693b84db2b
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
269 lines
11 KiB
Python
269 lines
11 KiB
Python
"""Custom API provider implementation."""
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import logging
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import os
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from typing import Optional
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from .openai_compatible import OpenAICompatibleProvider
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from .openrouter_registry import OpenRouterModelRegistry
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from .shared import ModelCapabilities, ModelResponse, ProviderType, TemperatureConstraint
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class CustomProvider(OpenAICompatibleProvider):
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"""Adapter for self-hosted or local OpenAI-compatible endpoints.
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Role
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Provide a uniform bridge between the MCP server and user-managed
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OpenAI-compatible services (Ollama, vLLM, LM Studio, bespoke gateways).
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By subclassing :class:`OpenAICompatibleProvider` it inherits request and
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token handling, while the custom registry exposes locally defined model
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metadata.
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Notable behaviour
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* Uses :class:`OpenRouterModelRegistry` to load model definitions and
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aliases so custom deployments share the same metadata pipeline as
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OpenRouter itself.
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* Normalises version-tagged model names (``model:latest``) and applies
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restriction policies just like cloud providers, ensuring consistent
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behaviour across environments.
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"""
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FRIENDLY_NAME = "Custom API"
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# Model registry for managing configurations and aliases (shared with OpenRouter)
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_registry: Optional[OpenRouterModelRegistry] = None
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def __init__(self, api_key: str = "", base_url: str = "", **kwargs):
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"""Initialize Custom provider for local/self-hosted models.
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This provider supports any OpenAI-compatible API endpoint including:
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- Ollama (typically no API key required)
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- vLLM (may require API key)
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- LM Studio (may require API key)
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- Text Generation WebUI (may require API key)
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- Enterprise/self-hosted APIs (typically require API key)
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Args:
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api_key: API key for the custom endpoint. Can be empty string for
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providers that don't require authentication (like Ollama).
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Falls back to CUSTOM_API_KEY environment variable if not provided.
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base_url: Base URL for the custom API endpoint (e.g., 'http://localhost:11434/v1').
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Falls back to CUSTOM_API_URL environment variable if not provided.
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**kwargs: Additional configuration passed to parent OpenAI-compatible provider
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Raises:
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ValueError: If no base_url is provided via parameter or environment variable
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"""
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# Fall back to environment variables only if not provided
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if not base_url:
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base_url = os.getenv("CUSTOM_API_URL", "")
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if not api_key:
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api_key = os.getenv("CUSTOM_API_KEY", "")
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if not base_url:
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raise ValueError(
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"Custom API URL must be provided via base_url parameter or CUSTOM_API_URL environment variable"
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)
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# For Ollama and other providers that don't require authentication,
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# set a dummy API key to avoid OpenAI client header issues
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if not api_key:
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api_key = "dummy-key-for-unauthenticated-endpoint"
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logging.debug("Using dummy API key for unauthenticated custom endpoint")
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logging.info(f"Initializing Custom provider with endpoint: {base_url}")
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super().__init__(api_key, base_url=base_url, **kwargs)
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# Initialize model registry (shared with OpenRouter for consistent aliases)
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if CustomProvider._registry is None:
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CustomProvider._registry = OpenRouterModelRegistry()
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# Log loaded models and aliases only on first load
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models = self._registry.list_models()
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aliases = self._registry.list_aliases()
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logging.info(f"Custom provider loaded {len(models)} models with {len(aliases)} aliases")
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# ------------------------------------------------------------------
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# Capability surface
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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 custom capabilities from the registry or generic defaults."""
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builtin = super()._lookup_capabilities(canonical_name, requested_name)
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if builtin is not None:
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return builtin
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capabilities = self._registry.get_capabilities(canonical_name)
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if capabilities:
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config = self._registry.resolve(canonical_name)
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if config and getattr(config, "is_custom", False):
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capabilities.provider = ProviderType.CUSTOM
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return capabilities
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# Non-custom models should fall through so OpenRouter handles them
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return None
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logging.debug(
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f"Using generic capabilities for '{canonical_name}' via Custom API. "
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"Consider adding to custom_models.json for specific capabilities."
