| |
| """Vibrato 情绪专项题库 — 类 Jev 契约(score + choice + noul 三题型) v0.1.1 |
| |
| Laya 的三种题型(qtype)在情绪域的完整特化: |
| score ×3 P/A/D × 9档李克特bin (契约在 pad_schema.py, 此处引用) |
| choice 8 族训练头 + OCC-22 距离排序(occ.py 解码层输出) |
| noul ×2 文本层才能判的是非信号 (宿主行为信号, 非情绪动力学) |
| |
| v0.1.1 变更: |
| - noul 5→2: 保留 suppressed(言不由衷) + directed_at_me(指向性)—— |
| 这两题 PAD 推不出来(定义性不可导), 只能靠文本判读; |
| negative(P<0 弱导出 0.78) / needs_comfort / escalating(宿主有ΔPAD历史自己算更准) |
| 移除——宿主或 LLM 自行判断更可靠 |
| - route 字段改名 host_signal, 去掉 chordia 路由错误表述(Chordia 是 agent 情绪 |
| 动力学引擎, 不是行为路由器) |
| |
| 冻结纪律同 pad_schema: 题干/选项/顺序改动 = 契约破裂, battery_digest() 两侧比对。 |
| teacher 标注: 一条消息一次调用, 18项+族+是非 合并一个 JSON(省 6 倍调用)。 |
| """ |
|
|
| from __future__ import annotations |
|
|
| import hashlib |
| import json |
| from typing import Any, Dict, List, Optional |
|
|
| import pad_schema |
|
|
| |
| |
| FAMILY_LABELS: List[Dict[str, str]] = [ |
| {"id": "happy", "zh": "开心"}, |
| {"id": "affectionate", "zh": "亲昵"}, |
| {"id": "calm", "zh": "平静"}, |
| {"id": "amused", "zh": "好笑"}, |
| {"id": "sad", "zh": "低落"}, |
| {"id": "anxious", "zh": "焦虑"}, |
| {"id": "angry", "zh": "生气"}, |
| {"id": "wronged", "zh": "委屈"}, |
| ] |
| FAMILY_IDS: List[str] = [f["id"] for f in FAMILY_LABELS] |
| N_FAMILY = len(FAMILY_IDS) |
|
|
| FAMILY_INSTRUCTIONS = ( |
| "TARGET 消息的发送者当前的主导情绪是哪一族？只选一个。" |
| "开心=愉悦满足；亲昵=对对方的喜爱亲近；平静=事务性/无明显情绪；" |
| "好笑=被逗乐/玩梗；低落=难过沮丧疲惫；焦虑=担心紧张不安；" |
| "生气=愤怒不满恼火；委屈=觉得被误解/被亏待/有苦说不出。" |
| ) |
|
|
| |
| |
| |
| |
| |
| NOUL_QUESTIONS: List[Dict[str, str]] = [ |
| {"id": "directed_at_me", "q": "情绪是否指向对话中的我", |
| "def": "情绪的靶子是接收者(我), 而非第三方/自身处境/泛泛而谈", |
| "host_signal": "真→宿主可能需要道歉或担责"}, |
| {"id": "suppressed", "q": "是否言不由衷/压抑", |
| "def": "表面措辞与真实情绪不符(敷衍/逞强/反话/故作轻松)则为真", |
| "host_signal": "真→宿主轻问深挖, 勿按字面回应"}, |
| ] |
| NOUL_IDS: List[str] = [q["id"] for q in NOUL_QUESTIONS] |
| N_NOUL = len(NOUL_IDS) |
|
|
|
|
| def battery_digest() -> str: |
| canonical = json.dumps( |
| {"pad": pad_schema.contract_digest(), |
| "family": {"ids": FAMILY_IDS, "instructions": FAMILY_INSTRUCTIONS}, |
| "noul": [{"id": q["id"], "q": q["q"]} for q in NOUL_QUESTIONS]}, |
| ensure_ascii=False, sort_keys=True, separators=(",", ":")) |
| return hashlib.sha256(canonical.encode("utf-8")).hexdigest() |
|
|
|
|
| def build_teacher_prompt(state: str, prev_pad: Optional[List[float]] = None) -> str: |
| """情绪专项合并标注提示词: 一次调用出 18项 + 情绪族 + 5是非。""" |
| lines = [ |
| "你是情绪标注专家。判断下面 TARGET 消息发送者的情绪状态, 只输出 JSON。", |
| "", state, "", |
| "回答三部分(合成一个 JSON 对象, 禁止解释文字):", |
| "1. I1-I18: PAD 情感量表 18 词项, 1.00-9.00 两位小数。", |
| " P维 I1快乐-I2高兴-I3满意-I4惬意-I5希望-I6放松(9为符合,5中立,1反面);", |
| " A维 I7兴奋-I8警觉-I9刺激-I10狂热-I11活跃-I12惊慌;", |
| " D维 I13支配-I14影响-I15领导-I16重要-I17自由-I18强力。", |
