99543d04c6
- Merge internal-eval into development.sh (single Celery/infra); internal-eval.sh wraps with LIFE_ECHO_WITH_INTERNAL_EVAL; EVAL_ATTACH_ONLY for attaching 8001 when :8000 is already up; document in api/docs/internal-eval.md. - Evaluation: transcript_for_judge, judge error surfacing, rubric/schema tweaks, execution_service and router updates; tests for judge and composite eval. - Memory: ingest nested transaction for embedding/enrichment rollback safety. - Conversation WS: logger.exception for pipeline errors (avoid loguru KeyError). - app-eval-web: Playground saved replays, dialogue turns helper, hash user_id for Memoir; Memoir chapter baseline↔DB row compare with title heuristics; Stories page (#memoir-stories); Markdown + copy buttons; toolbar/panel UI; react-markdown; development proxy and fixture updates.
79 lines
2.7 KiB
Python
79 lines
2.7 KiB
Python
"""评测用对话文本格式化（稳定 Turn 标签、便于评审引用）。"""
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from __future__ import annotations
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from typing import Any, Protocol
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class _MessageLike(Protocol):
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role: str | None
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content: str | None
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def assistant_text_for_eval_display(raw: str) -> str:
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"""评审与 transcript 展示：避免字面量 [SPLIT] 干扰 judge 阅读。"""
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return (raw or "").replace("[SPLIT]", "\n")
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def format_eval_turn_block(turn_index_0: int, user: str, assistant: str) -> str:
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"""单轮回放/节选：`[Turn k]` 从 1 起计。"""
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u = (user or "").strip()
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a = assistant_text_for_eval_display(assistant).strip()
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k = int(turn_index_0) + 1
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return f"[Turn {k}]\n用户: {u}\nAI: {a}"
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def format_export_turns_with_labels(turns: list[tuple[str, str]]) -> str:
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"""用户导出 fixture：每轮 (user, ai)。"""
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parts: list[str] = []
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for i, (u, ai) in enumerate(turns):
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parts.append(format_eval_turn_block(i, u, ai))
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return "\n\n".join(parts)
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def pair_session_messages_to_turns(messages: list[_MessageLike] | list[Any]) -> list[tuple[str, str]]:
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"""将对话消息序列为 (user, assistant) 轮次列表，语义与 `format_session_messages_with_turn_labels` 一致。
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末尾仅有 human、无紧随 assistant 时，补一轮 (user, "") 供 UI 与评审对齐。
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"""
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out: list[tuple[str, str]] = []
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pending_user: str | None = None
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for m in messages:
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r = (getattr(m, "role", None) or "").lower()
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body = (getattr(m, "content", None) or "").strip()
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if r == "system":
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continue
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if not body and r != "human":
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continue
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if r == "human":
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pending_user = body
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elif r in ("ai", "assistant"):
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u = (pending_user or "").strip()
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pending_user = None
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out.append((u, body))
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if pending_user is not None:
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out.append((pending_user.strip(), ""))
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return out
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def format_session_messages_with_turn_labels(messages: list[_MessageLike] | list[Any]) -> str:
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"""会话消息序列：按出现顺序将相邻 human→assistant 合并为一轮。"""
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blocks: list[str] = []
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turn_idx = 0
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pending_user: str | None = None
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for m in messages:
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r = (getattr(m, "role", None) or "").lower()
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body = (getattr(m, "content", None) or "").strip()
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if not body and r != "human":
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continue
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if r == "human":
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pending_user = body
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elif r in ("ai", "assistant", "system"):
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if r == "system":
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continue
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u = (pending_user or "").strip()
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pending_user = None
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blocks.append(format_eval_turn_block(turn_idx, u, body))
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turn_idx += 1
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return "\n\n".join(blocks)
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