build_final_knowledge_base.py
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#!/usr/bin/env python3
"""
基于统一索引生成最终可导入的合成知识库。
新原则:
- 培训文档是主事实层,完整保留
- Figma / 测试用例是补充层
- 模块仅作为辅助索引
- 主要组织轴:feature_scope + app_version + 来源优先级
输出目录:
dist/final_kb/
"""
from __future__ import annotations
import json
import re
from collections import Counter, defaultdict
from pathlib import Path
BASE_DIR = Path(__file__).parent.parent
RAG_DIR = BASE_DIR / "dist" / "rag"
OUT_DIR = BASE_DIR / "dist" / "final_kb"
BACKEND_CODE_DIR = BASE_DIR / "dist" / "backend_code"
SOURCE_PRIORITY = {"doc_rule": 0, "definition": 0, "rule": 1, "case_rule": 2}
SOURCE_LABEL = {
"doc_rule": "培训文档",
"definition": "培训文档定义",
"rule": "Figma",
"case_rule": "测试用例",
}
MODULE_ORDER = [
"AUTH",
"INCOME",
"INQUIRY",
"CLINIC",
"PATIENT",
"NOTIFICATION",
"BACKSTAGE",
"GENERAL",
]
MODULE_NAMES = {
"AUTH": "认证",
"INCOME": "收入提现",
"INQUIRY": "问诊",
"CLINIC": "门诊",
"PATIENT": "患者",
"NOTIFICATION": "通知",
"BACKSTAGE": "后台",
"GENERAL": "通用",
}
GENERIC_RESULTS = {"满足预期", "搜索出结果", "成功", "失败", "显示成功", "显示失败", "表现正常"}
SCREENSHOT_MARKERS = ("[截图]", "[图]", "截图")
GENERIC_DOC_HEADINGS = {
"APP端",
"PC端",
"小程序端",
"后台",
"数据定义",
"关注流程",
"关注对象",
"咨询列表",
"团队患者开方",
"团队医生列表",
"团队工作室医生列表",
}
def version_key(version: str) -> tuple[int, ...]:
return tuple(int(part) for part in re.findall(r"\d+", version or ""))
def clean_text(text: str) -> str:
text = str(text or "")
return re.sub(r"\s+", " ", text).strip()
def load_jsonl(path: Path) -> list[dict]:
rows = []
with path.open("r", encoding="utf-8") as handle:
for raw_line in handle:
line = raw_line.strip()
if line:
rows.append(json.loads(line))
return rows
def load_optional_jsonl(path: Path) -> list[dict]:
if not path.exists():
return []
return load_jsonl(path)
def is_clean_supplement(atom: dict) -> bool:
atom_type = atom.get("atom_type", "")
if atom_type not in {"rule", "case_rule"}:
return False
a = clean_text(atom.get("A", ""))
r = clean_text(atom.get("R", ""))
canon = clean_text(atom.get("canon_text", ""))
if not a or not r:
return False
if any(marker in a or marker in r or marker in canon for marker in SCREENSHOT_MARKERS):
return False
if r in GENERIC_RESULTS:
return False
if "?" in a or "?" in r or "???" in a or "???" in r:
return False
if atom_type == "case_rule" and re.search(r"^\d+[,、.]", a):
return False
return True
def atom_sort_key(atom: dict) -> tuple:
return (
version_key(atom.get("app_version", "")),
SOURCE_PRIORITY.get(atom.get("atom_type", ""), 9),
atom.get("merge_fingerprint", ""),
)
def feature_sort_key(feature_scope: str) -> tuple:
return (display_feature_scope(feature_scope).lower(),)
def display_feature_scope(feature_scope: str) -> str:
scope = clean_text(feature_scope)
scope = re.sub(r"^\d{1,2}\.\d+(?=\s|[^\d])\s*", "", scope)
scope = re.sub(r"^(?:\d+(?:[..]\d+)*[、..)]\s*)+", "", scope)
scope = re.sub(r"^\d(?=[\u4e00-\u9fff])", "", scope)
scope = re.sub(r"^[::、..\s]+", "", scope)
return scope or "未归类功能"
def normalize_title_candidate(text: str) -> str:
text = display_feature_scope(text)
text = re.sub(r"^[•◦■\-]+\s*", "", text)
