e64006bafe
A CLI tool to query local WeChat data with 11 commands: sessions, history, search, contacts, members, stats, export, favorites, unread, new-messages, and init. Features: - Self-contained init with key extraction (no external deps) - On-the-fly SQLCipher decryption with caching - JSON output by default for LLM/AI tool integration - Message type filtering and chat statistics - Markdown/txt export for conversations - Cross-platform: macOS, Windows, Linux
125 lines
4.7 KiB
Python
125 lines
4.7 KiB
Python
"""search-messages 命令"""
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import click
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from ..core.contacts import get_contact_names
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from ..core.messages import (
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MSG_TYPE_FILTERS,
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MSG_TYPE_NAMES,
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collect_chat_search,
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parse_time_range,
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resolve_chat_context,
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resolve_chat_contexts,
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search_all_messages,
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validate_pagination,
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_candidate_page_size,
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_page_ranked_entries,
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)
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from ..output.formatter import output
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@click.command("search")
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@click.argument("keyword")
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@click.option("--chat", multiple=True, help="限定聊天对象（可多次指定）")
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@click.option("--start-time", default="", help="起始时间")
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@click.option("--end-time", default="", help="结束时间")
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@click.option("--limit", default=20, help="返回数量（最大500）")
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@click.option("--offset", default=0, help="分页偏移量")
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@click.option("--format", "fmt", default="json", type=click.Choice(["json", "text"]), help="输出格式")
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@click.option("--type", "msg_type", default=None, type=click.Choice(MSG_TYPE_NAMES), help="消息类型过滤")
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@click.pass_context
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def search(ctx, keyword, chat, start_time, end_time, limit, offset, fmt, msg_type):
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"""搜索消息内容
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\b
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示例:
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wechat-cli search "Claude" # 全局搜索
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wechat-cli search "Claude" --chat "AI交流群" # 在指定群搜索
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wechat-cli search "开会" --chat "群A" --chat "群B" # 同时搜多个群
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wechat-cli search "你好" --start-time "2026-04-01" --limit 50
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"""
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app = ctx.obj
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try:
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validate_pagination(limit, offset)
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start_ts, end_ts = parse_time_range(start_time, end_time)
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except ValueError as e:
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click.echo(f"错误: {e}", err=True)
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ctx.exit(2)
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names = get_contact_names(app.cache, app.decrypted_dir)
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candidate_limit = _candidate_page_size(limit, offset)
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chat_names = list(chat)
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type_filter = MSG_TYPE_FILTERS[msg_type] if msg_type else None
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if len(chat_names) == 1:
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# 单聊搜索
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chat_ctx = resolve_chat_context(chat_names[0], app.msg_db_keys, app.cache, app.decrypted_dir)
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if not chat_ctx:
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click.echo(f"找不到聊天对象: {chat_names[0]}", err=True)
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ctx.exit(1)
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if not chat_ctx['db_path']:
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click.echo(f"找不到 {chat_ctx['display_name']} 的消息记录", err=True)
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ctx.exit(1)
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entries, failures = collect_chat_search(
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chat_ctx, names, keyword, app.display_name_fn,
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start_ts=start_ts, end_ts=end_ts, candidate_limit=candidate_limit,
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msg_type_filter=type_filter,
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)
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scope = chat_ctx['display_name']
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elif len(chat_names) > 1:
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# 多聊搜索
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resolved, unresolved, missing = resolve_chat_contexts(chat_names, app.msg_db_keys, app.cache, app.decrypted_dir)
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if not resolved:
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click.echo("错误: 没有可查询的聊天对象", err=True)
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ctx.exit(1)
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entries = []
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failures = []
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for rc in resolved:
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e, f = collect_chat_search(
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rc, names, keyword, app.display_name_fn,
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start_ts=start_ts, end_ts=end_ts, candidate_limit=candidate_limit,
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msg_type_filter=type_filter,
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)
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entries.extend(e)
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failures.extend(f)
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if unresolved:
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failures.append("未找到: " + "、".join(unresolved))
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scope = f"{len(resolved)} 个聊天对象"
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else:
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# 全局搜索
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entries, failures = search_all_messages(
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app.msg_db_keys, app.cache, names, keyword, app.display_name_fn,
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start_ts=start_ts, end_ts=end_ts, candidate_limit=candidate_limit,
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msg_type_filter=type_filter,
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)
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scope = "全部消息"
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paged = _page_ranked_entries(entries, limit, offset)
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if fmt == 'json':
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output({
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'scope': scope,
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'keyword': keyword,
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'count': len(paged),
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'offset': offset,
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'limit': limit,
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'start_time': start_time or None,
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'end_time': end_time or None,
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'type': msg_type or None,
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'results': [item[1] for item in paged],
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'failures': failures if failures else None,
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}, 'json')
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else:
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if not paged:
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output(f"在 {scope} 中未找到包含 \"{keyword}\" 的消息", 'text')
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return
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header = f"在 {scope} 中搜索 \"{keyword}\" 找到 {len(paged)} 条结果（offset={offset}, limit={limit}）"
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if start_time or end_time:
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header += f"\n时间范围: {start_time or '最早'} ~ {end_time or '最新'}"
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if failures:
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header += "\n查询失败: " + "；".join(failures)
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output(header + ":\n\n" + "\n\n".join(item[1] for item in paged), 'text')
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