35d72e7fa8
- Add LLMEndpoint model to models.py with encrypted api_key field - Create encryption.py with Fernet symmetric encryption (key derived from JWT_SECRET via PBKDF2) - Implement full endpoints router: list, get, create, update, delete + test_connection - Test endpoint calls adapter.test_connection() and list_models() - API keys never exposed in responses; has_api_key boolean flag added - 25 tests in test_endpoints.py, all 444 tests passing
299 lines
7.7 KiB
Python
299 lines
7.7 KiB
Python
"""PromptLooper Pydantic request/response schemas."""
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import uuid
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from datetime import datetime
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from pydantic import BaseModel, ConfigDict, Field
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from models import ExperimentStatus, RunStatus
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# ---------------------------------------------------------------------------
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# Shared mixins
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# ---------------------------------------------------------------------------
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class _TimestampMixin(BaseModel):
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created_at: datetime
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updated_at: datetime
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# ---------------------------------------------------------------------------
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# Project
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# ---------------------------------------------------------------------------
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class ProjectCreate(BaseModel):
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name: str = Field(..., min_length=1, max_length=255)
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description: str | None = None
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class ProjectUpdate(BaseModel):
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name: str | None = Field(None, min_length=1, max_length=255)
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description: str | None = None
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class ProjectResponse(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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id: uuid.UUID
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name: str
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description: str | None
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owner_id: uuid.UUID
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created_at: datetime
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updated_at: datetime
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class ProjectListResponse(BaseModel):
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items: list[ProjectResponse]
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total: int
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# ---------------------------------------------------------------------------
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# Experiment
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# ---------------------------------------------------------------------------
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class ExperimentCreate(BaseModel):
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name: str = Field(..., min_length=1, max_length=255)
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description: str | None = None
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sample_data: dict | None = None
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pipeline_stages: dict | None = None
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scoring_config: dict | None = None
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parameter_space: dict | None = None
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class ExperimentUpdate(BaseModel):
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name: str | None = Field(None, min_length=1, max_length=255)
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description: str | None = None
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sample_data: dict | None = None
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pipeline_stages: dict | None = None
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scoring_config: dict | None = None
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parameter_space: dict | None = None
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status: ExperimentStatus | None = None
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class ExperimentResponse(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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id: uuid.UUID
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project_id: uuid.UUID
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name: str
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description: str | None
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sample_data: dict | None
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pipeline_stages: dict | None
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scoring_config: dict | None
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parameter_space: dict | None
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status: ExperimentStatus
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created_at: datetime
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updated_at: datetime
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class ExperimentListResponse(BaseModel):
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items: list[ExperimentResponse]
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total: int
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# ---------------------------------------------------------------------------
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# Run
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# ---------------------------------------------------------------------------
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class RunResponse(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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id: uuid.UUID
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experiment_id: uuid.UUID
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config_hash: str
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config: dict
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status: RunStatus
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started_at: datetime | None
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completed_at: datetime | None
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duration_ms: int | None
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tokens_in: int | None
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tokens_out: int | None
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cost_estimate: float | None
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class RunListResponse(BaseModel):
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items: list[RunResponse]
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total: int
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# ---------------------------------------------------------------------------
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# StageResult (read-only, returned inside Run details)
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# ---------------------------------------------------------------------------
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class StageResultResponse(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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id: uuid.UUID
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run_id: uuid.UUID
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stage_index: int
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prompt_sent: str
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response_raw: str
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model_used: str
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parameters: dict | None
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tokens_in: int | None
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tokens_out: int | None
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latency_ms: int | None
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class RunDetailResponse(RunResponse):
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"""Run with nested stage results and scores."""
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stage_results: list[StageResultResponse] = []
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scores: list["ScoreResponse"] = []
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# ---------------------------------------------------------------------------
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# Score
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# ---------------------------------------------------------------------------
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class ScoreInput(BaseModel):
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scorer_name: str = Field(..., min_length=1, max_length=255)
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value: float
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metadata: dict | None = None
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class ScoreResponse(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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id: uuid.UUID
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run_id: uuid.UUID
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scorer_name: str
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value: float
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scorer_metadata: dict | None
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created_at: datetime
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# ---------------------------------------------------------------------------
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# Endpoint (LLM endpoint configuration)
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# ---------------------------------------------------------------------------
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class EndpointCreate(BaseModel):
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name: str = Field(..., min_length=1, max_length=255)
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url: str = Field(..., min_length=1, max_length=2048)
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api_key: str | None = None
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default_model: str | None = Field(None, max_length=255)
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class EndpointUpdate(BaseModel):
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name: str | None = Field(None, min_length=1, max_length=255)
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url: str | None = Field(None, min_length=1, max_length=2048)
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api_key: str | None = None
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default_model: str | None = Field(None, max_length=255)
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class EndpointResponse(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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id: uuid.UUID
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name: str
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url: str
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default_model: str | None
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has_api_key: bool = False
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class EndpointListResponse(BaseModel):
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items: list[EndpointResponse]
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total: int
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# ---------------------------------------------------------------------------
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# Webhook
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# ---------------------------------------------------------------------------
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class WebhookCreate(BaseModel):
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event_type: str = Field(..., min_length=1, max_length=255)
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url: str = Field(..., min_length=1, max_length=2048)
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headers: dict | None = None
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is_active: bool = True
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class WebhookUpdate(BaseModel):
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event_type: str | None = Field(None, min_length=1, max_length=255)
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url: str | None = Field(None, min_length=1, max_length=2048)
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headers: dict | None = None
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is_active: bool | None = None
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class WebhookResponse(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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id: uuid.UUID
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event_type: str
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url: str
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headers: dict | None
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is_active: bool
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class WebhookListResponse(BaseModel):
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items: list[WebhookResponse]
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total: int
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# ---------------------------------------------------------------------------
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# Auth
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# ---------------------------------------------------------------------------
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class SetupRequest(BaseModel):
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username: str = Field(..., min_length=1, max_length=255)
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password: str = Field(..., min_length=8)
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class LoginRequest(BaseModel):
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username: str
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password: str
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class TokenResponse(BaseModel):
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access_token: str
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token_type: str = "bearer"
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class UserResponse(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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id: uuid.UUID
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username: str
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is_admin: bool
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created_at: datetime
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# ---------------------------------------------------------------------------
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# Export
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# ---------------------------------------------------------------------------
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class ExportRunRow(BaseModel):
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"""Flat row for CSV/JSON export of run results."""
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run_id: uuid.UUID
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experiment_id: uuid.UUID
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config_hash: str
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config: dict
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status: RunStatus
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duration_ms: int | None = None
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tokens_in: int | None = None
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tokens_out: int | None = None
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cost_estimate: float | None = None
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scores: dict[str, float] = Field(
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default_factory=dict,
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description="Map of scorer_name → value",
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)
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class ExportResponse(BaseModel):
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experiment_id: uuid.UUID
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experiment_name: str
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rows: list[ExportRunRow]
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# ---------------------------------------------------------------------------
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# Health
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# ---------------------------------------------------------------------------
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class HealthResponse(BaseModel):
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status: str = "ok"
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database: bool
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redis: bool
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# Rebuild forward refs for RunDetailResponse
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RunDetailResponse.model_rebuild()
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