lollms-webui/docs/Usable_infos_for building/personality_info.md

Information for personality.py

Classes

AIPersonality

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_OPERATION_TYPE.MSG_OPERATION_TYPE_SET_CONTENT, metadata = [], callback: Callable[([str, int, dict, list, Any], bool)] = None) -> Any
    def set_message_content(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 set_message_content_invisible_to_ai(self, full_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any
    def set_message_content_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

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

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

class LoLLMsActionParametersEncoder:
    def default(self, obj) -> Any

LoLLMsAction

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

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 add_chunk_to_message_content(self, full_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any
    def set_message_content(self, full_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None, msg_type: MSG_TYPE = MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_SET_CONTENT) -> Any
    def set_message_content_invisible_to_ai(self, full_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any
    def set_message_content_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_OPERATION_TYPE.MSG_OPERATION_TYPE_SET_CONTENT, 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

class AIPersonalityInstaller:
    def __init__(self, personality: AIPersonality) -> None

PersonalityBuilder

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

def get_element_id(url, text) -> Any

craft_a_tag_to_specific_text

def craft_a_tag_to_specific_text(url, text, caption) -> Any

is_package_installed

def is_package_installed(package_name) -> Any

install_package

def install_package(package_name) -> Any

fix_json

def fix_json(json_text) -> Any

generate_actions

def generate_actions(potential_actions: List[LoLLMsAction], parsed_text: dict) -> List[LoLLMsAction]

init

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

def InfoMessage(self, content, duration: int = 4, client_id = None, verbose: bool = True) -> Any

ShowBlockingMessage

def ShowBlockingMessage(self, content, client_id = None, verbose: bool = True) -> Any

HideBlockingMessage

def HideBlockingMessage(self, client_id = None, verbose: bool = True) -> Any

info

def info(self, content, duration: int = 4, client_id = None, verbose: bool = True) -> Any

warning

def warning(self, content, duration: int = 4, client_id = None, verbose: bool = True) -> Any

success

def success(self, content, duration: int = 4, client_id = None, verbose: bool = True) -> Any

error

def error(self, content, duration: int = 4, client_id = None, verbose: bool = True) -> Any

notify

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

def new_message(self, message_text: str, message_type: MSG_TYPE = MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_SET_CONTENT, metadata = [], callback: Callable[([str, int, dict, list, Any], bool)] = None) -> Any

full

def set_message_content(self, full_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any

ui

def ui(self, ui_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any

full_invisible_to_ai

def set_message_content_invisible_to_ai(self, full_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any

full_invisible_to_user

def set_message_content_invisible_to_user(self, full_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any

build_prompt

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

def add_collapsible_entry(self, title, content) -> Any

internet_search_with_vectorization

def internet_search_with_vectorization(self, query, quick_search: bool = False, asses_using_llm = True) -> Any

sink

def sink(self, s = None, i = None, d = None) -> Any

yes_no

def yes_no(self, question: str, context: str = '', max_answer_length: int = 50, conditionning = '') -> bool

multichoice_question

def multichoice_question(self, question: str, possible_answers: list, context: str = '', max_answer_length: int = 50, conditionning = '') -> int

multichoice_ranking

def multichoice_ranking(self, question: str, possible_answers: list, context: str = '', max_answer_length: int = 50, conditionning = '') -> int

step_start

def step_start(self, step_text, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any

step_end

def step_end(self, step_text, status = True, callback: Callable[([str, int, dict, list], bool)] = None) -> Any

step

def step(self, step_text, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any

print_prompt

def print_prompt(self, title, prompt) -> Any

fast_gen_with_images

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

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

def process(self, text: str, message_type: MSG_TYPE, callback = None, show_progress = False) -> Any

generate_with_images

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

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

def setCallback(self, callback: Callable[([str, MSG_TYPE, dict, list], bool)]) -> Any

