openClaw_agent_dm/skills/mem0-integration/local_search.py

#!/usr/bin/env python3
"""
Layer 3 本地搜索 — Layer 4 (Qdrant) 不可达时的 fallback
基于 SQLite FTS5 全文检索，零额外内存开销。

用法:
    from local_search import LocalSearchFallback
    fb = LocalSearchFallback(agent_id='main')
    fb.rebuild_index()                       # 重建索引（启动或 MEMORY.md 变更时）
    results = fb.search("Qdrant 配置")       # 搜索
"""

import sqlite3
import logging
from pathlib import Path
from typing import List, Dict

logger = logging.getLogger(__name__)

WORKSPACE_ROOT = Path('/root/.openclaw/workspace')

AGENT_MEMORY_PATHS = {
    'main': [
        WORKSPACE_ROOT / 'MEMORY.md',
        WORKSPACE_ROOT / 'memory',
    ],
    'life': [
        WORKSPACE_ROOT / 'agents' / 'life-workspace' / 'MEMORY.md',
        WORKSPACE_ROOT / 'agents' / 'life-workspace' / 'memory',
    ],
}

SHARED_PATHS = [
    WORKSPACE_ROOT / 'CORE_INDEX.md',
    WORKSPACE_ROOT / 'IDENTITY.md',
    WORKSPACE_ROOT / 'SOUL.md',
]


def _is_cjk(ch: str) -> bool:
    cp = ord(ch)
    return (0x4E00 <= cp <= 0x9FFF
            or 0x3400 <= cp <= 0x4DBF
            or 0xF900 <= cp <= 0xFAFF)


def _tokenize_chinese(text: str) -> str:
    """简易中文分词：CJK 字符逐字拆分 + ASCII 单词保持完整，过滤标点"""
    tokens = []
    buf = []
    for ch in text:
        if ch.isascii() and ch.isalnum():
            buf.append(ch)
        else:
            if buf:
                tokens.append(''.join(buf))
                buf = []
            if _is_cjk(ch):
                tokens.append(ch)
    if buf:
        tokens.append(''.join(buf))
    return ' '.join(tokens)


class LocalSearchFallback:
    """基于 SQLite FTS5 的本地全文检索"""

    def __init__(self, agent_id: str = 'main', db_path: str = None):
        self.agent_id = agent_id
        if db_path is None:
            cache_dir = Path(f'/root/.openclaw/agents/{agent_id}/qmd/xdg-cache/qmd')
            cache_dir.mkdir(parents=True, exist_ok=True)
            db_path = str(cache_dir / 'fts5_index.sqlite')
        self.db_path = db_path
        self._init_db()

    def _init_db(self):
        conn = sqlite3.connect(self.db_path)
        conn.execute('''
            CREATE VIRTUAL TABLE IF NOT EXISTS memory_fts
            USING fts5(
                title,
                content,
                source_path,
                agent_id UNINDEXED,
                tokenize='unicode61'
            )
        ''')
        conn.commit()
        conn.close()

    def rebuild_index(self):
        """重建 FTS5 索引，扫描 agent 相关的所有 memory 文件"""
        conn = sqlite3.connect(self.db_path)
        conn.execute('DELETE FROM memory_fts')

        paths = list(SHARED_PATHS)
        agent_paths = AGENT_MEMORY_PATHS.get(self.agent_id, [])
        for p in agent_paths:
            if p.is_file():
                paths.append(p)
            elif p.is_dir():
                paths.extend(p.rglob('*.md'))

        indexed = 0
        for filepath in paths:
            if not filepath.exists():
                continue
            try:
                text = filepath.read_text(encoding='utf-8')
                title = filepath.stem
                tokenized = _tokenize_chinese(text)
                conn.execute(
                    'INSERT INTO memory_fts(title, content, source_path, agent_id) VALUES (?, ?, ?, ?)',
                    (title, tokenized, str(filepath), self.agent_id)
                )
                indexed += 1
            except Exception as e:
                logger.debug(f"索引文件失败 {filepath}: {e}")

        conn.commit()
        conn.close()
        logger.info(f"FTS5 索引重建完成: {indexed} 个文件 (agent={self.agent_id})")
        return indexed

    def search(self, query: str, top_k: int = 5) -> List[Dict]:
        """全文检索"""
        tokenized_query = _tokenize_chinese(query)

        conn = sqlite3.connect(self.db_path)
        try:
            cursor = conn.execute(
                '''SELECT title, snippet(memory_fts, 1, '>>>', '<<<', '...', 64) as snippet,
                          source_path, rank
                   FROM memory_fts
                   WHERE memory_fts MATCH ?
                   ORDER BY rank
                   LIMIT ?''',
                (tokenized_query, top_k)
            )
            results = []
            for row in cursor:
                results.append({
                    'title': row[0],
                    'snippet': row[1],
                    'source': row[2],
                    'score': -row[3],
                })
            return results
        except Exception as e:
            logger.debug(f"FTS5 检索失败: {e}")
            return []
        finally:
            conn.close()

    def get_stats(self) -> Dict:
        conn = sqlite3.connect(self.db_path)
        try:
            row = conn.execute('SELECT COUNT(*) FROM memory_fts').fetchone()
            return {'indexed_documents': row[0] if row else 0, 'db_path': self.db_path}
        finally:
            conn.close()


if __name__ == '__main__':
    import sys
    agent = sys.argv[1] if len(sys.argv) > 1 else 'main'
    fb = LocalSearchFallback(agent_id=agent)
    count = fb.rebuild_index()
    print(f"Indexed {count} files for agent '{agent}'")

    if len(sys.argv) > 2:
        query = ' '.join(sys.argv[2:])
        results = fb.search(query)
        for r in results:
            print(f"  [{r['score']:.2f}] {r['title']}: {r['snippet'][:100]}")