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)
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supports_temperature, temperature_constraint, temperature_reason = TemperatureConstraint.resolve_settings(
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canonical_name
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)
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logging.warning(
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f"Model '{canonical_name}' not found in custom_models.json. Using generic capabilities with inferred settings. "
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f"Temperature support: {supports_temperature} ({temperature_reason}). "
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"For better accuracy, add this model to your custom_models.json configuration."
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)
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generic = ModelCapabilities(
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provider=ProviderType.CUSTOM,
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model_name=canonical_name,
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friendly_name=f"{self.FRIENDLY_NAME} ({canonical_name})",
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context_window=32_768,
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max_output_tokens=32_768,
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supports_extended_thinking=False,
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supports_system_prompts=True,
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supports_streaming=True,
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supports_function_calling=False,
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supports_temperature=supports_temperature,
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temperature_constraint=temperature_constraint,
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)
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generic._is_generic = True
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return generic
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def get_provider_type(self) -> ProviderType:
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"""Identify this provider for restriction and logging logic."""
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return ProviderType.CUSTOM
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# ------------------------------------------------------------------
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# Validation
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# ------------------------------------------------------------------
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def validate_model_name(self, model_name: str) -> bool:
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"""Validate if the model name is allowed.
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For custom endpoints, only accept models that are explicitly intended for
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local/custom usage. This provider should NOT handle OpenRouter or cloud models.
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Args:
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model_name: Model name to validate
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Returns:
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True if model is intended for custom/local endpoint
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"""
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if super().validate_model_name(model_name):
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return True
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config = self._registry.resolve(model_name)
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if config and not getattr(config, "is_custom", False):
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return False
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clean_model_name = model_name
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if ":" in model_name:
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clean_model_name = model_name.split(":", 1)[0]
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logging.debug(f"Stripped version tag from '{model_name}' -> '{clean_model_name}'")
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if super().validate_model_name(clean_model_name):
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return True
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config = self._registry.resolve(clean_model_name)
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if config and not getattr(config, "is_custom", False):
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return False
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lowered = clean_model_name.lower()
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if any(indicator in lowered for indicator in ["local", "ollama", "vllm", "lmstudio"]):
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logging.debug(f"Model '{clean_model_name}' validated via local indicators")
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return True
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if "/" not in clean_model_name:
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logging.debug(f"Model '{clean_model_name}' validated as potential local model (no vendor prefix)")
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return True
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logging.debug(f"Model '{model_name}' rejected by custom provider (appears to be cloud model)")
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return False
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# ------------------------------------------------------------------
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# Request execution
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# ------------------------------------------------------------------
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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 custom API.
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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
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max_output_tokens: Maximum tokens to generate
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**kwargs: Additional 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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# Resolve model alias to actual model name
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resolved_model = self._resolve_model_name(model_name)
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# Call parent method with resolved model name
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return super().generate_content(
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prompt=prompt,
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model_name=resolved_model,
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system_prompt=system_prompt,
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temperature=temperature,
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max_output_tokens=max_output_tokens,
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**kwargs,
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)
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# ------------------------------------------------------------------
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# Registry helpers
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# ------------------------------------------------------------------
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def _resolve_model_name(self, model_name: str) -> str:
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"""Resolve registry aliases and strip version tags for local models."""
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config = self._registry.resolve(model_name)
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if config:
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if config.model_name != model_name:
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logging.info(f"Resolved model alias '{model_name}' to '{config.model_name}'")
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return config.model_name
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if ":" in model_name:
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base_model = model_name.split(":")[0]
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logging.debug(f"Stripped version tag from '{model_name}' -> '{base_model}'")
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base_config = self._registry.resolve(base_model)
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if base_config:
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logging.info(f"Resolved base model '{base_model}' to '{base_config.model_name}'")
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return base_config.model_name
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return base_model
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logging.debug(f"Model '{model_name}' not found in registry, using as-is")
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return model_name
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def get_all_model_capabilities(self) -> dict[str, ModelCapabilities]:
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"""Expose registry capabilities for models marked as custom."""
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if not self._registry:
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return {}
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capabilities: dict[str, ModelCapabilities] = {}
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for model_name in self._registry.list_models():
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config = self._registry.resolve(model_name)
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if config and getattr(config, "is_custom", False):
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capabilities[model_name] = config
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return capabilities
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