str

def __str__(self) -> Any

load_personality

def load_personality(self, package_path = None) -> Any

remove_file

def remove_file(self, file_name, callback = None) -> Any

remove_all_files

def remove_all_files(self, callback = None) -> Any

add_file

def add_file(self, path, client: Client, callback = None, process = True) -> Any

save_personality

def save_personality(self, package_path = None) -> Any

as_dict

def as_dict(self) -> Any

conditionning_commands

def conditionning_commands(self) -> Any

logo

def logo(self) -> Any

version

def version(self) -> Any

version

def version(self, value) -> Any

author

def author(self) -> Any

author

def author(self, value) -> Any

name

def name(self) -> str

name

def name(self, value: str) -> Any

user_name

def user_name(self) -> str

user_name

def user_name(self, value: str) -> Any

language

def language(self) -> str

category

def category(self) -> str

category_desc

def category_desc(self) -> str

language

def language(self, value: str) -> Any

category

def category(self, value: str) -> Any

category_desc

def category_desc(self, value: str) -> Any

supported_languages

def supported_languages(self) -> str

supported_languages

def supported_languages(self, value: str) -> Any

selected_language

def selected_language(self) -> str

selected_language

def selected_language(self, value: str) -> Any

ignore_discussion_documents_rag

def ignore_discussion_documents_rag(self) -> str

ignore_discussion_documents_rag

def ignore_discussion_documents_rag(self, value: str) -> Any

personality_description

def personality_description(self) -> str

personality_description

def personality_description(self, description: str) -> Any

personality_conditioning

def personality_conditioning(self) -> str

personality_conditioning

def personality_conditioning(self, conditioning: str) -> Any

prompts_list

def prompts_list(self) -> str

prompts_list

def prompts_list(self, prompts: str) -> Any

welcome_message

def welcome_message(self) -> str

welcome_message

def welcome_message(self, message: str) -> Any

include_welcome_message_in_discussion

def include_welcome_message_in_discussion(self) -> bool

include_welcome_message_in_discussion

def include_welcome_message_in_discussion(self, message: bool) -> Any

user_message_prefix

def user_message_prefix(self) -> str

user_message_prefix

def user_message_prefix(self, prefix: str) -> Any

link_text

def link_text(self) -> str

link_text

def link_text(self, text: str) -> Any

ai_message_prefix

def ai_message_prefix(self) -> Any

ai_message_prefix

def ai_message_prefix(self, prefix) -> Any

dependencies

def dependencies(self) -> List[str]

dependencies

def dependencies(self, dependencies: List[str]) -> Any

disclaimer

def disclaimer(self) -> str

disclaimer

def disclaimer(self, disclaimer: str) -> Any

help

def help(self) -> str

help

def help(self, help: str) -> Any

commands

def commands(self) -> str

commands

def commands(self, commands: str) -> Any

model_temperature

def model_temperature(self) -> float

model_temperature

def model_temperature(self, value: float) -> Any

model_top_k

def model_top_k(self) -> int

model_top_k

def model_top_k(self, value: int) -> Any

model_top_p

def model_top_p(self) -> float

model_top_p

def model_top_p(self, value: float) -> Any

model_repeat_penalty

def model_repeat_penalty(self) -> float

model_repeat_penalty

def model_repeat_penalty(self, value: float) -> Any

model_repeat_last_n

def model_repeat_last_n(self) -> int

model_repeat_last_n

def model_repeat_last_n(self, value: int) -> Any

assets_list

def assets_list(self) -> list

assets_list

def assets_list(self, value: list) -> Any

processor

def processor(self) -> APScript

processor

def processor(self, value: APScript) -> Any

processor_cfg

def processor_cfg(self) -> list

processor_cfg

def processor_cfg(self, value: dict) -> Any

start_header_id_template

def start_header_id_template(self) -> str

end_header_id_template

def end_header_id_template(self) -> str

system_message_template

def system_message_template(self) -> str

separator_template

def separator_template(self) -> str

start_user_header_id_template

def start_user_header_id_template(self) -> str

end_user_header_id_template

def end_user_header_id_template(self) -> str

end_user_message_id_template

def end_user_message_id_template(self) -> str

start_ai_header_id_template

def start_ai_header_id_template(self) -> str

end_ai_header_id_template

def end_ai_header_id_template(self) -> str

end_ai_message_id_template

def end_ai_message_id_template(self) -> str

system_full_header

def system_full_header(self) -> str

user_full_header

def user_full_header(self) -> str

ai_full_header

def ai_full_header(self) -> str

system_custom_header

def system_custom_header(self, ai_name) -> str

ai_custom_header

def ai_custom_header(self, ai_name) -> str

detect_antiprompt

def detect_antiprompt(self, text: str) -> bool

replace_keys

def replace_keys(input_string, replacements) -> Any

verify_rag_entry

def verify_rag_entry(self, query, rag_entry) -> Any

translate

def translate(self, text_chunk, output_language = 'french', max_generation_size = 3000) -> Any