text = re.sub(r"^[a-zA-ZivxIVX]+[.、)]\s*", "", text)
text = re.sub(r"^\d+\s+", "", text)
text = re.sub(r"^\d(?=\s|[\u4e00-\u9fff])", "", text)
text = re.split(r"\s*(?:场景|功能设计|需求背景|背景|处理方式|设计说明|说明)[::]", text, maxsplit=1)[0]
text = re.split(r"\s{2,}", text, maxsplit=1)[0]
if len(text) > 24:
text = re.split(r"[,。,;;]", text, maxsplit=1)[0]
text = re.sub(r"[,。,;;::]\s*$", "", text)
text = clean_text(text)
return text
def is_good_title(text: str) -> bool:
text = normalize_title_candidate(text)
if not text or len(text) < 4 or len(text) > 32:
return False
if text == "未归类功能":
return False
if re.match(r"^\d", text):
return False
if re.match(r"^[•◦■\-]", text):
return False
if text in GENERIC_DOC_HEADINGS:
return False
if any(keyword in text for keyword in ["灰度", "预估时间", "仅供参考", "咨询萧峰"]):
return False
if " " in text and len(text) > 18:
return False
if any(keyword in text for keyword in ["场景", "功能设计", "需求背景", "背景"]):
return False
return True
def fallback_title_from_atoms(atoms: list[dict]) -> str:
for atom in atoms:
for raw in (atom.get("A", ""), atom.get("R", ""), atom.get("C", "")):
text = normalize_rule_phrase(raw)
if not text:
continue
candidates = [text]
if ":" in text:
candidates.append(text.split(":", 1)[0])
candidates.extend(re.split(r"[,。,;;]", text, maxsplit=2))
for candidate in candidates:
candidate = normalize_title_candidate(candidate)
if is_good_title(candidate):
return candidate
return ""
def best_doc_title(atoms: list[dict], feature_scope: str) -> str:
candidates = [normalize_title_candidate(feature_scope)]
for atom in atoms:
a = normalize_title_candidate(atom.get("A", ""))
c = normalize_title_candidate(atom.get("C", "").replace("背景:", "", 1))
if a:
candidates.append(a)
if c:
candidates.append(c)
def score(title: str) -> tuple[int, int, str]:
good = 1 if is_good_title(title) else 0
ideal_len = abs(len(title) - 10)
return (good, -ideal_len, title)
unique = []
seen = set()
for item in candidates:
if item and item not in seen:
seen.add(item)
unique.append(item)
fallback = fallback_title_from_atoms(atoms)
if fallback and fallback not in seen:
unique.append(fallback)
if not unique:
return "未归类功能"
unique.sort(key=score, reverse=True)
return unique[0]
def sample_texts(atoms: list[dict], limit: int = 2) -> list[str]:
seen = set()
result = []
for atom in sorted(atoms, key=atom_sort_key):
text = clean_text(atom.get("R") or atom.get("A") or atom.get("rule_text", ""))
if not text or text in seen:
continue
seen.add(text)
result.append(text)
if len(result) >= limit:
break
return result
def group_by_feature(atoms: list[dict]) -> dict[str, list[dict]]:
grouped: dict[str, list[dict]] = defaultdict(list)
for atom in atoms:
grouped[atom["feature_scope"]].append(atom)
return grouped
def group_doc_facts(master_atoms: list[dict]) -> dict[str, list[dict]]:
docs = [atom for atom in master_atoms if atom.get("atom_type") in {"doc_rule", "definition"}]
grouped = group_by_feature(docs)
return {feature: sorted(items, key=atom_sort_key) for feature, items in grouped.items()}
def group_supplements(master_atoms: list[dict]) -> dict[str, list[dict]]:
supplements = [atom for atom in master_atoms if is_clean_supplement(atom)]
