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import difflib | |
import importlib | |
import inspect | |
import json | |
import re | |
from functools import wraps | |
from pathlib import Path | |
from typing import Any | |
from docstring_parser import parse | |
from langflow.logging.logger import logger | |
from langflow.schema import Data | |
from langflow.services.deps import get_settings_service | |
from langflow.template.frontend_node.constants import FORCE_SHOW_FIELDS | |
from langflow.utils import constants | |
def unescape_string(s: str): | |
# Replace escaped new line characters with actual new line characters | |
return s.replace("\\n", "\n") | |
def remove_ansi_escape_codes(text): | |
return re.sub(r"\x1b\[[0-9;]*[a-zA-Z]", "", text) | |
def build_template_from_function(name: str, type_to_loader_dict: dict, *, add_function: bool = False): | |
classes = [item.__annotations__["return"].__name__ for item in type_to_loader_dict.values()] | |
# Raise error if name is not in chains | |
if name not in classes: | |
msg = f"{name} not found" | |
raise ValueError(msg) | |
for _type, v in type_to_loader_dict.items(): | |
if v.__annotations__["return"].__name__ == name: | |
class_ = v.__annotations__["return"] | |
# Get the docstring | |
docs = parse(class_.__doc__) | |
variables = {"_type": _type} | |
for class_field_items, value in class_.model_fields.items(): | |
if class_field_items == "callback_manager": | |
continue | |
variables[class_field_items] = {} | |
for name_, value_ in value.__repr_args__(): | |
if name_ == "default_factory": | |
try: | |
variables[class_field_items]["default"] = get_default_factory( | |
module=class_.__base__.__module__, function=value_ | |
) | |
except Exception: # noqa: BLE001 | |
logger.opt(exception=True).debug(f"Error getting default factory for {value_}") | |
variables[class_field_items]["default"] = None | |
elif name_ != "name": | |
variables[class_field_items][name_] = value_ | |
variables[class_field_items]["placeholder"] = docs.params.get(class_field_items, "") | |
# Adding function to base classes to allow | |
# the output to be a function | |
base_classes = get_base_classes(class_) | |
if add_function: | |
base_classes.append("Callable") | |
return { | |
"template": format_dict(variables, name), | |
"description": docs.short_description or "", | |
"base_classes": base_classes, | |
} | |
return None | |
def build_template_from_method( | |
class_name: str, | |
method_name: str, | |
type_to_cls_dict: dict, | |
*, | |
add_function: bool = False, | |
): | |
classes = [item.__name__ for item in type_to_cls_dict.values()] | |
# Raise error if class_name is not in classes | |
if class_name not in classes: | |
msg = f"{class_name} not found." | |
raise ValueError(msg) | |
for _type, v in type_to_cls_dict.items(): | |
if v.__name__ == class_name: | |
class_ = v | |
# Check if the method exists in this class | |
if not hasattr(class_, method_name): | |
msg = f"Method {method_name} not found in class {class_name}" | |
raise ValueError(msg) | |
# Get the method | |
method = getattr(class_, method_name) | |
# Get the docstring | |
docs = parse(method.__doc__) | |
# Get the signature of the method | |
sig = inspect.signature(method) | |
# Get the parameters of the method | |
params = sig.parameters | |
# Initialize the variables dictionary with method parameters | |
variables = { | |
"_type": _type, | |
**{ | |
name: { | |
"default": (param.default if param.default != param.empty else None), | |
"type": (param.annotation if param.annotation != param.empty else None), | |
"required": param.default == param.empty, | |
} | |
for name, param in params.items() | |
if name not in {"self", "kwargs", "args"} | |
}, | |
} | |
base_classes = get_base_classes(class_) | |
# Adding function to base classes to allow the output to be a function | |
if add_function: | |
base_classes.append("Callable") | |
return { | |
"template": format_dict(variables, class_name), | |
"description": docs.short_description or "", | |
"base_classes": base_classes, | |
} | |
return None | |
def get_base_classes(cls): | |
"""Get the base classes of a class. | |
These are used to determine the output of the nodes. | |
""" | |
if hasattr(cls, "__bases__") and cls.__bases__: | |
bases = cls.__bases__ | |
result = [] | |
for base in bases: | |
if any(_type in base.__module__ for _type in ["pydantic", "abc"]): | |
continue | |
result.append(base.__name__) | |
base_classes = get_base_classes(base) | |
# check if the base_classes are in the result | |
# if not, add them | |
for base_class in base_classes: | |
