Files
iov_ana/layers/playbook.py
Jeason b7a27b12bd SQLite 持久连接 — sandbox 不再每次查询开关连接,改为 __init__ 时建连、close() 时释放
Explorer 的 system prompt 明确告知 sandbox 规则 — "每条 SQL 必须包含聚合函数或 LIMIT",减少 LLM 生成违规 SQL 浪费轮次
LLM 客户端单例 — 所有组件共享一个 openai.OpenAI 实例,不再各建各的
sanitize 顺序修复 — 小样本抑制放在 float round 之前,避免被 round 干扰
quick_detect 从 O(n²) 改为 O(n) — 按列聚合一次,加去重,不再对每行重复算整列统计
历史上下文实际生效 — get_context_for 的结果现在会注入到 Explorer 的初始 prompt 里,多轮分析时 LLM 能看到之前的发现
2026-03-20 13:20:31 +08:00

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"""
Layer 1.5: 预设分析剧本
"""
import json
import os
import re
from typing import Optional
from core.config import LLM_CONFIG
from core.utils import get_llm_client, extract_json_object, extract_json_array
class Playbook:
"""一个预设分析剧本"""
def __init__(self, data: dict):
self.name = data["name"]
self.description = data["description"]
self.tags = data.get("tags", [])
self.preset_queries: list[dict] = data.get("preset_queries", [])
self.exploration_hints = data.get("exploration_hints", "")
self.placeholders = data.get("placeholders", {})
def to_summary(self) -> str:
return f"[{self.name}] {self.description} (标签: {', '.join(self.tags)})"
def render_queries(self, schema: dict) -> list[dict]:
rendered = []
for q in self.preset_queries:
sql, purpose = q["sql"], q.get("purpose", "")
for key, val in self.placeholders.items():
sql = sql.replace(f"{{{{{key}}}}}", val)
purpose = purpose.replace(f"{{{{{key}}}}}", val)
rendered.append({"sql": sql, "purpose": purpose})
return rendered
class PlaybookManager:
"""加载和匹配 Playbook"""
def __init__(self, playbook_dir: str = ""):
self.playbooks: list[Playbook] = []
self.client, self.model = get_llm_client(LLM_CONFIG)
if playbook_dir and os.path.isdir(playbook_dir):
self._load_from_dir(playbook_dir)
def _load_from_dir(self, dir_path: str):
for fname in sorted(os.listdir(dir_path)):
if not fname.endswith(".json"):
continue
try:
with open(os.path.join(dir_path, fname), "r", encoding="utf-8") as f:
data = json.load(f)
items = data if isinstance(data, list) else [data]
for item in items:
self.playbooks.append(Playbook(item))
except (json.JSONDecodeError, KeyError) as e:
print(f" ⚠️ 加载 playbook 失败 {fname}: {e}")
def add(self, playbook: Playbook):
self.playbooks.append(playbook)
def auto_generate(self, schema_text: str, save_dir: str = "") -> list[Playbook]:
"""让 LLM 根据 Schema 自动生成 Playbook"""
prompt = f"""你是一个数据分析专家。根据以下数据库 Schema生成 3-5 个预设分析剧本。
## 数据库 Schema
{schema_text}
## 输出格式(严格 JSON 数组)
```json
[
{{
"name": "剧本名称",
"description": "一句话描述",
"tags": ["关键词1", "关键词2"],
"preset_queries": [
{{"purpose": "查询目的", "sql": "SELECT ... GROUP BY ..."}}
],
"exploration_hints": "后续探索提示"
}}
]
```
## SQL 规则
- 只用 SELECT必须有聚合函数或 GROUP BY
- 禁止 SELECT *,用 ROUND 控制精度,合理 LIMIT
- 直接使用实际表名和列名"""
try:
response = self.client.chat.completions.create(
model=self.model,
messages=[
{"role": "system", "content": "你是数据分析专家。只输出 JSON不要其他内容。"},
{"role": "user", "content": prompt},
],
temperature=0.3, max_tokens=4096,
)
content = response.choices[0].message.content.strip()
playbooks_data = extract_json_array(content)
if not playbooks_data:
return []
generated = []
for i, pb_data in enumerate(playbooks_data):
pb_data.setdefault("tags", [])
pb_data.setdefault("exploration_hints", "")
pb_data.setdefault("placeholders", {})
try:
pb = Playbook(pb_data)
self.playbooks.append(pb)
generated.append(pb)
if save_dir:
os.makedirs(save_dir, exist_ok=True)
safe = re.sub(r'[^\w\u4e00-\u9fff]', '_', pb.name)[:30]
fpath = os.path.join(save_dir, f"auto_{i+1}_{safe}.json")
with open(fpath, "w", encoding="utf-8") as f:
json.dump(pb_data, f, ensure_ascii=False, indent=2)
except (KeyError, TypeError) as e:
print(f" ⚠️ 跳过无效 Playbook: {e}")
return generated
except Exception as e:
print(f" ⚠️ 自动生成 Playbook 出错: {e}")
return []
def match(self, plan: dict, schema_text: str) -> Optional[dict]:
"""用 LLM 判断当前分析计划是否匹配某个 Playbook"""
if not self.playbooks:
return None
pb_summaries = []
for i, pb in enumerate(self.playbooks):
queries_desc = "\n".join(f" - {q.get('purpose', '')}: {q['sql'][:100]}" for q in pb.preset_queries)
pb_summaries.append(f"{i+1}. {pb.to_summary()}\n 预设查询:\n{queries_desc}")
prompt = f"""判断当前分析计划是否适合使用某个预设剧本。
## 分析计划
```json
{json.dumps(plan, ensure_ascii=False, indent=2)}
```
## Schema
{schema_text}
## 可用剧本
{chr(10).join(pb_summaries)}
## 输出(严格 JSON
匹配: {{"matched": true, "playbook_index": 1, "reasoning": "原因", "placeholders": {{}}}}
不匹配: {{"matched": false, "reasoning": "原因"}}"""
try:
response = self.client.chat.completions.create(
model=self.model,
messages=[
{"role": "system", "content": "你是分析计划匹配器。"},
{"role": "user", "content": prompt},
],
temperature=0.1, max_tokens=512,
)
result = extract_json_object(response.choices[0].message.content.strip())
if not result.get("matched"):
return None
idx = result.get("playbook_index", 1) - 1
if idx < 0 or idx >= len(self.playbooks):
return None
pb = self.playbooks[idx]
pb.placeholders = {**pb.placeholders, **result.get("placeholders", {})}
return {
"matched": True, "playbook_name": pb.name,
"reasoning": result.get("reasoning", ""),
"preset_queries": pb.render_queries({}),
"exploration_hints": pb.exploration_hints,
}
except Exception as e:
print(f" ⚠️ Playbook 匹配出错: {e}")
return None