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promptflow

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$schema: https://azuremlschemas.azureedge.net/promptflow/latest/Flow.schema.json inputs: chat_history: type: list is_chat_history: true default: [] question: type: string is_chat_input: true outputs: answer: type: string reference: ${chat.output} is_chat_output: true nodes: - name: chat type: llm source: type: code path: chat.jinja2 inputs: deployment_name: {{ deployment }} max_tokens: '256' temperature: '0.7' chat_history: ${inputs.chat_history} question: ${inputs.question} api: chat connection: {{ connection }} environment: python_requirements_txt: requirements.txt

promptflow/src/promptflow/promptflow/_cli/data/chat_flow/template/flow.dag.yaml.jinja2/0

import yaml import logging import tempfile import hashlib from pathlib import Path logger = logging.getLogger(__name__) package_name = "{{ package_name }}" def list_package_tools(raise_error=False): """ List the meta of all tools in the package. The key of meta dict is the module name of tools and value is the meta data of the tool. """ # This function is auto generated by pf CLI, please do not modify manually. tools = {} meta_cache_file = Path(__file__).parent / "yamls" / "tools_meta.yaml" if meta_cache_file.exists(): logger.debug(f"List tools meta from cache file {meta_cache_file.as_posix()}.") # Get tool meta from cache file. with open(meta_cache_file, "r") as f: tools = yaml.safe_load(f) else: from promptflow import PFClient pf_client = PFClient() tools = pf_client.tools._list_tools_in_package(package_name, raise_error=raise_error) return tools

promptflow/src/promptflow/promptflow/_cli/data/package_tool/utils.py.jinja2/0

# --------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # --------------------------------------------------------- import asyncio import functools import importlib import logging import os from importlib.metadata import version import openai from promptflow._core.operation_context import OperationContext from promptflow.contracts.trace import TraceType from .tracer import _traced_async, _traced_sync USER_AGENT_HEADER = "x-ms-useragent" PROMPTFLOW_PREFIX = "ms-azure-ai-promptflow-" IS_LEGACY_OPENAI = version("openai").startswith("0.") def inject_function_async(args_to_ignore=None, trace_type=TraceType.LLM): def decorator(func): return _traced_async(func, args_to_ignore=args_to_ignore, trace_type=trace_type) return decorator def inject_function_sync(args_to_ignore=None, trace_type=TraceType.LLM): def decorator(func): return _traced_sync(func, args_to_ignore=args_to_ignore, trace_type=trace_type) return decorator def get_aoai_telemetry_headers() -> dict: """Get the http headers for AOAI request. The header, whose name starts with "ms-azure-ai-" or "x-ms-", is used to track the request in AOAI. The value in this dict will be recorded as telemetry, so please do not put any sensitive information in it. Returns: A dictionary of http headers. """ # get promptflow info from operation context operation_context = OperationContext.get_instance() tracking_info = operation_context._get_tracking_info() tracking_info = {k.replace("_", "-"): v for k, v in tracking_info.items()} def is_primitive(value): return value is None or isinstance(value, (int, float, str, bool)) # Ensure that the telemetry info is primitive tracking_info = {k: v for k, v in tracking_info.items() if is_primitive(v)} # init headers headers = {USER_AGENT_HEADER: operation_context.get_user_agent()} # update header with promptflow info headers.update({f"{PROMPTFLOW_PREFIX}{k}": str(v) if v is not None else "" for k, v in tracking_info.items()}) return headers def inject_operation_headers(f): def inject_headers(kwargs): # Inject headers from operation context, overwrite injected header with headers from kwargs. injected_headers = get_aoai_telemetry_headers() original_headers = kwargs.get("headers" if IS_LEGACY_OPENAI else "extra_headers") if original_headers and isinstance(original_headers, dict): injected_headers.update(original_headers) kwargs["headers" if IS_LEGACY_OPENAI else "extra_headers"] = injected_headers if asyncio.iscoroutinefunction(f): @functools.wraps(f) async def wrapper(*args, **kwargs): inject_headers(kwargs) return await f(*args, **kwargs) else: @functools.wraps(f) def wrapper(*args, **kwargs): inject_headers(kwargs) return f(*args, **kwargs) return wrapper def inject_async(f): wrapper_fun = inject_operation_headers((inject_function_async(["api_key", "headers", "extra_headers"])(f))) wrapper_fun._original = f return wrapper_fun def inject_sync(f): wrapper_fun = inject_operation_headers((inject_function_sync(["api_key", "headers", "extra_headers"])(f))) wrapper_fun._original = f return wrapper_fun def _openai_api_list(): if IS_LEGACY_OPENAI: sync_apis = ( ("openai", "Completion", "create"), ("openai", "ChatCompletion", "create"), ("openai", "Embedding", "create"), ) async_apis = ( ("openai", "Completion", "acreate"), ("openai", "ChatCompletion", "acreate"), ("openai", "Embedding", "acreate"), ) else: sync_apis = ( ("openai.resources.chat", "Completions", "create"), ("openai.resources", "Completions", "create"), ("openai.resources", "Embeddings", "create"), ) async_apis = ( ("openai.resources.chat", "AsyncCompletions", "create"), ("openai.resources", "AsyncCompletions", "create"), ("openai.resources", "AsyncEmbeddings", "create"), ) yield sync_apis, inject_sync yield async_apis, inject_async def _generate_api_and_injector(apis): for apis, injector in apis: for module_name, class_name, method_name in apis: try: module = importlib.import_module(module_name) api = getattr(module, class_name) if hasattr(api, method_name): yield api, method_name, injector except AttributeError as e: # Log the attribute exception with the missing class information logging.warning( f"AttributeError: The module '{module_name}' does not have the class '{class_name}'. {str(e)}" ) except Exception as e: # Log other exceptions as a warning, as we're not sure what they might be logging.warning(f"An unexpected error occurred: {str(e)}") def available_openai_apis_and_injectors(): """ Generates a sequence of tuples containing OpenAI API classes, method names, and corresponding injector functions based on whether the legacy OpenAI interface is used. This function handles the discrepancy reported in https://github.com/openai/openai-python/issues/996, where async interfaces were not recognized as coroutines. It ensures that decorators are applied correctly to both synchronous and asynchronous methods. Yields: Tuples of (api_class, method_name, injector_function) """ yield from _generate_api_and_injector(_openai_api_list()) def inject_openai_api(): """This function: 1. Modifies the create methods of the OpenAI API classes to inject logic before calling the original methods. It stores the original methods as _original attributes of the create methods. 2. Updates the openai api configs from environment variables. """ for api, method, injector in available_openai_apis_and_injectors(): # Check if the create method of the openai_api class has already been modified if not hasattr(getattr(api, method), "_original"): setattr(api, method, injector(getattr(api, method))) if IS_LEGACY_OPENAI: # For the openai versions lower than 1.0.0, it reads api configs from environment variables only at # import time. So we need to update the openai api configs from environment variables here. # Please refer to this issue: https://github.com/openai/openai-python/issues/557. # The issue has been fixed in openai>=1.0.0. openai.api_key = os.environ.get("OPENAI_API_KEY", openai.api_key) openai.api_key_path = os.environ.get("OPENAI_API_KEY_PATH", openai.api_key_path) openai.organization = os.environ.get("OPENAI_ORGANIZATION", openai.organization) openai.api_base = os.environ.get("OPENAI_API_BASE", openai.api_base) openai.api_type = os.environ.get("OPENAI_API_TYPE", openai.api_type) openai.api_version = os.environ.get("OPENAI_API_VERSION", openai.api_version) def recover_openai_api(): """This function restores the original create methods of the OpenAI API classes by assigning them back from the _original attributes of the modified methods. """ for api, method, _ in available_openai_apis_and_injectors(): if hasattr(getattr(api, method), "_original"): setattr(api, method, getattr(getattr(api, method), "_original"))

promptflow/src/promptflow/promptflow/_core/openai_injector.py/0

# --------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # --------------------------------------------------------- __path__ = __import__("pkgutil").extend_path(__path__, __name__) # type: ignore from promptflow._sdk._orm.run_info import RunInfo from promptflow._sdk._orm.orchestrator import Orchestrator from promptflow._sdk._orm.experiment_node_run import ExperimentNodeRun from .connection import Connection from .experiment import Experiment from .session import mgmt_db_session __all__ = [ "RunInfo", "Connection", "Experiment", "ExperimentNodeRun", "Orchestrator", "mgmt_db_session", ]

promptflow/src/promptflow/promptflow/_sdk/_orm/__init__.py/0

# --------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # --------------------------------------------------------- import inspect from pathlib import Path from flask import jsonify, request import promptflow._sdk.schemas._connection as connection from promptflow._sdk._configuration import Configuration from promptflow._sdk._service import Namespace, Resource, fields from promptflow._sdk._service.utils.utils import build_pfs_user_agent, local_user_only, make_response_no_content from promptflow._sdk.entities._connection import _Connection api = Namespace("Connections", description="Connections Management") # azure connection def validate_working_directory(value): if value is None: return if not isinstance(value, str): value = str(value) if not Path(value).is_dir(): raise ValueError("Invalid working directory.") return value working_directory_parser = api.parser() working_directory_parser.add_argument( "working_directory", type=validate_working_directory, location="args", required=False ) # Response model of list connections list_connection_field = api.model( "Connection", { "name": fields.String, "type": fields.String, "module": fields.String, "expiry_time": fields.String, "created_date": fields.String, "last_modified_date": fields.String, }, ) # Response model of connection operation dict_field = api.schema_model("ConnectionDict", {"additionalProperties": True, "type": "object"}) # Response model of connection spec connection_config_spec_model = api.model( "ConnectionConfigSpec", { "name": fields.String, "optional": fields.Boolean, "default": fields.String, }, ) connection_spec_model = api.model( "ConnectionSpec", { "connection_type": fields.String, "config_spec": fields.List(fields.Nested(connection_config_spec_model)), }, ) def _get_connection_operation(working_directory=None): from promptflow._sdk._pf_client import PFClient connection_provider = Configuration().get_connection_provider(path=working_directory) # get_connection_operation is a shared function, so we build user agent based on request first and # then pass it to the function connection_operation = PFClient( connection_provider=connection_provider, user_agent=build_pfs_user_agent() ).connections return connection_operation @api.route("/") class ConnectionList(Resource): @api.doc(parser=working_directory_parser, description="List all connection") @api.marshal_with(list_connection_field, skip_none=True, as_list=True) @local_user_only @api.response( code=403, description="This service is available for local user only, please specify X-Remote-User in headers." ) def get(self): args = working_directory_parser.parse_args() connection_op = _get_connection_operation(args.working_directory) # parse query parameters max_results = request.args.get("max_results", default=50, type=int) all_results = request.args.get("all_results", default=False, type=bool) connections = connection_op.list(max_results=max_results, all_results=all_results) connections_dict = [connection._to_dict() for connection in connections] return connections_dict @api.route("/<string:name>") @api.param("name", "The connection name.") class Connection(Resource): @api.doc(parser=working_directory_parser, description="Get connection") @api.response(code=200, description="Connection details", model=dict_field) @local_user_only @api.response( code=403, description="This service is available for local user only, please specify X-Remote-User in headers." ) def get(self, name: str): args = working_directory_parser.parse_args() connection_op = _get_connection_operation(args.working_directory) connection = connection_op.get(name=name, raise_error=True) connection_dict = connection._to_dict() return jsonify(connection_dict) @api.doc(body=dict_field, description="Create connection") @api.response(code=200, description="Connection details", model=dict_field) @local_user_only @api.response( code=403, description="This service is available for local user only, please specify X-Remote-User in headers." ) def post(self, name: str): connection_op = _get_connection_operation() connection_data = request.get_json(force=True) connection_data["name"] = name connection = _Connection._load(data=connection_data) connection = connection_op.create_or_update(connection) return jsonify(connection._to_dict()) @api.doc(body=dict_field, description="Update connection") @api.response(code=200, description="Connection details", model=dict_field) @local_user_only @api.response( code=403, description="This service is available for local user only, please specify X-Remote-User in headers." ) def put(self, name: str): connection_op = _get_connection_operation() connection_dict = request.get_json(force=True) params_override = [{k: v} for k, v in connection_dict.items()] # TODO: check if we need to record registry for this private operation existing_connection = connection_op._get(name) connection = _Connection._load(data=existing_connection._to_dict(), params_override=params_override) connection._secrets = existing_connection._secrets connection = connection_op.create_or_update(connection) return jsonify(connection._to_dict()) @api.doc(description="Delete connection") @local_user_only @api.response(code=204, description="Delete connection", model=dict_field) @api.response( code=403, description="This service is available for local user only, please specify X-Remote-User in headers." ) def delete(self, name: str): connection_op = _get_connection_operation() connection_op.delete(name=name) return make_response_no_content() @api.route("/<string:name>/listsecrets") class ConnectionWithSecret(Resource): @api.doc(parser=working_directory_parser, description="Get connection with secret") @api.response(code=200, description="Connection details with secret", model=dict_field) @local_user_only @api.response( code=403, description="This service is available for local user only, please specify X-Remote-User in headers." ) def get(self, name: str): args = working_directory_parser.parse_args() connection_op = _get_connection_operation(args.working_directory) connection = connection_op.get(name=name, with_secrets=True, raise_error=True) connection_dict = connection._to_dict() return jsonify(connection_dict) @api.route("/specs") class ConnectionSpecs(Resource): @api.doc(description="List connection spec") @api.response(code=200, description="List connection spec", skip_none=True, model=connection_spec_model) def get(self): hide_connection_fields = ["module"] connection_specs = [] for name, obj in inspect.getmembers(connection): if ( inspect.isclass(obj) and issubclass(obj, connection.ConnectionSchema) and not isinstance(obj, connection.ConnectionSchema) ): config_specs = [] for field_name, field in obj._declared_fields.items(): if not field.dump_only and field_name not in hide_connection_fields: configs = {"name": field_name, "optional": field.allow_none} if field.default: configs["default"] = field.default if field_name == "type": configs["default"] = field.allowed_values[0] config_specs.append(configs) connection_spec = { "connection_type": name.replace("Schema", ""), "config_specs": config_specs, } connection_specs.append(connection_spec) return jsonify(connection_specs)

promptflow/src/promptflow/promptflow/_sdk/_service/apis/connection.py/0

# --------------------------------------------------------- # Copyright (c) 2013-2022 Caleb P. Burns credits dahlia <https://github.com/dahlia> # Licensed under the MPLv2 License. See License.txt in the project root for # license information. # --------------------------------------------------------- """ This file code has been vendored from pathspec repo. Please do not edit it, unless really necessary """ import dataclasses import os import posixpath import re import warnings from typing import Any, AnyStr, Iterable, Iterator from typing import Match as MatchHint from typing import Optional from typing import Pattern as PatternHint from typing import Tuple, Union NORMALIZE_PATH_SEPS = [sep for sep in [os.sep, os.altsep] if sep and sep != posixpath.sep] # The encoding to use when parsing a byte string pattern. # This provides the base definition for patterns. _BYTES_ENCODING = "latin1" class Pattern(object): """ The :class:`Pattern` class is the abstract definition of a pattern. """ # Make the class dict-less. __slots__ = ("include",) def __init__(self, include: Optional[bool]) -> None: """ Initializes the :class:`Pattern` instance. *include* (:class:`bool` or :data:`None`) is whether the matched files should be included (:data:`True`), excluded (:data:`False`), or is a null-operation (:data:`None`). """ self.include = include """ *include* (:class:`bool` or :data:`None`) is whether the matched files should be included (:data:`True`), excluded (:data:`False`), or is a null-operation (:data:`None`). """ def match(self, files: Iterable[str]) -> Iterator[str]: """ DEPRECATED: This method is no longer used and has been replaced by :meth:`.match_file`. Use the :meth:`.match_file` method with a loop for similar results. Matches this pattern against the specified files. *files* (:class:`~collections.abc.Iterable` of :class:`str`) contains each file relative to the root directory (e.g., :data:`"relative/path/to/file"`). Returns an :class:`~collections.abc.Iterable` yielding each matched file path (:class:`str`). """ warnings.warn( ( "{0.__module__}.{0.__qualname__}.match() is deprecated. Use " "{0.__module__}.{0.__qualname__}.match_file() with a loop for " "similar results." ).format(self.__class__), DeprecationWarning, stacklevel=2, ) for file in files: if self.match_file(file) is not None: yield file def match_file(self, file: str) -> Optional[Any]: """ Matches this pattern against the specified file. *file* (:class:`str`) is the normalized file path to match against. Returns the match result if *file* matched; otherwise, :data:`None`. """ raise NotImplementedError( ("{0.__module__}.{0.__qualname__} must override match_file().").format(self.__class__) ) class RegexPattern(Pattern): """ The :class:`RegexPattern` class is an implementation of a pattern using regular expressions. """ # Keep the class dict-less. __slots__ = ("regex",) def __init__( self, pattern: Union[AnyStr, PatternHint], include: Optional[bool] = None, ) -> None: """ Initializes the :class:`RegexPattern` instance. *pattern* (:class:`str`, :class:`bytes`, :class:`re.Pattern`, or :data:`None`) is the pattern to compile into a regular expression. *include* (:class:`bool` or :data:`None`) must be :data:`None` unless *pattern* is a precompiled regular expression (:class:`re.Pattern`) in which case it is whether matched files should be included (:data:`True`), excluded (:data:`False`), or is a null operation (:data:`None`). .. NOTE:: Subclasses do not need to support the *include* parameter. """ if isinstance(pattern, (str, bytes)): assert include is None, ("include:{!r} must be null when pattern:{!r} is a string.").format( include, pattern ) regex, include = self.pattern_to_regex(pattern) # NOTE: Make sure to allow a null regular expression to be # returned for a null-operation. if include is not None: regex = re.compile(regex) elif pattern is not None and hasattr(pattern, "match"): # Assume pattern is a precompiled regular expression. # - NOTE: Used specified *include*. regex = pattern elif pattern is None: # NOTE: Make sure to allow a null pattern to be passed for a # null-operation. assert include is None, ("include:{!r} must be null when pattern:{!r} is null.").format(include, pattern) else: raise TypeError("pattern:{!r} is not a string, re.Pattern, or None.".format(pattern)) super(RegexPattern, self).__init__(include) self.regex: PatternHint = regex """ *regex* (:class:`re.Pattern`) is the regular expression for the pattern. """ def __eq__(self, other: "RegexPattern") -> bool: """ Tests the equality of this regex pattern with *other* (:class:`RegexPattern`) by comparing their :attr:`~Pattern.include` and :attr:`~RegexPattern.regex` attributes. """ if isinstance(other, RegexPattern): return self.include == other.include and self.regex == other.regex return NotImplemented def match_file(self, file: str) -> Optional["RegexMatchResult"]: """ Matches this pattern against the specified file. *file* (:class:`str`) contains each file relative to the root directory (e.g., "relative/path/to/file"). Returns the match result (:class:`RegexMatchResult`) if *file* matched; otherwise, :data:`None`. """ if self.include is not None: match = self.regex.match(file) if match is not None: return RegexMatchResult(match) return None @classmethod def pattern_to_regex(cls, pattern: str) -> Tuple[str, bool]: """ Convert the pattern into an un-compiled regular expression. *pattern* (:class:`str`) is the pattern to convert into a regular expression. Returns the un-compiled regular expression (:class:`str` or :data:`None`), and whether matched files should be included (:data:`True`), excluded (:data:`False`), or is a null-operation (:data:`None`). .. NOTE:: The default implementation simply returns *pattern* and :data:`True`. """ return pattern, True @dataclasses.dataclass() class RegexMatchResult(object): """ The :class:`RegexMatchResult` data class is used to return information about the matched regular expression. """ # Keep the class dict-less. __slots__ = ("match",) match: MatchHint """ *match* (:class:`re.Match`) is the regex match result. """ class GitWildMatchPatternError(ValueError): """ The :class:`GitWildMatchPatternError` indicates an invalid git wild match pattern. """ class GitWildMatchPattern(RegexPattern): """ The :class:`GitWildMatchPattern` class represents a compiled Git wildmatch pattern. """ # Keep the dict-less class hierarchy. __slots__ = () @classmethod # pylint: disable=too-many-branches,too-many-statements def pattern_to_regex( cls, pattern: AnyStr, ) -> Tuple[Optional[AnyStr], Optional[bool]]: """ Convert the pattern into a regular expression. *pattern* (:class:`str` or :class:`bytes`) is the pattern to convert into a regular expression. Returns the un-compiled regular expression (:class:`str`, :class:`bytes`, or :data:`None`); and whether matched files should be included (:data:`True`), excluded (:data:`False`), or if it is a null-operation (:data:`None`). """ if isinstance(pattern, str): return_type = str elif isinstance(pattern, bytes): return_type = bytes pattern = pattern.decode(_BYTES_ENCODING) else: raise TypeError(f"pattern:{pattern!r} is not a unicode or byte string.") original_pattern = pattern pattern = pattern.strip() if pattern.startswith("#"): # A pattern starting with a hash ('#') serves as a comment # (neither includes nor excludes files). Escape the hash with a # back-slash to match a literal hash (i.e., '\#'). regex = None include = None elif pattern == "/": # EDGE CASE: According to `git check-ignore` (v2.4.1), a single # '/' does not match any file. regex = None include = None elif pattern: if pattern.startswith("!"): # A pattern starting with an exclamation mark ('!') negates the # pattern (exclude instead of include). Escape the exclamation # mark with a back-slash to match a literal exclamation mark # (i.e., '\!'). include = False # Remove leading exclamation mark. pattern = pattern[1:] else: include = True # Allow a regex override for edge cases that cannot be handled # through normalization. override_regex = None # Split pattern into segments. pattern_segments = pattern.split("/") # Normalize pattern to make processing easier. # EDGE CASE: Deal with duplicate double-asterisk sequences. # Collapse each sequence down to one double-asterisk. Iterate over # the segments in reverse and remove the duplicate double # asterisks as we go. for i in range(len(pattern_segments) - 1, 0, -1): prev = pattern_segments[i - 1] seg = pattern_segments[i] if prev == "**" and seg == "**": del pattern_segments[i] if len(pattern_segments) == 2 and pattern_segments[0] == "**" and not pattern_segments[1]: # EDGE CASE: The '**/' pattern should match everything except # individual files in the root directory. This case cannot be # adequately handled through normalization. Use the override. override_regex = "^.+(?P<ps_d>/).*$" if not pattern_segments[0]: # A pattern beginning with a slash ('/') will only match paths # directly on the root directory instead of any descendant # paths. So, remove empty first segment to make pattern relative # to root. del pattern_segments[0] elif len(pattern_segments) == 1 or (len(pattern_segments) == 2 and not pattern_segments[1]): # A single pattern without a beginning slash ('/') will match # any descendant path. This is equivalent to "**/{pattern}". So, # prepend with double-asterisks to make pattern relative to # root. # EDGE CASE: This also holds for a single pattern with a # trailing slash (e.g. dir/). if pattern_segments[0] != "**": pattern_segments.insert(0, "**") else: # EDGE CASE: A pattern without a beginning slash ('/') but # contains at least one prepended directory (e.g. # "dir/{pattern}") should not match "**/dir/{pattern}", # according to `git check-ignore` (v2.4.1). pass if not pattern_segments: # After resolving the edge cases, we end up with no pattern at # all. This must be because the pattern is invalid. raise GitWildMatchPatternError(f"Invalid git pattern: {original_pattern!r}") if not pattern_segments[-1] and len(pattern_segments) > 1: # A pattern ending with a slash ('/') will match all descendant # paths if it is a directory but not if it is a regular file. # This is equivalent to "{pattern}/**". So, set last segment to # a double-asterisk to include all descendants. pattern_segments[-1] = "**" if override_regex is None: # Build regular expression from pattern. output = ["^"] need_slash = False end = len(pattern_segments) - 1 for i, seg in enumerate(pattern_segments): if seg == "**": if i == 0 and i == end: # A pattern consisting solely of double-asterisks ('**') # will match every path. output.append(".+") elif i == 0: # A normalized pattern beginning with double-asterisks # ('**') will match any leading path segments. output.append("(?:.+/)?") need_slash = False elif i == end: # A normalized pattern ending with double-asterisks ('**') # will match any trailing path segments. output.append("(?P<ps_d>/).*") else: # A pattern with inner double-asterisks ('**') will match # multiple (or zero) inner path segments. output.append("(?:/.+)?") need_slash = True elif seg == "*": # Match single path segment. if need_slash: output.append("/") output.append("[^/]+") if i == end: # A pattern ending without a slash ('/') will match a file # or a directory (with paths underneath it). E.g., "foo" # matches "foo", "foo/bar", "foo/bar/baz", etc. output.append("(?:(?P<ps_d>/).*)?") need_slash = True else: # Match segment glob pattern. if need_slash: output.append("/") try: output.append(cls._translate_segment_glob(seg)) except ValueError as e: raise GitWildMatchPatternError(f"Invalid git pattern: {original_pattern!r}") from e if i == end: # A pattern ending without a slash ('/') will match a file # or a directory (with paths underneath it). E.g., "foo" # matches "foo", "foo/bar", "foo/bar/baz", etc. output.append("(?:(?P<ps_d>/).*)?") need_slash = True output.append("$") regex = "".join(output) else: # Use regex override. regex = override_regex else: # A blank pattern is a null-operation (neither includes nor # excludes files). regex = None include = None if regex is not None and return_type is bytes: regex = regex.encode(_BYTES_ENCODING) return regex, include @staticmethod def _translate_segment_glob(pattern: str) -> str: """ Translates the glob pattern to a regular expression. This is used in the constructor to translate a path segment glob pattern to its corresponding regular expression. *pattern* (:class:`str`) is the glob pattern. Returns the regular expression (:class:`str`). """ # NOTE: This is derived from `fnmatch.translate()` and is similar to # the POSIX function `fnmatch()` with the `FNM_PATHNAME` flag set. escape = False regex = "" i, end = 0, len(pattern) while i < end: # Get next character. char = pattern[i] i += 1 if escape: # Escape the character. escape = False regex += re.escape(char) elif char == "\\": # Escape character, escape next character. escape = True elif char == "*": # Multi-character wildcard. Match any string (except slashes), # including an empty string. regex += "[^/]*" elif char == "?": # Single-character wildcard. Match any single character (except # a slash). regex += "[^/]" elif char == "[": # Bracket expression wildcard. Except for the beginning # exclamation mark, the whole bracket expression can be used # directly as regex but we have to find where the expression # ends. # - "[][!]" matches ']', '[' and '!'. # - "[]-]" matches ']' and '-'. # - "[!]a-]" matches any character except ']', 'a' and '-'. j = i # Pass back expression negation. if j < end and pattern[j] == "!": j += 1 # Pass first closing bracket if it is at the beginning of the # expression. if j < end and pattern[j] == "]": j += 1 # Find closing bracket. Stop once we reach the end or find it. while j < end and pattern[j] != "]": j += 1 if j < end: # Found end of bracket expression. Increment j to be one past # the closing bracket: # # [...] # ^ ^ # i j # j += 1 expr = "[" if pattern[i] == "!": # Bracket expression needs to be negated. expr += "^" i += 1 elif pattern[i] == "^": # POSIX declares that the regex bracket expression negation # "[^...]" is undefined in a glob pattern. Python's # `fnmatch.translate()` escapes the caret ('^') as a # literal. To maintain consistency with undefined behavior, # I am escaping the '^' as well. expr += "\\^" i += 1 # Build regex bracket expression. Escape slashes so they are # treated as literal slashes by regex as defined by POSIX. expr += pattern[i:j].replace("\\", "\\\\") # Add regex bracket expression to regex result. regex += expr # Set i to one past the closing bracket. i = j else: # Failed to find closing bracket, treat opening bracket as a # bracket literal instead of as an expression. regex += "\\[" else: # Regular character, escape it for regex. regex += re.escape(char) if escape: raise ValueError(f"Escape character found with no next character to escape: {pattern!r}") return regex @staticmethod def escape(s: AnyStr) -> AnyStr: """ Escape special characters in the given string. *s* (:class:`str` or :class:`bytes`) a filename or a string that you want to escape, usually before adding it to a ".gitignore". Returns the escaped string (:class:`str` or :class:`bytes`). """ if isinstance(s, str): return_type = str string = s elif isinstance(s, bytes): return_type = bytes string = s.decode(_BYTES_ENCODING) else: raise TypeError(f"s:{s!r} is not a unicode or byte string.") # Reference: https://git-scm.com/docs/gitignore#_pattern_format meta_characters = r"[]!*#?" out_string = "".join("\\" + x if x in meta_characters else x for x in string) if return_type is bytes: return out_string.encode(_BYTES_ENCODING) return out_string def normalize_file(file, separators=None): # type - (Union[Text, PathLike], Optional[Collection[Text]]) -> Text """ Normalizes the file path to use the POSIX path separator (i.e., ``'/'``), and make the paths relative (remove leading ``'/'``). *file* (:class:`str` or :class:`pathlib.PurePath`) is the file path. *separators* (:class:`~collections.abc.Collection` of :class:`str`; or :data:`None`) optionally contains the path separators to normalize. This does not need to include the POSIX path separator (``'/'``), but including it will not affect the results. Default is :data:`None` for :data:`NORMALIZE_PATH_SEPS`. To prevent normalization, pass an empty container (e.g., an empty tuple ``()``). Returns the normalized file path (:class:`str`). """ # Normalize path separators. if separators is None: separators = NORMALIZE_PATH_SEPS # Convert path object to string. norm_file = str(file) for sep in separators: norm_file = norm_file.replace(sep, posixpath.sep) if norm_file.startswith("/"): # Make path relative. norm_file = norm_file[1:] elif norm_file.startswith("./"): # Remove current directory prefix. norm_file = norm_file[2:] return norm_file

