = 'french', max_generation_size = 3000) -> Any ``` ### summarize_text ```python def summarize_text(self, text, summary_instruction = 'summarize', doc_name = 'chunk', answer_start = '', max_generation_size = 3000, max_summary_size = 512, callback = None, chunk_summary_post_processing = None, summary_mode = SUMMARY_MODE.SUMMARY_MODE_SEQUENCIAL) -> Any ``` ### smart_data_extraction ```python def smart_data_extraction(self, text, data_extraction_instruction = 'summarize', final_task_instruction = 'reformulate with better wording', doc_name = 'chunk', answer_start = '', max_generation_size = 3000, max_summary_size = 512, callback = None, chunk_summary_post_processing = None, summary_mode = SUMMARY_MODE.SUMMARY_MODE_SEQUENCIAL) -> Any ``` ### summarize_chunks ```python def summarize_chunks(self, chunks, summary_instruction = 'summarize', doc_name = 'chunk', answer_start = '', max_generation_size = 3000, callback = None, chunk_summary_post_processing = None, summary_mode = SUMMARY_MODE.SUMMARY_MODE_SEQUENCIAL) -> Any ``` ### sequencial_chunks_summary ```python def sequencial_chunks_summary(self, chunks, summary_instruction = 'summarize', doc_name = 'chunk', answer_start = '', max_generation_size = 3000, callback = None, chunk_summary_post_processing = None) -> Any ``` ### build_prompt_from_context_details ```python def build_prompt_from_context_details(self, context_details: dict, custom_entries = '', suppress = []) -> Any ``` ### build_prompt ```python def build_prompt(self, prompt_parts: List[str], sacrifice_id: int = -1, context_size: int = None, minimum_spare_context_size: int = None) -> Any ``` ### add_collapsible_entry ```python def add_collapsible_entry(self, title, content, subtitle = '') -> Any ``` ### internet_search_with_vectorization ```python def internet_search_with_vectorization(self, query, quick_search: bool = False) -> Any ``` ### vectorize_and_query ```python def vectorize_and_query(self, title, url, text, query, max_chunk_size = 512, overlap_size = 20, internet_vectorization_nb_chunks = 3) -> Any ``` ### step_start ```python def step_start(self, step_text, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any ``` ### step_end ```python def step_end(self, step_text, status = True, callback: Callable[([str, int, dict, list], bool)] = None) -> Any ``` ### step ```python def step(self, step_text, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any ``` ### exception ```python def exception(self, ex, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any ``` ### warning ```python def warning(self, warning: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any ``` ### json ```python def json(self, title: str, json_infos: dict, callback: Callable[([str, int, dict, list], bool)] = None, indent = 4) -> Any ``` ### ui ```python def ui(self, html_ui: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any ``` ### ui_in_iframe ```python def ui_in_iframe(self, html_ui: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any ``` ### code ```python def code(self, code: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any ``` ### chunk ```python def chunk(self, full_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any ``` ### full ```python def full(self, full_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None, msg_type: MSG_TYPE = MSG_TYPE.MSG_TYPE_FULL) -> Any ``` ### full_invisible_to_ai ```python def full_invisible_to_ai(self, full_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any ``` ### full_invisible_to_user ```python def full_invisible_to_user(self, full_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any ``` ### execute_python ```python def execute_python(self, code, code_folder = None, code_file_name = None) -> Any ``` ### build_python_code ```python def build_python_code(self, prompt, max_title_length = 4096) -> Any ``` ### make_title ```python def make_title(self, prompt, max_title_length: int = 50) -> Any ``` ### plan_with_images ```python def plan_with_images(self, request: str, images: list, actions_list: list = [LoLLMsAction], context: str = '', max_answer_length: int = 512) -> List[LoLLMsAction] ``` ### plan ```python def plan(self, request: str, actions_list: list = [LoLLMsAction], context: str = '', max_answer_length: int = 512) -> List[LoLLMsAction] ``` ### parse_directory_structure ```python def parse_directory_structure(self, structure) -> Any ``` ### extract_code_blocks ```python def extract_code_blocks(self, text: str) -> List[dict] ``` ### build_and_execute_python_code ```python def build_and_execute_python_code(self, context, instructions, execution_function_signature, extra_imports = '') -> Any ``` ### yes_no ```python def yes_no(self, question: str, context: str = '', max_answer_length: int = 50, conditionning = '') -> bool ``` ### multichoice_question ```python def multichoice_question(self, question: str, possible_answers: list, context: str = '', max_answer_length: int = 50, conditionning = '') -> int ``` ### multichoice_ranking ```python def multichoice_ranking(self, question: str, possible_answers: list, context: str = '', max_answer_length: int = 50, conditionning = '') -> int ``` ### build_html5_integration ```python def build_html5_integration(self, html, ifram_name = 'unnamed') -> Any ``` ### InfoMessage ```python def InfoMessage(self, content, client_id = None, verbose: bool = None) -> Any ``` ### info ```python def info(self, info_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any ``` ### step_progress ```python def step_progress(self, step_text: