ExternalVendorCode/lollms-webui
1
0
Fork 0
mirror of https://github.com/ParisNeo/lollms-webui.git synced 2024-12-27 07:42:27 +00:00
Code Issues Actions Packages Projects Releases Wiki Activity
ba771d54af
lollms-webui/docs/Usable_infos_for building/personality_info.md

1777 lines
49 KiB
Markdown
Raw Normal View History

sync
2024-07-23 00:38:58 +00:00
# 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
```
Reference in New Issue Copy Permalink