promptflow/src/promptflow/promptflow/_sdk/_vendor/_pathspec.py/0

# --------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # --------------------------------------------------------- # pylint: disable=protected-access import json import typing from marshmallow import Schema, ValidationError from promptflow._utils.logger_utils import LoggerFactory from .core import MutableValidationResult, ValidationResultBuilder module_logger = LoggerFactory.get_logger(__name__) class SchemaValidatableMixin: """The mixin class for schema validation.""" @classmethod def _create_empty_validation_result(cls) -> MutableValidationResult: """Simply create an empty validation result To reduce _ValidationResultBuilder importing, which is a private class. :return: An empty validation result :rtype: MutableValidationResult """ return ValidationResultBuilder.success() @classmethod def _load_with_schema(cls, data, *, context, raise_original_exception=False, **kwargs): schema = cls._create_schema_for_validation(context=context) try: return schema.load(data, **kwargs) except ValidationError as e: if raise_original_exception: raise e msg = "Trying to load data with schema failed. Data:\n%s\nError: %s" % ( json.dumps(data, indent=4) if isinstance(data, dict) else data, json.dumps(e.messages, indent=4), ) raise cls._create_validation_error( message=msg, no_personal_data_message=str(e), ) from e @classmethod # pylint: disable-next=docstring-missing-param def _create_schema_for_validation(cls, context) -> Schema: """Create a schema of the resource with specific context. Should be overridden by subclass. :return: The schema of the resource. :rtype: Schema. """ raise NotImplementedError() def _default_context(self) -> dict: """Get the default context for schema validation. Should be overridden by subclass. :return: The default context for schema validation :rtype: dict """ raise NotImplementedError() @property def _schema_for_validation(self) -> Schema: """Return the schema of this Resource with default context. Do not override this method. Override _create_schema_for_validation instead. :return: The schema of the resource. :rtype: Schema. """ return self._create_schema_for_validation(context=self._default_context()) def _dump_for_validation(self) -> typing.Dict: """Convert the resource to a dictionary. :return: Converted dictionary :rtype: typing.Dict """ return self._schema_for_validation.dump(self) @classmethod def _create_validation_error(cls, message: str, no_personal_data_message: str) -> Exception: """The function to create the validation exception to raise in _try_raise and _validate when raise_error is True. Should be overridden by subclass. :param message: The error message containing detailed information :type message: str :param no_personal_data_message: The error message without personal data :type no_personal_data_message: str :return: The validation exception to raise :rtype: Exception """ raise NotImplementedError() @classmethod def _try_raise( cls, validation_result: MutableValidationResult, *, raise_error: bool = True ) -> MutableValidationResult: return validation_result.try_raise(raise_error=raise_error, error_func=cls._create_validation_error) def _validate(self, raise_error=False) -> MutableValidationResult: """Validate the resource. If raise_error is True, raise ValidationError if validation fails and log warnings if applicable; Else, return the validation result. :param raise_error: Whether to raise ValidationError if validation fails. :type raise_error: bool :return: The validation result :rtype: MutableValidationResult """ result = self.__schema_validate() result.merge_with(self._customized_validate()) return self._try_raise(result, raise_error=raise_error) def _customized_validate(self) -> MutableValidationResult: """Validate the resource with customized logic. Override this method to add customized validation logic. :return: The customized validation result :rtype: MutableValidationResult """ return self._create_empty_validation_result() @classmethod def _get_skip_fields_in_schema_validation( cls, ) -> typing.List[str]: """Get the fields that should be skipped in schema validation. Override this method to add customized validation logic. :return: The fields to skip in schema validation :rtype: typing.List[str] """ return [] def __schema_validate(self) -> MutableValidationResult: """Validate the resource with the schema. :return: The validation result :rtype: MutableValidationResult """ data = self._dump_for_validation() messages = self._schema_for_validation.validate(data) for skip_field in self._get_skip_fields_in_schema_validation(): if skip_field in messages: del messages[skip_field] return ValidationResultBuilder.from_validation_messages(messages, data=data)

promptflow/src/promptflow/promptflow/_sdk/entities/_validation/schema.py/0

# --------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # --------------------------------------------------------- import copy import typing from pathlib import Path from marshmallow import fields from marshmallow.exceptions import FieldInstanceResolutionError, ValidationError from marshmallow.fields import _T, Field, Nested from marshmallow.utils import RAISE, resolve_field_instance from promptflow._sdk._constants import BASE_PATH_CONTEXT_KEY from promptflow._sdk.schemas._base import PathAwareSchema from promptflow._utils.logger_utils import LoggerFactory # pylint: disable=unused-argument,no-self-use,protected-access module_logger = LoggerFactory.get_logger(__name__) class StringTransformedEnum(Field): def __init__(self, **kwargs): # pop marshmallow unknown args to avoid warnings self.allowed_values = kwargs.pop("allowed_values", None) self.casing_transform = kwargs.pop("casing_transform", lambda x: x.lower()) self.pass_original = kwargs.pop("pass_original", False) super().__init__(**kwargs) if isinstance(self.allowed_values, str): self.allowed_values = [self.allowed_values] self.allowed_values = [self.casing_transform(x) for x in self.allowed_values] def _jsonschema_type_mapping(self): schema = {"type": "string", "enum": self.allowed_values} if self.name is not None: schema["title"] = self.name if self.dump_only: schema["readonly"] = True return schema def _serialize(self, value, attr, obj, **kwargs): if not value: return if isinstance(value, str) and self.casing_transform(value) in self.allowed_values: return value if self.pass_original else self.casing_transform(value) raise ValidationError(f"Value {value!r} passed is not in set {self.allowed_values}") def _deserialize(self, value, attr, data, **kwargs): if isinstance(value, str) and self.casing_transform(value) in self.allowed_values: return value if self.pass_original else self.casing_transform(value) raise ValidationError(f"Value {value!r} passed is not in set {self.allowed_values}") class LocalPathField(fields.Str): """A field that validates that the input is a local path. Can only be used as fields of PathAwareSchema. """ default_error_messages = { "invalid_path": "The filename, directory name, or volume label syntax is incorrect.", "path_not_exist": "Can't find {allow_type} in resolved absolute path: {path}.", } def __init__(self, allow_dir=True, allow_file=True, **kwargs): self._allow_dir = allow_dir self._allow_file = allow_file self._pattern = kwargs.get("pattern", None) super().__init__(**kwargs) def _resolve_path(self, value) -> Path: """Resolve path to absolute path based on base_path in context. Will resolve the path if it's already an absolute path. """ try: result = Path(value) base_path = Path(self.context[BASE_PATH_CONTEXT_KEY]) if not result.is_absolute(): result = base_path / result # for non-path string like "azureml:/xxx", OSError can be raised in either # resolve() or is_dir() or is_file() result = result.resolve() if (self._allow_dir and result.is_dir()) or (self._allow_file and result.is_file()): return result except OSError: raise self.make_error("invalid_path") raise self.make_error("path_not_exist", path=result.as_posix(), allow_type=self.allowed_path_type) @property def allowed_path_type(self) -> str: if self._allow_dir and self._allow_file: return "directory or file" if self._allow_dir: return "directory" return "file" def _validate(self, value): # inherited validations like required, allow_none, etc. super(LocalPathField, self)._validate(value) if value is None: return self._resolve_path(value) def _serialize(self, value, attr, obj, **kwargs) -> typing.Optional[str]: # do not block serializing None even if required or not allow_none. if value is None: return None # always dump path as absolute path in string as base_path will be dropped after serialization return super(LocalPathField, self)._serialize(self._resolve_path(value).as_posix(), attr, obj, **kwargs) def _deserialize(self, value, attr, data, **kwargs): # resolve to absolute path if value is None: return None return super()._deserialize(self._resolve_path(value).as_posix(), attr, data, **kwargs) # Note: Currently contains a bug where the order in which fields are inputted can potentially cause a bug # Example, the first line below works, but the second one fails upon calling load_from_dict # with the error " AttributeError: 'list' object has no attribute 'get'" # inputs = UnionField([fields.List(NestedField(DataSchema)), NestedField(DataSchema)]) # inputs = UnionField([NestedField(DataSchema), fields.List(NestedField(DataSchema))]) class UnionField(fields.Field): def __init__(self, union_fields: typing.List[fields.Field], is_strict=False, **kwargs): super().__init__(**kwargs) try: # add the validation and make sure union_fields must be subclasses or instances of # marshmallow.base.FieldABC self._union_fields = [resolve_field_instance(cls_or_instance) for cls_or_instance in union_fields] # TODO: make serialization/de-serialization work in the same way as json schema when is_strict is True self.is_strict = is_strict # S\When True, combine fields with oneOf instead of anyOf at schema generation except FieldInstanceResolutionError as error: raise ValueError( 'Elements of "union_fields" must be subclasses or ' "instances of marshmallow.base.FieldABC." ) from error @property def union_fields(self): return iter(self._union_fields) def insert_union_field(self, field): self._union_fields.insert(0, field) # This sets the parent for the schema and also handles nesting. def _bind_to_schema(self, field_name, schema): super()._bind_to_schema(field_name, schema) self._union_fields = self._create_bind_fields(self._union_fields, field_name) def _create_bind_fields(self, _fields, field_name): new_union_fields = [] for field in _fields: field = copy.deepcopy(field) field._bind_to_schema(field_name, self) new_union_fields.append(field) return new_union_fields def _serialize(self, value, attr, obj, **kwargs): if value is None: return None errors = [] for field in self._union_fields: try: return field._serialize(value, attr, obj, **kwargs) except ValidationError as e: errors.extend(e.messages) except (TypeError, ValueError, AttributeError) as e: errors.extend([str(e)]) raise ValidationError(message=errors, field_name=attr) def _deserialize(self, value, attr, data, **kwargs): errors = [] for schema in self._union_fields: try: return schema.deserialize(value, attr, data, **kwargs) except ValidationError as e: errors.append(e.normalized_messages()) except (FileNotFoundError, TypeError) as e: errors.append([str(e)]) finally: # Revert base path to original path when job schema fail to deserialize job. For example, when load # parallel job with component file reference starting with FILE prefix, maybe first CommandSchema will # load component yaml according to AnonymousCommandComponentSchema, and YamlFileSchema will update base # path. When CommandSchema fail to load, then Parallelschema will load component yaml according to # AnonymousParallelComponentSchema, but base path now is incorrect, and will raise path not found error # when load component yaml file. if ( hasattr(schema, "name") and schema.name == "jobs" and hasattr(schema, "schema") and isinstance(schema.schema, PathAwareSchema) ): # use old base path to recover original base path schema.schema.context[BASE_PATH_CONTEXT_KEY] = schema.schema.old_base_path # recover base path of parent schema schema.context[BASE_PATH_CONTEXT_KEY] = schema.schema.context[BASE_PATH_CONTEXT_KEY] raise ValidationError(errors, field_name=attr) class NestedField(Nested): """anticipates the default coming in next marshmallow version, unknown=True.""" def __init__(self, *args, **kwargs): if kwargs.get("unknown") is None: kwargs["unknown"] = RAISE super().__init__(*args, **kwargs) class DumpableIntegerField(fields.Integer): """An int field that cannot serialize other type of values to int if self.strict.""" def _serialize(self, value, attr, obj, **kwargs) -> typing.Optional[typing.Union[str, _T]]: if self.strict and not isinstance(value, int): # this implementation can serialize bool to bool raise self.make_error("invalid", input=value) return super()._serialize(value, attr, obj, **kwargs) class DumpableFloatField(fields.Float): """A float field that cannot serialize other type of values to float if self.strict.""" def __init__( self, *, strict: bool = False, allow_nan: bool = False, as_string: bool = False, **kwargs, ): self.strict = strict super().__init__(allow_nan=allow_nan, as_string=as_string, **kwargs) def _validated(self, value): if self.strict and not isinstance(value, float): raise self.make_error("invalid", input=value) return super()._validated(value) def _serialize(self, value, attr, obj, **kwargs) -> typing.Optional[typing.Union[str, _T]]: return super()._serialize(self._validated(value), attr, obj, **kwargs) def PrimitiveValueField(**kwargs): """Function to return a union field for primitive value. :return: The primitive value field :rtype: Field """ return UnionField( [ # Note: order matters here - to make sure value parsed correctly. # By default, when strict is false, marshmallow downcasts float to int. # Setting it to true will throw a validation error when loading a float to int. # https://github.com/marshmallow-code/marshmallow/pull/755 # Use DumpableIntegerField to make sure there will be validation error when # loading/dumping a float to int. # note that this field can serialize bool instance but cannot deserialize bool instance. DumpableIntegerField(strict=True), # Use DumpableFloatField with strict of True to avoid '1'(str) serialized to 1.0(float) DumpableFloatField(strict=True), # put string schema after Int and Float to make sure they won't dump to string fields.Str(), # fields.Bool comes last since it'll parse anything non-falsy to True fields.Bool(), ], **kwargs, )

promptflow/src/promptflow/promptflow/_sdk/schemas/_fields.py/0

# --------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # --------------------------------------------------------- import re from typing import Any, Dict, Mapping from promptflow._constants import LINE_NUMBER_KEY from promptflow._utils.logger_utils import LoggerFactory from promptflow.batch._errors import InputMappingError logger = LoggerFactory.get_logger(name=__name__) def apply_inputs_mapping( inputs: Mapping[str, Mapping[str, Any]], inputs_mapping: Mapping[str, str], ) -> Dict[str, Any]: """Apply input mapping to inputs for new contract. .. admonition:: Examples .. code-block:: python inputs: { "data": {"answer": "I'm fine, thank you.", "question": "How are you?"}, "baseline": {"answer": "The weather is good."}, } inputs_mapping: { "question": "${data.question}", "groundtruth": "${data.answer}", "baseline": "${baseline.answer}", "deployment_name": "literal_value", } Returns: { "question": "How are you?", "groundtruth": "I'm fine, thank you." "baseline": "The weather is good.", "deployment_name": "literal_value", } :param inputs: A mapping of input keys to their corresponding values. :type inputs: Mapping[str, Mapping[str, Any]] :param inputs_mapping: A mapping of input keys to their corresponding mapping expressions. :type inputs_mapping: Mapping[str, str] :return: A dictionary of input keys to their corresponding mapped values. :rtype: Dict[str, Any] :raises InputMappingError: If any of the input mapping relations are not found in the inputs. """ result = {} notfound_mapping_relations = [] for map_to_key, map_value in inputs_mapping.items(): # Ignore reserved key configuration from input mapping. if map_to_key == LINE_NUMBER_KEY: continue if not isinstance(map_value, str): # All non-string values are literal values. result[map_to_key] = map_value continue match = re.search(r"^\${([^{}]+)}$", map_value) if match is not None: pattern = match.group(1) # Could also try each pair of key value from inputs to match the pattern. # But split pattern by '.' is one deterministic way. # So, give key with less '.' higher priority. splitted_str = pattern.split(".") find_match = False for i in range(1, len(splitted_str)): key = ".".join(splitted_str[:i]) source = ".".join(splitted_str[i:]) if key in inputs and source in inputs[key]: find_match = True result[map_to_key] = inputs[key][source] break if not find_match: notfound_mapping_relations.append(map_value) else: result[map_to_key] = map_value # Literal value # Return all not found mapping relations in one exception to provide better debug experience. if notfound_mapping_relations: invalid_relations = ", ".join(notfound_mapping_relations) raise InputMappingError( message_format=( "The input for batch run is incorrect. Couldn't find these mapping relations: {invalid_relations}. " "Please make sure your input mapping keys and values match your YAML input section and input data. " "For more information, refer to the following documentation: https://aka.ms/pf/column-mapping" ), invalid_relations=invalid_relations, ) # For PRS scenario, apply_inputs_mapping will be used for exec_line and line_number is not necessary. if LINE_NUMBER_KEY in inputs: result[LINE_NUMBER_KEY] = inputs[LINE_NUMBER_KEY] return result

promptflow/src/promptflow/promptflow/_utils/inputs_mapping_utils.py/0

# --------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # --------------------------------------------------------- from pathlib import Path RESOURCE_FOLDER = Path(__file__).parent.parent / "resources" COMMAND_COMPONENT_SPEC_TEMPLATE = RESOURCE_FOLDER / "component_spec_template.yaml" DEFAULT_PYTHON_VERSION = "3.9"

