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-#!/usr/bin/env python3
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-"""
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-feedback_collector.py — 结构化反馈收集器
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-反馈数据写入 evolution/session_state.json 和项目数据库。
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-"""
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-
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-import sys, os, re, json
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-from pathlib import Path
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-from datetime import datetime
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-from collections import Counter
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-from typing import Any
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-
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-sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
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-from utils import (
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- find_project_root, get_evolution_dir,
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- load_evolution, save_evolution, load_project_db, save_project_db,
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- log_evolution_event,
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-)
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-
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-
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-def collect_chapter_feedback(project: Path, chapter_num: int,
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- scores: dict[str, int],
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- prompt_used: str = "",
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- issues: list[str] | None = None,
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- notes: str = "") -> dict:
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- db = load_project_db(project)
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- entry = {
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- "timestamp": datetime.now().isoformat(),
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- "chapter": chapter_num,
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- "scores": scores,
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- "composite": sum(scores.values()) / len(scores) if scores else 0,
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- "prompt_used_hash": hash(prompt_used) % 100000 if prompt_used else None,
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- "prompt_used": prompt_used[:200] if prompt_used else "",
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- "issues": issues or [],
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- "notes": notes,
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- }
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- db.setdefault("feedback", []).append(entry)
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- db.setdefault("meta", {}).setdefault("quality_scores", {})[str(chapter_num)] = entry["composite"]
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- save_project_db(project, db)
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-
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- # 更新会话状态
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- state = load_evolution("session_state.json") or {}
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- state.setdefault("recent_chapters", []).append({
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- "chapter": chapter_num,
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- "composite": entry["composite"],
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- "timestamp": entry["timestamp"],
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- })
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- # 只保留最近 20 章
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- state["recent_chapters"] = state["recent_chapters"][-20:]
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- state["total_feedback_count"] = state.get("total_feedback_count", 0) + 1
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- save_evolution("session_state.json", state)
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-
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- # 写入事件日志（Event Sourcing — git 共享无冲突）
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- if prompt_used:
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- _write_feedback_event(project, chapter_num, scores, prompt_used)
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-
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- log_evolution_event(project, "章节反馈收集", {
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- "章节": chapter_num,
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- "综合评分": f"{entry['composite']:.0f}",
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- "各维评分": ", ".join(f"{k}:{v}" for k, v in scores.items()),
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- "问题数": len(issues or []),
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- })
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- return entry
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-
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-
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-def _write_feedback_event(project: Path, chapter_num: int,
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- scores: dict[str, int],
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- prompt_used: str) -> None:
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- """将反馈写入事件日志（追加写入，天然无 git 冲突）。
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-
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- 不再直接修改 population.json —— 改为写入不可变事件文件。
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- population.json 通过 `evolve.sh --compile` 从事件编译生成。
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- """
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- from hashlib import md5 as _md5
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- from utils import (find_project_genre, map_genre_to_inkos_id,
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- load_genre_evolution)
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- from event_store import write_events
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-
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- genre_name = find_project_genre(project)
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- genre_id = map_genre_to_inkos_id(genre_name)
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-
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- # 匹配变体：从当前编译后的 population 中查找
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- pop = load_genre_evolution(genre_id, "prompts/population.json")
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- prompt_hash = _md5(prompt_used.encode()).hexdigest()[:12]
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- prompt_key = prompt_used[:40] if len(prompt_used) > 40 else prompt_used
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-
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- matched_island = "writing"
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- matched_id = prompt_hash
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-
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- if pop:
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- for cat, pop_data in pop.items():
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- for variant in pop_data.get("variants", []):
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- tmpl = variant.get("template", "")
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- if (variant.get("id") == prompt_hash
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- or (prompt_key and prompt_key in tmpl)
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- or (prompt_used and len(tmpl) >= 40 and tmpl[:40] in prompt_used)):
