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chore: import upstream snapshot with attribution
2026-07-13 12:37:14 +08:00

215 lines
6.3 KiB
Python

# Copyright 2025 Google LLC.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Provider discovery and registration system.
This module provides centralized provider discovery without circular imports.
It supports both built-in providers and third-party providers via entry points.
"""
from __future__ import annotations
from importlib import metadata
import functools
import importlib
from absl import logging
from langextract.core import base_model
__all__ = ["available_providers", "get_provider_class"]
# Static mapping for built-in providers (always available)
_BUILTINS: dict[str, str] = {
"gemini": "langextract.providers.gemini:GeminiLanguageModel",
"ollama": "langextract.providers.ollama:OllamaLanguageModel",
}
# Optional built-in providers (require extra dependencies)
_OPTIONAL_BUILTINS: dict[str, str] = {
"openai": "langextract.providers.openai:OpenAILanguageModel",
}
def _safe_entry_points(group: str) -> list:
"""Get entry points with Python 3.8-3.12 compatibility.
Args:
group: Entry point group name.
Returns:
List of entry points in the specified group.
"""
eps = metadata.entry_points()
try:
# Python 3.10+
return list(eps.select(group=group))
except AttributeError:
# Python 3.8-3.9
return list(getattr(eps, "get")(group, []))
@functools.lru_cache(maxsize=1)
def _discovered() -> dict[str, str]:
"""Cache discovered third-party providers.
Returns:
Dictionary mapping provider names to import specs.
"""
discovered: dict[str, str] = {}
for ep in _safe_entry_points("langextract.providers"):
# Handle both old and new entry_points API
if hasattr(ep, "value"):
discovered.setdefault(ep.name, ep.value)
else:
# Legacy API - construct from module and attr
value = f"{ep.module}:{ep.attr}" if ep.attr else ep.module
discovered.setdefault(ep.name, value)
if discovered:
logging.debug(
"Discovered third-party providers: %s", list(discovered.keys())
)
return discovered
def available_providers(
allow_override: bool = False, include_optional: bool = True
) -> dict[str, str]:
"""Get all available providers (built-in + optional + third-party).
Args:
allow_override: If True, third-party providers can override built-ins.
If False (default), built-ins take precedence.
include_optional: If True (default), include optional built-in providers
that may require extra dependencies.
Returns:
Dictionary mapping provider names to import specifications.
"""
providers = dict(_discovered())
if include_optional:
if allow_override:
# Third-party can override optional built-ins
providers.update(_OPTIONAL_BUILTINS)
else:
# Optional built-ins override third-party
providers = {**providers, **_OPTIONAL_BUILTINS}
# Always add core built-ins with highest precedence (unless allow_override)
if allow_override:
# Third-party and optional can override core built-ins
providers.update(_BUILTINS)
else:
# Core built-ins take precedence over everything
providers = {**providers, **_BUILTINS}
return providers
def _load_class(spec: str) -> type[base_model.BaseLanguageModel]:
"""Load a provider class from module:Class specification.
Args:
spec: Import specification in format "module.path:ClassName".
Returns:
The loaded provider class.
Raises:
ImportError: If the spec is invalid or module cannot be imported.
TypeError: If the loaded class is not a BaseLanguageModel.
"""
module_path, _, class_name = spec.partition(":")
if not module_path or not class_name:
raise ImportError(
f"Invalid provider spec '{spec}' - expected 'module:Class'"
)
try:
module = importlib.import_module(module_path)
except ImportError as e:
raise ImportError(
f"Failed to import provider module '{module_path}': {e}"
) from e
try:
cls = getattr(module, class_name)
except AttributeError as e:
raise ImportError(
f"Provider class '{class_name}' not found in module '{module_path}'"
) from e
# Validate it's a language model
if not isinstance(cls, type) or not issubclass(
cls, base_model.BaseLanguageModel
):
# Fallback: check structural compatibility for non-ABC classes
missing = []
for method in ("infer", "parse_output"):
if not hasattr(cls, method):
missing.append(method)
if missing:
raise TypeError(
f"{cls} is not a BaseLanguageModel and missing required methods:"
f" {missing}"
)
logging.warning(
"Provider %s does not inherit from BaseLanguageModel but appears"
" compatible",
cls,
)
return cls
@functools.lru_cache(maxsize=None) # Cache all loaded classes
def get_provider_class(
name: str, allow_override: bool = False, include_optional: bool = True
) -> type[base_model.BaseLanguageModel]:
"""Get a provider class by name.
Args:
name: Provider name (e.g., "gemini", "openai", "ollama").
allow_override: If True, allow third-party providers to override built-ins.
include_optional: If True (default), include optional providers that
may require extra dependencies.
Returns:
The provider class.
Raises:
KeyError: If the provider name is not found.
ImportError: If the provider module cannot be imported (including
missing optional dependencies).
TypeError: If the provider class is not compatible.
"""
providers = available_providers(allow_override, include_optional)
if name not in providers:
available = sorted(providers.keys())
raise KeyError(
f"Unknown provider '{name}'. Available providers:"
f" {', '.join(available) if available else 'none'}.\nHint: Did you"
" install the necessary extras (e.g., pip install"
f" langextract[{name}])?"
)
return _load_class(providers[name])