promptflow/src/promptflow/promptflow/azure/_constants/_component.py/0

# coding=utf-8 # -------------------------------------------------------------------------- # Code generated by Microsoft (R) AutoRest Code Generator (autorest: 3.9.2, generator: @autorest/[email protected]) # Changes may cause incorrect behavior and will be lost if the code is regenerated. # -------------------------------------------------------------------------- from copy import deepcopy from typing import Any, Awaitable, Optional from azure.core import AsyncPipelineClient from azure.core.rest import AsyncHttpResponse, HttpRequest from msrest import Deserializer, Serializer from .. import models from ._configuration import AzureMachineLearningDesignerServiceClientConfiguration from .operations import BulkRunsOperations, ConnectionOperations, ConnectionsOperations, FlowRuntimesOperations, FlowRuntimesWorkspaceIndependentOperations, FlowSessionsOperations, FlowsOperations, FlowsProviderOperations, ToolsOperations, TraceSessionsOperations class AzureMachineLearningDesignerServiceClient: """AzureMachineLearningDesignerServiceClient. :ivar bulk_runs: BulkRunsOperations operations :vartype bulk_runs: flow.aio.operations.BulkRunsOperations :ivar connection: ConnectionOperations operations :vartype connection: flow.aio.operations.ConnectionOperations :ivar connections: ConnectionsOperations operations :vartype connections: flow.aio.operations.ConnectionsOperations :ivar flow_runtimes: FlowRuntimesOperations operations :vartype flow_runtimes: flow.aio.operations.FlowRuntimesOperations :ivar flow_runtimes_workspace_independent: FlowRuntimesWorkspaceIndependentOperations operations :vartype flow_runtimes_workspace_independent: flow.aio.operations.FlowRuntimesWorkspaceIndependentOperations :ivar flows: FlowsOperations operations :vartype flows: flow.aio.operations.FlowsOperations :ivar flow_sessions: FlowSessionsOperations operations :vartype flow_sessions: flow.aio.operations.FlowSessionsOperations :ivar flows_provider: FlowsProviderOperations operations :vartype flows_provider: flow.aio.operations.FlowsProviderOperations :ivar tools: ToolsOperations operations :vartype tools: flow.aio.operations.ToolsOperations :ivar trace_sessions: TraceSessionsOperations operations :vartype trace_sessions: flow.aio.operations.TraceSessionsOperations :param base_url: Service URL. Default value is ''. :type base_url: str :param api_version: Api Version. The default value is "1.0.0". :type api_version: str """ def __init__( self, base_url: str = "", api_version: Optional[str] = "1.0.0", **kwargs: Any ) -> None: self._config = AzureMachineLearningDesignerServiceClientConfiguration(api_version=api_version, **kwargs) self._client = AsyncPipelineClient(base_url=base_url, config=self._config, **kwargs) client_models = {k: v for k, v in models.__dict__.items() if isinstance(v, type)} self._serialize = Serializer(client_models) self._deserialize = Deserializer(client_models) self._serialize.client_side_validation = False self.bulk_runs = BulkRunsOperations(self._client, self._config, self._serialize, self._deserialize) self.connection = ConnectionOperations(self._client, self._config, self._serialize, self._deserialize) self.connections = ConnectionsOperations(self._client, self._config, self._serialize, self._deserialize) self.flow_runtimes = FlowRuntimesOperations(self._client, self._config, self._serialize, self._deserialize) self.flow_runtimes_workspace_independent = FlowRuntimesWorkspaceIndependentOperations(self._client, self._config, self._serialize, self._deserialize) self.flows = FlowsOperations(self._client, self._config, self._serialize, self._deserialize) self.flow_sessions = FlowSessionsOperations(self._client, self._config, self._serialize, self._deserialize) self.flows_provider = FlowsProviderOperations(self._client, self._config, self._serialize, self._deserialize) self.tools = ToolsOperations(self._client, self._config, self._serialize, self._deserialize) self.trace_sessions = TraceSessionsOperations(self._client, self._config, self._serialize, self._deserialize) def _send_request( self, request: HttpRequest, **kwargs: Any ) -> Awaitable[AsyncHttpResponse]: """Runs the network request through the client's chained policies. >>> from azure.core.rest import HttpRequest >>> request = HttpRequest("GET", "https://www.example.org/") <HttpRequest [GET], url: 'https://www.example.org/'> >>> response = await client._send_request(request) <AsyncHttpResponse: 200 OK> For more information on this code flow, see https://aka.ms/azsdk/python/protocol/quickstart :param request: The network request you want to make. Required. :type request: ~azure.core.rest.HttpRequest :keyword bool stream: Whether the response payload will be streamed. Defaults to False. :return: The response of your network call. Does not do error handling on your response. :rtype: ~azure.core.rest.AsyncHttpResponse """ request_copy = deepcopy(request) request_copy.url = self._client.format_url(request_copy.url) return self._client.send_request(request_copy, **kwargs) async def close(self) -> None: await self._client.close() async def __aenter__(self) -> "AzureMachineLearningDesignerServiceClient": await self._client.__aenter__() return self async def __aexit__(self, *exc_details) -> None: await self._client.__aexit__(*exc_details)

promptflow/src/promptflow/promptflow/azure/_restclient/flow/aio/_azure_machine_learning_designer_service_client.py/0