str, progress: float, callback: Callable[([str, MSG_TYPE, dict, list, AIPersonality], bool)] = None) -> Any ``` ### new_message ```python def new_message(self, message_text: str, message_type: MSG_TYPE = MSG_TYPE.MSG_TYPE_FULL, metadata = [], callback: Callable[([str, int, dict, list, AIPersonality], bool)] = None) -> Any ``` ### finished_message ```python def finished_message(self, message_text: str = '', callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any ``` ### print_prompt ```python def print_prompt(self, title, prompt) -> Any ``` ### fast_gen_with_images ```python def fast_gen_with_images(self, prompt: str, images: list, max_generation_size: int = None, placeholders: dict = {}, sacrifice: list = ['previous_discussion'], debug: bool = False, callback = None, show_progress = False) -> str ``` ### fast_gen ```python def fast_gen(self, prompt: str, max_generation_size: int = None, placeholders: dict = {}, sacrifice: list = ['previous_discussion'], debug: bool = False, callback = None, show_progress = False) -> str ``` ### mix_it_up ```python def mix_it_up(self, prompt: str, models, master_model, nb_rounds = 2, max_generation_size: int = None, placeholders: dict = {}, sacrifice: list = ['previous_discussion'], debug: bool = False, callback = None, show_progress = False) -> dict ``` ### generate_with_function_calls ```python def generate_with_function_calls(self, context_details: dict, functions: List[Dict[(str, Any)]], max_answer_length: Optional[int] = None, callback = None) -> List[Dict[(str, Any)]] ``` ### generate_with_function_calls_and_images ```python def generate_with_function_calls_and_images(self, context_details: dict, images: list, functions: List[Dict[(str, Any)]], max_answer_length: Optional[int] = None, callback = None) -> List[Dict[(str, Any)]] ``` ### execute_function ```python def execute_function(self, code, function_definitions = None) -> Any ``` ### execute_function_calls ```python def execute_function_calls(self, function_calls: List[Dict[(str, Any)]], function_definitions: List[Dict[(str, Any)]]) -> List[Any] ``` ### transform_functions_to_text ```python def transform_functions_to_text(self, functions) -> Any ``` ### transform_functions ```python def transform_functions(self, functions) -> Any ``` ### _upgrade_prompt_with_function_info ```python def _upgrade_prompt_with_function_info(self, context_details: dict, functions: List[Dict[(str, Any)]]) -> str ``` ### extract_function_calls_as_json ```python def extract_function_calls_as_json(self, text: str) -> List[Dict[(str, Any)]] ``` ### interact ```python def interact(self, context_details, callback = None) -> Any ``` ### interact_with_function_call ```python def interact_with_function_call(self, context_details, function_definitions, prompt_after_execution = True, callback = None, hide_function_call = False, separate_output = False, max_nested_function_calls = 10) -> Any ``` ### path2url ```python def path2url(file) -> Any ``` ### build_a_document_block ```python def build_a_document_block(self, title = 'Title', link = '', content = 'content') -> Any ``` ### build_a_folder_link ```python def build_a_folder_link(self, folder_path, link_text = 'Open Folder') -> Any ``` ### build_a_file_link ```python def build_a_file_link(self, file_path, link_text = 'Open Folder') -> Any ``` ### compress_js ```python def compress_js(self, code) -> Any ``` ### compress_python ```python def compress_python(self, code) -> Any ``` ### compress_html ```python def compress_html(self, code) -> Any ``` ### select_model ```python def select_model(self, binding_name, model_name) -> Any ``` ### verify_rag_entry ```python def verify_rag_entry(self, query, rag_entry) -> Any ``` ### start_header_id_template ```python def start_header_id_template(self) -> str ``` ### end_header_id_template ```python def end_header_id_template(self) -> str ``` ### system_message_template ```python def system_message_template(self) -> str ``` ### separator_template ```python def separator_template(self) -> str ``` ### start_user_header_id_template ```python def start_user_header_id_template(self) -> str ``` ### end_user_header_id_template ```python def end_user_header_id_template(self) -> str ``` ### end_user_message_id_template ```python def end_user_message_id_template(self) -> str ``` ### start_ai_header_id_template ```python def start_ai_header_id_template(self) -> str ``` ### end_ai_header_id_template ```python def end_ai_header_id_template(self) -> str ``` ### end_ai_message_id_template ```python def end_ai_message_id_template(self) -> str ``` ### system_full_header ```python def system_full_header(self) -> str ``` ### user_full_header ```python def user_full_header(self) -> str ``` ### ai_full_header ```python def ai_full_header(self) -> str ``` ### system_custom_header ```python def system_custom_header(self, ai_name) -> str ``` ### ai_custom_header ```python def ai_custom_header(self, ai_name) -> str ``` ### __init__ ```python def __init__(self, personality: AIPersonality) -> None ``` ### __init__ ```python def __init__(self, lollms_paths: LollmsPaths, config: LOLLMSConfig, model: LLMBinding, app = None, installation_option: InstallOption = InstallOption.INSTALL_IF_NECESSARY, callback = None) -> Any ``` ### build_personality ```python def build_personality(self, id: int = None) -> Any ``` ### get_personality ```python def get_personality(self) -> Any ``` ### extract_function_call ```python def extract_function_call(self, query) -> Any ``` ### replace ```python def replace(match) -> Any ```