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- matched_island = cat
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- matched_id = variant.get("id", prompt_hash)
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- break
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- else:
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- continue
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- break
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-
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- event = {
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- "type": "feedback",
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- "chapter": chapter_num,
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- "island": matched_island,
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- "variant_id": matched_id,
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- "variant_template": prompt_used, # 携带模板文本，编译时可重建缺失变体
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- "scores": {k.upper(): v for k, v in scores.items()},
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- }
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- write_events(genre_id, [event])
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-
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-
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-def parse_user_feedback(text: str) -> dict:
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- feedback = {"sentiment": "neutral", "mentioned_dimensions": [],
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- "mentioned_chapters": [], "action_items": []}
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-
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- pos_words = ["好", "不错", "很好", "精彩", "满意", "perfect", "great"]
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- neg_words = ["差", "不好", "弱", "无聊", "平淡", "不行", "重写", "废弃"]
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- pos_count = sum(1 for w in pos_words if w in text)
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- neg_count = sum(1 for w in neg_words if w in text)
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- if pos_count > neg_count:
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- feedback["sentiment"] = "positive"
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- elif neg_count > pos_count:
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- feedback["sentiment"] = "negative"
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-
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- dim_keywords = {
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- "结构": ["结构", "节奏", "场景", "布局"],
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- "角色": ["角色", "人物", "主角", "配角", "人设"],
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- "原创性": ["套路", "新鲜", "创新", "模板"],
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- "对话": ["对话", "对白", "台词"],
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- "文本": ["文字", "措辞", "句式", "描写"],
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- "钩子": ["钩子", "悬念", "伏笔", "期待"],
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- "爽点": ["爽点", "高潮", "打脸", "爽感"],
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- "情感": ["情感", "情绪", "心理"],
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- }
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- for dim, keywords in dim_keywords.items():
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- if any(kw in text for kw in keywords):
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- feedback["mentioned_dimensions"].append(dim)
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-
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- chapter_refs = re.findall(r"第(\d+)章", text)
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- feedback["mentioned_chapters"] = [int(c) for c in chapter_refs]
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-
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- for m in re.finditer(r"(?:需要|应该|必须|要)\s*(.+?)(?:[。！，,.]|$)", text):
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- feedback["action_items"].append({"type": "required", "content": m.group(1).strip()})
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-
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- return feedback
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-
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-
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-if __name__ == "__main__":
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- import argparse
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- parser = argparse.ArgumentParser(description="反馈收集器")
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- parser.add_argument("action", choices=["collect", "parse", "state"])
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- parser.add_argument("--project", "-p", default=".")
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- parser.add_argument("--chapter", "-c", type=int)
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- parser.add_argument("--scores", "-s", type=str, default="{}")
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- parser.add_argument("--prompt", type=str, default="")
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- parser.add_argument("--issues", "-i", nargs="*", default=[])
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- parser.add_argument("--notes", "-n", type=str, default="")
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- parser.add_argument("--text", "-t", type=str, default="")
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- args = parser.parse_args()
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-
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- if args.action == "collect":
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- root = find_project_root(Path(args.project).resolve())
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- if not root:
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- print("错误: 未找到小说项目根目录")
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- sys.exit(1)
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- if not args.chapter:
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- print("错误: 需要 --chapter")
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- sys.exit(1)
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- try:
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- scores = json.loads(args.scores)
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- except json.JSONDecodeError:
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- print("错误: --scores 需要 JSON 格式")
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- sys.exit(1)
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- result = collect_chapter_feedback(root, args.chapter, scores,
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- prompt_used=args.prompt,
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- issues=args.issues, notes=args.notes)
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- print(f"✓ 章节 {args.chapter} 反馈已收集 (综合: {result['composite']:.0f})")
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-
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- elif args.action == "parse":
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- if not args.text:
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- print("错误: 需要 --text")
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- sys.exit(1)
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- result = parse_user_feedback(args.text)
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- print(json.dumps(result, ensure_ascii=False, indent=2))
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-
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- elif args.action == "state":
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- state = load_evolution("session_state.json") or {}
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- print(json.dumps(state, ensure_ascii=False, indent=2))
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