| f"2. family: 主导情绪族, 只能取: {', '.join(FAMILY_IDS)}。", |
| "3. noul: 两个是非判断(true/false):", |
| ] |
| for q in NOUL_QUESTIONS: |
| lines.append(f" {q['id']}: {q['def']}") |
| lines += [ |
| "", |
| '输出格式: {"I1":..,"I18":..,"analysis":"..","family":"..",', |
| ' "noul":{"directed_at_me":true,"suppressed":false}}', |
| ] |
| return "\n".join(lines) |
|
|
|
|
| def parse_teacher_json(raw: str) -> Dict[str, Any]: |
| """teacher 输出 → {items: {I1..I18}, family: id, noul: {id: bool}}。校验+裁剪。 |
| |
| 词项分越界(如 0.0 或归一化值混入)一律钳位到 [1,9] 而非拒收——0.0 多为 |
| 模型把量表当 0-9 用(即极度负向), 钳位保信息保 echo 链连续。 |
| """ |
| text = raw.strip() |
| if text.startswith("```"): |
| text = text.strip("`").removeprefix("json").strip() |
| data = json.loads(text) |
| items = {} |
| for i in range(1, 19): |
| v = float(data[f"I{i}"]) |
| items[f"I{i}"] = max(1.0, min(9.0, v)) |
| family = data["family"] |
| if family not in FAMILY_IDS: |
| raise ValueError(f"未知情绪族: {family}") |
| noul_raw = data["noul"] |
| noul = {qid: bool(noul_raw[qid]) for qid in NOUL_IDS} |
| return {"items": items, "family": family, "noul": noul, "analysis": data.get("analysis", "")} |
|
|
|
|
| def validate_battery_gold(gold: Dict[str, Any]) -> List[str]: |
| problems: List[str] = list(pad_schema.validate_gold(gold)) |
| if gold.get("family") not in FAMILY_IDS: |
| problems.append(f"family 非法: {gold.get('family')}") |
| for qid in NOUL_IDS: |
| if not isinstance(gold.get("noul", {}).get(qid), bool): |
| problems.append(f"noul.{qid} 缺失或非布尔") |
| return problems |
|
|
|
|
| if __name__ == "__main__": |
| |
| assert N_FAMILY == 8 and N_NOUL == 2 and len(set(FAMILY_IDS)) == N_FAMILY |
| assert set(NOUL_IDS) == {"directed_at_me", "suppressed"} |
| prompt = build_teacher_prompt("TARGET message to judge:\n[them]: 哼, 随便你吧") |
| for token in ["I18", "family", "wronged", "suppressed", "directed_at_me"]: |
| assert token in prompt, token |
| parsed = parse_teacher_json(json.dumps({ |
| **{f"I{i}": 5.0 for i in range(1, 19)}, "family": "wronged", |
| "noul": {q: True for q in NOUL_IDS}})) |
| assert parsed["family"] == "wronged" and all(parsed["noul"].values()) |
| assert pad_schema.bins_to_pad(pad_schema.items_to_bins(parsed["items"]))["pleasure"] == 0.0 |
| good = {"pad_bins": pad_schema.items_to_bins({f"I{i}": 5.0 for i in range(1, 19)}), |
| "echo": [0.0] * 3, "family": "calm", |
| "noul": {q: False for q in NOUL_IDS}} |
| assert validate_battery_gold(good) == [] |
| bad = {"pad_bins": good["pad_bins"], "echo": [0.0] * 3, "family": "happy", "noul": {}} |
| assert len(validate_battery_gold(bad)) == N_NOUL |
| print("battery_digest:", battery_digest()) |
| print("题库: score×3(P/A/D×9档) + choice(8族训练+OCC-22解码) + noul×2(文本层信号)") |
| print("✓ battery 自检全部通过") |
|
|
