395 lines
14 KiB
Python
395 lines
14 KiB
Python
"""Base interfaces and common behaviour for model providers."""
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import logging
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import time
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from abc import ABC, abstractmethod
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from typing import TYPE_CHECKING, Any, Callable, Optional
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if TYPE_CHECKING:
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from tools.models import ToolModelCategory
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from .shared import ModelCapabilities, ModelResponse, ProviderType
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logger = logging.getLogger(__name__)
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class ModelProvider(ABC):
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"""Abstract base class for all model backends in the MCP server.
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Role
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Defines the interface every provider must implement so the registry,
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restriction service, and tools have a uniform surface for listing
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models, resolving aliases, and executing requests.
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Responsibilities
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* expose static capability metadata for each supported model via
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:class:`ModelCapabilities`
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* accept user prompts, forward them to the underlying SDK, and wrap
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responses in :class:`ModelResponse`
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* report tokenizer counts for budgeting and validation logic
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* advertise provider identity (``ProviderType``) so restriction
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policies can map environment configuration onto providers
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* validate whether a model name or alias is recognised by the provider
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Shared helpers like temperature validation, alias resolution, and
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restriction-aware ``list_models`` live here so concrete subclasses only
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need to supply their catalogue and wire up SDK-specific behaviour.
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"""
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# All concrete providers must define their supported models
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MODEL_CAPABILITIES: dict[str, Any] = {}
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def __init__(self, api_key: str, **kwargs):
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"""Initialize the provider with API key and optional configuration."""
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self.api_key = api_key
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self.config = kwargs
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self._sorted_capabilities_cache: Optional[list[tuple[str, ModelCapabilities]]] = None
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# ------------------------------------------------------------------
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# Provider identity & capability surface
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# ------------------------------------------------------------------
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@abstractmethod
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def get_provider_type(self) -> ProviderType:
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"""Return the concrete provider identity."""
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def get_capabilities(self, model_name: str) -> ModelCapabilities:
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"""Resolve capability metadata for a model name.
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This centralises the alias resolution → lookup → restriction check
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pipeline so providers only override the pieces they genuinely need to
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customise. Subclasses usually only override ``_lookup_capabilities`` to
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integrate a registry or dynamic source, or ``_finalise_capabilities`` to
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tweak the returned object.
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"""
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resolved_name = self._resolve_model_name(model_name)
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capabilities = self._lookup_capabilities(resolved_name, model_name)
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if capabilities is None:
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self._raise_unsupported_model(model_name)
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self._ensure_model_allowed(capabilities, resolved_name, model_name)
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return self._finalise_capabilities(capabilities, resolved_name, model_name)
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def get_all_model_capabilities(self) -> dict[str, ModelCapabilities]:
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"""Return statically declared capabilities when available."""
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model_map = getattr(self, "MODEL_CAPABILITIES", None)
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if isinstance(model_map, dict) and model_map:
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return {k: v for k, v in model_map.items() if isinstance(v, ModelCapabilities)}
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return {}
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def get_capabilities_by_rank(self) -> list[tuple[str, ModelCapabilities]]:
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"""Return model capabilities sorted by effective capability rank."""
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if self._sorted_capabilities_cache is not None:
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return list(self._sorted_capabilities_cache)
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model_configs = self.get_all_model_capabilities()
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if not model_configs:
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self._sorted_capabilities_cache = []
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return []
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items = list(model_configs.items())
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items.sort(key=lambda item: (-item[1].get_effective_capability_rank(), item[0]))
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self._sorted_capabilities_cache = items
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return list(items)
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def _invalidate_capability_cache(self) -> None:
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"""Clear cached sorted capability data (call after dynamic updates)."""
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self._sorted_capabilities_cache = None
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def list_models(
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self,
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*,
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respect_restrictions: bool = True,
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include_aliases: bool = True,
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lowercase: bool = False,
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unique: bool = False,
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) -> list[str]:
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"""Return formatted model names supported by this provider."""