# coding=utf-8 # -------------------------------------------------------------------------- # Code generated by Microsoft (R) AutoRest Code Generator (autorest: 3.9.2, generator: @autorest/[email protected]) # Changes may cause incorrect behavior and will be lost if the code is regenerated. # -------------------------------------------------------------------------- try: from ._models_py3 import ACIAdvanceSettings from ._models_py3 import AEVAComputeConfiguration from ._models_py3 import AEVAResourceConfiguration from ._models_py3 import AISuperComputerConfiguration from ._models_py3 import AISuperComputerScalePolicy from ._models_py3 import AISuperComputerStorageReferenceConfiguration from ._models_py3 import AKSAdvanceSettings from ._models_py3 import AKSReplicaStatus from ._models_py3 import AMLComputeConfiguration from ._models_py3 import APCloudConfiguration from ._models_py3 import Activate from ._models_py3 import AdditionalErrorInfo from ._models_py3 import AdhocTriggerScheduledCommandJobRequest from ._models_py3 import AdhocTriggerScheduledSparkJobRequest from ._models_py3 import AetherAPCloudConfiguration from ._models_py3 import AetherAmlDataset from ._models_py3 import AetherAmlSparkCloudSetting from ._models_py3 import AetherArgumentAssignment from ._models_py3 import AetherAssetDefinition from ._models_py3 import AetherAssetOutputSettings from ._models_py3 import AetherAutoFeaturizeConfiguration from ._models_py3 import AetherAutoMLComponentConfiguration from ._models_py3 import AetherAutoTrainConfiguration from ._models_py3 import AetherAzureBlobReference from ._models_py3 import AetherAzureDataLakeGen2Reference from ._models_py3 import AetherAzureDataLakeReference from ._models_py3 import AetherAzureDatabaseReference from ._models_py3 import AetherAzureFilesReference from ._models_py3 import AetherBatchAiComputeInfo from ._models_py3 import AetherBuildArtifactInfo from ._models_py3 import AetherCloudBuildDropPathInfo from ._models_py3 import AetherCloudBuildInfo from ._models_py3 import AetherCloudBuildQueueInfo from ._models_py3 import AetherCloudPrioritySetting from ._models_py3 import AetherCloudSettings from ._models_py3 import AetherColumnTransformer from ._models_py3 import AetherComputeConfiguration from ._models_py3 import AetherComputeSetting from ._models_py3 import AetherControlInput from ._models_py3 import AetherControlOutput from ._models_py3 import AetherCopyDataTask from ._models_py3 import AetherCosmosReference from ._models_py3 import AetherCreatedBy from ._models_py3 import AetherCustomReference from ._models_py3 import AetherDBFSReference from ._models_py3 import AetherDataLocation from ._models_py3 import AetherDataLocationReuseCalculationFields from ._models_py3 import AetherDataPath from ._models_py3 import AetherDataReference from ._models_py3 import AetherDataSetDefinition from ._models_py3 import AetherDataSetDefinitionValue from ._models_py3 import AetherDataSettings from ._models_py3 import AetherDataTransferCloudConfiguration from ._models_py3 import AetherDataTransferSink from ._models_py3 import AetherDataTransferSource from ._models_py3 import AetherDataTransferV2CloudSetting from ._models_py3 import AetherDatabaseSink from ._models_py3 import AetherDatabaseSource from ._models_py3 import AetherDatabricksComputeInfo from ._models_py3 import AetherDatasetOutput from ._models_py3 import AetherDatasetOutputOptions from ._models_py3 import AetherDatasetRegistration from ._models_py3 import AetherDatastoreSetting from ._models_py3 import AetherDoWhileControlFlowInfo from ._models_py3 import AetherDoWhileControlFlowRunSettings from ._models_py3 import AetherDockerSettingConfiguration from ._models_py3 import AetherEntityInterfaceDocumentation from ._models_py3 import AetherEntrySetting from ._models_py3 import AetherEnvironmentConfiguration from ._models_py3 import AetherEsCloudConfiguration from ._models_py3 import AetherExportDataTask from ._models_py3 import AetherFeaturizationSettings from ._models_py3 import AetherFileSystem from ._models_py3 import AetherForecastHorizon from ._models_py3 import AetherForecastingSettings from ._models_py3 import AetherGeneralSettings from ._models_py3 import AetherGlobsOptions from ._models_py3 import AetherGraphControlNode from ._models_py3 import AetherGraphControlReferenceNode from ._models_py3 import AetherGraphDatasetNode from ._models_py3 import AetherGraphEdge from ._models_py3 import AetherGraphEntity from ._models_py3 import AetherGraphModuleNode from ._models_py3 import AetherGraphReferenceNode from ._models_py3 import AetherHdfsReference from ._models_py3 import AetherHdiClusterComputeInfo from ._models_py3 import AetherHdiRunConfiguration from ._models_py3 import AetherHyperDriveConfiguration from ._models_py3 import AetherIdentitySetting from ._models_py3 import AetherImportDataTask from ._models_py3 import AetherInputSetting from ._models_py3 import AetherInteractiveConfig from ._models_py3 import AetherK8SConfiguration from ._models_py3 import AetherLegacyDataPath from ._models_py3 import AetherLimitSettings from ._models_py3 import AetherMlcComputeInfo from ._models_py3 import AetherModuleEntity from ._models_py3 import AetherModuleExtendedProperties from ._models_py3 import AetherNCrossValidations from ._models_py3 import AetherOutputSetting from ._models_py3 import AetherParallelForControlFlowInfo from ._models_py3 import AetherParameterAssignment from ._models_py3 import AetherPhillyHdfsReference from ._models_py3 import AetherPortInfo from ._models_py3 import AetherPriorityConfig from ._models_py3 import AetherPriorityConfiguration from ._models_py3 import AetherRegisteredDataSetReference from ._models_py3 import AetherRemoteDockerComputeInfo from ._models_py3 import AetherResourceAssignment from ._models_py3 import AetherResourceAttributeAssignment from ._models_py3 import AetherResourceAttributeDefinition from ._models_py3 import AetherResourceConfig from ._models_py3 import AetherResourceConfiguration from ._models_py3 import AetherResourceModel from ._models_py3 import AetherResourcesSetting from ._models_py3 import AetherSavedDataSetReference from ._models_py3 import AetherScopeCloudConfiguration from ._models_py3 import AetherSeasonality from ._models_py3 import AetherSqlDataPath from ._models_py3 import AetherStackEnsembleSettings from ._models_py3 import AetherStoredProcedureParameter from ._models_py3 import AetherStructuredInterface from ._models_py3 import AetherStructuredInterfaceInput from ._models_py3 import AetherStructuredInterfaceOutput from ._models_py3 import AetherStructuredInterfaceParameter from ._models_py3 import AetherSubGraphConfiguration from ._models_py3 import AetherSweepEarlyTerminationPolicy from ._models_py3 import AetherSweepSettings from ._models_py3 import AetherSweepSettingsLimits from ._models_py3 import AetherTargetLags from ._models_py3 import AetherTargetRollingWindowSize from ._models_py3 import AetherTargetSelectorConfiguration from ._models_py3 import AetherTestDataSettings from ._models_py3 import AetherTorchDistributedConfiguration from ._models_py3 import AetherTrainingOutput from ._models_py3 import AetherTrainingSettings from ._models_py3 import AetherUIAzureOpenAIDeploymentNameSelector from ._models_py3 import AetherUIAzureOpenAIModelCapabilities from ._models_py3 import AetherUIColumnPicker from ._models_py3 import AetherUIJsonEditor from ._models_py3 import AetherUIParameterHint from ._models_py3 import AetherUIPromptFlowConnectionSelector from ._models_py3 import AetherValidationDataSettings from ._models_py3 import AetherVsoBuildArtifactInfo from ._models_py3 import AetherVsoBuildDefinitionInfo from ._models_py3 import AetherVsoBuildInfo from ._models_py3 import AmlDataset from ._models_py3 import AmlK8SConfiguration from ._models_py3 import AmlK8SPriorityConfiguration from ._models_py3 import AmlSparkCloudSetting from ._models_py3 import ApiAndParameters from ._models_py3 import ApplicationEndpointConfiguration from ._models_py3 import ArgumentAssignment from ._models_py3 import Asset from ._models_py3 import AssetDefinition from ._models_py3 import AssetNameAndVersionIdentifier from ._models_py3 import AssetOutputSettings from ._models_py3 import AssetOutputSettingsParameter from ._models_py3 import AssetPublishResult from ._models_py3 import AssetPublishSingleRegionResult from ._models_py3 import AssetTypeMetaInfo from ._models_py3 import AssetVersionPublishRequest from ._models_py3 import AssignedUser from ._models_py3 import AttachCosmosRequest from ._models_py3 import AuthKeys from ._models_py3 import AutoClusterComputeSpecification from ._models_py3 import AutoDeleteSetting from ._models_py3 import AutoFeaturizeConfiguration from ._models_py3 import AutoMLComponentConfiguration from ._models_py3 import AutoScaler from ._models_py3 import AutoTrainConfiguration from ._models_py3 import AutologgerSettings from ._models_py3 import AvailabilityResponse from ._models_py3 import AzureBlobReference from ._models_py3 import AzureDataLakeGen2Reference from ._models_py3 import AzureDataLakeReference from ._models_py3 import AzureDatabaseReference from ._models_py3 import AzureFilesReference from ._models_py3 import AzureMLModuleVersionDescriptor from ._models_py3 import AzureOpenAIDeploymentDto from ._models_py3 import AzureOpenAIModelCapabilities from ._models_py3 import BatchAiComputeInfo from ._models_py3 import BatchDataInput from ._models_py3 import BatchExportComponentSpecResponse from ._models_py3 import BatchExportRawComponentResponse from ._models_py3 import BatchGetComponentHashesRequest from ._models_py3 import BatchGetComponentRequest from ._models_py3 import Binding from ._models_py3 import BulkTestDto from ._models_py3 import CloudError from ._models_py3 import CloudPrioritySetting from ._models_py3 import CloudSettings from ._models_py3 import ColumnTransformer from ._models_py3 import CommandJob from ._models_py3 import CommandJobLimits from ._models_py3 import CommandReturnCodeConfig from ._models_py3 import ComponentConfiguration from ._models_py3 import ComponentInput from ._models_py3 import ComponentJob from ._models_py3 import ComponentJobInput from ._models_py3 import ComponentJobOutput from ._models_py3 import ComponentNameAndDefaultVersion from ._models_py3 import ComponentNameMetaInfo from ._models_py3 import ComponentOutput from ._models_py3 import ComponentPreflightResult from ._models_py3 import ComponentSpecMetaInfo from ._models_py3 import ComponentUpdateRequest from ._models_py3 import ComponentValidationRequest from ._models_py3 import ComponentValidationResponse from ._models_py3 import Compute from ._models_py3 import ComputeConfiguration from ._models_py3 import ComputeContract from ._models_py3 import ComputeIdentityContract from ._models_py3 import ComputeIdentityDto from ._models_py3 import ComputeInfo from ._models_py3 import ComputeProperties from ._models_py3 import ComputeRPUserAssignedIdentity from ._models_py3 import ComputeRequest from ._models_py3 import ComputeSetting from ._models_py3 import ComputeStatus from ._models_py3 import ComputeStatusDetail from ._models_py3 import ComputeWarning from ._models_py3 import ConnectionConfigSpec from ._models_py3 import ConnectionDto from ._models_py3 import ConnectionEntity from ._models_py3 import ConnectionOverrideSetting from ._models_py3 import ConnectionSpec from ._models_py3 import ContainerInstanceConfiguration from ._models_py3 import ContainerRegistry from ._models_py3 import ContainerResourceRequirements from ._models_py3 import ControlInput from ._models_py3 import ControlOutput from ._models_py3 import CopyDataTask from ._models_py3 import CreateFlowRequest from ._models_py3 import CreateFlowRuntimeRequest from ._models_py3 import CreateFlowSessionRequest from ._models_py3 import CreateInferencePipelineRequest from ._models_py3 import CreateOrUpdateConnectionRequest from ._models_py3 import CreateOrUpdateConnectionRequestDto from ._models_py3 import CreatePipelineDraftRequest from ._models_py3 import CreatePipelineJobScheduleDto from ._models_py3 import CreatePublishedPipelineRequest from ._models_py3 import CreateRealTimeEndpointRequest from ._models_py3 import CreatedBy from ._models_py3 import CreatedFromDto from ._models_py3 import CreationContext from ._models_py3 import Cron from ._models_py3 import CustomConnectionConfig from ._models_py3 import CustomReference from ._models_py3 import DBFSReference from ._models_py3 import Data from ._models_py3 import DataInfo from ._models_py3 import DataLocation from ._models_py3 import DataPath from ._models_py3 import DataPathParameter from ._models_py3 import DataPortDto from ._models_py3 import DataReference from ._models_py3 import DataReferenceConfiguration from ._models_py3 import DataSetDefinition from ._models_py3 import DataSetDefinitionValue from ._models_py3 import DataSetPathParameter from ._models_py3 import DataSettings from ._models_py3 import DataTransferCloudConfiguration from ._models_py3 import DataTransferSink from ._models_py3 import DataTransferSource from ._models_py3 import DataTransferV2CloudSetting from ._models_py3 import DataTypeCreationInfo from ._models_py3 import DatabaseSink from ._models_py3 import DatabaseSource from ._models_py3 import DatabricksComputeInfo from ._models_py3 import DatabricksConfiguration from ._models_py3 import DatacacheConfiguration from ._models_py3 import DatasetIdentifier from ._models_py3 import DatasetInputDetails from ._models_py3 import DatasetLineage from ._models_py3 import DatasetOutput from ._models_py3 import DatasetOutputDetails from ._models_py3 import DatasetOutputOptions from ._models_py3 import DatasetRegistration from ._models_py3 import DatasetRegistrationOptions from ._models_py3 import DatastoreSetting from ._models_py3 import DbfsStorageInfoDto from ._models_py3 import DebugInfoResponse from ._models_py3 import DeployFlowRequest from ._models_py3 import DeploymentInfo from ._models_py3 import DistributionConfiguration from ._models_py3 import DistributionParameter from ._models_py3 import DoWhileControlFlowInfo from ._models_py3 import DoWhileControlFlowRunSettings from ._models_py3 import DockerBuildContext from ._models_py3 import DockerConfiguration from ._models_py3 import DockerImagePlatform from ._models_py3 import DockerSection from ._models_py3 import DockerSettingConfiguration from ._models_py3 import DownloadResourceInfo from ._models_py3 import EPRPipelineRunErrorClassificationRequest from ._models_py3 import EndpointSetting from ._models_py3 import EntityInterface from ._models_py3 import EntrySetting from ._models_py3 import EnumParameterRule from ._models_py3 import EnvironmentConfiguration from ._models_py3 import EnvironmentDefinition from ._models_py3 import EnvironmentDefinitionDto from ._models_py3 import ErrorAdditionalInfo from ._models_py3 import ErrorResponse from ._models_py3 import EsCloudConfiguration from ._models_py3 import EvaluationFlowRunSettings from ._models_py3 import ExampleRequest from ._models_py3 import ExecutionContextDto from ._models_py3 import ExecutionDataLocation from ._models_py3 import ExecutionDataPath from ._models_py3 import ExecutionGlobsOptions from ._models_py3 import ExperimentComputeMetaInfo from ._models_py3 import ExperimentInfo from ._models_py3 import ExportComponentMetaInfo from ._models_py3 import ExportDataTask from ._models_py3 import FeaturizationSettings from ._models_py3 import FeedDto from ._models_py3 import FeedDtoSupportedAssetTypes from ._models_py3 import FileSystem from ._models_py3 import Flow from ._models_py3 import FlowAnnotations from ._models_py3 import FlowBaseDto from ._models_py3 import FlowDto from ._models_py3 import FlowEnvironment from ._models_py3 import FlowFeature from ._models_py3 import FlowFeatureState from ._models_py3 import FlowGraph from ._models_py3 import FlowGraphAnnotationNode from ._models_py3 import FlowGraphLayout from ._models_py3 import FlowGraphReference from ._models_py3 import FlowIndexEntity from ._models_py3 import FlowInputDefinition from ._models_py3 import FlowNode from ._models_py3 import FlowNodeLayout from ._models_py3 import FlowNodeVariant from ._models_py3 import FlowOutputDefinition from ._models_py3 import FlowProperties from ._models_py3 import FlowRunBasePath from ._models_py3 import FlowRunInfo from ._models_py3 import FlowRunResult from ._models_py3 import FlowRunSettings from ._models_py3 import FlowRunSettingsBase from ._models_py3 import FlowRunStatusResponse from ._models_py3 import FlowRuntimeCapability from ._models_py3 import FlowRuntimeDto from ._models_py3 import FlowSampleDto from ._models_py3 import FlowSessionDto from ._models_py3 import FlowSnapshot from ._models_py3 import FlowSubmitRunSettings from ._models_py3 import FlowTestInfo from ._models_py3 import FlowTestStorageSetting from ._models_py3 import FlowToolSettingParameter from ._models_py3 import FlowToolsDto from ._models_py3 import FlowVariantNode from ._models_py3 import ForecastHorizon from ._models_py3 import ForecastingSettings from ._models_py3 import GeneralSettings from ._models_py3 import GeneratePipelineComponentRequest from ._models_py3 import GenerateToolMetaRequest from ._models_py3 import GetDynamicListRequest from ._models_py3 import GetRunDataResultDto from ._models_py3 import GetTrainingSessionDto from ._models_py3 import GlobalJobDispatcherConfiguration from ._models_py3 import GlobsOptions from ._models_py3 import GraphAnnotationNode from ._models_py3 import GraphControlNode from ._models_py3 import GraphControlReferenceNode from ._models_py3 import GraphDatasetNode from ._models_py3 import GraphDraftEntity from ._models_py3 import GraphEdge from ._models_py3 import GraphLayout from ._models_py3 import GraphLayoutCreationInfo from ._models_py3 import GraphModuleNode from ._models_py3 import GraphModuleNodeRunSetting from ._models_py3 import GraphModuleNodeUIInputSetting from ._models_py3 import GraphNodeStatusInfo from ._models_py3 import GraphReferenceNode from ._models_py3 import HdfsReference from ._models_py3 import HdiClusterComputeInfo from ._models_py3 import HdiConfiguration from ._models_py3 import HdiRunConfiguration from ._models_py3 import HistoryConfiguration from ._models_py3 import HyperDriveConfiguration from ._models_py3 import ICheckableLongRunningOperationResponse from ._models_py3 import IdentityConfiguration from ._models_py3 import IdentitySetting from ._models_py3 import ImportDataTask from ._models_py3 import IndexedErrorResponse from ._models_py3 import InitScriptInfoDto from ._models_py3 import InnerErrorDetails from ._models_py3 import InnerErrorResponse from ._models_py3 import InputAsset from ._models_py3 import InputData from ._models_py3 import InputDataBinding from ._models_py3 import InputDefinition from ._models_py3 import InputOutputPortMetadata from ._models_py3 import InputSetting from ._models_py3 import IntellectualPropertyPublisherInformation from ._models_py3 import InteractiveConfig from ._models_py3 import InteractiveConfiguration from ._models_py3 import JobCost from ._models_py3 import JobEndpoint from ._models_py3 import JobInput from ._models_py3 import JobOutput from ._models_py3 import JobOutputArtifacts from ._models_py3 import JobScheduleDto from ._models_py3 import K8SConfiguration from ._models_py3 import KeyValuePairComponentNameMetaInfoErrorResponse from ._models_py3 import KeyValuePairComponentNameMetaInfoModuleDto from ._models_py3 import KeyValuePairStringObject from ._models_py3 import KubernetesConfiguration from ._models_py3 import Kwarg from ._models_py3 import LegacyDataPath from ._models_py3 import LimitSettings from ._models_py3 import LinkedADBWorkspaceMetadata from ._models_py3 import LinkedPipelineInfo from ._models_py3 import LoadFlowAsComponentRequest from ._models_py3 import LogRunTerminatedEventDto from ._models_py3 import LongRunningOperationUriResponse from ._models_py3 import LongRunningUpdateRegistryComponentRequest from ._models_py3 import ManagedServiceIdentity from ._models_py3 import MavenLibraryDto from ._models_py3 import MetricProperties from ._models_py3 import MetricSchemaDto from ._models_py3 import MetricSchemaPropertyDto from ._models_py3 import MetricV2Dto from ._models_py3 import MetricV2Value from ._models_py3 import MfeInternalAutologgerSettings from ._models_py3 import MfeInternalIdentityConfiguration from ._models_py3 import MfeInternalNodes from ._models_py3 import MfeInternalOutputData from ._models_py3 import MfeInternalSecretConfiguration from ._models_py3 import MfeInternalUriReference from ._models_py3 import MfeInternalV20211001ComponentJob from ._models_py3 import MinMaxParameterRule from ._models_py3 import MlcComputeInfo from ._models_py3 import ModelDto from ._models_py3 import ModelManagementErrorResponse from ._models_py3 import ModifyPipelineJobScheduleDto from ._models_py3 import ModuleDto from ._models_py3 import ModuleDtoWithErrors from ._models_py3 import ModuleDtoWithValidateStatus from ._models_py3 import ModuleEntity from ._models_py3 import ModulePythonInterface from ._models_py3 import MpiConfiguration from ._models_py3 import NCrossValidations from ._models_py3 import Node from ._models_py3 import NodeInputPort from ._models_py3 import NodeLayout from ._models_py3 import NodeOutputPort from ._models_py3 import NodePortInterface from ._models_py3 import NodeSource from ._models_py3 import NodeTelemetryMetaInfo from ._models_py3 import NodeVariant from ._models_py3 import Nodes from ._models_py3 import NoteBookTaskDto from ._models_py3 import NotificationSetting from ._models_py3 import ODataError from ._models_py3 import ODataErrorDetail from ._models_py3 import ODataErrorResponse from ._models_py3 import ODataInnerError from ._models_py3 import OutputData from ._models_py3 import OutputDataBinding from ._models_py3 import OutputDatasetLineage from ._models_py3 import OutputDefinition from ._models_py3 import OutputOptions from ._models_py3 import OutputSetting from ._models_py3 import OutputSettingSpec from ._models_py3 import PaginatedDataInfoList from ._models_py3 import PaginatedModelDtoList from ._models_py3 import PaginatedModuleDtoList from ._models_py3 import PaginatedPipelineDraftSummaryList from ._models_py3 import PaginatedPipelineEndpointSummaryList from ._models_py3 import PaginatedPipelineRunSummaryList from ._models_py3 import PaginatedPublishedPipelineSummaryList from ._models_py3 import ParallelForControlFlowInfo from ._models_py3 import ParallelTaskConfiguration from ._models_py3 import Parameter from ._models_py3 import ParameterAssignment from ._models_py3 import ParameterDefinition from ._models_py3 import PatchFlowRequest from ._models_py3 import Pipeline from ._models_py3 import PipelineDraft from ._models_py3 import PipelineDraftStepDetails from ._models_py3 import PipelineDraftSummary from ._models_py3 import PipelineEndpoint from ._models_py3 import PipelineEndpointSummary from ._models_py3 import PipelineGraph from ._models_py3 import PipelineInput from ._models_py3 import PipelineJob from ._models_py3 import PipelineJobRuntimeBasicSettings from ._models_py3 import PipelineJobScheduleDto from ._models_py3 import PipelineOutput from ._models_py3 import PipelineRun from ._models_py3 import PipelineRunGraphDetail from ._models_py3 import PipelineRunGraphStatus from ._models_py3 import PipelineRunProfile from ._models_py3 import PipelineRunStatus from ._models_py3 import PipelineRunStepDetails from ._models_py3 import PipelineRunSummary from ._models_py3 import PipelineStatus from ._models_py3 import PipelineStepRun from ._models_py3 import PipelineStepRunOutputs from ._models_py3 import PipelineSubDraft from ._models_py3 import PolicyValidationResponse from ._models_py3 import PortInfo from ._models_py3 import PortOutputInfo from ._models_py3 import PriorityConfig from ._models_py3 import PriorityConfiguration from ._models_py3 import PromoteDataSetRequest from ._models_py3 import ProviderEntity from ._models_py3 import PublishedPipeline from ._models_py3 import PublishedPipelineSummary from ._models_py3 import PyTorchConfiguration from ._models_py3 import PythonInterfaceMapping from ._models_py3 import PythonPyPiOrRCranLibraryDto from ._models_py3 import PythonSection from ._models_py3 import QueueingInfo from ._models_py3 import RCranPackage from ._models_py3 import RGitHubPackage from ._models_py3 import RSection from ._models_py3 import RawComponentDto from ._models_py3 import RayConfiguration from ._models_py3 import RealTimeEndpoint from ._models_py3 import RealTimeEndpointInfo from ._models_py3 import RealTimeEndpointStatus from ._models_py3 import RealTimeEndpointSummary from ._models_py3 import RealTimeEndpointTestRequest from ._models_py3 import Recurrence from ._models_py3 import RecurrencePattern from ._models_py3 import RecurrenceSchedule from ._models_py3 import RegenerateServiceKeysRequest from ._models_py3 import RegisterComponentMetaInfo from ._models_py3 import RegisterComponentMetaInfoExtraHashes from ._models_py3 import RegisterComponentMetaInfoIdentifierHashes from ._models_py3 import RegisterRegistryComponentMetaInfo from ._models_py3 import RegisterRegistryComponentMetaInfoExtraHashes from ._models_py3 import RegisterRegistryComponentMetaInfoIdentifierHashes from ._models_py3 import RegisteredDataSetReference from ._models_py3 import RegistrationOptions from ._models_py3 import RegistryBlobReferenceData from ._models_py3 import RegistryIdentity from ._models_py3 import Relationship from ._models_py3 import RemoteDockerComputeInfo from ._models_py3 import ResourceConfig from ._models_py3 import ResourceConfiguration from ._models_py3 import ResourcesSetting from ._models_py3 import RetrieveToolFuncResultRequest from ._models_py3 import RetryConfiguration from ._models_py3 import RootError from ._models_py3 import RunAnnotations from ._models_py3 import RunCommandsCommandResult from ._models_py3 import RunConfiguration from ._models_py3 import RunDatasetReference from ._models_py3 import RunDefinition from ._models_py3 import RunDetailsDto from ._models_py3 import RunDetailsWarningDto from ._models_py3 import RunDto from ._models_py3 import RunIndexEntity from ._models_py3 import RunIndexMetricSummary from ._models_py3 import RunIndexMetricSummarySystemObject from ._models_py3 import RunIndexResourceMetricSummary from ._models_py3 import RunMetricDto from ._models_py3 import RunMetricsTypesDto from ._models_py3 import RunProperties from ._models_py3 import RunSettingParameter from ._models_py3 import RunSettingParameterAssignment from ._models_py3 import RunSettingUIParameterHint from ._models_py3 import RunStatusPeriod from ._models_py3 import RunTypeV2 from ._models_py3 import RunTypeV2Index from ._models_py3 import RuntimeConfiguration from ._models_py3 import SampleMeta from ._models_py3 import SavePipelineDraftRequest from ._models_py3 import SavedDataSetReference from ._models_py3 import ScheduleBase from ._models_py3 import SchemaContractsCreatedBy from ._models_py3 import ScopeCloudConfiguration from ._models_py3 import Seasonality from ._models_py3 import SecretConfiguration from ._models_py3 import SegmentedResult1 from ._models_py3 import ServiceLogRequest from ._models_py3 import SessionApplication from ._models_py3 import SessionApplicationRunCommandResult from ._models_py3 import SessionProperties from ._models_py3 import SetupFlowSessionRequest from ._models_py3 import SharingScope from ._models_py3 import Snapshot from ._models_py3 import SnapshotInfo from ._models_py3 import SourceCodeDataReference from ._models_py3 import SparkConfiguration from ._models_py3 import SparkJarTaskDto from ._models_py3 import SparkJob from ._models_py3 import SparkJobEntry from ._models_py3 import SparkMavenPackage from ._models_py3 import SparkPythonTaskDto from ._models_py3 import SparkResourceConfiguration from ._models_py3 import SparkSection from ._models_py3 import SparkSubmitTaskDto from ._models_py3 import SqlDataPath from ._models_py3 import StackEnsembleSettings from ._models_py3 import StandbyPoolProperties from ._models_py3 import StandbyPoolResourceStatus from ._models_py3 import StartRunResult from ._models_py3 import StepRunProfile from ._models_py3 import StorageInfo from ._models_py3 import StoredProcedureParameter from ._models_py3 import Stream from ._models_py3 import StructuredInterface from ._models_py3 import StructuredInterfaceInput from ._models_py3 import StructuredInterfaceOutput from ._models_py3 import StructuredInterfaceParameter from ._models_py3 import StudioMigrationInfo from ._models_py3 import SubGraphConcatenateAssignment from ._models_py3 import SubGraphConfiguration from ._models_py3 import SubGraphConnectionInfo from ._models_py3 import SubGraphDataPathParameterAssignment from ._models_py3 import SubGraphInfo from ._models_py3 import SubGraphParameterAssignment from ._models_py3 import SubGraphPortInfo from ._models_py3 import SubPipelineDefinition from ._models_py3 import SubPipelineParameterAssignment from ._models_py3 import SubPipelinesInfo from ._models_py3 import SubStatusPeriod from ._models_py3 import SubmitBulkRunRequest from ._models_py3 import SubmitBulkRunResponse from ._models_py3 import SubmitFlowRequest from ._models_py3 import SubmitPipelineRunRequest from ._models_py3 import SweepEarlyTerminationPolicy from ._models_py3 import SweepSettings from ._models_py3 import SweepSettingsLimits from ._models_py3 import SystemData from ._models_py3 import SystemMeta from ._models_py3 import SystemMetaExtraHashes from ._models_py3 import SystemMetaIdentifierHashes from ._models_py3 import TargetLags from ._models_py3 import TargetRollingWindowSize from ._models_py3 import TargetSelectorConfiguration from ._models_py3 import Task from ._models_py3 import TaskControlFlowInfo from ._models_py3 import TaskReuseInfo from ._models_py3 import TensorflowConfiguration from ._models_py3 import TestDataSettings from ._models_py3 import Tool from ._models_py3 import ToolFuncResponse from ._models_py3 import ToolInputDynamicList from ._models_py3 import ToolInputGeneratedBy from ._models_py3 import ToolMetaDto from ._models_py3 import ToolSetting from ._models_py3 import ToolSourceMeta from ._models_py3 import TorchDistributedConfiguration from ._models_py3 import TrainingDiagnosticConfiguration from ._models_py3 import TrainingOutput from ._models_py3 import TrainingSettings from ._models_py3 import TriggerAsyncOperationStatus from ._models_py3 import TuningNodeRunSetting from ._models_py3 import TuningNodeSetting from ._models_py3 import TypedAssetReference from ._models_py3 import UIAzureOpenAIDeploymentNameSelector from ._models_py3 import UIAzureOpenAIModelCapabilities from ._models_py3 import UIColumnPicker from ._models_py3 import UIComputeSelection from ._models_py3 import UIHyperparameterConfiguration from ._models_py3 import UIInputSetting from ._models_py3 import UIJsonEditor from ._models_py3 import UIParameterHint from ._models_py3 import UIPromptFlowConnectionSelector from ._models_py3 import UIWidgetMetaInfo from ._models_py3 import UIYamlEditor from ._models_py3 import UnversionedEntityRequestDto from ._models_py3 import UnversionedEntityResponseDto from ._models_py3 import UnversionedRebuildIndexDto from ._models_py3 import UnversionedRebuildResponseDto from ._models_py3 import UpdateComponentRequest from ._models_py3 import UpdateFlowRequest from ._models_py3 import UpdateFlowRuntimeRequest from ._models_py3 import UpdateFlowStatusRequest from ._models_py3 import UpdateRegistryComponentRequest from ._models_py3 import UploadOptions from ._models_py3 import UriReference from ._models_py3 import User from ._models_py3 import UserAssignedIdentity from ._models_py3 import ValidationDataSettings from ._models_py3 import VariantIdentifier from ._models_py3 import VariantNode from ._models_py3 import Volume from ._models_py3 import WebServiceComputeMetaInfo from ._models_py3 import WebServicePort from ._models_py3 import Webhook from ._models_py3 import WorkspaceConnectionSpec except (SyntaxError, ImportError): from ._models import ACIAdvanceSettings # type: ignore from ._models import AEVAComputeConfiguration # type: ignore from ._models import AEVAResourceConfiguration # type: ignore from ._models import