refactor: cleanup provider base class; cleanup shared responsibilities; cleanup public contract
docs: document provider base class refactor: cleanup custom provider, it should only deal with `is_custom` model configurations fix: make sure openrouter provider does not load `is_custom` models fix: listmodels tool cleanup
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Fahad
@@ -43,128 +43,37 @@ class ModelProvider(ABC):
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self.api_key = api_key
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self.config = kwargs
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@abstractmethod
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def get_capabilities(self, model_name: str) -> ModelCapabilities:
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"""Get capabilities for a specific model."""
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pass
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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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Args:
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prompt: User prompt to send to the model
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model_name: Name of the model to use
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system_prompt: Optional system prompt for model behavior
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temperature: Sampling temperature (0-2)
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max_output_tokens: Maximum tokens to generate
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**kwargs: Provider-specific parameters
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Returns:
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ModelResponse with generated content and metadata
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"""
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pass
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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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Providers can rely on this shared implementation or override it when
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they expose a more accurate tokenizer. This default uses a simple
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character-based heuristic so it works even without provider-specific
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tooling.
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"""
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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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# Rough estimation: ~4 characters per token for English text
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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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# ------------------------------------------------------------------
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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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"""Get the provider type."""
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pass
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"""Return the concrete provider identity."""
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@abstractmethod
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def validate_model_name(self, model_name: str) -> bool:
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"""Validate if the model name is supported by this provider."""
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pass
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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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def validate_parameters(self, model_name: str, temperature: float, **kwargs) -> None:
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"""Validate model parameters against capabilities.
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Raises:
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ValueError: If parameters are invalid
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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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capabilities = self.get_capabilities(model_name)
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# Validate temperature using constraint
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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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resolved_name = self._resolve_model_name(model_name)
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capabilities = self._lookup_capabilities(resolved_name, model_name)
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def get_model_configurations(self) -> dict[str, ModelCapabilities]:
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"""Get model configurations for this provider.
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if capabilities is None:
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self._raise_unsupported_model(model_name)
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This is a hook method that subclasses can override to provide
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their model configurations from different sources.
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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 the provider's statically declared model capabilities."""
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Returns:
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Dictionary mapping model names to their ModelCapabilities objects
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"""
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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 _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_model_configurations()
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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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def list_models(
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self,
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*,
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@@ -175,7 +84,7 @@ class ModelProvider(ABC):
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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_model_configurations()
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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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@@ -202,36 +111,155 @@ class ModelProvider(ABC):
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unique=unique,
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)
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def close(self):
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"""Clean up any resources held by the provider.
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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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Default implementation does nothing.
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Subclasses should override if they hold resources that need cleanup.
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"""
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# Base implementation: no resources to clean up
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return
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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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"""Get the preferred model from this provider for a given category."""
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Args:
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category: The tool category requiring a model
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allowed_models: Pre-filtered list of model names that are allowed by restrictions
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Returns:
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Model name if this provider has a preference, None otherwise
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"""
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# Default implementation - providers can override with specific logic
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return None
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def get_model_registry(self) -> Optional[dict[str, Any]]:
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"""Get the model registry for providers that maintain one.
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"""Return the model registry backing this provider, if any."""
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This is a hook method for providers like CustomProvider that maintain
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a dynamic model registry.
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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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Model registry dict or None if not applicable
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Resolved model name
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"""
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# Default implementation - most providers don't have a registry
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return None
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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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