if base_class not in result: | |
result.append(base_class) | |
else: | |
result = [cls.__name__] | |
if not result: | |
result = [cls.__name__] | |
return list({*result, cls.__name__}) | |
def get_default_factory(module: str, function: str): | |
pattern = r"<function (\w+)>" | |
if match := re.search(pattern, function): | |
imported_module = importlib.import_module(module) | |
return getattr(imported_module, match[1])() | |
return None | |
def update_verbose(d: dict, *, new_value: bool) -> dict: | |
"""Recursively updates the value of the 'verbose' key in a dictionary. | |
Args: | |
d: the dictionary to update | |
new_value: the new value to set | |
Returns: | |
The updated dictionary. | |
""" | |
for k, v in d.items(): | |
if isinstance(v, dict): | |
update_verbose(v, new_value=new_value) | |
elif k == "verbose": | |
d[k] = new_value | |
return d | |
def sync_to_async(func): | |
"""Decorator to convert a sync function to an async function.""" | |
async def async_wrapper(*args, **kwargs): | |
return func(*args, **kwargs) | |
return async_wrapper | |
def format_dict(dictionary: dict[str, Any], class_name: str | None = None) -> dict[str, Any]: | |
"""Formats a dictionary by removing certain keys and modifying the values of other keys. | |
Returns: | |
A new dictionary with the desired modifications applied. | |
""" | |
for key, value in dictionary.items(): | |
if key == "_type": | |
continue | |
type_: str | type = get_type(value) | |
if "BaseModel" in str(type_): | |
continue | |
type_ = remove_optional_wrapper(type_) | |
type_ = check_list_type(type_, value) | |
type_ = replace_mapping_with_dict(type_) | |
type_ = get_type_from_union_literal(type_) | |
value["type"] = get_formatted_type(key, type_) | |
value["show"] = should_show_field(value, key) | |
value["password"] = is_password_field(key) | |
value["multiline"] = is_multiline_field(key) | |
if key == "dict_": | |
set_dict_file_attributes(value) | |
replace_default_value_with_actual(value) | |
if key == "headers": | |
set_headers_value(value) | |
add_options_to_field(value, class_name, key) | |
return dictionary | |
# "Union[Literal['f-string'], Literal['jinja2']]" -> "str" | |
def get_type_from_union_literal(union_literal: str) -> str: | |
# if types are literal strings | |
# the type is a string | |
if "Literal" in union_literal: | |
return "str" | |
return union_literal | |
def get_type(value: Any) -> str | type: | |
"""Retrieves the type value from the dictionary. | |
Returns: | |
The type value. | |
""" | |
# get "type" or "annotation" from the value | |
type_ = value.get("type") or value.get("annotation") | |
return type_ if isinstance(type_, str) else type_.__name__ | |
def remove_optional_wrapper(type_: str | type) -> str: | |
"""Removes the 'Optional' wrapper from the type string. | |
Returns: | |
The type string with the 'Optional' wrapper removed. | |
""" | |
if isinstance(type_, type): | |
type_ = str(type_) | |
if "Optional" in type_: | |
type_ = type_.replace("Optional[", "")[:-1] | |
return type_ | |
def check_list_type(type_: str, value: dict[str, Any]) -> str: | |
"""Checks if the type is a list type and modifies the value accordingly. | |
Returns: | |
The modified type string. | |
""" | |
if any(list_type in type_ for list_type in ["List", "Sequence", "Set"]): | |
type_ = type_.replace("List[", "").replace("Sequence[", "").replace("Set[", "")[:-1] | |
value["list"] = True | |
else: | |
value["list"] = False | |
return type_ | |
def replace_mapping_with_dict(type_: str) -> str: | |
"""Replaces 'Mapping' with 'dict' in the type string. | |
Returns: | |
The modified type string. | |
""" | |
if "Mapping" in type_: | |
type_ = type_.replace("Mapping", "dict") | |
return type_ | |
def get_formatted_type(key: str, type_: str) -> str: | |
"""Formats the type value based on the given key. | |
Returns: | |
The formatted type value. | |
""" | |
if key == "allowed_tools": | |
return "Tool" | |
if key == "max_value_length": | |
return "int" | |
return type_ | |
def should_show_field(value: dict[str, Any], key: str) -> bool: | |
"""Determines if the field should be shown or not. | |
Returns: | |
True if the field should be shown, False otherwise. | |
""" | |
return ( | |
(value["required"] and key != "input_variables") | |
or key in FORCE_SHOW_FIELDS | |
or any(text in key.lower() for text in ["password", "token", "api", "key"]) | |
) | |
def is_password_field(key: str) -> bool: | |
"""Determines if the field is a password field. | |
Returns: | |
True if the field is a password field, False otherwise. | |
""" | |
return any(text in key.lower() for text in ["password", "token", "api", "key"]) | |
