mirror of
https://github.com/meta-llama/llama-stack.git
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9e6561a1ec
# What does this PR do? The goal of this PR is code base modernization. Schema reflection code needed a minor adjustment to handle UnionTypes and collections.abc.AsyncIterator. (Both are preferred for latest Python releases.) Note to reviewers: almost all changes here are automatically generated by pyupgrade. Some additional unused imports were cleaned up. The only change worth of note can be found under `docs/openapi_generator` and `llama_stack/strong_typing/schema.py` where reflection code was updated to deal with "newer" types. Signed-off-by: Ihar Hrachyshka <ihar.hrachyshka@gmail.com>
282 lines
11 KiB
Python
282 lines
11 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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import inspect
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import json
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import logging
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from enum import Enum
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from typing import Annotated, Any, Literal, Union, get_args, get_origin
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from pydantic import BaseModel
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from pydantic.fields import FieldInfo
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from pydantic_core import PydanticUndefinedType
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log = logging.getLogger(__name__)
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def is_list_of_primitives(field_type):
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"""Check if a field type is a List of primitive types."""
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origin = get_origin(field_type)
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if origin is list or origin is list:
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args = get_args(field_type)
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if len(args) == 1 and args[0] in (int, float, str, bool):
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return True
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return False
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def is_basemodel_without_fields(typ):
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return inspect.isclass(typ) and issubclass(typ, BaseModel) and len(typ.__fields__) == 0
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def can_recurse(typ):
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return inspect.isclass(typ) and issubclass(typ, BaseModel) and len(typ.__fields__) > 0
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def get_literal_values(field):
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"""Extract literal values from a field if it's a Literal type."""
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if get_origin(field.annotation) is Literal:
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return get_args(field.annotation)
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return None
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def is_optional(field_type):
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"""Check if a field type is Optional."""
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return get_origin(field_type) is Union and type(None) in get_args(field_type)
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def get_non_none_type(field_type):
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"""Get the non-None type from an Optional type."""
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return next(arg for arg in get_args(field_type) if arg is not type(None))
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def manually_validate_field(model: type[BaseModel], field_name: str, value: Any):
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validators = model.__pydantic_decorators__.field_validators
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for _name, validator in validators.items():
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if field_name in validator.info.fields:
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validator.func(value)
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return value
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def is_discriminated_union(typ) -> bool:
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if isinstance(typ, FieldInfo):
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return typ.discriminator
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else:
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if get_origin(typ) is not Annotated:
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return False
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args = get_args(typ)
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return len(args) >= 2 and args[1].discriminator
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def prompt_for_discriminated_union(
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field_name,
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typ,
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existing_value,
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):
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if isinstance(typ, FieldInfo):
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inner_type = typ.annotation
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discriminator = typ.discriminator
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default_value = typ.default
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else:
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args = get_args(typ)
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inner_type = args[0]
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discriminator = args[1].discriminator
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default_value = args[1].default
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union_types = get_args(inner_type)
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# Find the discriminator field in each union type
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type_map = {}
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for t in union_types:
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disc_field = t.__fields__[discriminator]
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literal_values = get_literal_values(disc_field)
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if literal_values:
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for value in literal_values:
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type_map[value] = t
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while True:
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prompt = f"Enter `{discriminator}` for {field_name} (options: {', '.join(type_map.keys())})"
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if default_value is not None:
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prompt += f" (default: {default_value})"
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discriminator_value = input(f"{prompt}: ")
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if discriminator_value == "" and default_value is not None:
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discriminator_value = default_value
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if discriminator_value in type_map:
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chosen_type = type_map[discriminator_value]
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log.info(f"\nConfiguring {chosen_type.__name__}:")
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if existing_value and (getattr(existing_value, discriminator) != discriminator_value):
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existing_value = None
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sub_config = prompt_for_config(chosen_type, existing_value)
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# Set the discriminator field in the sub-config
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setattr(sub_config, discriminator, discriminator_value)
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return sub_config
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else:
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log.error(f"Invalid {discriminator}. Please try again.")
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# This is somewhat elaborate, but does not purport to be comprehensive in any way.
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# We should add handling for the most common cases to tide us over.
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#
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# doesn't support List[nested_class] yet or Dicts of any kind. needs a bunch of
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# unit tests for coverage.
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def prompt_for_config(config_type: type[BaseModel], existing_config: BaseModel | None = None) -> BaseModel:
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"""
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Recursively prompt the user for configuration values based on a Pydantic BaseModel.
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Args:
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config_type: A Pydantic BaseModel class representing the configuration structure.
