2fded6fbd9
- Drop interview_reply_length and utterance_substance; always run stage LLM and memory retrieval when enabled; trim Settings fields and .env.example. - Replace guided/opening prompts with compact fact blocks plus unified behavior guidance; slim background_voice and persona to tone hints. - InterviewAgent uses fixed chat_interview max_tokens/chars/segments. Also includes stacked work: profile followup/extract path, evaluation rubric and judge schema updates, transcript SPLIT handling in execution service, user export markdown split tests, and golden case fixture.
32 lines
1.4 KiB
Python
32 lines
1.4 KiB
Python
"""default 路径下根据用户职业自由文本注入轻量提示（与 cadre/military 专属块正交）。"""
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from __future__ import annotations
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from app.agents.chat.background_voice import normalize_background_voice
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def get_occupation_chat_hint(occupation: str | None, background_voice: str) -> str:
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"""一句职业事实（仅 default 路径）；cadre/military 语气由 background_voice 覆盖。"""
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if normalize_background_voice(background_voice) != "default":
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return ""
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occ = (occupation or "").strip()
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if not occ:
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return ""
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return f"从事过「{occ}」相关工作，聊天可自然贴近其经历，不要刻意。"
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def get_occupation_narrative_hint(occupation: str | None, background_voice: str) -> str:
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"""default 路径的叙事职业上下文。"""
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if normalize_background_voice(background_voice) != "default":
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return ""
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occ = (occupation or "").strip()
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if not occ:
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return ""
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return (
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f"## 用户职业背景（仅供文体微调，须遵守事实边界）\n"
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f"用户从事过「{occ}」相关工作。叙事时可适度使用该领域常见的书面用语，"
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f"让正文贴近讲述者的身份感。\n"
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f"**禁止**因职业背景而补充口述未出现的岗位职责、行业流程、单位层级或专业术语细节；"
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f"只有当用户口述里已出现相关表达时，才可顺势书面化。"
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)
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