308 lines
7.1 KiB
Python
308 lines
7.1 KiB
Python
"""HTTP / OpenAPI 模型。"""
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from __future__ import annotations
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from datetime import datetime
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from typing import Any
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from pydantic import BaseModel, ConfigDict, Field
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class RegressionSetCreate(BaseModel):
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name: str
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description: str | None = None
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class RegressionSetOut(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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id: str
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name: str
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description: str | None
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created_at: datetime
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class CaseCreate(BaseModel):
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title: str | None = None
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user_utterances: list[str]
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source_conversation_id: str | None = None
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source_user_id: str | None = None
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reference_memoir_markdown: str | None = None
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is_protected: bool = False
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meta: dict[str, Any] | None = None
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class CaseOut(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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id: str
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regression_set_id: str
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source_conversation_id: str | None
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source_user_id: str | None
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title: str | None
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user_utterances: list[Any]
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is_protected: bool
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created_at: datetime
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class VersionCreate(BaseModel):
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name: str
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runner_kind: str = "llm_chat_v1"
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config_json: dict[str, Any] | None = None
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class VersionOut(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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id: str
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name: str
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runner_kind: str
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config_json: dict[str, Any] | None
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created_at: datetime
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class ExperimentCreate(BaseModel):
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name: str
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regression_set_id: str
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baseline_version_id: str
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candidate_version_id: str
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rubric_pack: str = "conversation_v1+memoir_v1"
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composite_weights_json: dict[str, Any] | None = Field(
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default=None,
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description='默认 {"conversation":0.5,"memoir":0.5}',
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)
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class ExperimentOut(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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id: str
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name: str
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regression_set_id: str
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baseline_version_id: str
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candidate_version_id: str
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rubric_pack: str
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status: str
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error_message: str | None
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created_at: datetime
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completed_at: datetime | None
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class SessionDialogueMessageOut(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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role: str
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content: str
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created_at: datetime | None = None
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class SessionDialogueOut(BaseModel):
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conversation_id: str
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messages: list[SessionDialogueMessageOut]
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class SessionListItem(BaseModel):
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id: str
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user_id: str
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user_phone: str | None = Field(default=None, description="users.phone，列表展示用")
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started_at: datetime | None
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last_message_at: datetime | None = None
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conversation_stage: str | None
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current_topic: str | None
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status: str | None
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class SessionListResponse(BaseModel):
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items: list[SessionListItem]
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total: int
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class SessionTranscriptOut(BaseModel):
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conversation_id: str
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user_id: str
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user_utterances_from_segments: list[str]
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user_utterances_from_messages: list[str]
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class UserExportFixtureTurnOut(BaseModel):
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user: str
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ai: str
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class UserExportFixtureListOut(BaseModel):
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items: list[str]
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class MemoirSectionBaselineOut(BaseModel):
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title: str
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body: str
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class UserExportFixtureDetailOut(BaseModel):
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filename: str
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turns: list[UserExportFixtureTurnOut]
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source_user_id: str | None = None
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memoir_sections: list[MemoirSectionBaselineOut] = Field(default_factory=list)
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class ReplayBootstrapBody(BaseModel):
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user_id: str
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class ReplayBootstrapOut(BaseModel):
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conversation_id: str
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class EvalSandboxOut(BaseModel):
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"""内部评测专用：一次性临时账号 + 空白会话，不落真实手机号业务。"""
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user_id: str
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conversation_id: str
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phone: str
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nickname: str
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class ReplayConversationBody(BaseModel):
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conversation_id: str
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fixture_filename: str | None = None
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user_utterances: list[str] | None = None
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flush_memoir_after: bool = True
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skip_tts: bool = True
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class ReplayConversationOut(BaseModel):
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conversation_id: str
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turns_replayed: int
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utterances_echo: list[str] = Field(default_factory=list)
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class ManualJudgeConversationBody(BaseModel):
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conversation_id: str
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"""与当前评测台选中的 MD 一致，供基准 transcript / 整体打分。"""
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fixture_filename: str | None = None
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class ManualJudgeConversationStreamBody(BaseModel):
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conversation_id: str
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fixture_filename: str | None = None
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class ManualJudgeConversationOut(BaseModel):
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conversation_id: str
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fixture_filename: str | None = None
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baseline_transcript: str = ""
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replay_transcript: str
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baseline_judge: dict[str, Any] | None = None
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replay_judge: dict[str, Any] | None = None
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errors: list[str] = Field(default_factory=list)
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class ManualJudgeMemoirBody(BaseModel):
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user_id: str
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baseline_sections: list[MemoirSectionBaselineOut] | None = None
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class ManualJudgeMemoirOut(BaseModel):
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user_id: str
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chapter_results: list[dict[str, Any]] = Field(default_factory=list)
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story_results: list[dict[str, Any]] = Field(default_factory=list)
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class MemoirChapterSnapOut(BaseModel):
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id: str
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title: str
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category: str | None = None
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order_index: int | None = None
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canonical_markdown: str | None = None
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class MemoirStorySnapOut(BaseModel):
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id: str
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title: str
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stage: str | None = None
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canonical_markdown: str | None = None
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class UserMemoirSnapshotOut(BaseModel):
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user_id: str
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chapters: list[MemoirChapterSnapOut]
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stories: list[MemoirStorySnapOut]
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class SnapshotFromConversationBody(BaseModel):
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title: str | None = None
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use_messages: bool = False
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is_protected: bool = False
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class ImportMarkdownBody(BaseModel):
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markdown: str
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title: str | None = None
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is_protected: bool = False
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class ImportJsonCaseBody(BaseModel):
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regression_set_id: str
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utterances: list[str] | None = None
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raw_json: dict[str, Any] | list[Any] | None = Field(
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default=None,
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description="与 utterances 二选一：对象含 utterances 键或根数组",
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)
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title: str | None = None
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is_protected: bool = False
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class RunTurnOut(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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id: str
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turn_index: int
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user_utterance: str
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assistant_reply: str | None
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duration_ms: int | None
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judge_scores_json: dict[str, Any] | None
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judge_rationale: str | None
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class EvalRunOut(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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id: str
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experiment_id: str
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case_id: str
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side: str
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status: str
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error_message: str | None
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memoir_markdown: str | None
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conversation_score_total: float | None
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memoir_score_total: float | None
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composite_score: float | None
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judge_bundle_json: dict[str, Any] | None = None
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turns: list[RunTurnOut] = []
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class SessionEvalRunItem(BaseModel):
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experiment_name: str
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run: EvalRunOut
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class SessionEvalRunsOut(BaseModel):
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conversation_id: str
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items: list[SessionEvalRunItem]
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class GateVerdictOut(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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passed: bool
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mean_composite_delta: float | None
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protected_regressions_json: list[dict[str, Any]] | None
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details_json: dict[str, Any] | None
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computed_at: datetime
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class ExperimentDetailOut(BaseModel):
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experiment: ExperimentOut
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runs: list[EvalRunOut]
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gate: GateVerdictOut | None
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