grouped = group_by_feature(supplements)
return {feature: sorted(items, key=atom_sort_key) for feature, items in grouped.items()}
def module_counter_from_features(feature_atoms: dict[str, list[dict]]) -> Counter:
counter = Counter()
for atoms in feature_atoms.values():
modules = {mod for atom in atoms for mod in atom.get("modules", [])}
if not modules and atoms:
modules = {atoms[0].get("primary_module", "GENERAL")}
for module in modules:
counter[module] += 1
return counter
def split_doc_facts(doc_features: dict[str, list[dict]]) -> tuple[dict[str, list[dict]], dict[str, list[dict]]]:
def is_readable(atom: dict) -> bool:
scope = display_feature_scope(atom.get("feature_scope", ""))
a = clean_text(atom.get("A", ""))
r = clean_text(atom.get("R", ""))
if len(scope) <= 2:
return False
if "背景:" in r or "功能:" in r or "目标:" in r:
return False
if len(r) > 180:
return False
if a == r and len(r) <= 4:
return False
return True
primary: dict[str, list[dict]] = {}
retained: dict[str, list[dict]] = {}
for feature, atoms in doc_features.items():
title = best_doc_title(atoms, feature)
preferred = [atom for atom in atoms if atom.get("_source_file", "").endswith("doc_atoms_model.jsonl") and is_readable(atom)]
readable_rules = summarize_doc_rules(preferred, limit=4) if preferred else []
if preferred and is_good_title(title) and readable_rules:
primary[feature] = preferred
preferred_fp = {atom.get("merge_fingerprint") for atom in preferred}
extra = [atom for atom in atoms if atom.get("merge_fingerprint") not in preferred_fp]
if extra:
retained[feature] = extra
else:
retained[feature] = atoms
return primary, retained
def normalize_rule_phrase(text: str) -> str:
text = clean_text(text)
text = re.sub(r"^[a-zA-ZivxIVX]+[.、]\s*", "", text)
text = re.sub(r"^[a-zA-ZivxIVX]+[)]\s*", "", text)
text = re.sub(r"^\d+[..、,)]\s*", "", text)
text = re.sub(r"^\d+\s+", "", text)
text = re.sub(r"^\d(?=[\u4e00-\u9fff])", "", text)
text = re.split(r"\s*(?:场景|功能设计|需求背景|背景|说明)[::]", text, maxsplit=1)[0]
text = text.strip("::;;")
return text
def is_pretty_rule(line: str, title: str = "") -> bool:
line = clean_text(line)
if not line:
return False
if len(line) < 6 or len(line) > 88:
return False
if line == title:
return False
if line.startswith(("•", "◦", "-", "但是", "同时", "这样")):
return False
if any(marker in line for marker in ["•", "◦", "功能设计", "需求背景"]):
return False
if re.search(r"\b(?:i|ii|iii|iv|v|vi)\b[..)]?", line, re.IGNORECASE):
return False
if any(keyword in line for keyword in ["灰度", "预估时间", "仅供参考", "咨询萧峰"]):
return False
return True
def summarize_doc_rules(atoms: list[dict], limit: int = 12) -> list[str]:
rules = []
seen = set()
for atom in atoms:
a = normalize_rule_phrase(atom.get("A", ""))
r = normalize_rule_phrase(atom.get("R", ""))
feature = display_feature_scope(atom.get("feature_scope", ""))
if not r:
continue
if r == a or not a or a == feature:
line = r
elif len(r) <= 18 and len(a) <= 28:
line = f"{a}:{r}"
elif any(keyword in a for keyword in ["逻辑", "排序", "操作", "显示", "默认", "规则", "变化"]):
line = f"{a}:{r}"
else:
line = r
line = clean_text(line)