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model_configs = self.get_all_model_capabilities()
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if not model_configs:
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return []
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restriction_service = None
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if respect_restrictions:
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from utils.model_restrictions import get_restriction_service
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restriction_service = get_restriction_service()
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if restriction_service:
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allowed_configs = {}
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for model_name, config in model_configs.items():
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if restriction_service.is_allowed(self.get_provider_type(), model_name):
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allowed_configs[model_name] = config
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model_configs = allowed_configs
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if not model_configs:
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return []
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return ModelCapabilities.collect_model_names(
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model_configs,
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include_aliases=include_aliases,
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lowercase=lowercase,
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unique=unique,
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)
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# ------------------------------------------------------------------
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# Request execution
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# ------------------------------------------------------------------
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@abstractmethod
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def generate_content(
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self,
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prompt: str,
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model_name: str,
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system_prompt: Optional[str] = None,
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temperature: float = 0.3,
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max_output_tokens: Optional[int] = None,
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**kwargs,
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) -> ModelResponse:
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"""Generate content using the model."""
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def count_tokens(self, text: str, model_name: str) -> int:
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"""Estimate token usage for a piece of text."""
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resolved_model = self._resolve_model_name(model_name)
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if not text:
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return 0
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estimated = max(1, len(text) // 4)
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logger.debug("Estimating %s tokens for model %s via character heuristic", estimated, resolved_model)
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return estimated
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def close(self) -> None:
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"""Clean up any resources held by the provider."""
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return
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# ------------------------------------------------------------------
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# Retry helpers
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# ------------------------------------------------------------------
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def _is_error_retryable(self, error: Exception) -> bool:
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"""Return True when an error warrants another attempt.
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Subclasses with structured provider errors should override this hook.
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The default implementation only retries obvious transient failures such
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as timeouts or 5xx responses detected via string inspection.
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"""
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error_str = str(error).lower()
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if "429" in error_str or "rate limit" in error_str:
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return False
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retryable_indicators = [
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"timeout",
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"connection",
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"temporary",
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"unavailable",
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"retry",
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"reset",
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"refused",
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"broken pipe",
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"tls",
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"handshake",
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"network",
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"500",
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"502",
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"503",
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"504",
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]
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return any(indicator in error_str for indicator in retryable_indicators)
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def _run_with_retries(
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self,
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operation: Callable[[], Any],
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*,
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max_attempts: int,
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delays: Optional[list[float]] = None,
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log_prefix: str = "",
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):
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"""Execute ``operation`` with retry semantics.
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Args:
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operation: Callable returning the provider result.
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max_attempts: Maximum number of attempts (>=1).
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delays: Optional list of sleep durations between attempts.
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log_prefix: Optional identifier for log clarity.
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Returns:
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Whatever ``operation`` returns.
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Raises:
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The last exception when all retries fail or the error is not retryable.
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"""
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if max_attempts < 1:
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raise ValueError("max_attempts must be >= 1")
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attempts = max_attempts
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delays = delays or []
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last_exc: Optional[Exception] = None
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for attempt_index in range(attempts):
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try:
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return operation()
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except Exception as exc: # noqa: BLE001 - bubble exact provider errors
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last_exc = exc
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attempt_number = attempt_index + 1
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# Decide whether to retry based on subclass hook
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retryable = self._is_error_retryable(exc)
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if not retryable or attempt_number >= attempts:
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raise
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delay_idx = min(attempt_index, len(delays) - 1) if delays else -1
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delay = delays[delay_idx] if delay_idx >= 0 else 0.0
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if delay > 0:
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logger.warning(
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"%s retryable error (attempt %s/%s): %s. Retrying in %ss...",
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log_prefix or self.__class__.__name__,
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attempt_number,
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attempts,
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exc,
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delay,
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)
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time.sleep(delay)
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else:
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logger.warning(
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"%s retryable error (attempt %s/%s): %s. Retrying...",
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log_prefix or self.__class__.__name__,
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attempt_number,
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attempts,
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exc,
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)
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# Should never reach here because loop either returns or raises
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raise last_exc if last_exc else RuntimeError("Retry loop exited without result")
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# ------------------------------------------------------------------
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# Validation hooks
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# ------------------------------------------------------------------
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def validate_model_name(self, model_name: str) -> bool:
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"""Return ``True`` when the model resolves to an allowed capability."""