def is_multiline_field(key: str) -> bool: | |
"""Determines if the field is a multiline field. | |
Returns: | |
True if the field is a multiline field, False otherwise. | |
""" | |
return key in { | |
"suffix", | |
"prefix", | |
"template", | |
"examples", | |
"code", | |
"headers", | |
"format_instructions", | |
} | |
def set_dict_file_attributes(value: dict[str, Any]) -> None: | |
"""Sets the file attributes for the 'dict_' key.""" | |
value["type"] = "file" | |
value["fileTypes"] = [".json", ".yaml", ".yml"] | |
def replace_default_value_with_actual(value: dict[str, Any]) -> None: | |
"""Replaces the default value with the actual value.""" | |
if "default" in value: | |
value["value"] = value["default"] | |
value.pop("default") | |
def set_headers_value(value: dict[str, Any]) -> None: | |
"""Sets the value for the 'headers' key.""" | |
value["value"] = """{"Authorization": "Bearer <token>"}""" | |
def add_options_to_field(value: dict[str, Any], class_name: str | None, key: str) -> None: | |
"""Adds options to the field based on the class name and key.""" | |
options_map = { | |
"OpenAI": constants.OPENAI_MODELS, | |
"ChatOpenAI": constants.CHAT_OPENAI_MODELS, | |
"Anthropic": constants.ANTHROPIC_MODELS, | |
"ChatAnthropic": constants.ANTHROPIC_MODELS, | |
} | |
if class_name in options_map and key == "model_name": | |
value["options"] = options_map[class_name] | |
value["list"] = True | |
value["value"] = options_map[class_name][0] | |
def build_loader_repr_from_data(data: list[Data]) -> str: | |
"""Builds a string representation of the loader based on the given data. | |
Args: | |
data (List[Data]): A list of data. | |
Returns: | |
str: A string representation of the loader. | |
""" | |
if data: | |
avg_length = sum(len(doc.text) for doc in data) / len(data) | |
return f"""{len(data)} data | |
\nAvg. Data Length (characters): {int(avg_length)} | |
Data: {data[:3]}...""" | |
return "0 data" | |
def update_settings( | |
*, | |
config: str | None = None, | |
cache: str | None = None, | |
dev: bool = False, | |
remove_api_keys: bool = False, | |
components_path: Path | None = None, | |
store: bool = True, | |
auto_saving: bool = True, | |
auto_saving_interval: int = 1000, | |
health_check_max_retries: int = 5, | |
max_file_size_upload: int = 100, | |
) -> None: | |
"""Update the settings from a config file.""" | |
from langflow.services.utils import initialize_settings_service | |
# Check for database_url in the environment variables | |
initialize_settings_service() | |
settings_service = get_settings_service() | |
if config: | |
logger.debug(f"Loading settings from {config}") | |
settings_service.settings.update_from_yaml(config, dev=dev) | |
if remove_api_keys: | |
logger.debug(f"Setting remove_api_keys to {remove_api_keys}") | |
settings_service.settings.update_settings(remove_api_keys=remove_api_keys) | |
if cache: | |
logger.debug(f"Setting cache to {cache}") | |
settings_service.settings.update_settings(cache=cache) | |
if components_path: | |
logger.debug(f"Adding component path {components_path}") | |
settings_service.settings.update_settings(components_path=components_path) | |
if not store: | |
logger.debug("Setting store to False") | |
settings_service.settings.update_settings(store=False) | |
if not auto_saving: | |
logger.debug("Setting auto_saving to False") | |
settings_service.settings.update_settings(auto_saving=False) | |
if auto_saving_interval is not None: | |
logger.debug(f"Setting auto_saving_interval to {auto_saving_interval}") | |
settings_service.settings.update_settings(auto_saving_interval=auto_saving_interval) | |
if health_check_max_retries is not None: | |
logger.debug(f"Setting health_check_max_retries to {health_check_max_retries}") | |
settings_service.settings.update_settings(health_check_max_retries=health_check_max_retries) | |
if max_file_size_upload is not None: | |
logger.debug(f"Setting max_file_size_upload to {max_file_size_upload}") | |
settings_service.settings.update_settings(max_file_size_upload=max_file_size_upload) | |
def is_class_method(func, cls): | |
"""Check if a function is a class method.""" | |
return inspect.ismethod(func) and func.__self__ is cls.__class__ | |
def escape_json_dump(edge_dict): | |
return json.dumps(edge_dict).replace('"', "œ") | |
def find_closest_match(string: str, list_of_strings: list[str]) -> str | None: | |
"""Find the closest match in a list of strings.""" | |
closest_match = difflib.get_close_matches(string, list_of_strings, n=1, cutoff=0.2) | |
if closest_match: | |
return closest_match[0] | |
return None | |