if len(line) < 6:
continue
if line == feature:
continue
if line in GENERIC_DOC_HEADINGS:
continue
if re.match(r"^\d", line):
continue
if any(keyword in line for keyword in ["灰度", "预估时间", "仅供参考", "咨询萧峰"]):
continue
if "背景" in line and len(line) <= 18:
continue
if not is_pretty_rule(line, feature):
continue
if not line or line in seen:
continue
seen.add(line)
rules.append(line)
if len(rules) >= limit:
break
return rules
def render_doc_atom(atom: dict) -> list[str]:
lines = []
if atom.get("atom_type") == "definition":
term = clean_text(atom.get("term", ""))
definition = clean_text(atom.get("definition", ""))
lines.append(f"- 定义:{term}")
lines.append(f"- 说明:{definition}")
else:
c = clean_text(atom.get("C", ""))
a = clean_text(atom.get("A", ""))
r = clean_text(atom.get("R", ""))
if c:
lines.append(f"- 前提:{c}")
if a:
lines.append(f"- 操作/场景:{a}")
if r:
lines.append(f"- 规则:{r}")
lines.append(f"- 版本:{atom.get('app_version', '')}")
return lines
def render_supplement_atom(atom: dict) -> list[str]:
c = clean_text(atom.get("C", ""))
a = clean_text(atom.get("A", ""))
r = clean_text(atom.get("R", ""))
lines = []
if c:
lines.append(f"- 前提:{c}")
lines.append(f"- 操作:{a}")
lines.append(f"- 结果:{r}")
lines.append(f"- 来源:{SOURCE_LABEL.get(atom.get('atom_type', ''), atom.get('atom_type', ''))} · {atom.get('app_version', '')}")
return lines
def render_manifest(doc_features: dict[str, list[dict]], supplement_features: dict[str, list[dict]]) -> str:
module_stats = module_counter_from_features(doc_features)
has_backend = (BACKEND_CODE_DIR / "code_atoms.jsonl").exists()
lines = [
"# 最终知识库导入说明",
"",
"推荐导入顺序:",
"1. `00_导入说明.md`",
"2. `01_知识库设计原则.md`",
"3. `02_培训文档主事实库.md`",
"4. `03_培训文档保留项.md`",
"5. `04_Figma与测试补充库.md`",
"6. `05_版本演进.md`",
"7. `06_需求预评审.md`",
"8. `07_模块辅助索引.md`",
"",
f"- 培训文档功能主题数:{len(doc_features)}",
f"- 补充层功能主题数:{len(supplement_features)}",
"",
"## 模块辅助索引分布",
"",
]
for module in MODULE_ORDER:
if module_stats.get(module):
lines.append(f"- {module} / {MODULE_NAMES.get(module, module)}:{module_stats[module]}")
lines.extend(
[
"",
"## 使用原则",
"",
"- 培训文档是主事实层,完整保留。",
"- Figma 和测试用例只做补充,不抢培训文档主定义权。",
"- 后台代码仓库是实现补充层,用于补接口契约、枚举状态和实现约束。",
"- 模块仅用于辅助过滤、路由和预评审提示,不作为知识主切分轴。",
]
)
if has_backend:
lines.insert(11, "9. `08_后台代码实现补充库.md`")
return "\n".join(lines) + "\n"
def render_design_principles() -> str:
return "\n".join(
[
"# 知识库设计原则",
"",
"## 主轴",
"",
"- `feature_scope`:功能主题",
"- `app_version`:版本演进",
"- `事实源优先级`:培训文档 > Figma > 测试用例",
"",
"## 事实源定位",
"",
"- 培训文档:主事实源,必须完整保留。",
"- Figma:交互细节补充源。",
"- 测试用例:行为验证与边界补充源。",
"- 后台代码:实现补充源,补接口、枚举、状态和实现边界。",
"",
"## 模块定位",
"",
"- 模块保留,但仅作为辅助索引。",
"- 非预定义模块内容不因分类问题被删除。",
"- `GENERAL` 只表示兜底归类,不表示低价值。",
]
) + "\n"
def render_primary_facts(doc_features: dict[str, list[dict]]) -> str:
lines = [
"# 培训文档主事实库",
"",
"这份文档优先采用增强后的培训文档原子组织主事实,不因为模块体系而过滤。",
"如果某些历史培训文档原子未被增强原子覆盖,会在“培训文档保留项”中继续保留。",
"",
]
for feature in sorted(doc_features.keys(), key=feature_sort_key):
atoms = doc_features[feature]
versions = sorted({atom["app_version"] for atom in atoms}, key=version_key)
modules = sorted({mod for atom in atoms for mod in atom.get("modules", []) if mod})