AISuperComputerConfiguration # type: ignore from ._models import AISuperComputerScalePolicy # type: ignore from ._models import AISuperComputerStorageReferenceConfiguration # type: ignore from ._models import AKSAdvanceSettings # type: ignore from ._models import AKSReplicaStatus # type: ignore from ._models import AMLComputeConfiguration # type: ignore from ._models import APCloudConfiguration # type: ignore from ._models import Activate # type: ignore from ._models import AdditionalErrorInfo # type: ignore from ._models import AdhocTriggerScheduledCommandJobRequest # type: ignore from ._models import AdhocTriggerScheduledSparkJobRequest # type: ignore from ._models import AetherAPCloudConfiguration # type: ignore from ._models import AetherAmlDataset # type: ignore from ._models import AetherAmlSparkCloudSetting # type: ignore from ._models import AetherArgumentAssignment # type: ignore from ._models import AetherAssetDefinition # type: ignore from ._models import AetherAssetOutputSettings # type: ignore from ._models import AetherAutoFeaturizeConfiguration # type: ignore from ._models import AetherAutoMLComponentConfiguration # type: ignore from ._models import AetherAutoTrainConfiguration # type: ignore from ._models import AetherAzureBlobReference # type: ignore from ._models import AetherAzureDataLakeGen2Reference # type: ignore from ._models import AetherAzureDataLakeReference # type: ignore from ._models import AetherAzureDatabaseReference # type: ignore from ._models import AetherAzureFilesReference # type: ignore from ._models import AetherBatchAiComputeInfo # type: ignore from ._models import AetherBuildArtifactInfo # type: ignore from ._models import AetherCloudBuildDropPathInfo # type: ignore from ._models import AetherCloudBuildInfo # type: ignore from ._models import AetherCloudBuildQueueInfo # type: ignore from ._models import AetherCloudPrioritySetting # type: ignore from ._models import AetherCloudSettings # type: ignore from ._models import AetherColumnTransformer # type: ignore from ._models import AetherComputeConfiguration # type: ignore from ._models import AetherComputeSetting # type: ignore from ._models import AetherControlInput # type: ignore from ._models import AetherControlOutput # type: ignore from ._models import AetherCopyDataTask # type: ignore from ._models import AetherCosmosReference # type: ignore from ._models import AetherCreatedBy # type: ignore from ._models import AetherCustomReference # type: ignore from ._models import AetherDBFSReference # type: ignore from ._models import AetherDataLocation # type: ignore from ._models import AetherDataLocationReuseCalculationFields # type: ignore from ._models import AetherDataPath # type: ignore from ._models import AetherDataReference # type: ignore from ._models import AetherDataSetDefinition # type: ignore from ._models import AetherDataSetDefinitionValue # type: ignore from ._models import AetherDataSettings # type: ignore from ._models import AetherDataTransferCloudConfiguration # type: ignore from ._models import AetherDataTransferSink # type: ignore from ._models import AetherDataTransferSource # type: ignore from ._models import AetherDataTransferV2CloudSetting # type: ignore from ._models import AetherDatabaseSink # type: ignore from ._models import AetherDatabaseSource # type: ignore from ._models import AetherDatabricksComputeInfo # type: ignore from ._models import AetherDatasetOutput # type: ignore from ._models import AetherDatasetOutputOptions # type: ignore from ._models import AetherDatasetRegistration # type: ignore from ._models import AetherDatastoreSetting # type: ignore from ._models import AetherDoWhileControlFlowInfo # type: ignore from ._models import AetherDoWhileControlFlowRunSettings # type: ignore from ._models import AetherDockerSettingConfiguration # type: ignore from ._models import AetherEntityInterfaceDocumentation # type: ignore from ._models import AetherEntrySetting # type: ignore from ._models import AetherEnvironmentConfiguration # type: ignore from ._models import AetherEsCloudConfiguration # type: ignore from ._models import AetherExportDataTask # type: ignore from ._models import AetherFeaturizationSettings # type: ignore from ._models import AetherFileSystem # type: ignore from ._models import AetherForecastHorizon # type: ignore from ._models import AetherForecastingSettings # type: ignore from ._models import AetherGeneralSettings # type: ignore from ._models import AetherGlobsOptions # type: ignore from ._models import AetherGraphControlNode # type: ignore from ._models import AetherGraphControlReferenceNode # type: ignore from ._models import AetherGraphDatasetNode # type: ignore from ._models import AetherGraphEdge # type: ignore from ._models import AetherGraphEntity # type: ignore from ._models import AetherGraphModuleNode # type: ignore from ._models import AetherGraphReferenceNode # type: ignore from ._models import AetherHdfsReference # type: ignore from ._models import AetherHdiClusterComputeInfo # type: ignore from ._models import AetherHdiRunConfiguration # type: ignore from ._models import AetherHyperDriveConfiguration # type: ignore from ._models import AetherIdentitySetting # type: ignore from ._models import AetherImportDataTask # type: ignore from ._models import AetherInputSetting # type: ignore from ._models import AetherInteractiveConfig # type: ignore from ._models import AetherK8SConfiguration # type: ignore from ._models import AetherLegacyDataPath # type: ignore from ._models import AetherLimitSettings # type: ignore from ._models import AetherMlcComputeInfo # type: ignore from ._models import AetherModuleEntity # type: ignore from ._models import AetherModuleExtendedProperties # type: ignore from ._models import AetherNCrossValidations # type: ignore from ._models import AetherOutputSetting # type: ignore from ._models import AetherParallelForControlFlowInfo # type: ignore from ._models import AetherParameterAssignment # type: ignore from ._models import AetherPhillyHdfsReference # type: ignore from ._models import AetherPortInfo # type: ignore from ._models import AetherPriorityConfig # type: ignore from ._models import AetherPriorityConfiguration # type: ignore from ._models import AetherRegisteredDataSetReference # type: ignore from ._models import AetherRemoteDockerComputeInfo # type: ignore from ._models import AetherResourceAssignment # type: ignore from ._models import AetherResourceAttributeAssignment # type: ignore from ._models import AetherResourceAttributeDefinition # type: ignore from ._models import AetherResourceConfig # type: ignore from ._models import AetherResourceConfiguration # type: ignore from ._models import AetherResourceModel # type: ignore from ._models import AetherResourcesSetting # type: ignore from ._models import AetherSavedDataSetReference # type: ignore from ._models import AetherScopeCloudConfiguration # type: ignore from ._models import AetherSeasonality # type: ignore from ._models import AetherSqlDataPath # type: ignore from ._models import AetherStackEnsembleSettings # type: ignore from ._models import AetherStoredProcedureParameter # type: ignore from ._models import AetherStructuredInterface # type: ignore from ._models import AetherStructuredInterfaceInput # type: ignore from ._models import AetherStructuredInterfaceOutput # type: ignore from ._models import AetherStructuredInterfaceParameter # type: ignore from ._models import AetherSubGraphConfiguration # type: ignore from ._models import AetherSweepEarlyTerminationPolicy # type: ignore from ._models import AetherSweepSettings # type: ignore from ._models import AetherSweepSettingsLimits # type: ignore from ._models import AetherTargetLags # type: ignore from ._models import AetherTargetRollingWindowSize # type: ignore from ._models import AetherTargetSelectorConfiguration # type: ignore from ._models import AetherTestDataSettings # type: ignore from ._models import AetherTorchDistributedConfiguration # type: ignore from ._models import AetherTrainingOutput # type: ignore from ._models import AetherTrainingSettings # type: ignore from ._models import AetherUIAzureOpenAIDeploymentNameSelector # type: ignore from ._models import AetherUIAzureOpenAIModelCapabilities # type: ignore from ._models import AetherUIColumnPicker # type: ignore from ._models import AetherUIJsonEditor # type: ignore from ._models import AetherUIParameterHint # type: ignore from ._models import AetherUIPromptFlowConnectionSelector # type: ignore from ._models import AetherValidationDataSettings # type: ignore from ._models import AetherVsoBuildArtifactInfo # type: ignore from ._models import AetherVsoBuildDefinitionInfo # type: ignore from ._models import AetherVsoBuildInfo # type: ignore from ._models import AmlDataset # type: ignore from ._models import AmlK8SConfiguration # type: ignore from ._models import AmlK8SPriorityConfiguration # type: ignore from ._models import AmlSparkCloudSetting # type: ignore from ._models import ApiAndParameters # type: ignore from ._models import ApplicationEndpointConfiguration # type: ignore from ._models import ArgumentAssignment # type: ignore from ._models import Asset # type: ignore from ._models import AssetDefinition # type: ignore from ._models import AssetNameAndVersionIdentifier # type: ignore from ._models import AssetOutputSettings # type: ignore from ._models import AssetOutputSettingsParameter # type: ignore from ._models import AssetPublishResult # type: ignore from ._models import AssetPublishSingleRegionResult # type: ignore from ._models import AssetTypeMetaInfo # type: ignore from ._models import AssetVersionPublishRequest # type: ignore from ._models import AssignedUser # type: ignore from ._models import AttachCosmosRequest # type: ignore from ._models import AuthKeys # type: ignore from ._models import AutoClusterComputeSpecification # type: ignore from ._models import AutoDeleteSetting # type: ignore from ._models import AutoFeaturizeConfiguration # type: ignore from ._models import AutoMLComponentConfiguration # type: ignore from ._models import AutoScaler # type: ignore from ._models import AutoTrainConfiguration # type: ignore from ._models import AutologgerSettings # type: ignore from ._models import AvailabilityResponse # type: ignore from ._models import AzureBlobReference # type: ignore from ._models import AzureDataLakeGen2Reference # type: ignore from ._models import AzureDataLakeReference # type: ignore from ._models import AzureDatabaseReference # type: ignore from ._models import AzureFilesReference # type: ignore from ._models import AzureMLModuleVersionDescriptor # type: ignore from ._models import AzureOpenAIDeploymentDto # type: ignore from ._models import AzureOpenAIModelCapabilities # type: ignore from ._models import BatchAiComputeInfo # type: ignore from ._models import BatchDataInput # type: ignore from ._models import BatchExportComponentSpecResponse # type: ignore from ._models import BatchExportRawComponentResponse # type: ignore from ._models import BatchGetComponentHashesRequest # type: ignore from ._models import BatchGetComponentRequest # type: ignore from ._models import Binding # type: ignore from ._models import BulkTestDto # type: ignore from ._models import CloudError # type: ignore from ._models import CloudPrioritySetting # type: ignore from ._models import CloudSettings # type: ignore from ._models import ColumnTransformer # type: ignore from ._models import CommandJob # type: ignore from ._models import CommandJobLimits # type: ignore from ._models import CommandReturnCodeConfig # type: ignore from ._models import ComponentConfiguration # type: ignore from ._models import ComponentInput # type: ignore from ._models import ComponentJob # type: ignore from ._models import ComponentJobInput # type: ignore from ._models import ComponentJobOutput # type: ignore from ._models import ComponentNameAndDefaultVersion # type: ignore from ._models import ComponentNameMetaInfo # type: ignore from ._models import ComponentOutput # type: ignore from ._models import ComponentPreflightResult # type: ignore from ._models import ComponentSpecMetaInfo # type: ignore from ._models import ComponentUpdateRequest # type: ignore from ._models import ComponentValidationRequest # type: ignore from ._models import ComponentValidationResponse # type: ignore from ._models import Compute # type: ignore from ._models import ComputeConfiguration # type: ignore from ._models import ComputeContract # type: ignore from ._models import ComputeIdentityContract # type: ignore from ._models import ComputeIdentityDto # type: ignore from ._models import ComputeInfo # type: ignore from ._models import ComputeProperties # type: ignore from ._models import ComputeRPUserAssignedIdentity # type: ignore from ._models import ComputeRequest # type: ignore from ._models import ComputeSetting # type: ignore from ._models import ComputeStatus # type: ignore from ._models import ComputeStatusDetail # type: ignore from ._models import ComputeWarning # type: ignore from ._models import ConnectionConfigSpec # type: ignore from ._models import ConnectionDto # type: ignore from ._models import ConnectionEntity # type: ignore from ._models import ConnectionOverrideSetting # type: ignore from ._models import ConnectionSpec # type: ignore from ._models import ContainerInstanceConfiguration # type: ignore from ._models import ContainerRegistry # type: ignore from ._models import ContainerResourceRequirements # type: ignore from ._models import ControlInput # type: ignore from ._models import ControlOutput # type: ignore from ._models import CopyDataTask # type: ignore from ._models import CreateFlowRequest # type: ignore from ._models import CreateFlowRuntimeRequest # type: ignore from ._models import CreateFlowSessionRequest # type: ignore from ._models import CreateInferencePipelineRequest # type: ignore from ._models import CreateOrUpdateConnectionRequest # type: ignore from ._models import CreateOrUpdateConnectionRequestDto # type: ignore from ._models import CreatePipelineDraftRequest # type: ignore from ._models import CreatePipelineJobScheduleDto # type: ignore from ._models import CreatePublishedPipelineRequest # type: ignore from ._models import CreateRealTimeEndpointRequest # type: ignore from ._models import CreatedBy # type: ignore from ._models import CreatedFromDto # type: ignore from ._models import CreationContext # type: ignore from ._models import Cron # type: ignore from ._models import CustomConnectionConfig # type: ignore from ._models import CustomReference # type: ignore from ._models import DBFSReference # type: ignore from ._models import Data # type: ignore from ._models import DataInfo # type: ignore from ._models import DataLocation # type: ignore from ._models import DataPath # type: ignore from ._models import DataPathParameter # type: ignore from ._models import DataPortDto # type: ignore from ._models import DataReference # type: ignore from ._models import DataReferenceConfiguration # type: ignore from ._models import DataSetDefinition # type: ignore from ._models import DataSetDefinitionValue # type: ignore from ._models import DataSetPathParameter # type: ignore from ._models import DataSettings # type: ignore from ._models import DataTransferCloudConfiguration # type: ignore from ._models import DataTransferSink # type: ignore from ._models import DataTransferSource # type: ignore from ._models import DataTransferV2CloudSetting # type: ignore from ._models import DataTypeCreationInfo # type: ignore from ._models import DatabaseSink # type: ignore from ._models import DatabaseSource # type: ignore from ._models import DatabricksComputeInfo # type: ignore from ._models import DatabricksConfiguration # type: ignore from ._models import DatacacheConfiguration # type: ignore from ._models import DatasetIdentifier # type: ignore from ._models import DatasetInputDetails # type: ignore from ._models import DatasetLineage # type: ignore from ._models import DatasetOutput # type: ignore from ._models import DatasetOutputDetails # type: ignore from ._models import DatasetOutputOptions # type: ignore from ._models import DatasetRegistration # type: ignore from ._models import DatasetRegistrationOptions # type: ignore from ._models import DatastoreSetting # type: ignore from ._models import DbfsStorageInfoDto # type: ignore from ._models import DebugInfoResponse # type: ignore from ._models import DeployFlowRequest # type: ignore from ._models import DeploymentInfo # type: ignore from ._models import DistributionConfiguration # type: ignore from ._models import DistributionParameter # type: ignore from ._models import DoWhileControlFlowInfo # type: ignore from ._models import DoWhileControlFlowRunSettings # type: ignore from ._models import DockerBuildContext # type: ignore from ._models import DockerConfiguration # type: ignore from ._models import DockerImagePlatform # type: ignore from ._models import DockerSection # type: ignore from ._models import DockerSettingConfiguration # type: ignore from ._models import DownloadResourceInfo # type: ignore from ._models import EPRPipelineRunErrorClassificationRequest # type: ignore from ._models import EndpointSetting # type: ignore from ._models import EntityInterface # type: ignore from ._models import EntrySetting # type: ignore from ._models import EnumParameterRule # type: ignore from ._models import EnvironmentConfiguration # type: ignore from ._models import EnvironmentDefinition # type: ignore from ._models import EnvironmentDefinitionDto # type: ignore from ._models import ErrorAdditionalInfo # type: ignore from ._models import ErrorResponse # type: ignore from ._models import EsCloudConfiguration # type: ignore from ._models import EvaluationFlowRunSettings # type: ignore from ._models import ExampleRequest # type: ignore from ._models import ExecutionContextDto # type: ignore from ._models import ExecutionDataLocation # type: ignore from ._models import ExecutionDataPath # type: ignore from ._models import ExecutionGlobsOptions # type: ignore from ._models import ExperimentComputeMetaInfo # type: ignore from ._models import ExperimentInfo # type: ignore from ._models import ExportComponentMetaInfo # type: ignore from ._models import ExportDataTask # type: ignore from ._models import FeaturizationSettings # type: ignore from ._models import FeedDto # type: ignore from ._models import FeedDtoSupportedAssetTypes # type: ignore from ._models import FileSystem # type: ignore from ._models import Flow # type: ignore from ._models import FlowAnnotations # type: ignore from ._models import FlowBaseDto # type: ignore from ._models import FlowDto # type: ignore from ._models import FlowEnvironment # type: ignore from ._models import FlowFeature # type: ignore from ._models import FlowFeatureState # type: ignore from ._models import FlowGraph # type: ignore from ._models import FlowGraphAnnotationNode # type: ignore from ._models import FlowGraphLayout # type: ignore from ._models import FlowGraphReference # type: ignore from ._models import FlowIndexEntity # type: ignore from ._models import FlowInputDefinition # type: ignore from ._models import FlowNode # type: ignore from ._models import FlowNodeLayout # type: ignore from ._models import FlowNodeVariant # type: ignore from ._models import FlowOutputDefinition # type: ignore from ._models import FlowProperties # type: ignore from ._models import FlowRunBasePath # type: ignore from ._models import FlowRunInfo # type: ignore from ._models import FlowRunResult # type: ignore from ._models import FlowRunSettings # type: ignore from ._models import FlowRunSettingsBase # type: ignore from ._models import FlowRunStatusResponse # type: ignore from ._models import FlowRuntimeCapability # type: ignore from ._models import FlowRuntimeDto # type: ignore from ._models import FlowSampleDto # type: ignore from ._models import FlowSessionDto # type: ignore from ._models import FlowSnapshot # type: ignore from ._models import FlowSubmitRunSettings # type: ignore from ._models import FlowTestInfo # type: ignore from ._models import FlowTestStorageSetting # type: ignore from ._models import FlowToolSettingParameter # type: ignore from ._models import FlowToolsDto # type: ignore from ._models import FlowVariantNode # type: ignore from ._models import ForecastHorizon # type: ignore from ._models import ForecastingSettings # type: ignore from ._models import GeneralSettings # type: ignore from ._models import GeneratePipelineComponentRequest # type: ignore from ._models import GenerateToolMetaRequest # type: ignore from ._models import GetDynamicListRequest # type: ignore from ._models import GetRunDataResultDto # type: ignore from ._models import GetTrainingSessionDto # type: ignore from ._models import GlobalJobDispatcherConfiguration # type: ignore from ._models import GlobsOptions # type: ignore from ._models import GraphAnnotationNode # type: ignore from ._models import GraphControlNode # type: ignore from ._models import GraphControlReferenceNode # type: ignore from ._models import GraphDatasetNode # type: ignore from ._models import GraphDraftEntity # type: ignore from ._models import GraphEdge # type: ignore from ._models import GraphLayout # type: ignore from ._models import GraphLayoutCreationInfo # type: ignore from ._models import GraphModuleNode # type: ignore from ._models import GraphModuleNodeRunSetting # type: ignore from ._models import GraphModuleNodeUIInputSetting # type: ignore from ._models import GraphNodeStatusInfo # type: ignore from ._models import GraphReferenceNode # type: ignore from ._models import HdfsReference # type: ignore from ._models import HdiClusterComputeInfo # type: ignore from ._models import HdiConfiguration # type: ignore from ._models import HdiRunConfiguration # type: ignore from ._models import HistoryConfiguration # type: ignore from ._models import HyperDriveConfiguration # type: ignore from ._models import ICheckableLongRunningOperationResponse # type: ignore from ._models import IdentityConfiguration # type: ignore from ._models import IdentitySetting # type: ignore from ._models import ImportDataTask # type: ignore from ._models import IndexedErrorResponse # type: ignore from ._models import InitScriptInfoDto # type: ignore from ._models import InnerErrorDetails # type: ignore from ._models import InnerErrorResponse # type: ignore from ._models import InputAsset # type: ignore from ._models import InputData # type: ignore from ._models import InputDataBinding # type: ignore from ._models import InputDefinition # type: ignore from ._models import InputOutputPortMetadata # type: ignore from ._models import InputSetting # type: ignore from ._models import IntellectualPropertyPublisherInformation # type: ignore from ._models import InteractiveConfig # type: ignore from ._models import InteractiveConfiguration # type: ignore from ._models import JobCost # type: ignore from ._models import JobEndpoint # type: ignore from ._models import JobInput # type: ignore from ._models import JobOutput # type: ignore from ._models import JobOutputArtifacts # type: ignore from ._models import JobScheduleDto # type: ignore from ._models import K8SConfiguration # type: ignore from ._models import KeyValuePairComponentNameMetaInfoErrorResponse # type: ignore from ._models import KeyValuePairComponentNameMetaInfoModuleDto # type: ignore from ._models import KeyValuePairStringObject # type: ignore from ._models import KubernetesConfiguration # type: ignore from ._models import Kwarg # type: ignore from ._models import LegacyDataPath # type: ignore from ._models import LimitSettings # type: ignore from ._models import LinkedADBWorkspaceMetadata # type: ignore from ._models import LinkedPipelineInfo # type: ignore from ._models import LoadFlowAsComponentRequest # type: ignore from ._models import LogRunTerminatedEventDto # type: ignore from ._models import LongRunningOperationUriResponse # type: ignore from ._models import LongRunningUpdateRegistryComponentRequest # type: ignore from ._models import ManagedServiceIdentity # type: ignore from ._models import MavenLibraryDto # type: ignore from ._models import MetricProperties # type: ignore from ._models import MetricSchemaDto # type: ignore from ._models import MetricSchemaPropertyDto # type: ignore from ._models import MetricV2Dto # type: ignore from ._models import MetricV2Value # type: ignore from ._models import MfeInternalAutologgerSettings # type: ignore from ._models import MfeInternalIdentityConfiguration # type: ignore from ._models import MfeInternalNodes # type: ignore from ._models import MfeInternalOutputData # type: ignore from ._models import MfeInternalSecretConfiguration # type: ignore from ._models import MfeInternalUriReference # type: ignore from ._models import MfeInternalV20211001ComponentJob # type: ignore from ._models import MinMaxParameterRule # type: ignore from ._models import MlcComputeInfo # type: ignore from ._models import ModelDto # type: ignore from ._models import ModelManagementErrorResponse # type: ignore from ._models import ModifyPipelineJobScheduleDto # type: ignore from ._models import ModuleDto # type: ignore from ._models import ModuleDtoWithErrors # type: ignore from ._models import ModuleDtoWithValidateStatus # type: ignore from ._models import ModuleEntity # type: ignore from ._models import ModulePythonInterface # type: ignore from ._models import MpiConfiguration # type: ignore from ._models import NCrossValidations # type: ignore from ._models import Node # type: ignore from ._models import NodeInputPort # type: ignore from ._models import NodeLayout # type: ignore from ._models import NodeOutputPort # type: ignore from ._models import NodePortInterface # type: ignore from ._models import NodeSource # type: ignore from ._models import NodeTelemetryMetaInfo # type: ignore from ._models import NodeVariant # type: ignore from ._models import Nodes # type: ignore from ._models import NoteBookTaskDto # type: ignore from ._models import NotificationSetting # type: ignore from ._models import ODataError # type: ignore from ._models import ODataErrorDetail # type: ignore from ._models import ODataErrorResponse # type: ignore from ._models import ODataInnerError # type: ignore from ._models import OutputData # type: ignore from ._models import OutputDataBinding # type: ignore from ._models import OutputDatasetLineage # type: ignore from ._models import OutputDefinition # type: ignore from ._models import OutputOptions # type: ignore from ._models import OutputSetting # type: ignore from ._models import OutputSettingSpec # type: ignore from ._models import PaginatedDataInfoList # type: ignore from ._models import PaginatedModelDtoList # type: ignore from ._models import PaginatedModuleDtoList # type: ignore from ._models import PaginatedPipelineDraftSummaryList # type: ignore from ._models import PaginatedPipelineEndpointSummaryList # type: ignore from ._models import PaginatedPipelineRunSummaryList # type: ignore from ._models import PaginatedPublishedPipelineSummaryList # type: ignore from ._models import ParallelForControlFlowInfo # type: ignore from ._models import ParallelTaskConfiguration # type: ignore from ._models import Parameter # type: ignore from ._models import ParameterAssignment # type: ignore from ._models import ParameterDefinition # type: ignore from ._models import PatchFlowRequest # type: ignore from ._models import Pipeline # type: ignore from ._models import PipelineDraft # type: ignore from ._models import PipelineDraftStepDetails # type: ignore from ._models import PipelineDraftSummary # type: ignore from ._models import PipelineEndpoint # type: ignore from ._models import PipelineEndpointSummary # type: ignore from ._models import PipelineGraph # type: ignore from ._models import PipelineInput # type: ignore from ._models import PipelineJob # type: ignore from ._models import PipelineJobRuntimeBasicSettings # type: ignore from ._models import PipelineJobScheduleDto # type: ignore from ._models import PipelineOutput # type: ignore from ._models import PipelineRun # type: ignore from ._models import PipelineRunGraphDetail # type: ignore from ._models import PipelineRunGraphStatus # type: ignore from ._models import PipelineRunProfile # type: ignore from ._models import PipelineRunStatus # type: ignore from ._models import PipelineRunStepDetails # type: ignore from ._models import PipelineRunSummary # type: ignore from ._models import PipelineStatus # type: ignore from ._models import PipelineStepRun # type: ignore from ._models import PipelineStepRunOutputs # type: ignore from ._models import PipelineSubDraft # type: ignore from ._models import PolicyValidationResponse # type: ignore from ._models import PortInfo # type: ignore from ._models import PortOutputInfo # type: ignore from ._models import PriorityConfig # type: ignore from ._models import PriorityConfiguration # type: ignore from ._models import PromoteDataSetRequest # type: ignore from ._models import ProviderEntity # type: ignore from ._models import PublishedPipeline # type: ignore from ._models import PublishedPipelineSummary # type: ignore from ._models import PyTorchConfiguration # type: ignore from ._models import PythonInterfaceMapping # type: ignore from ._models import PythonPyPiOrRCranLibraryDto # type: ignore from ._models import PythonSection # type: ignore from ._models import QueueingInfo # type: ignore from ._models import RCranPackage # type: ignore from ._models import RGitHubPackage # type: ignore from ._models import RSection # type: ignore from ._models import RawComponentDto # type: ignore from ._models import RayConfiguration # type: ignore from ._models import RealTimeEndpoint # type: ignore from ._models import RealTimeEndpointInfo # type: ignore from ._models import RealTimeEndpointStatus # type: ignore from ._models import RealTimeEndpointSummary # type: ignore from ._models import RealTimeEndpointTestRequest # type: ignore from ._models import Recurrence # type: ignore from ._models import RecurrencePattern # type: ignore from ._models import RecurrenceSchedule # type: ignore from ._models import RegenerateServiceKeysRequest # type: ignore from ._models import RegisterComponentMetaInfo # type: ignore from ._models import RegisterComponentMetaInfoExtraHashes # type: ignore from ._models import RegisterComponentMetaInfoIdentifierHashes # type: ignore from ._models import RegisterRegistryComponentMetaInfo # type: ignore from ._models import RegisterRegistryComponentMetaInfoExtraHashes # type: ignore from ._models import RegisterRegistryComponentMetaInfoIdentifierHashes # type: ignore from ._models import RegisteredDataSetReference # type: ignore from ._models import RegistrationOptions # type: ignore from ._models import RegistryBlobReferenceData # type: ignore from ._models import RegistryIdentity # type: ignore from ._models import Relationship # type: ignore from ._models import RemoteDockerComputeInfo # type: ignore from ._models import ResourceConfig # type: ignore from ._models import ResourceConfiguration # type: ignore from ._models import ResourcesSetting # type: ignore from ._models import RetrieveToolFuncResultRequest # type: ignore from ._models import RetryConfiguration # type: ignore from ._models import RootError # type: ignore from ._models import RunAnnotations # type: ignore from ._models import RunCommandsCommandResult # type: ignore from ._models import RunConfiguration # type: ignore from ._models import RunDatasetReference # type: ignore from ._models import RunDefinition # type: ignore from ._models import RunDetailsDto # type: ignore from ._models import RunDetailsWarningDto # type: ignore from ._models import RunDto # type: ignore from ._models import RunIndexEntity # type: ignore from ._models import RunIndexMetricSummary # type: ignore from ._models import RunIndexMetricSummarySystemObject # type: ignore from ._models import RunIndexResourceMetricSummary # type: ignore from ._models import RunMetricDto # type: ignore from ._models import RunMetricsTypesDto # type: ignore from ._models import RunProperties # type: ignore from ._models import RunSettingParameter # type: ignore from ._models import RunSettingParameterAssignment # type: ignore from ._models import RunSettingUIParameterHint # type: ignore from ._models