summarize_text

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

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

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

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

def __init__(self, states_list) -> Any

goto_state

def goto_state(self, state) -> Any

process_state

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

def __init__(self, name: str, parameter_type: Type, range: Optional[List] = None, options: Optional[List] = None, value: Any = None) -> None

str

def __str__(self) -> str

from_str

def from_str(string: str) -> LoLLMsActionParameters

from_dict

def from_dict(parameter_dict: dict) -> LoLLMsActionParameters

default

def default(self, obj) -> Any

init

def __init__(self, name, parameters: List[LoLLMsActionParameters], callback: Callable, description: str = '') -> None

str

def __str__(self) -> str

from_str

def from_str(string: str) -> LoLLMsAction

from_dict

def from_dict(action_dict: dict) -> LoLLMsAction

run

def run(self) -> None

init

def __init__(self, personality: AIPersonality, personality_config: TypedConfig, states_list: dict = {}, callback = None) -> None

sink

def sink(self, s = None, i = None, d = None) -> Any

settings_updated

def settings_updated(self) -> Any

mounted

def mounted(self) -> Any

get_welcome

def get_welcome(self, welcome_message: str, client: Client) -> Any

selected

def selected(self) -> Any

execute_command

def execute_command(self, command: str, parameters: list = [], client: Client = None) -> Any

load_personality_config

def load_personality_config(self) -> Any

install

def install(self) -> Any

uninstall

def uninstall(self) -> Any

add_file

def add_file(self, path, client: Client, callback = None, process = True) -> Any

remove_file

def remove_file(self, path) -> Any

load_config_file

def load_config_file(self, path, default_config = None) -> Any

save_config_file

def save_config_file(self, path, data) -> Any

generate_with_images

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

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

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

def compile_latex(self, file_path, pdf_latex_path = None) -> Any

find_numeric_value

def find_numeric_value(self, text) -> Any

remove_backticks

def remove_backticks(self, text) -> Any

search_duckduckgo

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

def translate(self, text_chunk, output_language = 'french', max_generation_size = 3000) -> Any

summarize_text

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

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

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

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

def build_prompt_from_context_details(self, context_details: dict, custom_entries = '', suppress = []) -> Any

build_prompt

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

def add_collapsible_entry(self, title, content, subtitle = '') -> Any

internet_search_with_vectorization

def internet_search_with_vectorization(self, query, quick_search: bool = False) -> Any

vectorize_and_query

def vectorize_and_query(self, title, url, text, query, max_chunk_size = 512, overlap_size = 20, internet_vectorization_nb_chunks = 3) -> Any

step_start

def step_start(self, step_text, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any

step_end

def step_end(self, step_text, status = True, callback: Callable[([str, int, dict, list], bool)] = None) -> Any

step

def step(self, step_text, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any

exception

def exception(self, ex, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any

warning

def warning(self, warning: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any

json

def json(self, title: str, json_infos: dict, callback: Callable[([str, int, dict, list], bool)] = None, indent = 4) -> Any

ui

def ui(self, html_ui: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any

ui_in_iframe

def ui_in_iframe(self, html_ui: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any

code

def code(self, code: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any

chunk

def add_chunk_to_message_content(self, full_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any

full

def set_message_content(self, full_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None, msg_type: MSG_TYPE = MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_SET_CONTENT) -> Any

full_invisible_to_ai

def set_message_content_invisible_to_ai(self, full_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any

full_invisible_to_user

def set_message_content_invisible_to_user(self, full_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any

execute_python

def execute_python(self, code, code_folder = None, code_file_name = None) -> Any

build_python_code

def build_python_code(self, prompt, max_title_length = 4096) -> Any

make_title

def make_title(self, prompt, max_title_length: int = 50) -> Any

plan_with_images

def plan_with_images(self, request: str, images: list, actions_list: list = [LoLLMsAction], context: str = '', max_answer_length: int = 512) -> List[LoLLMsAction]

plan

def plan(self, request: str, actions_list: list = [LoLLMsAction], context: str = '', max_answer_length: int = 512) -> List[LoLLMsAction]