display_scope = best_doc_title(atoms, feature)
background = ""
for atom in atoms:
c = clean_text(atom.get("C", ""))
if c.startswith("背景:"):
background = c.replace("背景:", "", 1).strip()
break
rules = summarize_doc_rules(atoms)
lines.append(f"## {display_scope}")
lines.append("")
lines.append(f"- 涉及版本:{', '.join(versions)}")
if modules:
lines.append(f"- 模块辅助标签:{', '.join(modules)}")
if background:
lines.append(f"- 背景:{background}")
lines.append("")
lines.append("### 关键规则")
lines.append("")
for rule in rules:
lines.append(f"- {rule}")
if not rules:
lines.append("- 当前仅保留原文事实,详见培训文档保留项。")
lines.append("")
lines.append("---")
lines.append("")
return "\n".join(lines)
def render_retained_doc_facts(retained_features: dict[str, list[dict]]) -> str:
lines = [
"# 培训文档保留项",
"",
"这份文档保留历史培训文档原子中未被增强原子覆盖的内容。",
"它们不应被删除,因为培训文档是主事实源;这里只是把可读性较弱的遗留项单独存放。",
"",
]
if not retained_features:
lines.append("- 当前无额外保留项。")
lines.append("")
return "\n".join(lines)
for feature in sorted(retained_features.keys(), key=feature_sort_key):
atoms = retained_features[feature]
versions = sorted({atom["app_version"] for atom in atoms}, key=version_key)
lines.append(f"## {best_doc_title(atoms, feature)}")
lines.append("")
lines.append(f"- 涉及版本:{', '.join(versions)}")
lines.append("")
for atom in atoms:
lines.extend(render_doc_atom(atom))
lines.append("")
lines.append("---")
lines.append("")
return "\n".join(lines)
def render_supplement_facts(doc_features: dict[str, list[dict]], supplement_features: dict[str, list[dict]]) -> str:
lines = [
"# Figma 与测试补充库",
"",
"这份文档只保留较干净的 Figma / 测试用例补充信息,用于补交互细节、边界场景和培训文档缺失内容。",
"",
]
feature_names = sorted(set(doc_features.keys()) | set(supplement_features.keys()), key=feature_sort_key)
for feature in feature_names:
supp = supplement_features.get(feature, [])
if not supp:
continue
has_doc = feature in doc_features
versions = sorted({atom["app_version"] for atom in supp}, key=version_key)
modules = sorted({mod for atom in supp for mod in atom.get("modules", []) if mod})
lines.append(f"## {display_feature_scope(feature)}")
lines.append("")
lines.append(f"- 培训文档主事实:{'有' if has_doc else '无'}")
lines.append(f"- 补充来源版本:{', '.join(versions)}")
if modules:
lines.append(f"- 模块辅助标签:{', '.join(modules)}")
lines.append("")
for atom in supp[:12]:
lines.extend(render_supplement_atom(atom))
lines.append("")
lines.append("---")
lines.append("")
return "\n".join(lines)
def render_version_history(doc_features: dict[str, list[dict]], supplement_features: dict[str, list[dict]]) -> str:
lines = [
"# 版本演进",
"",
"按功能主题组织,先看培训文档主事实,再看补充层变化。",
"",
]
feature_names = sorted(set(doc_features.keys()) | set(supplement_features.keys()), key=feature_sort_key)
for feature in feature_names:
primary = doc_features.get(feature, [])
supp = supplement_features.get(feature, [])
versions = sorted({atom["app_version"] for atom in primary + supp}, key=version_key)
lines.append(f"## {display_feature_scope(feature)}")
lines.append("")
lines.append(f"- 版本范围:{', '.join(versions)}")
if primary:
lines.append(f"- 培训文档版本:{', '.join(sorted({atom['app_version'] for atom in primary}, key=version_key))}")