import RunStatusPeriod # type: ignore from ._models import RunTypeV2 # type: ignore from ._models import RunTypeV2Index # type: ignore from ._models import RuntimeConfiguration # type: ignore from ._models import SampleMeta # type: ignore from ._models import SavePipelineDraftRequest # type: ignore from ._models import SavedDataSetReference # type: ignore from ._models import ScheduleBase # type: ignore from ._models import SchemaContractsCreatedBy # type: ignore from ._models import ScopeCloudConfiguration # type: ignore from ._models import Seasonality # type: ignore from ._models import SecretConfiguration # type: ignore from ._models import SegmentedResult1 # type: ignore from ._models import ServiceLogRequest # type: ignore from ._models import SessionApplication # type: ignore from ._models import SessionApplicationRunCommandResult # type: ignore from ._models import SessionProperties # type: ignore from ._models import SetupFlowSessionRequest # type: ignore from ._models import SharingScope # type: ignore from ._models import Snapshot # type: ignore from ._models import SnapshotInfo # type: ignore from ._models import SourceCodeDataReference # type: ignore from ._models import SparkConfiguration # type: ignore from ._models import SparkJarTaskDto # type: ignore from ._models import SparkJob # type: ignore from ._models import SparkJobEntry # type: ignore from ._models import SparkMavenPackage # type: ignore from ._models import SparkPythonTaskDto # type: ignore from ._models import SparkResourceConfiguration # type: ignore from ._models import SparkSection # type: ignore from ._models import SparkSubmitTaskDto # type: ignore from ._models import SqlDataPath # type: ignore from ._models import StackEnsembleSettings # type: ignore from ._models import StandbyPoolProperties # type: ignore from ._models import StandbyPoolResourceStatus # type: ignore from ._models import StartRunResult # type: ignore from ._models import StepRunProfile # type: ignore from ._models import StorageInfo # type: ignore from ._models import StoredProcedureParameter # type: ignore from ._models import Stream # type: ignore from ._models import StructuredInterface # type: ignore from ._models import StructuredInterfaceInput # type: ignore from ._models import StructuredInterfaceOutput # type: ignore from ._models import StructuredInterfaceParameter # type: ignore from ._models import StudioMigrationInfo # type: ignore from ._models import SubGraphConcatenateAssignment # type: ignore from ._models import SubGraphConfiguration # type: ignore from ._models import SubGraphConnectionInfo # type: ignore from ._models import SubGraphDataPathParameterAssignment # type: ignore from ._models import SubGraphInfo # type: ignore from ._models import SubGraphParameterAssignment # type: ignore from ._models import SubGraphPortInfo # type: ignore from ._models import SubPipelineDefinition # type: ignore from ._models import SubPipelineParameterAssignment # type: ignore from ._models import SubPipelinesInfo # type: ignore from ._models import SubStatusPeriod # type: ignore from ._models import SubmitBulkRunRequest # type: ignore from ._models import SubmitBulkRunResponse # type: ignore from ._models import SubmitFlowRequest # type: ignore from ._models import SubmitPipelineRunRequest # type: ignore from ._models import SweepEarlyTerminationPolicy # type: ignore from ._models import SweepSettings # type: ignore from ._models import SweepSettingsLimits # type: ignore from ._models import SystemData # type: ignore from ._models import SystemMeta # type: ignore from ._models import SystemMetaExtraHashes # type: ignore from ._models import SystemMetaIdentifierHashes # type: ignore from ._models import TargetLags # type: ignore from ._models import TargetRollingWindowSize # type: ignore from ._models import TargetSelectorConfiguration # type: ignore from ._models import Task # type: ignore from ._models import TaskControlFlowInfo # type: ignore from ._models import TaskReuseInfo # type: ignore from ._models import TensorflowConfiguration # type: ignore from ._models import TestDataSettings # type: ignore from ._models import Tool # type: ignore from ._models import ToolFuncResponse # type: ignore from ._models import ToolInputDynamicList # type: ignore from ._models import ToolInputGeneratedBy # type: ignore from ._models import ToolMetaDto # type: ignore from ._models import ToolSetting # type: ignore from ._models import ToolSourceMeta # type: ignore from ._models import TorchDistributedConfiguration # type: ignore from ._models import TrainingDiagnosticConfiguration # type: ignore from ._models import TrainingOutput # type: ignore from ._models import TrainingSettings # type: ignore from ._models import TriggerAsyncOperationStatus # type: ignore from ._models import TuningNodeRunSetting # type: ignore from ._models import TuningNodeSetting # type: ignore from ._models import TypedAssetReference # type: ignore from ._models import UIAzureOpenAIDeploymentNameSelector # type: ignore from ._models import UIAzureOpenAIModelCapabilities # type: ignore from ._models import UIColumnPicker # type: ignore from ._models import UIComputeSelection # type: ignore from ._models import UIHyperparameterConfiguration # type: ignore from ._models import UIInputSetting # type: ignore from ._models import UIJsonEditor # type: ignore from ._models import UIParameterHint # type: ignore from ._models import UIPromptFlowConnectionSelector # type: ignore from ._models import UIWidgetMetaInfo # type: ignore from ._models import UIYamlEditor # type: ignore from ._models import UnversionedEntityRequestDto # type: ignore from ._models import UnversionedEntityResponseDto # type: ignore from ._models import UnversionedRebuildIndexDto # type: ignore from ._models import UnversionedRebuildResponseDto # type: ignore from ._models import UpdateComponentRequest # type: ignore from ._models import UpdateFlowRequest # type: ignore from ._models import UpdateFlowRuntimeRequest # type: ignore from ._models import UpdateFlowStatusRequest # type: ignore from ._models import UpdateRegistryComponentRequest # type: ignore from ._models import UploadOptions # type: ignore from ._models import UriReference # type: ignore from ._models import User # type: ignore from ._models import UserAssignedIdentity # type: ignore from ._models import ValidationDataSettings # type: ignore from ._models import VariantIdentifier # type: ignore from ._models import VariantNode # type: ignore from ._models import Volume # type: ignore from ._models import WebServiceComputeMetaInfo # type: ignore from ._models import WebServicePort # type: ignore from ._models import Webhook # type: ignore from ._models import WorkspaceConnectionSpec # type: ignore from ._azure_machine_learning_designer_service_client_enums import ( AEVAAssetType, AEVADataStoreMode, AEVAIdentityType, ActionType, AetherArgumentValueType, AetherAssetType, AetherBuildSourceType, AetherComputeType, AetherControlFlowType, AetherControlInputValue, AetherDataCopyMode, AetherDataLocationStorageType, AetherDataReferenceType, AetherDataStoreMode, AetherDataTransferStorageType, AetherDataTransferTaskType, AetherDatasetType, AetherEarlyTerminationPolicyType, AetherEntityStatus, AetherExecutionEnvironment, AetherExecutionPhase, AetherFeaturizationMode, AetherFileBasedPathType, AetherForecastHorizonMode, AetherIdentityType, AetherLogVerbosity, AetherModuleDeploymentSource, AetherModuleHashVersion, AetherModuleType, AetherNCrossValidationMode, AetherParameterType, AetherParameterValueType, AetherPrimaryMetrics, AetherRepositoryType, AetherResourceOperator, AetherResourceValueType, AetherSamplingAlgorithmType, AetherSeasonalityMode, AetherShortSeriesHandlingConfiguration, AetherStackMetaLearnerType, AetherStoredProcedureParameterType, AetherTabularTrainingMode, AetherTargetAggregationFunction, AetherTargetLagsMode, AetherTargetRollingWindowSizeMode, AetherTaskType, AetherTrainingOutputType, AetherUIScriptLanguageEnum, AetherUIWidgetTypeEnum, AetherUploadState, AetherUseStl, ApplicationEndpointType, ArgumentValueType, AssetScopeTypes, AssetSourceType, AssetType, AutoDeleteCondition, BuildContextLocationType, Communicator, ComponentRegistrationTypeEnum, ComponentType, ComputeEnvironmentType, ComputeTargetType, ComputeType, ConfigValueType, ConnectionCategory, ConnectionScope, ConnectionSourceType, ConnectionType, ConsumeMode, ControlFlowType, ControlInputValue, DataBindingMode, DataCategory, DataCopyMode, DataLocationStorageType, DataPortType, DataReferenceType, DataSourceType, DataStoreMode, DataTransferStorageType, DataTransferTaskType, DataTypeMechanism, DatasetAccessModes, DatasetConsumptionType, DatasetDeliveryMechanism, DatasetOutputType, DatasetType, DeliveryMechanism, DistributionParameterEnum, DistributionType, EarlyTerminationPolicyType, EmailNotificationEnableType, EndpointAuthMode, EntityKind, EntityStatus, ErrorHandlingMode, ExecutionPhase, FeaturizationMode, FlowFeatureStateEnum, FlowLanguage, FlowPatchOperationType, FlowRunMode, FlowRunStatusEnum, FlowRunTypeEnum, FlowTestMode, FlowType, ForecastHorizonMode, Framework, Frequency, GlobalJobDispatcherSupportedComputeType, GraphComponentsMode, GraphDatasetsLoadModes, GraphSdkCodeType, HttpStatusCode, IdentityType, InputType, IntellectualPropertyAccessMode, JobInputType, JobLimitsType, JobOutputType, JobProvisioningState, JobStatus, JobType, KeyType, ListViewType, LogLevel, LogVerbosity, LongRunningUpdateType, MLFlowAutologgerState, ManagedServiceIdentityType, MetricValueType, MfeInternalIdentityType, MfeInternalMLFlowAutologgerState, MfeInternalScheduleStatus, ModuleDtoFields, ModuleInfoFromYamlStatusEnum, ModuleRunSettingTypes, ModuleScope, ModuleSourceType, ModuleType, ModuleUpdateOperationType, ModuleWorkingMechanism, NCrossValidationMode, NodeCompositionMode, NodesValueType, Orientation, OutputMechanism, ParameterType, ParameterValueType, PipelineDraftMode, PipelineRunStatusCode, PipelineStatusCode, PipelineType, PortAction, PrimaryMetrics, PromptflowEngineType, ProvisioningState, RealTimeEndpointInternalStepCode, RealTimeEndpointOpCode, RealTimeEndpointOpStatusCode, RecurrenceFrequency, RunDisplayNameGenerationType, RunSettingParameterType, RunSettingUIWidgetTypeEnum, RunStatus, RunType, RuntimeStatusEnum, RuntimeType, SamplingAlgorithmType, ScheduleProvisioningStatus, ScheduleStatus, ScheduleType, ScopeType, ScriptType, SeasonalityMode, Section, SessionConfigModeEnum, SessionSetupModeEnum, SetupFlowSessionAction, SeverityLevel, ShortSeriesHandlingConfiguration, StackMetaLearnerType, StorageAuthType, StoredProcedureParameterType, SuccessfulCommandReturnCode, TabularTrainingMode, TargetAggregationFunction, TargetLagsMode, TargetRollingWindowSizeMode, TaskCreationOptions, TaskStatus, TaskStatusCode, TaskType, ToolFuncCallScenario, ToolState, ToolType, TrainingOutputType, TriggerOperationType, TriggerType, UIInputDataDeliveryMode, UIScriptLanguageEnum, UIWidgetTypeEnum, UploadState, UseStl, UserType, ValidationStatus, ValueType, VmPriority, WebServiceState, WeekDays, Weekday, YarnDeployMode, ) __all__ = [ 'ACIAdvanceSettings', 'AEVAComputeConfiguration', 'AEVAResourceConfiguration', 'AISuperComputerConfiguration', 'AISuperComputerScalePolicy', 'AISuperComputerStorageReferenceConfiguration', 'AKSAdvanceSettings', 'AKSReplicaStatus', 'AMLComputeConfiguration', 'APCloudConfiguration', 'Activate', 'AdditionalErrorInfo', 'AdhocTriggerScheduledCommandJobRequest', 'AdhocTriggerScheduledSparkJobRequest', 'AetherAPCloudConfiguration', 'AetherAmlDataset', 'AetherAmlSparkCloudSetting', 'AetherArgumentAssignment', 'AetherAssetDefinition', 'AetherAssetOutputSettings', 'AetherAutoFeaturizeConfiguration', 'AetherAutoMLComponentConfiguration', 'AetherAutoTrainConfiguration', 'AetherAzureBlobReference', 'AetherAzureDataLakeGen2Reference', 'AetherAzureDataLakeReference', 'AetherAzureDatabaseReference', 'AetherAzureFilesReference', 'AetherBatchAiComputeInfo', 'AetherBuildArtifactInfo', 'AetherCloudBuildDropPathInfo', 'AetherCloudBuildInfo', 'AetherCloudBuildQueueInfo', 'AetherCloudPrioritySetting', 'AetherCloudSettings', 'AetherColumnTransformer', 'AetherComputeConfiguration', 'AetherComputeSetting', 'AetherControlInput', 'AetherControlOutput', 'AetherCopyDataTask', 'AetherCosmosReference', 'AetherCreatedBy', 'AetherCustomReference', 'AetherDBFSReference', 'AetherDataLocation', 'AetherDataLocationReuseCalculationFields', 'AetherDataPath', 'AetherDataReference', 'AetherDataSetDefinition', 'AetherDataSetDefinitionValue', 'AetherDataSettings', 'AetherDataTransferCloudConfiguration', 'AetherDataTransferSink', 'AetherDataTransferSource', 'AetherDataTransferV2CloudSetting', 'AetherDatabaseSink', 'AetherDatabaseSource', 'AetherDatabricksComputeInfo', 'AetherDatasetOutput', 'AetherDatasetOutputOptions', 'AetherDatasetRegistration', 'AetherDatastoreSetting', 'AetherDoWhileControlFlowInfo', 'AetherDoWhileControlFlowRunSettings', 'AetherDockerSettingConfiguration', 'AetherEntityInterfaceDocumentation', 'AetherEntrySetting', 'AetherEnvironmentConfiguration', 'AetherEsCloudConfiguration', 'AetherExportDataTask', 'AetherFeaturizationSettings', 'AetherFileSystem', 'AetherForecastHorizon', 'AetherForecastingSettings', 'AetherGeneralSettings', 'AetherGlobsOptions', 'AetherGraphControlNode', 'AetherGraphControlReferenceNode', 'AetherGraphDatasetNode', 'AetherGraphEdge', 'AetherGraphEntity', 'AetherGraphModuleNode', 'AetherGraphReferenceNode', 'AetherHdfsReference', 'AetherHdiClusterComputeInfo', 'AetherHdiRunConfiguration', 'AetherHyperDriveConfiguration', 'AetherIdentitySetting', 'AetherImportDataTask', 'AetherInputSetting', 'AetherInteractiveConfig', 'AetherK8SConfiguration', 'AetherLegacyDataPath', 'AetherLimitSettings', 'AetherMlcComputeInfo', 'AetherModuleEntity', 'AetherModuleExtendedProperties', 'AetherNCrossValidations', 'AetherOutputSetting', 'AetherParallelForControlFlowInfo', 'AetherParameterAssignment', 'AetherPhillyHdfsReference', 'AetherPortInfo', 'AetherPriorityConfig', 'AetherPriorityConfiguration', 'AetherRegisteredDataSetReference', 'AetherRemoteDockerComputeInfo', 'AetherResourceAssignment', 'AetherResourceAttributeAssignment', 'AetherResourceAttributeDefinition', 'AetherResourceConfig', 'AetherResourceConfiguration', 'AetherResourceModel', 'AetherResourcesSetting', 'AetherSavedDataSetReference', 'AetherScopeCloudConfiguration', 'AetherSeasonality', 'AetherSqlDataPath', 'AetherStackEnsembleSettings', 'AetherStoredProcedureParameter', 'AetherStructuredInterface', 'AetherStructuredInterfaceInput', 'AetherStructuredInterfaceOutput', 'AetherStructuredInterfaceParameter', 'AetherSubGraphConfiguration', 'AetherSweepEarlyTerminationPolicy', 'AetherSweepSettings', 'AetherSweepSettingsLimits', 'AetherTargetLags', 'AetherTargetRollingWindowSize', 'AetherTargetSelectorConfiguration', 'AetherTestDataSettings', 'AetherTorchDistributedConfiguration', 'AetherTrainingOutput', 'AetherTrainingSettings', 'AetherUIAzureOpenAIDeploymentNameSelector', 'AetherUIAzureOpenAIModelCapabilities', 'AetherUIColumnPicker', 'AetherUIJsonEditor', 'AetherUIParameterHint', 'AetherUIPromptFlowConnectionSelector', 'AetherValidationDataSettings', 'AetherVsoBuildArtifactInfo', 'AetherVsoBuildDefinitionInfo', 'AetherVsoBuildInfo', 'AmlDataset', 'AmlK8SConfiguration', 'AmlK8SPriorityConfiguration', 'AmlSparkCloudSetting', 'ApiAndParameters', 'ApplicationEndpointConfiguration', 'ArgumentAssignment', 'Asset', 'AssetDefinition', 'AssetNameAndVersionIdentifier', 'AssetOutputSettings', 'AssetOutputSettingsParameter', 'AssetPublishResult', 'AssetPublishSingleRegionResult', 'AssetTypeMetaInfo', 'AssetVersionPublishRequest', 'AssignedUser', 'AttachCosmosRequest', 'AuthKeys', 'AutoClusterComputeSpecification', 'AutoDeleteSetting', 'AutoFeaturizeConfiguration', 'AutoMLComponentConfiguration', 'AutoScaler', 'AutoTrainConfiguration', 'AutologgerSettings', 'AvailabilityResponse', 'AzureBlobReference', 'AzureDataLakeGen2Reference', 'AzureDataLakeReference', 'AzureDatabaseReference', 'AzureFilesReference', 'AzureMLModuleVersionDescriptor', 'AzureOpenAIDeploymentDto', 'AzureOpenAIModelCapabilities', 'BatchAiComputeInfo', 'BatchDataInput', 'BatchExportComponentSpecResponse', 'BatchExportRawComponentResponse', 'BatchGetComponentHashesRequest', 'BatchGetComponentRequest', 'Binding', 'BulkTestDto', 'CloudError', 'CloudPrioritySetting', 'CloudSettings', 'ColumnTransformer', 'CommandJob', 'CommandJobLimits', 'CommandReturnCodeConfig', 'ComponentConfiguration', 'ComponentInput', 'ComponentJob', 'ComponentJobInput', 'ComponentJobOutput', 'ComponentNameAndDefaultVersion', 'ComponentNameMetaInfo', 'ComponentOutput', 'ComponentPreflightResult', 'ComponentSpecMetaInfo', 'ComponentUpdateRequest', 'ComponentValidationRequest', 'ComponentValidationResponse', 'Compute', 'ComputeConfiguration', 'ComputeContract', 'ComputeIdentityContract', 'ComputeIdentityDto', 'ComputeInfo', 'ComputeProperties', 'ComputeRPUserAssignedIdentity', 'ComputeRequest', 'ComputeSetting', 'ComputeStatus', 'ComputeStatusDetail', 'ComputeWarning', 'ConnectionConfigSpec', 'ConnectionDto', 'ConnectionEntity', 'ConnectionOverrideSetting', 'ConnectionSpec', 'ContainerInstanceConfiguration', 'ContainerRegistry', 'ContainerResourceRequirements', 'ControlInput', 'ControlOutput', 'CopyDataTask', 'CreateFlowRequest', 'CreateFlowRuntimeRequest', 'CreateFlowSessionRequest', 'CreateInferencePipelineRequest', 'CreateOrUpdateConnectionRequest', 'CreateOrUpdateConnectionRequestDto', 'CreatePipelineDraftRequest', 'CreatePipelineJobScheduleDto', 'CreatePublishedPipelineRequest', 'CreateRealTimeEndpointRequest', 'CreatedBy', 'CreatedFromDto', 'CreationContext', 'Cron', 'CustomConnectionConfig', 'CustomReference', 'DBFSReference', 'Data', 'DataInfo', 'DataLocation', 'DataPath', 'DataPathParameter', 'DataPortDto', 'DataReference', 'DataReferenceConfiguration', 'DataSetDefinition', 'DataSetDefinitionValue', 'DataSetPathParameter', 'DataSettings', 'DataTransferCloudConfiguration', 'DataTransferSink', 'DataTransferSource', 'DataTransferV2CloudSetting', 'DataTypeCreationInfo', 'DatabaseSink', 'DatabaseSource', 'DatabricksComputeInfo', 'DatabricksConfiguration', 'DatacacheConfiguration', 'DatasetIdentifier', 'DatasetInputDetails', 'DatasetLineage', 'DatasetOutput', 'DatasetOutputDetails', 'DatasetOutputOptions', 'DatasetRegistration', 'DatasetRegistrationOptions', 'DatastoreSetting', 'DbfsStorageInfoDto', 'DebugInfoResponse', 'DeployFlowRequest', 'DeploymentInfo', 'DistributionConfiguration', 'DistributionParameter', 'DoWhileControlFlowInfo', 'DoWhileControlFlowRunSettings', 'DockerBuildContext', 'DockerConfiguration', 'DockerImagePlatform', 'DockerSection', 'DockerSettingConfiguration', 'DownloadResourceInfo', 'EPRPipelineRunErrorClassificationRequest', 'EndpointSetting', 'EntityInterface', 'EntrySetting', 'EnumParameterRule', 'EnvironmentConfiguration', 'EnvironmentDefinition', 'EnvironmentDefinitionDto', 'ErrorAdditionalInfo', 'ErrorResponse', 'EsCloudConfiguration', 'EvaluationFlowRunSettings', 'ExampleRequest', 'ExecutionContextDto', 'ExecutionDataLocation', 'ExecutionDataPath', 'ExecutionGlobsOptions', 'ExperimentComputeMetaInfo', 'ExperimentInfo', 'ExportComponentMetaInfo', 'ExportDataTask', 'FeaturizationSettings', 'FeedDto', 'FeedDtoSupportedAssetTypes', 'FileSystem', 'Flow', 'FlowAnnotations', 'FlowBaseDto', 'FlowDto', 'FlowEnvironment', 'FlowFeature', 'FlowFeatureState', 'FlowGraph', 'FlowGraphAnnotationNode', 'FlowGraphLayout', 'FlowGraphReference', 'FlowIndexEntity', 'FlowInputDefinition', 'FlowNode', 'FlowNodeLayout', 'FlowNodeVariant', 'FlowOutputDefinition', 'FlowProperties', 'FlowRunBasePath', 'FlowRunInfo', 'FlowRunResult', 'FlowRunSettings', 'FlowRunSettingsBase', 'FlowRunStatusResponse', 'FlowRuntimeCapability', 'FlowRuntimeDto', 'FlowSampleDto', 'FlowSessionDto', 'FlowSnapshot', 'FlowSubmitRunSettings', 'FlowTestInfo', 'FlowTestStorageSetting', 'FlowToolSettingParameter', 'FlowToolsDto', 'FlowVariantNode', 'ForecastHorizon', 'ForecastingSettings', 'GeneralSettings', 'GeneratePipelineComponentRequest', 'GenerateToolMetaRequest', 'GetDynamicListRequest', 'GetRunDataResultDto', 'GetTrainingSessionDto', 'GlobalJobDispatcherConfiguration', 'GlobsOptions', 'GraphAnnotationNode', 'GraphControlNode', 'GraphControlReferenceNode', 'GraphDatasetNode', 'GraphDraftEntity', 'GraphEdge', 'GraphLayout', 'GraphLayoutCreationInfo', 'GraphModuleNode', 'GraphModuleNodeRunSetting', 'GraphModuleNodeUIInputSetting', 'GraphNodeStatusInfo', 'GraphReferenceNode', 'HdfsReference', 'HdiClusterComputeInfo', 'HdiConfiguration', 'HdiRunConfiguration', 'HistoryConfiguration', 'HyperDriveConfiguration', 'ICheckableLongRunningOperationResponse', 'IdentityConfiguration', 'IdentitySetting', 'ImportDataTask', 'IndexedErrorResponse', 'InitScriptInfoDto', 'InnerErrorDetails', 'InnerErrorResponse', 'InputAsset', 'InputData', 'InputDataBinding', 'InputDefinition', 'InputOutputPortMetadata', 'InputSetting', 'IntellectualPropertyPublisherInformation', 'InteractiveConfig', 'InteractiveConfiguration', 'JobCost', 'JobEndpoint', 'JobInput', 'JobOutput', 'JobOutputArtifacts', 'JobScheduleDto', 'K8SConfiguration', 'KeyValuePairComponentNameMetaInfoErrorResponse', 'KeyValuePairComponentNameMetaInfoModuleDto', 'KeyValuePairStringObject', 'KubernetesConfiguration', 'Kwarg', 'LegacyDataPath', 'LimitSettings', 'LinkedADBWorkspaceMetadata', 'LinkedPipelineInfo', 'LoadFlowAsComponentRequest', 'LogRunTerminatedEventDto', 'LongRunningOperationUriResponse', 'LongRunningUpdateRegistryComponentRequest', 'ManagedServiceIdentity', 'MavenLibraryDto', 'MetricProperties', 'MetricSchemaDto', 'MetricSchemaPropertyDto', 'MetricV2Dto', 'MetricV2Value', 'MfeInternalAutologgerSettings', 'MfeInternalIdentityConfiguration', 'MfeInternalNodes', 'MfeInternalOutputData', 'MfeInternalSecretConfiguration', 'MfeInternalUriReference', 'MfeInternalV20211001ComponentJob', 'MinMaxParameterRule', 'MlcComputeInfo', 'ModelDto', 'ModelManagementErrorResponse', 'ModifyPipelineJobScheduleDto', 'ModuleDto', 'ModuleDtoWithErrors', 'ModuleDtoWithValidateStatus', 'ModuleEntity', 'ModulePythonInterface', 'MpiConfiguration', 'NCrossValidations', 'Node', 'NodeInputPort', 'NodeLayout', 'NodeOutputPort', 'NodePortInterface', 'NodeSource', 'NodeTelemetryMetaInfo', 'NodeVariant', 'Nodes', 'NoteBookTaskDto', 'NotificationSetting', 'ODataError', 'ODataErrorDetail', 'ODataErrorResponse', 'ODataInnerError', 'OutputData', 'OutputDataBinding', 'OutputDatasetLineage', 'OutputDefinition', 'OutputOptions', 'OutputSetting', 'OutputSettingSpec', 'PaginatedDataInfoList', 'PaginatedModelDtoList', 'PaginatedModuleDtoList', 'PaginatedPipelineDraftSummaryList', 'PaginatedPipelineEndpointSummaryList', 'PaginatedPipelineRunSummaryList', 'PaginatedPublishedPipelineSummaryList', 'ParallelForControlFlowInfo', 'ParallelTaskConfiguration', 'Parameter', 'ParameterAssignment', 'ParameterDefinition', 'PatchFlowRequest', 'Pipeline', 'PipelineDraft', 'PipelineDraftStepDetails', 'PipelineDraftSummary', 'PipelineEndpoint', 'PipelineEndpointSummary', 'PipelineGraph', 'PipelineInput', 'PipelineJob', 'PipelineJobRuntimeBasicSettings', 'PipelineJobScheduleDto', 'PipelineOutput', 'PipelineRun', 'PipelineRunGraphDetail', 'PipelineRunGraphStatus', 'PipelineRunProfile', 'PipelineRunStatus', 'PipelineRunStepDetails', 'PipelineRunSummary', 'PipelineStatus', 'PipelineStepRun', 'PipelineStepRunOutputs', 'PipelineSubDraft', 'PolicyValidationResponse', 'PortInfo', 'PortOutputInfo', 'PriorityConfig', 'PriorityConfiguration', 'PromoteDataSetRequest', 'ProviderEntity', 'PublishedPipeline', 'PublishedPipelineSummary', 'PyTorchConfiguration', 'PythonInterfaceMapping', 'PythonPyPiOrRCranLibraryDto', 'PythonSection', 'QueueingInfo', 'RCranPackage', 'RGitHubPackage', 'RSection', 'RawComponentDto', 'RayConfiguration', 'RealTimeEndpoint', 'RealTimeEndpointInfo', 'RealTimeEndpointStatus', 'RealTimeEndpointSummary', 'RealTimeEndpointTestRequest', 'Recurrence', 'RecurrencePattern', 'RecurrenceSchedule', 'RegenerateServiceKeysRequest', 'RegisterComponentMetaInfo', 'RegisterComponentMetaInfoExtraHashes', 'RegisterComponentMetaInfoIdentifierHashes', 'RegisterRegistryComponentMetaInfo', 'RegisterRegistryComponentMetaInfoExtraHashes', 'RegisterRegistryComponentMetaInfoIdentifierHashes', 'RegisteredDataSetReference', 'RegistrationOptions', 'RegistryBlobReferenceData', 'RegistryIdentity', 'Relationship', 'RemoteDockerComputeInfo', 'ResourceConfig', 'ResourceConfiguration', 'ResourcesSetting', 'RetrieveToolFuncResultRequest', 'RetryConfiguration', 'RootError', 'RunAnnotations', 'RunCommandsCommandResult', 'RunConfiguration', 'RunDatasetReference', 'RunDefinition', 'RunDetailsDto', 'RunDetailsWarningDto', 'RunDto', 'RunIndexEntity', 'RunIndexMetricSummary', 'RunIndexMetricSummarySystemObject', 'RunIndexResourceMetricSummary', 'RunMetricDto', 'RunMetricsTypesDto', 'RunProperties', 'RunSettingParameter', 'RunSettingParameterAssignment', 'RunSettingUIParameterHint', 'RunStatusPeriod', 'RunTypeV2', 'RunTypeV2Index', 'RuntimeConfiguration', 'SampleMeta', 'SavePipelineDraftRequest', 'SavedDataSetReference', 'ScheduleBase', 'SchemaContractsCreatedBy', 'ScopeCloudConfiguration', 'Seasonality', 'SecretConfiguration', 'SegmentedResult1', 'ServiceLogRequest', 'SessionApplication', 'SessionApplicationRunCommandResult', 'SessionProperties', 'SetupFlowSessionRequest', 'SharingScope', 'Snapshot', 'SnapshotInfo', 'SourceCodeDataReference', 'SparkConfiguration', 'SparkJarTaskDto', 'SparkJob', 'SparkJobEntry', 'SparkMavenPackage', 'SparkPythonTaskDto', 'SparkResourceConfiguration', 'SparkSection', 'SparkSubmitTaskDto', 'SqlDataPath', 'StackEnsembleSettings', 'StandbyPoolProperties', 'StandbyPoolResourceStatus', 'StartRunResult', 'StepRunProfile', 'StorageInfo', 'StoredProcedureParameter', 'Stream', 'StructuredInterface', 'StructuredInterfaceInput', 'StructuredInterfaceOutput', 'StructuredInterfaceParameter', 'StudioMigrationInfo', 'SubGraphConcatenateAssignment', 'SubGraphConfiguration', 'SubGraphConnectionInfo', 'SubGraphDataPathParameterAssignment', 'SubGraphInfo', 'SubGraphParameterAssignment', 'SubGraphPortInfo', 'SubPipelineDefinition', 'SubPipelineParameterAssignment', 'SubPipelinesInfo', 'SubStatusPeriod', 'SubmitBulkRunRequest', 'SubmitBulkRunResponse', 'SubmitFlowRequest', 'SubmitPipelineRunRequest', 'SweepEarlyTerminationPolicy', 'SweepSettings', 'SweepSettingsLimits', 'SystemData', 'SystemMeta', 'SystemMetaExtraHashes', 'SystemMetaIdentifierHashes', 'TargetLags', 'TargetRollingWindowSize', 'TargetSelectorConfiguration', 'Task', 'TaskControlFlowInfo', 'TaskReuseInfo', 'TensorflowConfiguration', 'TestDataSettings', 'Tool', 'ToolFuncResponse', 'ToolInputDynamicList', 'ToolInputGeneratedBy', 'ToolMetaDto', 'ToolSetting', 'ToolSourceMeta', 'TorchDistributedConfiguration', 'TrainingDiagnosticConfiguration', 'TrainingOutput', 'TrainingSettings', 'TriggerAsyncOperationStatus', 'TuningNodeRunSetting', 'TuningNodeSetting', 'TypedAssetReference', 'UIAzureOpenAIDeploymentNameSelector', 'UIAzureOpenAIModelCapabilities', 'UIColumnPicker', 'UIComputeSelection', 'UIHyperparameterConfiguration', 'UIInputSetting', 'UIJsonEditor', 'UIParameterHint', 'UIPromptFlowConnectionSelector', 'UIWidgetMetaInfo', 'UIYamlEditor', 'UnversionedEntityRequestDto', 'UnversionedEntityResponseDto', 'UnversionedRebuildIndexDto', 'UnversionedRebuildResponseDto', 'UpdateComponentRequest', 'UpdateFlowRequest', 'UpdateFlowRuntimeRequest', 'UpdateFlowStatusRequest', 'UpdateRegistryComponentRequest', 'UploadOptions', 'UriReference', 'User', 'UserAssignedIdentity', 'ValidationDataSettings', 'VariantIdentifier', 'VariantNode', 'Volume', 'WebServiceComputeMetaInfo', 'WebServicePort', 'Webhook', 'WorkspaceConnectionSpec', 'AEVAAssetType', 'AEVADataStoreMode', 'AEVAIdentityType', 'ActionType', 'AetherArgumentValueType', 'AetherAssetType', 'AetherBuildSourceType', 'AetherComputeType', 'AetherControlFlowType', 'AetherControlInputValue', 'AetherDataCopyMode', 'AetherDataLocationStorageType', 'AetherDataReferenceType', 'AetherDataStoreMode', 'AetherDataTransferStorageType', 'AetherDataTransferTaskType', 'AetherDatasetType', 'AetherEarlyTerminationPolicyType', 'AetherEntityStatus', 'AetherExecutionEnvironment', 'AetherExecutionPhase', 'AetherFeaturizationMode', 'AetherFileBasedPathType', 'AetherForecastHorizonMode', 'AetherIdentityType', 'AetherLogVerbosity', 'AetherModuleDeploymentSource', 'AetherModuleHashVersion', 'AetherModuleType', 'AetherNCrossValidationMode', 'AetherParameterType', 'AetherParameterValueType', 'AetherPrimaryMetrics', 'AetherRepositoryType', 'AetherResourceOperator', 'AetherResourceValueType', 'AetherSamplingAlgorithmType', 'AetherSeasonalityMode', 'AetherShortSeriesHandlingConfiguration', 'AetherStackMetaLearnerType', 'AetherStoredProcedureParameterType', 'AetherTabularTrainingMode', 'AetherTargetAggregationFunction', 'AetherTargetLagsMode', 'AetherTargetRollingWindowSizeMode', 'AetherTaskType', 'AetherTrainingOutputType', 'AetherUIScriptLanguageEnum', 'AetherUIWidgetTypeEnum', 'AetherUploadState', 'AetherUseStl', 'ApplicationEndpointType', 'ArgumentValueType', 'AssetScopeTypes', 'AssetSourceType', 'AssetType', 'AutoDeleteCondition', 'BuildContextLocationType', 'Communicator', 'ComponentRegistrationTypeEnum', 'ComponentType', 'ComputeEnvironmentType', 'ComputeTargetType', 'ComputeType', 'ConfigValueType', 'ConnectionCategory', 'ConnectionScope', 'ConnectionSourceType', 'ConnectionType', 'ConsumeMode', 'ControlFlowType', 'ControlInputValue', 'DataBindingMode', 'DataCategory', 'DataCopyMode', 'DataLocationStorageType', 'DataPortType', 'DataReferenceType', 'DataSourceType', 'DataStoreMode', 'DataTransferStorageType', 'DataTransferTaskType', 'DataTypeMechanism', 'DatasetAccessModes', 'DatasetConsumptionType', 'DatasetDeliveryMechanism', 'DatasetOutputType', 'DatasetType', 'DeliveryMechanism', 'DistributionParameterEnum', 'DistributionType', 'EarlyTerminationPolicyType', 'EmailNotificationEnableType', 'EndpointAuthMode', 'EntityKind', 'EntityStatus', 'ErrorHandlingMode', 'ExecutionPhase', 'FeaturizationMode', 'FlowFeatureStateEnum', 'FlowLanguage', 'FlowPatchOperationType', 'FlowRunMode', 'FlowRunStatusEnum', 'FlowRunTypeEnum', 'FlowTestMode', 'FlowType', 'ForecastHorizonMode', 'Framework', 'Frequency', 'GlobalJobDispatcherSupportedComputeType', 'GraphComponentsMode', 'GraphDatasetsLoadModes', 'GraphSdkCodeType', 'HttpStatusCode', 'IdentityType', 'InputType', 'IntellectualPropertyAccessMode', 'JobInputType', 'JobLimitsType', 'JobOutputType', 'JobProvisioningState', 'JobStatus', 'JobType', 'KeyType', 'ListViewType', 'LogLevel', 'LogVerbosity', 'LongRunningUpdateType', 'MLFlowAutologgerState', 'ManagedServiceIdentityType', 'MetricValueType', 'MfeInternalIdentityType', 'MfeInternalMLFlowAutologgerState', 'MfeInternalScheduleStatus', 'ModuleDtoFields', 'ModuleInfoFromYamlStatusEnum', 'ModuleRunSettingTypes', 'ModuleScope', 'ModuleSourceType', 'ModuleType', 'ModuleUpdateOperationType', 'ModuleWorkingMechanism', 'NCrossValidationMode', 'NodeCompositionMode', 'NodesValueType', 'Orientation', 'OutputMechanism', 'ParameterType', 'ParameterValueType', 'PipelineDraftMode', 'PipelineRunStatusCode', 'PipelineStatusCode', 'PipelineType', 'PortAction', 'PrimaryMetrics', 'PromptflowEngineType', 'ProvisioningState', 'RealTimeEndpointInternalStepCode', 'RealTimeEndpointOpCode', 'RealTimeEndpointOpStatusCode', 'RecurrenceFrequency', 'RunDisplayNameGenerationType', 'RunSettingParameterType', 'RunSettingUIWidgetTypeEnum', 'RunStatus', 'RunType', 'RuntimeStatusEnum', 'RuntimeType', 'SamplingAlgorithmType', 'ScheduleProvisioningStatus', 'ScheduleStatus', 'ScheduleType', 'ScopeType', 'ScriptType', 'SeasonalityMode', 'Section', 'SessionConfigModeEnum', 'SessionSetupModeEnum', 'SetupFlowSessionAction', 'SeverityLevel', 'ShortSeriesHandlingConfiguration', 'StackMetaLearnerType', 'StorageAuthType', 'StoredProcedureParameterType', 'SuccessfulCommandReturnCode', 'TabularTrainingMode', 'TargetAggregationFunction', 'TargetLagsMode', 'TargetRollingWindowSizeMode', 'TaskCreationOptions', 'TaskStatus', 'TaskStatusCode', 'TaskType', 'ToolFuncCallScenario', 'ToolState', 'ToolType', 'TrainingOutputType', 'TriggerOperationType', 'TriggerType', 'UIInputDataDeliveryMode', 'UIScriptLanguageEnum', 'UIWidgetTypeEnum', 'UploadState', 'UseStl', 'UserType', 'ValidationStatus', 'ValueType', 'VmPriority', 'WebServiceState', 'WeekDays', 'Weekday', 'YarnDeployMode', ]