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try:
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self.get_capabilities(model_name)
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except ValueError:
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return False
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return True
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def validate_parameters(self, model_name: str, temperature: float, **kwargs) -> None:
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"""Validate model parameters against capabilities."""
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capabilities = self.get_capabilities(model_name)
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if not capabilities.temperature_constraint.validate(temperature):
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constraint_desc = capabilities.temperature_constraint.get_description()
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raise ValueError(f"Temperature {temperature} is invalid for model {model_name}. {constraint_desc}")
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# ------------------------------------------------------------------
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# Preference / registry hooks
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# ------------------------------------------------------------------
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def get_preferred_model(self, category: "ToolModelCategory", allowed_models: list[str]) -> Optional[str]:
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"""Get the preferred model from this provider for a given category."""
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return None
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def get_model_registry(self) -> Optional[dict[str, Any]]:
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"""Return the model registry backing this provider, if any."""
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return None
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# ------------------------------------------------------------------
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# Capability lookup pipeline
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# ------------------------------------------------------------------
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def _lookup_capabilities(
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self,
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canonical_name: str,
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requested_name: Optional[str] = None,
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) -> Optional[ModelCapabilities]:
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"""Return ``ModelCapabilities`` for the canonical model name."""
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return self.get_all_model_capabilities().get(canonical_name)
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def _ensure_model_allowed(
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self,
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capabilities: ModelCapabilities,
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canonical_name: str,
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requested_name: str,
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) -> None:
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"""Raise ``ValueError`` if the model violates restriction policy."""
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try:
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from utils.model_restrictions import get_restriction_service
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except Exception: # pragma: no cover - only triggered if service import breaks
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return
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restriction_service = get_restriction_service()
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if not restriction_service:
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return
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if restriction_service.is_allowed(self.get_provider_type(), canonical_name, requested_name):
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return
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raise ValueError(
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f"{self.get_provider_type().value} model '{canonical_name}' is not allowed by restriction policy."
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)
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def _finalise_capabilities(
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self,
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capabilities: ModelCapabilities,
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canonical_name: str,
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requested_name: str,
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) -> ModelCapabilities:
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"""Allow subclasses to adjust capability metadata before returning."""
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return capabilities
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def _raise_unsupported_model(self, model_name: str) -> None:
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"""Raise the canonical unsupported-model error."""
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raise ValueError(f"Unsupported model '{model_name}' for provider {self.get_provider_type().value}.")
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def _resolve_model_name(self, model_name: str) -> str:
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"""Resolve model shorthand to full name.
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This implementation uses the hook methods to support different
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model configuration sources.
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Args:
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model_name: Model name that may be an alias
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Returns:
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Resolved model name
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"""
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# Get model configurations from the hook method
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model_configs = self.get_all_model_capabilities()
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# First check if it's already a base model name (case-sensitive exact match)
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if model_name in model_configs:
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return model_name
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# Check case-insensitively for both base models and aliases
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model_name_lower = model_name.lower()
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# Check base model names case-insensitively
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for base_model in model_configs:
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if base_model.lower() == model_name_lower:
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return base_model
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# Check aliases from the model configurations
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alias_map = ModelCapabilities.collect_aliases(model_configs)
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for base_model, aliases in alias_map.items():
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if any(alias.lower() == model_name_lower for alias in aliases):
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return base_model
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# If not found, return as-is
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return model_name
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