parse_directory_structure

def parse_directory_structure(self, structure) -> Any

extract_code_blocks

def extract_code_blocks(self, text: str) -> List[dict]

build_and_execute_python_code

def build_and_execute_python_code(self, context, instructions, execution_function_signature, extra_imports = '') -> Any

yes_no

def yes_no(self, question: str, context: str = '', max_answer_length: int = 50, conditionning = '') -> bool

multichoice_question

def multichoice_question(self, question: str, possible_answers: list, context: str = '', max_answer_length: int = 50, conditionning = '') -> int

multichoice_ranking

def multichoice_ranking(self, question: str, possible_answers: list, context: str = '', max_answer_length: int = 50, conditionning = '') -> int

build_html5_integration

def build_html5_integration(self, html, ifram_name = 'unnamed') -> Any

InfoMessage

def InfoMessage(self, content, client_id = None, verbose: bool = None) -> Any

info

def info(self, info_text: str, callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any

step_progress

def step_progress(self, step_text: str, progress: float, callback: Callable[([str, MSG_TYPE, dict, list, AIPersonality], bool)] = None) -> Any

new_message

def new_message(self, message_text: str, message_type: MSG_TYPE = MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_SET_CONTENT, metadata = [], callback: Callable[([str, int, dict, list, AIPersonality], bool)] = None) -> Any

finished_message

def finished_message(self, message_text: str = '', callback: Callable[([str, MSG_TYPE, dict, list], bool)] = None) -> Any

print_prompt

def print_prompt(self, title, prompt) -> Any

fast_gen_with_images

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

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

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

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

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

def execute_function(self, code, function_definitions = None) -> Any

execute_function_calls

def execute_function_calls(self, function_calls: List[Dict[(str, Any)]], function_definitions: List[Dict[(str, Any)]]) -> List[Any]

transform_functions_to_text

def transform_functions_to_text(self, functions) -> Any

transform_functions

def transform_functions(self, functions) -> Any

_upgrade_prompt_with_function_info

def _upgrade_prompt_with_function_info(self, context_details: dict, functions: List[Dict[(str, Any)]]) -> str

extract_function_calls_as_json

def extract_function_calls_as_json(self, text: str) -> List[Dict[(str, Any)]]

interact

def interact(self, context_details, callback = None) -> Any

interact_with_function_call

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

def path2url(file) -> Any

build_a_document_block

def build_a_document_block(self, title = 'Title', link = '', content = 'content') -> Any

build_a_folder_link

def build_a_folder_link(self, folder_path, link_text = 'Open Folder') -> Any

build_a_file_link

def build_a_file_link(self, file_path, link_text = 'Open Folder') -> Any

compress_js

def compress_js(self, code) -> Any

compress_python

def compress_python(self, code) -> Any

compress_html

def compress_html(self, code) -> Any

select_model

def select_model(self, binding_name, model_name) -> Any

verify_rag_entry

def verify_rag_entry(self, query, rag_entry) -> Any

start_header_id_template

def start_header_id_template(self) -> str

end_header_id_template

def end_header_id_template(self) -> str

system_message_template

def system_message_template(self) -> str

separator_template

def separator_template(self) -> str

start_user_header_id_template

def start_user_header_id_template(self) -> str

end_user_header_id_template

def end_user_header_id_template(self) -> str

end_user_message_id_template

def end_user_message_id_template(self) -> str

start_ai_header_id_template

def start_ai_header_id_template(self) -> str

end_ai_header_id_template

def end_ai_header_id_template(self) -> str

end_ai_message_id_template

def end_ai_message_id_template(self) -> str

system_full_header

def system_full_header(self) -> str

user_full_header

def user_full_header(self) -> str

ai_full_header

def ai_full_header(self) -> str

system_custom_header

def system_custom_header(self, ai_name) -> str

ai_custom_header

def ai_custom_header(self, ai_name) -> str

init

def __init__(self, personality: AIPersonality) -> None

init

def __init__(self, lollms_paths: LollmsPaths, config: LOLLMSConfig, model: LLMBinding, app = None, installation_option: InstallOption = InstallOption.INSTALL_IF_NECESSARY, callback = None) -> Any

build_personality

def build_personality(self, id: int = None) -> Any

get_personality

def get_personality(self) -> Any

extract_function_call

def extract_function_call(self, query) -> Any

replace

def replace(match) -> Any