promptflow/src/promptflow/promptflow/azure/_restclient/flow/models/__init__.py/0

# coding=utf-8 # -------------------------------------------------------------------------- # Code generated by Microsoft (R) AutoRest Code Generator (autorest: 3.9.2, generator: @autorest/[email protected]) # Changes may cause incorrect behavior and will be lost if the code is regenerated. # -------------------------------------------------------------------------- import functools from typing import TYPE_CHECKING import warnings from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error from azure.core.pipeline import PipelineResponse from azure.core.pipeline.transport import HttpResponse from azure.core.rest import HttpRequest from azure.core.tracing.decorator import distributed_trace from msrest import Serializer from .. import models as _models from .._vendor import _convert_request, _format_url_section if TYPE_CHECKING: # pylint: disable=unused-import,ungrouped-imports from typing import Any, Callable, Dict, Generic, Optional, TypeVar T = TypeVar('T') ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]] _SERIALIZER = Serializer() _SERIALIZER.client_side_validation = False # fmt: off def build_attach_cosmos_account_request( subscription_id, # type: str resource_group_name, # type: str workspace_name, # type: str **kwargs # type: Any ): # type: (...) -> HttpRequest content_type = kwargs.pop('content_type', None) # type: Optional[str] overwrite = kwargs.pop('overwrite', False) # type: Optional[bool] accept = "application/json" # Construct URL url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/TraceSessions/attachDb') path_format_arguments = { "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'), "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'), "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'), } url = _format_url_section(url, **path_format_arguments) # Construct parameters query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any] if overwrite is not None: query_parameters['overwrite'] = _SERIALIZER.query("overwrite", overwrite, 'bool') # Construct headers header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any] if content_type is not None: header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str') header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str') return HttpRequest( method="POST", url=url, params=query_parameters, headers=header_parameters, **kwargs ) def build_get_cosmos_resource_token_request( subscription_id, # type: str resource_group_name, # type: str workspace_name, # type: str container_name, # type: str **kwargs # type: Any ): # type: (...) -> HttpRequest acquire_write = kwargs.pop('acquire_write', False) # type: Optional[bool] accept = "application/json" # Construct URL url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/TraceSessions/container/{containerName}/resourceToken') path_format_arguments = { "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'), "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'), "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'), "containerName": _SERIALIZER.url("container_name", container_name, 'str'), } url = _format_url_section(url, **path_format_arguments) # Construct parameters query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any] if acquire_write is not None: query_parameters['acquireWrite'] = _SERIALIZER.query("acquire_write", acquire_write, 'bool') # Construct headers header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any] header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str') return HttpRequest( method="GET", url=url, params=query_parameters, headers=header_parameters, **kwargs ) # fmt: on class TraceSessionsOperations(object): """TraceSessionsOperations operations. You should not instantiate this class directly. Instead, you should create a Client instance that instantiates it for you and attaches it as an attribute. :ivar models: Alias to model classes used in this operation group. :type models: ~flow.models :param client: Client for service requests. :param config: Configuration of service client. :param serializer: An object model serializer. :param deserializer: An object model deserializer. """ models = _models def __init__(self, client, config, serializer, deserializer): self._client = client self._serialize = serializer self._deserialize = deserializer self._config = config @distributed_trace def attach_cosmos_account( self, subscription_id, # type: str resource_group_name, # type: str workspace_name, # type: str overwrite=False, # type: Optional[bool] body=None, # type: Optional["_models.AttachCosmosRequest"] **kwargs # type: Any ): # type: (...) -> Any """attach_cosmos_account. :param subscription_id: The Azure Subscription ID. :type subscription_id: str :param resource_group_name: The Name of the resource group in which the workspace is located. :type resource_group_name: str :param workspace_name: The name of the workspace. :type workspace_name: str :param overwrite: :type overwrite: bool :param body: :type body: ~flow.models.AttachCosmosRequest :keyword callable cls: A custom type or function that will be passed the direct response :return: any, or the result of cls(response) :rtype: any :raises: ~azure.core.exceptions.HttpResponseError """ cls = kwargs.pop('cls', None) # type: ClsType[Any] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError } error_map.update(kwargs.pop('error_map', {})) content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] if body is not None: _json = self._serialize.body(body, 'AttachCosmosRequest') else: _json = None request = build_attach_cosmos_account_request( subscription_id=subscription_id, resource_group_name=resource_group_name, workspace_name=workspace_name, content_type=content_type, json=_json, overwrite=overwrite, template_url=self.attach_cosmos_account.metadata['url'], ) request = _convert_request(request) request.url = self._client.format_url(request.url) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) raise HttpResponseError(response=response, model=error) deserialized = self._deserialize('object', pipeline_response) if cls: return cls(pipeline_response, deserialized, {}) return deserialized attach_cosmos_account.metadata = {'url': '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/TraceSessions/attachDb'} # type: ignore @distributed_trace def get_cosmos_resource_token( self, subscription_id, # type: str resource_group_name, # type: str workspace_name, # type: str container_name, # type: str acquire_write=False, # type: Optional[bool] **kwargs # type: Any ): # type: (...) -> str """get_cosmos_resource_token. :param subscription_id: The Azure Subscription ID. :type subscription_id: str :param resource_group_name: The Name of the resource group in which the workspace is located. :type resource_group_name: str :param workspace_name: The name of the workspace. :type workspace_name: str :param container_name: :type container_name: str :param acquire_write: :type acquire_write: bool :keyword callable cls: A custom type or function that will be passed the direct response :return: str, or the result of cls(response) :rtype: str :raises: ~azure.core.exceptions.HttpResponseError """ cls = kwargs.pop('cls', None) # type: ClsType[str] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError } error_map.update(kwargs.pop('error_map', {})) request = build_get_cosmos_resource_token_request( subscription_id=subscription_id, resource_group_name=resource_group_name, workspace_name=workspace_name, container_name=container_name, acquire_write=acquire_write, template_url=self.get_cosmos_resource_token.metadata['url'], ) request = _convert_request(request) request.url = self._client.format_url(request.url) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) raise HttpResponseError(response=response, model=error) deserialized = self._deserialize('str', pipeline_response) if cls: return cls(pipeline_response, deserialized, {}) return deserialized get_cosmos_resource_token.metadata = {'url': '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/TraceSessions/container/{containerName}/resourceToken'} # type: ignore

promptflow/src/promptflow/promptflow/azure/_restclient/flow/operations/_trace_sessions_operations.py/0