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Returns:
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An instance of the config_type with user-provided values.
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"""
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config_data = {}
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for field_name, field in config_type.__fields__.items():
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field_type = field.annotation
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existing_value = getattr(existing_config, field_name) if existing_config else None
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if existing_value:
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default_value = existing_value
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else:
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default_value = field.default if not isinstance(field.default, PydanticUndefinedType) else None
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is_required = field.is_required
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# Skip fields with Literal type
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if get_origin(field_type) is Literal:
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continue
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# Skip fields with no type annotations
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if is_basemodel_without_fields(field_type):
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config_data[field_name] = field_type()
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continue
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if inspect.isclass(field_type) and issubclass(field_type, Enum):
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prompt = f"Choose {field_name} (options: {', '.join(e.name for e in field_type)}):"
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while True:
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# this branch does not handle existing and default values yet
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user_input = input(prompt + " ")
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try:
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value = field_type[user_input]
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validated_value = manually_validate_field(config_type, field, value)
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config_data[field_name] = validated_value
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break
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except KeyError:
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log.error(f"Invalid choice. Please choose from: {', '.join(e.name for e in field_type)}")
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continue
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if is_discriminated_union(field):
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config_data[field_name] = prompt_for_discriminated_union(field_name, field, existing_value)
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continue
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if is_optional(field_type) and can_recurse(get_non_none_type(field_type)):
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prompt = f"Do you want to configure {field_name}? (y/n): "
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if input(prompt).lower() == "n":
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config_data[field_name] = None
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continue
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nested_type = get_non_none_type(field_type)
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log.info(f"Entering sub-configuration for {field_name}:")
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config_data[field_name] = prompt_for_config(nested_type, existing_value)
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elif is_optional(field_type) and is_discriminated_union(get_non_none_type(field_type)):
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prompt = f"Do you want to configure {field_name}? (y/n): "
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if input(prompt).lower() == "n":
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config_data[field_name] = None
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continue
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nested_type = get_non_none_type(field_type)
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config_data[field_name] = prompt_for_discriminated_union(
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field_name,
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nested_type,
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existing_value,
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)
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elif can_recurse(field_type):
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log.info(f"\nEntering sub-configuration for {field_name}:")
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config_data[field_name] = prompt_for_config(
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field_type,
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existing_value,
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)
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else:
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prompt = f"Enter value for {field_name}"
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if existing_value is not None:
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prompt += f" (existing: {existing_value})"
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elif default_value is not None:
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prompt += f" (default: {default_value})"
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if is_optional(field_type):
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prompt += " (optional)"
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elif is_required:
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prompt += " (required)"
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prompt += ": "
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while True:
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user_input = input(prompt)
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if user_input == "":
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if default_value is not None:
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config_data[field_name] = default_value
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break
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elif is_optional(field_type) or not is_required:
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config_data[field_name] = None
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break
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else:
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log.error("This field is required. Please provide a value.")
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continue
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else:
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try:
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# Handle Optional types
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if is_optional(field_type):
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if user_input.lower() == "none":
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value = None
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else:
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field_type = get_non_none_type(field_type)
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value = user_input
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# Handle List of primitives
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elif is_list_of_primitives(field_type):
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try:
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value = json.loads(user_input)
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if not isinstance(value, list):
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raise ValueError("Input must be a JSON-encoded list")
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element_type = get_args(field_type)[0]
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value = [element_type(item) for item in value]
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except json.JSONDecodeError:
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log.error('Invalid JSON. Please enter a valid JSON-encoded list e.g., ["foo","bar"]')
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continue
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except ValueError as e:
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log.error(f"{str(e)}")
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continue
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elif get_origin(field_type) is dict:
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try:
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value = json.loads(user_input)
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if not isinstance(value, dict):
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raise ValueError("Input must be a JSON-encoded dictionary")
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except json.JSONDecodeError:
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log.error("Invalid JSON. Please enter a valid JSON-encoded dict.")
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continue
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# Convert the input to the correct type
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elif inspect.isclass(field_type) and issubclass(field_type, BaseModel):
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# For nested BaseModels, we assume a dictionary-like string input
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import ast
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value = field_type(**ast.literal_eval(user_input))
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else:
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value = field_type(user_input)
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except ValueError:
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log.error(f"Invalid input. Expected type: {getattr(field_type, '__name__', str(field_type))}")
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continue
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try:
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# Validate the field using our manual validation function
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validated_value = manually_validate_field(config_type, field_name, value)
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config_data[field_name] = validated_value
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break
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except ValueError as e:
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log.error(f"Validation error: {str(e)}")
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return config_type(**config_data)
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