lines.append(f"- 培训文档样例:{';'.join(sample_texts(primary, 2)) or '无'}")
else:
lines.append("- 培训文档版本:无")
if supp:
lines.append(f"- 补充层版本:{', '.join(sorted({atom['app_version'] for atom in supp}, key=version_key))}")
lines.append(f"- 补充层样例:{';'.join(sample_texts(supp, 2)) or '无'}")
else:
lines.append("- 补充层版本:无")
lines.append("")
return "\n".join(lines)
def module_code_summary(code_atoms: list[dict], modules: list[str]) -> dict[str, list[str] | int]:
atoms = [atom for atom in code_atoms if atom.get("primary_module") in modules]
api_atoms = [atom for atom in atoms if atom.get("atom_type") == "api_contract"]
enum_atoms = [atom for atom in atoms if atom.get("atom_type") == "enum_definition"]
constraint_atoms = [atom for atom in atoms if atom.get("atom_type") == "impl_constraint"]
api_samples = []
seen_api = set()
for atom in sorted(api_atoms, key=lambda x: (x.get("route_path", ""), x.get("method_name", ""))):
text = f"{atom.get('http_method', '')} {atom.get('route_path', '')}".strip()
if text and text not in seen_api:
seen_api.add(text)
api_samples.append(text)
if len(api_samples) >= 4:
break
enum_samples = []
seen_enum = set()
for atom in sorted(enum_atoms, key=lambda x: x.get("feature_scope", "")):
text = atom.get("feature_scope", "")
if text and text not in seen_enum:
seen_enum.add(text)
enum_samples.append(text)
if len(enum_samples) >= 4:
break
constraint_samples = []
seen_constraint = set()
for atom in sorted(constraint_atoms, key=lambda x: (x.get("feature_scope", ""), x.get("rule_text", ""))):
text = atom.get("rule_text", "")
if text and text not in seen_constraint:
seen_constraint.add(text)
constraint_samples.append(text)
if len(constraint_samples) >= 4:
break
return {
"api_count": len(api_atoms),
"enum_count": len(enum_atoms),
"constraint_count": len(constraint_atoms),
"api_samples": api_samples,
"enum_samples": enum_samples,
"constraint_samples": constraint_samples,
}
def review_feature_rank(item: dict) -> tuple:
has_primary = 1 if item["primary"] else 0
has_supp = 1 if item["supp"] else 0
touchpoints = len(item["touchpoints"])
versions = len(item["versions"])
title = clean_text(item["title"])
return (-has_primary, -(has_primary + has_supp), -touchpoints, -versions, title.lower())
def render_review_playbook(
doc_features: dict[str, list[dict]],
supplement_features: dict[str, list[dict]],
backend_code_atoms: list[dict],
) -> str:
lines = [
"# 需求预评审",
"",
"新增需求时,先检查培训文档主事实,再检查 Figma 与测试用例补充层,最后结合后台代码实现补充层判断接口、状态与改造边界。",
"本页按模块聚合,只保留更适合做预评审入口的高信息密度主题。",
"",
]
module_groups: dict[str, list[dict]] = defaultdict(list)
feature_names = set(doc_features.keys()) | set(supplement_features.keys())
for feature in feature_names:
primary = doc_features.get(feature, [])
supp = supplement_features.get(feature, [])
versions = sorted({atom["app_version"] for atom in primary + supp}, key=version_key)
modules = sorted({mod for atom in primary + supp for mod in atom.get("modules", []) if mod})
touchpoints = sorted({tp for atom in primary + supp for tp in atom.get("touchpoints", []) if tp})
