e1e067bac4
Introduce ModelPurpose.ANALYSIS and a globally-unique is_analysis_default marker on chat model configs so campaign analysis can resolve its model. Service rejects disabled or non-chat configs; repo clears the previous holder on set. Documented the analysis role in CONTEXT.md.
105 lines
3.5 KiB
Python
105 lines
3.5 KiB
Python
"""Request and response schemas for the model configuration center."""
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from datetime import datetime
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from pydantic import BaseModel, Field
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from agenteval.models import ModelCapability, ModelModality, ModelProtocol
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from agenteval.storage.db import ModelConfigDB, iso_utc
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class ModelConfigCreate(BaseModel):
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name: str = Field(min_length=1, max_length=100)
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provider: ModelProtocol = ModelProtocol.OPENAI_COMPATIBLE
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capability: ModelCapability
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endpoint_url: str
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model_name: str | None = None
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vendor_name: str = ""
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input_modalities: list[ModelModality] = Field(default_factory=lambda: [ModelModality.TEXT], min_length=1)
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output_modalities: list[ModelModality] = Field(default_factory=lambda: [ModelModality.TEXT], min_length=1)
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context_window: int | None = Field(default=None, gt=0)
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max_output_tokens: int | None = Field(default=None, gt=0)
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supports_streaming: bool = False
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supports_tool_calling: bool = False
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supports_structured_output: bool = False
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supports_reasoning: bool = False
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region: str = ""
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documentation_url: str | None = None
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api_key: str | None = None
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enabled: bool = True
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is_default: bool = False
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is_analysis_default: bool = False
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description: str = ""
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class ModelConfigUpdate(ModelConfigCreate):
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clear_api_key: bool = False
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class ModelConfigResponse(BaseModel):
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id: str
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name: str
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provider: ModelProtocol
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capability: ModelCapability
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endpoint_url: str
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model_name: str | None
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vendor_name: str
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input_modalities: list[ModelModality]
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output_modalities: list[ModelModality]
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context_window: int | None
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max_output_tokens: int | None
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supports_streaming: bool
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supports_tool_calling: bool
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supports_structured_output: bool
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supports_reasoning: bool
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region: str
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documentation_url: str | None
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has_api_key: bool
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enabled: bool
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is_default: bool
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is_analysis_default: bool
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description: str
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created_at: str | None
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updated_at: str | None
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@classmethod
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def from_db(cls, config: ModelConfigDB) -> "ModelConfigResponse":
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return cls(
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id=config.id or "",
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name=config.name,
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provider=ModelProtocol(config.provider),
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capability=ModelCapability(config.capability),
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endpoint_url=config.endpoint_url,
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model_name=config.model_name,
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vendor_name=config.vendor_name,
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input_modalities=[ModelModality(item) for item in config.get_input_modalities()],
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output_modalities=[ModelModality(item) for item in config.get_output_modalities()],
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context_window=config.context_window,
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max_output_tokens=config.max_output_tokens,
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supports_streaming=config.supports_streaming,
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supports_tool_calling=config.supports_tool_calling,
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supports_structured_output=config.supports_structured_output,
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supports_reasoning=config.supports_reasoning,
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region=config.region,
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documentation_url=config.documentation_url,
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has_api_key=bool(config.api_key_encrypted),
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enabled=config.enabled,
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is_default=config.is_default,
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is_analysis_default=config.is_analysis_default,
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description=config.description,
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created_at=iso_utc(config.created_at),
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updated_at=iso_utc(config.updated_at),
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)
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class ModelConfigReference(BaseModel):
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scenario_id: str
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scenario_name: str
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purpose: str
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class ModelConnectionTestResponse(BaseModel):
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ok: bool
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message: str
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tested_at: datetime
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