# --------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # --------------------------------------------------------- # pylint: disable=protected-access import copy import json import os import re from datetime import datetime from functools import cached_property from pathlib import Path from typing import Dict, List, Optional, Union import requests from azure.ai.ml._artifacts._artifact_utilities import _check_and_upload_path from azure.ai.ml._scope_dependent_operations import ( OperationConfig, OperationsContainer, OperationScope, _ScopeDependentOperations, ) from azure.ai.ml.constants._common import SHORT_URI_FORMAT from azure.ai.ml.entities import Workspace from azure.ai.ml.operations._operation_orchestrator import OperationOrchestrator from azure.core.exceptions import HttpResponseError from promptflow._sdk._constants import ( CLIENT_FLOW_TYPE_2_SERVICE_FLOW_TYPE, DAG_FILE_NAME, MAX_LIST_CLI_RESULTS, WORKSPACE_LINKED_DATASTORE_NAME, FlowType, ListViewType, ) from promptflow._sdk._errors import FlowOperationError from promptflow._sdk._telemetry import ActivityType, WorkspaceTelemetryMixin, monitor_operation from promptflow._sdk._utils import PromptflowIgnoreFile from promptflow._sdk._vendor._asset_utils import traverse_directory from promptflow._utils.logger_utils import get_cli_sdk_logger from promptflow.azure._constants._flow import DEFAULT_STORAGE from promptflow.azure._entities._flow import Flow from promptflow.azure._load_functions import load_flow from promptflow.azure._restclient.flow_service_caller import FlowServiceCaller from promptflow.azure.operations._artifact_utilities import _get_datastore_name, get_datastore_info from promptflow.azure.operations._fileshare_storeage_helper import FlowFileStorageClient from promptflow.exceptions import SystemErrorException, UserErrorException logger = get_cli_sdk_logger() class FlowOperations(WorkspaceTelemetryMixin, _ScopeDependentOperations): """FlowOperations that can manage flows. You should not instantiate this class directly. Instead, you should create a :class:`~promptflow.azure.PFClient` instance and this operation is available as the instance's attribute. """ _FLOW_RESOURCE_PATTERN = re.compile(r"azureml:.*?/workspaces/(?P<experiment_id>.*?)/flows/(?P<flow_id>.*?)$") def __init__( self, operation_scope: OperationScope, operation_config: OperationConfig, all_operations: OperationsContainer, credential, service_caller: FlowServiceCaller, workspace: Workspace, **kwargs: Dict, ): super().__init__( operation_scope=operation_scope, operation_config=operation_config, workspace_name=operation_scope.workspace_name, subscription_id=operation_scope.subscription_id, resource_group_name=operation_scope.resource_group_name, ) self._all_operations = all_operations self._service_caller = service_caller self._credential = credential self._workspace = workspace @cached_property def _workspace_id(self): return self._workspace._workspace_id @cached_property def _index_service_endpoint_url(self): """Get the endpoint url for the workspace.""" endpoint = self._service_caller._service_endpoint return endpoint + "index/v1.0" + self._service_caller._common_azure_url_pattern @monitor_operation(activity_name="pfazure.flows.create_or_update", activity_type=ActivityType.PUBLICAPI) def create_or_update(self, flow: Union[str, Path], display_name=None, type=None, **kwargs) -> Flow: """Create a flow to remote from local source, or update the metadata of an existing flow. .. note:: Functionality of updating flow metadata is yet to be supported. :param flow: The source of the flow to create. :type flow: Union[str, Path] :param display_name: The display name of the flow to create. Default to be flow folder name + timestamp if not specified. e.g. "web-classification-10-27-2023-14-19-10" :type display_name: str :param type: The type of the flow to create. One of ["standard", evaluation", "chat"]. Default to be "standard" if not specified. :type type: str :param description: The description of the flow to create. Default to be the description in flow yaml file. :type description: str :param tags: The tags of the flow to create. Default to be the tags in flow yaml file. :type tags: Dict[str, str] """ # validate the parameters azure_flow, flow_display_name, flow_type, kwargs = FlowOperations._validate_flow_creation_parameters( flow, display_name, type, **kwargs ) # upload to file share file_share_flow_path = self._resolve_flow_code_and_upload_to_file_share(flow=azure_flow) if not file_share_flow_path: raise FlowOperationError(f"File share path should not be empty, got {file_share_flow_path!r}.") # create flow to remote flow_definition_file_path = f"{file_share_flow_path}/{DAG_FILE_NAME}" rest_flow = self._create_remote_flow_via_file_share_path( flow_display_name=flow_display_name, flow_type=flow_type, flow_definition_file_path=flow_definition_file_path, **kwargs, ) result_flow = Flow._from_pf_service(rest_flow) flow_dict = result_flow._to_dict() print(f"Flow created successfully:\n{json.dumps(flow_dict, indent=4)}") return result_flow @staticmethod def _validate_flow_creation_parameters(source, flow_display_name=None, flow_type=None, **kwargs): """Validate the parameters for flow creation operation.""" # validate the source folder logger.info("Validating flow source.") if not Path(source, DAG_FILE_NAME).exists(): raise UserErrorException( f"Flow source must be a directory with flow definition yaml '{DAG_FILE_NAME}'. " f"Got {Path(source).resolve().as_posix()!r}." ) # validate flow source with flow schema logger.info("Validating flow schema.") flow_dict = FlowOperations._validate_flow_schema(source, flow_display_name, flow_type, **kwargs) logger.info("Validating flow creation parameters.") flow = load_flow(source) # if no flow name specified, use "flow name + timestamp" flow_display_name = flow_dict.get("display_name", None) if not flow_display_name: flow_display_name = f"{Path(source).name}-{datetime.now().strftime('%m-%d-%Y-%H-%M-%S')}" # if no flow type specified, use default flow type "standard" flow_type = flow_dict.get("type", None) if not flow_type: flow_type = FlowType.STANDARD # update description and tags to be the final value description = flow_dict.get("description", None) if isinstance(description, str): kwargs["description"] = description tags = flow_dict.get("tags", None) if tags: kwargs["tags"] = tags return flow, flow_display_name, flow_type, kwargs @staticmethod def _validate_flow_schema(source, display_name=None, type=None, **kwargs): """Validate the flow schema.""" from promptflow._sdk.entities._flow import ProtectedFlow params_override = copy.deepcopy(kwargs) if display_name is not None: params_override["display_name"] = display_name if type is not None: params_override["type"] = type flow_entity = ProtectedFlow.load(source=source, params_override=params_override) flow_entity._validate(raise_error=True) # raise error if validation failed flow_dict = flow_entity._dump_for_validation() return flow_dict def _resolve_flow_code_and_upload_to_file_share(self, flow: Flow, ignore_tools_json=False) -> str: remote_file_share_folder_name = f"{Path(flow.code).name}-{datetime.now().strftime('%m-%d-%Y-%H-%M-%S')}" ops = OperationOrchestrator(self._all_operations, self._operation_scope, self._operation_config) file_share_flow_path = "" logger.info("Building flow code.") with flow._build_code() as code: if code is None: raise FlowOperationError("Failed to build flow code.") # ignore flow.tools.json if needed (e.g. for flow run scenario) if ignore_tools_json: ignore_file = code._ignore_file if isinstance(ignore_file, PromptflowIgnoreFile): ignore_file._ignore_tools_json = ignore_tools_json else: raise FlowOperationError( message=f"Flow code should have PromptflowIgnoreFile, got {type(ignore_file)}" ) code.datastore = DEFAULT_STORAGE datastore_name = _get_datastore_name(datastore_name=DEFAULT_STORAGE) datastore_operation = ops._code_assets._datastore_operation datastore_info = get_datastore_info(datastore_operation, datastore_name) logger.debug("Creating storage client for uploading flow to file share.") storage_client = FlowFileStorageClient( credential=datastore_info["credential"], file_share_name=datastore_info["container_name"], account_url=datastore_info["account_url"], azure_cred=datastore_operation._credential, ) # set storage client to flow operation, can be used in test case self._storage_client = storage_client # check if the file share directory exists logger.debug("Checking if the file share directory exists.") if storage_client._check_file_share_directory_exist(remote_file_share_folder_name): raise FlowOperationError( f"Remote flow folder {remote_file_share_folder_name!r} already exists under " f"'{storage_client.file_share_prefix}'. Please change the flow folder name and try again." ) try: logger.info("Uploading flow directory to file share.") storage_client.upload_dir( source=code.path, dest=remote_file_share_folder_name, msg="test", ignore_file=code._ignore_file, show_progress=False, ) except Exception as e: raise FlowOperationError(f"Failed to upload flow to file share due to: {str(e)}.") from e file_share_flow_path = f"{storage_client.file_share_prefix}/{remote_file_share_folder_name}" logger.info(f"Successfully uploaded flow to file share path {file_share_flow_path!r}.") return file_share_flow_path def _create_remote_flow_via_file_share_path( self, flow_display_name, flow_type, flow_definition_file_path, **kwargs ): """Create a flow to remote from file share path.""" service_flow_type = CLIENT_FLOW_TYPE_2_SERVICE_FLOW_TYPE[flow_type] description = kwargs.get("description", None) tags = kwargs.get("tags", None) body = { "flow_name": flow_display_name, "flow_definition_file_path": flow_definition_file_path, "flow_type": service_flow_type, "description": description, "tags": tags, } rest_flow_result = self._service_caller.create_flow( subscription_id=self._operation_scope.subscription_id, resource_group_name=self._operation_scope.resource_group_name, workspace_name=self._operation_scope.workspace_name, body=body, ) return rest_flow_result def get(self, name: str) -> Flow: """Get a flow from azure. :param name: The name of the flow to get. :type name: str :return: The flow. :rtype: ~promptflow.azure.entities.Flow """ try: rest_flow = self._service_caller.get_flow( subscription_id=self._operation_scope.subscription_id, resource_group_name=self._operation_scope.resource_group_name, workspace_name=self._operation_scope.workspace_name, flow_id=name, experiment_id=self._workspace_id, # for flow operations, current experiment id is workspace id ) except HttpResponseError as e: if e.status_code == 404: raise FlowOperationError(f"Flow {name!r} not found.") from e else: raise FlowOperationError(f"Failed to get flow {name!r} due to: {str(e)}.") from e flow = Flow._from_pf_service(rest_flow) return flow @monitor_operation(activity_name="pfazure.flows.list", activity_type=ActivityType.PUBLICAPI) def list( self, max_results: int = MAX_LIST_CLI_RESULTS, flow_type: Optional[FlowType] = None, list_view_type: ListViewType = ListViewType.ACTIVE_ONLY, include_others: bool = False, **kwargs, ) -> List[Flow]: """List flows from azure. :param max_results: The max number of runs to return, defaults to 50, max is 100 :type max_results: int :param flow_type: The flow type, defaults to None, which means all flow types. Other supported flow types are ["standard", "evaluation", "chat"]. :type flow_type: Optional[FlowType] :param list_view_type: The list view type, defaults to ListViewType.ACTIVE_ONLY :type list_view_type: ListViewType :param include_others: Whether to list flows owned by other users in the remote workspace, defaults to False :type include_others: bool :return: The list of flows. :rtype: List[~promptflow.azure.entities.Flow] """ if not isinstance(max_results, int) or max_results < 1: raise FlowOperationError(f"'max_results' must be a positive integer, got {max_results!r}") normalized_flow_type = str(flow_type).lower() if flow_type is not None and normalized_flow_type not in FlowType.get_all_values(): raise FlowOperationError(f"'flow_type' must be one of {FlowType.get_all_values()}, got {flow_type!r}.") headers = self._service_caller._get_headers() if list_view_type == ListViewType.ACTIVE_ONLY: filter_archived = ["false"] elif list_view_type == ListViewType.ARCHIVED_ONLY: filter_archived = ["true"] elif list_view_type == ListViewType.ALL: filter_archived = ["true", "false"] else: raise FlowOperationError( f"Invalid list view type: {list_view_type!r}, expecting one of ['ActiveOnly', 'ArchivedOnly', 'All']" ) user_object_id, user_tenant_id = self._service_caller._get_user_identity_info() payload = { "filters": [ {"field": "type", "operator": "eq", "values": ["flows"]}, {"field": "annotations/isArchived", "operator": "eq", "values": filter_archived}, { "field": "properties/creationContext/createdBy/userTenantId", "operator": "eq", "values": [user_tenant_id], }, ], "freeTextSearch": "", "order": [{"direction": "Desc", "field": "properties/creationContext/createdTime"}], # index service can return 100 results at most "pageSize": min(max_results, 100), "skip": 0, "includeTotalResultCount": True, "searchBuilder": "AppendPrefix", } # add flow filter to only list flows from current user if not include_others: payload["filters"].append( { "field": "properties/creationContext/createdBy/userObjectId", "operator": "eq", "values": [user_object_id], } ) endpoint = self._index_service_endpoint_url url = endpoint + "/entities" response = requests.post(url, headers=headers, json=payload) if response.status_code == 200: entities = json.loads(response.text) flow_entities = entities["value"] else: raise FlowOperationError( f"Failed to get flows from index service. Code: {response.status_code}, text: {response.text}" ) # transform to flow instances flow_instances = [] for entity in flow_entities: flow = Flow._from_index_service(entity) flow_instances.append(flow) return flow_instances def _download(self, source, dest): # TODO: support download flow raise NotImplementedError("Not implemented yet") def _resolve_arm_id_or_upload_dependencies(self, flow: Flow, ignore_tools_json=False) -> None: ops = OperationOrchestrator(self._all_operations, self._operation_scope, self._operation_config) # resolve flow's code self._try_resolve_code_for_flow(flow=flow, ops=ops, ignore_tools_json=ignore_tools_json) @classmethod def _try_resolve_code_for_flow(cls, flow: Flow, ops: OperationOrchestrator, ignore_tools_json=False) -> None: if flow.path: # remote path if flow.path.startswith("azureml://datastores"): flow._code_uploaded = True return else: raise ValueError("Path is required for flow.") with flow._build_code() as code: if code is None: return if flow._code_uploaded: return # TODO(2917889): generate flow meta for eager flow if ignore_tools_json: ignore_file = code._ignore_file if isinstance(ignore_file, PromptflowIgnoreFile): ignore_file._ignore_tools_json = ignore_tools_json else: raise SystemErrorException( message=f"Flow code should have PromptflowIgnoreFile, got {type(ignore_file)}" ) # flow directory per file upload summary # as the upload logic locates in azure-ai-ml, we cannot touch during the upload # copy the logic here to print per file upload summary ignore_file = code._ignore_file upload_paths = [] source_path = Path(code.path).resolve() prefix = os.path.basename(source_path) + "/" for root, _, files in os.walk(source_path, followlinks=True): upload_paths += list( traverse_directory( root, files, prefix=prefix, ignore_file=ignore_file, ) ) ignore_files = code._ignore_file._get_ignore_list() for file_path in ignore_files: logger.debug(f"will ignore file: {file_path}...") for file_path, _ in upload_paths: logger.debug(f"will upload file: {file_path}...") code.datastore = WORKSPACE_LINKED_DATASTORE_NAME # NOTE: For flow directory upload, we prefer to upload it to the workspace linked datastore, # therefore we will directly use _check_and_upload_path, instead of v2 SDK public API # CodeOperations.create_or_update, as later one will upload the code asset to another # container in the storage account, which may fail with vnet for MT. # However, we might run into list secret permission error(especially in Heron workspace), # in this case, we will leverage v2 SDK public API, which has solution for Heron, # and request MT with the blob url; # refer to except block for more details. try: uploaded_code_asset, _ = _check_and_upload_path( artifact=code, asset_operations=ops._code_assets, artifact_type="Code", datastore_name=WORKSPACE_LINKED_DATASTORE_NAME, # actually not work at all show_progress=True, ) path = uploaded_code_asset.path path = path[path.find("LocalUpload") :] # path on container flow.code = path # azureml://datastores/workspaceblobstore/paths/<path-to-flow-dag-yaml> flow.path = SHORT_URI_FORMAT.format( WORKSPACE_LINKED_DATASTORE_NAME, (Path(path) / flow.path).as_posix() ) except HttpResponseError as e: # catch authorization error for list secret on datastore if "AuthorizationFailed" in str(e) and "datastores/listSecrets/action" in str(e): uploaded_code_asset = ops._code_assets.create_or_update(code) path = uploaded_code_asset.path path = path.replace(".blob.core.windows.net:443/", ".blob.core.windows.net/") # remove :443 port flow.code = path # https://<storage-account-name>.blob.core.windows.net/<container-name>/<path-to-flow-dag-yaml> flow.path = f"{path}/{flow.path}" else: raise flow._code_uploaded = True # region deprecated but keep for runtime test dependencies def _resolve_arm_id_or_upload_dependencies_to_file_share(self, flow: Flow) -> None: ops = OperationOrchestrator(self._all_operations, self._operation_scope, self._operation_config) # resolve flow's code self._try_resolve_code_for_flow_to_file_share(flow=flow, ops=ops) @classmethod def _try_resolve_code_for_flow_to_file_share(cls, flow: Flow, ops: OperationOrchestrator) -> None: from azure.ai.ml._utils._storage_utils import AzureMLDatastorePathUri from ._artifact_utilities import _check_and_upload_path if flow.path: if flow.path.startswith("azureml://datastores"): # remote path path_uri = AzureMLDatastorePathUri(flow.path) if path_uri.datastore != DEFAULT_STORAGE: raise ValueError(f"Only {DEFAULT_STORAGE} is supported as remote storage for now.") flow.path = path_uri.path flow._code_uploaded = True return else: raise ValueError("Path is required for flow.") with flow._build_code() as code: if code is None: return if flow._code_uploaded: return code.datastore = DEFAULT_STORAGE uploaded_code_asset = _check_and_upload_path( artifact=code, asset_operations=ops._code_assets, artifact_type="Code", show_progress=False, ) if "remote_path" in uploaded_code_asset: path = uploaded_code_asset["remote_path"] elif "remote path" in uploaded_code_asset: path = uploaded_code_asset["remote path"] flow.code = path flow.path = (Path(path) / flow.path).as_posix() flow._code_uploaded = True # endregion

promptflow/src/promptflow/promptflow/azure/operations/_flow_operations.py/0

# --------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # --------------------------------------------------------- import json from dataclasses import dataclass from typing import Any, Dict, List, Optional from promptflow._sdk._constants import VIS_JS_BUNDLE_FILENAME @dataclass class RunDetail: flow_runs: List[dict] node_runs: List[dict] @dataclass class RunMetadata: name: str display_name: str create_time: str flow_path: str output_path: str tags: Optional[List[Dict[str, str]]] lineage: Optional[str] metrics: Optional[Dict[str, Any]] dag: Optional[str] flow_tools_json: Optional[dict] mode: Optional[str] = "" @dataclass class VisualizationConfig: # use camel name here to fit contract requirement from js availableIDEList: List[str] @dataclass class RunVisualization: detail: List[RunDetail] metadata: List[RunMetadata] config: List[VisualizationConfig] @dataclass class VisualizationRender: data: dict js_path: str = VIS_JS_BUNDLE_FILENAME def __post_init__(self): self.data = json.dumps(json.dumps(self.data)) # double json.dumps to match JS requirements

promptflow/src/promptflow/promptflow/contracts/_run_management.py/0

# --------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # --------------------------------------------------------- import asyncio import contextvars import inspect import threading from concurrent import futures from concurrent.futures import Future, ThreadPoolExecutor from typing import Dict, List, Optional, Tuple from promptflow._core.flow_execution_context import FlowExecutionContext from promptflow._core.tools_manager import ToolsManager from promptflow._utils.logger_utils import flow_logger from promptflow._utils.utils import set_context from promptflow.contracts.flow import Node from promptflow.executor._dag_manager import DAGManager from promptflow.executor._errors import LineExecutionTimeoutError, NoNodeExecutedError RUN_FLOW_NODES_LINEARLY = 1 DEFAULT_CONCURRENCY_BULK = 2 DEFAULT_CONCURRENCY_FLOW = 16 class FlowNodesScheduler: def __init__( self, tools_manager: ToolsManager, inputs: Dict, nodes_from_invoker: List[Node], node_concurrency: int, context: FlowExecutionContext, ) -> None: self._tools_manager = tools_manager self._future_to_node: Dict[Future, Node] = {} self._node_concurrency = min(node_concurrency, DEFAULT_CONCURRENCY_FLOW) flow_logger.info(f"Start to run {len(nodes_from_invoker)} nodes with concurrency level {node_concurrency}.") self._dag_manager = DAGManager(nodes_from_invoker, inputs) self._context = context def wait_within_timeout(self, execution_event: threading.Event, timeout: int): flow_logger.info(f"Timeout task is scheduled to wait for {timeout} seconds.") signal = execution_event.wait(timeout=timeout) if signal: flow_logger.info("Timeout task is cancelled because the execution is finished.") else: flow_logger.warning(f"Timeout task timeouted after waiting for {timeout} seconds.") def execute( self, line_timeout_sec: Optional[int] = None, ) -> Tuple[dict, dict]: parent_context = contextvars.copy_context() with ThreadPoolExecutor( max_workers=self._node_concurrency, initializer=set_context, initargs=(parent_context,) ) as executor: self._execute_nodes(executor) timeout_task = None event = threading.Event() if line_timeout_sec is not None: timeout_task = executor.submit(self.wait_within_timeout, event, line_timeout_sec) try: while not self._dag_manager.completed(): if not self._future_to_node: raise NoNodeExecutedError("No nodes are ready for execution, but the flow is not completed.") tasks_to_wait = list(self._future_to_node.keys()) if timeout_task is not None: tasks_to_wait.append(timeout_task) completed_futures_with_wait, _ = futures.wait(tasks_to_wait, return_when=futures.FIRST_COMPLETED) completed_futures = [f for f in completed_futures_with_wait if f in self._future_to_node] self._dag_manager.complete_nodes(self._collect_outputs(completed_futures)) for each_future in completed_futures: del self._future_to_node[each_future] if timeout_task and timeout_task.done(): raise LineExecutionTimeoutError(self._context._line_number, line_timeout_sec) self._execute_nodes(executor) except Exception as e: err_msg = "Flow execution has failed." if isinstance(e, LineExecutionTimeoutError): err_msg = f"Line execution timeout after {line_timeout_sec} seconds." self._context.cancel_node_runs(err_msg) node_names = ",".join(node.name for node in self._future_to_node.values()) flow_logger.error(f"{err_msg} Cancelling all running nodes: {node_names}.") for unfinished_future in self._future_to_node.keys(): # We can't cancel running tasks here, only pending tasks could be cancelled. unfinished_future.cancel() # Even we raise exception here, still need to wait all running jobs finish to exit. raise e finally: # Cancel timeout task no matter the execution is finished or failed. event.set() for node in self._dag_manager.bypassed_nodes: self._dag_manager.completed_nodes_outputs[node] = None return self._dag_manager.completed_nodes_outputs, self._dag_manager.bypassed_nodes def _execute_nodes(self, executor: ThreadPoolExecutor): # Skip nodes and update node run info until there are no nodes to bypass nodes_to_bypass = self._dag_manager.pop_bypassable_nodes() while nodes_to_bypass: for node in nodes_to_bypass: self._context.bypass_node(node) nodes_to_bypass = self._dag_manager.pop_bypassable_nodes() # Submit nodes that are ready to run nodes_to_exec = self._dag_manager.pop_ready_nodes() if nodes_to_exec: self._submit_nodes(executor, nodes_to_exec) def _collect_outputs(self, completed_futures: List[Future]): completed_nodes_outputs = {} for each_future in completed_futures: each_node_result = each_future.result() each_node = self._future_to_node[each_future] completed_nodes_outputs[each_node.name] = each_node_result return completed_nodes_outputs def _submit_nodes(self, executor: ThreadPoolExecutor, nodes): for each_node in nodes: future = executor.submit(self._exec_single_node_in_thread, (each_node, self._dag_manager)) self._future_to_node[future] = each_node def _exec_single_node_in_thread(self, args: Tuple[Node, DAGManager]): node, dag_manager = args # We are using same run tracker and cache manager for all threads, which may not thread safe. # But for bulk run scenario, we've doing this for a long time, and it works well. context = self._context f = self._tools_manager.get_tool(node.name) kwargs = dag_manager.get_node_valid_inputs(node, f) if inspect.iscoroutinefunction(f): # TODO: Run async functions in flow level event loop result = asyncio.run(context.invoke_tool_async(node, f, kwargs=kwargs)) else: result = context.invoke_tool(node, f, kwargs=kwargs) return result

promptflow/src/promptflow/promptflow/executor/_flow_nodes_scheduler.py/0

# --------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # --------------------------------------------------------- from promptflow._core.tool import ToolInvoker class DefaultToolInvoker(ToolInvoker): def invoke_tool(self, f, *args, **kwargs): return f(*args, **kwargs) # Do nothing

promptflow/src/promptflow/promptflow/executor/_tool_invoker.py/0