title = best_doc_title(primary, feature) if primary else display_feature_scope(feature)
item = {
"feature": feature,
"title": title,
"primary": primary,
"supp": supp,
"versions": versions,
"modules": modules,
"touchpoints": touchpoints,
}
target_modules = modules or ["GENERAL"]
for module in target_modules:
module_groups[module].append(item)
for module in MODULE_ORDER:
items = module_groups.get(module, [])
if not items:
continue
unique_items = []
seen = set()
for item in sorted(items, key=review_feature_rank):
if item["feature"] in seen:
continue
seen.add(item["feature"])
unique_items.append(item)
code_summary = module_code_summary(backend_code_atoms, [module]) if backend_code_atoms else None
lines.append(f"## {module} / {MODULE_NAMES.get(module, module)}")
lines.append("")
lines.append(f"- 主题数:{len(unique_items)}")
if code_summary:
lines.append(
f"- 后台实现范围:接口 {code_summary['api_count']} / 枚举 {code_summary['enum_count']} / 约束 {code_summary['constraint_count']}"
)
if code_summary["api_samples"]:
lines.append(f"- 后台接口样例:{';'.join(code_summary['api_samples'])}")
if code_summary["enum_samples"]:
lines.append(f"- 后台枚举样例:{';'.join(code_summary['enum_samples'])}")
if code_summary["constraint_samples"]:
lines.append(f"- 后台约束样例:{';'.join(code_summary['constraint_samples'])}")
lines.append("")
for item in unique_items[:18]:
lines.append(f"### {item['title']}")
lines.append("")
if item["touchpoints"]:
lines.append(f"- 触点:{', '.join(item['touchpoints'])}")
if item["versions"]:
lines.append(f"- 涉及版本:{', '.join(item['versions'])}")
lines.append(f"- 主事实样例:{';'.join(sample_texts(item['primary'], 2)) or '无'}")
lines.append(f"- 补充样例:{';'.join(sample_texts(item['supp'], 2)) or '无'}")
lines.append("")
lines.append("---")
lines.append("")
return "\n".join(lines)
def render_module_index(doc_features: dict[str, list[dict]], supplement_features: dict[str, list[dict]]) -> str:
module_features: dict[str, list[str]] = defaultdict(list)
for feature, atoms in {**doc_features, **supplement_features}.items():
modules = sorted({mod for atom in atoms for mod in atom.get("modules", []) if mod})
for module in modules or ["GENERAL"]:
module_features[module].append(feature)
lines = [
"# 模块辅助索引",
"",
"模块仅用于辅助检索和路由,不作为知识主切分维度。",
"",
]
for module in MODULE_ORDER:
features = sorted(set(module_features.get(module, [])), key=feature_sort_key)
if not features:
continue
lines.append(f"## {module} / {MODULE_NAMES.get(module, module)}")
lines.append("")
for feature in features:
primary = "有" if feature in doc_features else "无"
supplement = "有" if feature in supplement_features else "无"
lines.append(f"- {display_feature_scope(feature)} | 培训文档 {primary} | 补充层 {supplement}")
lines.append("")
return "\n".join(lines)
def render_backend_code_supplement(code_atoms: list[dict]) -> str:
lines = [
"# 后台代码实现补充库",
"",
"这份文档来自后台代码仓库,用于补接口契约、枚举状态和实现约束。",
"它不覆盖培训文档主事实,只用于回答“系统实际上怎么实现、受什么条件限制”。",
"",
]
if not code_atoms:
lines.append("- 当前未接入后台代码知识。")
lines.append("")
return "\n".join(lines)
groups: dict[str, list[dict]] = defaultdict(list)
for atom in code_atoms:
groups[atom.get("primary_module", "GENERAL")].append(atom)
