Piotr Oleszczyk
cfd2485b7e
Enable on-demand INCI retrieval in /routines/suggest through Gemini function calling so detailed ingredient data is fetched only when needed. Persist and normalize tool_trace data in AI logs to make function-call behavior directly inspectable via /ai-logs endpoints.
33 lines
1.2 KiB
Python
33 lines
1.2 KiB
Python
from datetime import datetime
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from typing import Any, ClassVar
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from uuid import UUID, uuid4
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from sqlalchemy import JSON, Column
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from sqlmodel import Field, SQLModel
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from .base import utc_now
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from .domain import Domain
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class AICallLog(SQLModel, table=True):
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__tablename__ = "ai_call_logs"
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__domains__: ClassVar[frozenset[Domain]] = frozenset()
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id: UUID = Field(default_factory=uuid4, primary_key=True)
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created_at: datetime = Field(default_factory=utc_now, nullable=False)
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endpoint: str = Field(index=True)
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model: str
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system_prompt: str | None = Field(default=None)
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user_input: str | None = Field(default=None)
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response_text: str | None = Field(default=None)
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prompt_tokens: int | None = Field(default=None)
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completion_tokens: int | None = Field(default=None)
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total_tokens: int | None = Field(default=None)
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duration_ms: int | None = Field(default=None)
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finish_reason: str | None = Field(default=None)
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tool_trace: dict[str, Any] | None = Field(
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default=None,
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sa_column=Column(JSON, nullable=True),
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)
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success: bool = Field(default=True, index=True)
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error_detail: str | None = Field(default=None)
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