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| from typing import Any, Literal | |
| from pydantic import BaseModel, ConfigDict, Field, field_validator, model_validator | |
| from registry import normalize_tool | |
| from context_adapter import DecisionContext | |
| class RouteRequest(BaseModel): | |
| decision_context: DecisionContext = Field(default_factory=DecisionContext) | |
| input: str = Field(..., min_length=1) | |
| tools: list[dict[str, Any]] = Field(..., min_length=1, max_length=5) | |
| system: str | None = None | |
| def _normalize_tools(cls, value: list[dict[str, Any]]) -> list[dict[str, Any]]: | |
| return [normalize_tool(item) for item in value] | |
| class RouteResponse(BaseModel): | |
| outcome: Literal["selected", "confirm", "abstain", "error"] | |
| function_calls: list[dict[str, Any]] = Field(default_factory=list) | |
| suppressed_calls: list[dict[str, Any]] = Field(default_factory=list) | |
| confidence: float | None = None | |
| reasoning: str | None = None | |
| validation: dict[str, Any] | None = None | |
| model: str | |
| class AutoRouteRequest(BaseModel): | |
| decision_context: DecisionContext = Field(default_factory=DecisionContext) | |
| query: str = Field(..., min_length=1) | |
| tools: list[dict[str, Any]] = Field(..., min_length=1) | |
| system: str | None = None | |
| max_candidates: int = Field(5, ge=1, le=5) | |
| def _normalize_tools(cls, value: list[dict[str, Any]]) -> list[dict[str, Any]]: | |
| return [normalize_tool(item) for item in value] | |
| class AutoRouteResponse(BaseModel): | |
| outcome: Literal["selected", "confirm", "abstain", "error"] | |
| candidates: list[dict[str, Any]] | |
| retrieval_scores: list[float] | |
| function_calls: list[dict[str, Any]] | |
| suppressed_calls: list[dict[str, Any]] | |
| confidence: float | None | |
| reasoning: str | None | |
| validation: dict[str, Any] | None | |
| model: str | |
| diagnostics: dict[str, Any] = Field(default_factory=dict) | |
| class ToolRegistration(BaseModel): | |
| namespace: str | |
| tools: list[dict[str, Any]] | |
| class ToolRegistrationResponse(BaseModel): | |
| registered_count: int | |
| namespace: str | |
| class RetrieveRequest(BaseModel): | |
| query: str | |
| namespace: str | None = None | |
| max_candidates: int = Field(5, ge=1, le=5) | |
| workflow_context: dict[str, Any] | None = None | |
| class EvaluateRequest(BaseModel): | |
| tools: list[dict[str, Any]] | |
| class EvaluateResponse(BaseModel): | |
| evaluations: list[dict[str, Any]] | |
| class Message(BaseModel): | |
| role: str | |
| content: str | list[dict[str, Any]] | None = None | |
| tool_call_id: str | None = None | |
| name: str | None = None | |
| tool_calls: list[dict[str, Any]] | None = None | |
| class RegistryReference(BaseModel): | |
| model_config = ConfigDict(extra="forbid") | |
| version: int = Field(1, ge=1, le=1) | |
| namespace: str = Field(..., min_length=1, max_length=256) | |
| sha256: str = Field(..., pattern="^[a-f0-9]{64}$") | |
| class ChatCompletionRequest(BaseModel): | |
| registry_reference: RegistryReference | None = None | |
| decision_context: DecisionContext = Field(default_factory=DecisionContext) | |
| model: str | |
| messages: list[Message] | |
| tools: list[dict[str, Any]] | None = None | |
| stream: bool | None = False | |
| def _one_tool_source(self): | |
| if self.registry_reference is not None and self.tools is not None: | |
| raise ValueError("provide tools or registry_reference, not both") | |
| return self | |
| def _normalize_chat_tools(cls, value): | |
| return [normalize_tool(t) for t in value] if value is not None else None | |
| class LayaEvaluationRequest(BaseModel): | |
| workflow_state: str | |
| candidates: list[dict[str, Any]] | |
| scores: list[float] | |
| function_calls: list[dict[str, Any]] | |
| confidence: float | None | |
| class LayaEvaluationResponse(BaseModel): | |
| decision: Literal["proceed", "escalate", "abstain"] | |
| reasoning: str | None = None | |