for module in MODULE_ORDER:
atoms = groups.get(module, [])
if not atoms:
continue
lines.append(f"## {module} / {MODULE_NAMES.get(module, module)}")
lines.append("")
api_atoms = [a for a in atoms if a.get("atom_type") == "api_contract"][:12]
enum_atoms = [a for a in atoms if a.get("atom_type") == "enum_definition"][:10]
constraint_atoms = [a for a in atoms if a.get("atom_type") == "impl_constraint"][:12]
lines.append(f"- 接口契约数:{len([a for a in atoms if a.get('atom_type') == 'api_contract'])}")
lines.append(f"- 枚举定义数:{len([a for a in atoms if a.get('atom_type') == 'enum_definition'])}")
lines.append(f"- 实现约束数:{len([a for a in atoms if a.get('atom_type') == 'impl_constraint'])}")
lines.append("")
if api_atoms:
lines.append("### 接口契约样例")
lines.append("")
for atom in api_atoms:
lines.append(f"- {atom.get('rule_text', '')} | {atom.get('repo_relative_path', '')}")
lines.append("")
if enum_atoms:
lines.append("### 枚举样例")
lines.append("")
for atom in enum_atoms:
lines.append(f"- {atom.get('rule_text', '')} | {atom.get('repo_relative_path', '')}")
lines.append("")
if constraint_atoms:
lines.append("### 实现约束样例")
lines.append("")
for atom in constraint_atoms:
lines.append(f"- {atom.get('rule_text', '')} | {atom.get('repo_relative_path', '')}")
lines.append("")
lines.append("---")
lines.append("")
return "\n".join(lines)
def main() -> None:
master_atoms = load_jsonl(RAG_DIR / "master_atoms.jsonl")
backend_code_atoms = load_optional_jsonl(BACKEND_CODE_DIR / "code_atoms.jsonl")
all_doc_features = group_doc_facts(master_atoms)
doc_features, retained_doc_features = split_doc_facts(all_doc_features)
supplement_features = group_supplements(master_atoms)
OUT_DIR.mkdir(parents=True, exist_ok=True)
for old_file in OUT_DIR.glob("*"):
if old_file.is_file():
old_file.unlink()
(OUT_DIR / "00_导入说明.md").write_text(render_manifest(doc_features, supplement_features), encoding="utf-8")
(OUT_DIR / "01_知识库设计原则.md").write_text(render_design_principles(), encoding="utf-8")
(OUT_DIR / "02_培训文档主事实库.md").write_text(render_primary_facts(doc_features), encoding="utf-8")
(OUT_DIR / "03_培训文档保留项.md").write_text(render_retained_doc_facts(retained_doc_features), encoding="utf-8")
(OUT_DIR / "04_Figma与测试补充库.md").write_text(render_supplement_facts(doc_features, supplement_features), encoding="utf-8")
(OUT_DIR / "05_版本演进.md").write_text(render_version_history(doc_features, supplement_features), encoding="utf-8")
(OUT_DIR / "06_需求预评审.md").write_text(
render_review_playbook(doc_features, supplement_features, backend_code_atoms),
encoding="utf-8",
)
(OUT_DIR / "07_模块辅助索引.md").write_text(render_module_index(doc_features, supplement_features), encoding="utf-8")
if backend_code_atoms:
(OUT_DIR / "08_后台代码实现补充库.md").write_text(render_backend_code_supplement(backend_code_atoms), encoding="utf-8")
print(f"primary_features={len(doc_features)}")
print(f"retained_doc_features={len(retained_doc_features)}")
print(f"supplement_features={len(supplement_features)}")
print(f"backend_code_atoms={len(backend_code_atoms)}")
print(f"output={OUT_DIR.relative_to(BASE_DIR)}")
if __name__ == "__main__":
main()