feat: 新增语音 MCP 工具 + macOS 密钥提取修复 (#53)
* feat: 新增语音 MCP 工具 + macOS 密钥提取修复 - 新增 get_voice_messages / decode_voice / transcribe_voice MCP 工具 - 语音数据存储在 media_0.db VoiceInfo 表（SILK v3 格式） - decode_voice 解码为 WAV 文件（saved to decoded_voices/） - transcribe_voice 通过 Whisper 自动识别语言转录 - 新增 get_chat_history oldest_first 参数，支持从最早消息开始分页 - 修复 macOS 下 check_wechat_running / ensure_keys 逻辑 - 改用 pgrep 检测微信进程，绕过不支持 macOS 的 Python 扫描器 - 无 all_keys.json 时打印清晰引导，提示运行 C 版扫描器 - 新增 Makefile（build / keys / decrypt / web 快捷命令） - .gitignore 补充 find_all_keys_macos 二进制和 decoded_voices/ * fix: 语音查询支持多分片 media DB + 文件名唯一化 解决 PR #53 review 的阻塞项 #1，顺手修 #3、#6。 #1 `_get_media_db_path()` 硬编码 `media_0.db` - 新增模块级 `MEDIA_DB_KEYS`，镜像 `MSG_DB_KEYS` 的分片发现逻辑 - `_fetch_voice_row` 遍历所有分片，按 `(chat_name_id, local_id)` 首个命中即返回；单条语音在 media DB 家族内唯一，命中即可停 - `get_voice_messages` 从每个分片各取 `LIMIT limit`，合并排序后 截断到 `limit`。选择"每分片取 limit 条再合并"而非"按 max(create_time) 排序后逐个取到 limit 即停止"：后者假设分片 间时间不重叠，一旦 WeChat 改分片策略就会静默丢消息；前者工作 量 O(N 分片 × limit)，在任何分片布局下都正确 #3 输出文件名冲突 - `_silk_to_wav` 增加 `local_id` 参数，输出 `{user}_{time}_{lid}.wav`， 同一秒内两条语音不会互相覆盖；两个调用方都已在作用域内持有 `local_id` #6 `_fetch_voice_row` 的 `local_id=None` 死分支 - 随 #1 的重写一并删除，`local_id` 改为必填位置参数 Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * refactor: macOS 密钥提取分层下沉到 find_all_keys.py 解决 PR #53 review 的阻塞项 #2。 review 里提到"跟 PR #51 冲突"实测不存在 —— PR #51 当前 0 文件改动 （fork 分支已与上游同步），但架构建议本身是对的：macOS 处理应集中 在 `find_all_keys.py`，而不是在 `main.py` 提前 return 截胡。 - `main.py:ensure_keys()` 移除 darwin 专属提前返回分支，macOS 走 和其他平台相同的 `extract_keys()` 路径 - `find_all_keys.py:_load_impl()` 在 darwin 分支抛出带 `sudo ./find_all_keys_macos` 操作指引的 RuntimeError；非 macOS 的平台兜底分支保留 - `main.py` 里已有 `except RuntimeError` 会打印并 `sys.exit(1)`， 用户可见行为不变 未来若有 PR 在 `find_all_keys.py` 加 macOS 自动编译 / dispatch， 直接替换这段 RuntimeError 即可，不再需要改 `main.py`。 Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * chore: Makefile 支持 PYTHON 变量覆盖 解决 PR #53 review 的非阻塞项 #7。 原 Makefile 硬编码 `.venv/bin/python3`，没有 venv 的用户跑 `make decrypt` 直接报错。引入 `PYTHON ?= .venv/bin/python3`：默认行为 不变（仍走 venv），想用系统 Python 的用户 `PYTHON=python3 make decrypt` 即可。 Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * docs: 回应 PR #53 review #4 — 澄清 silk-python 与 pysilk 包名关系 验证：本项目 import 的 `pysilk` 实际由 `pip install silk-python` (synodriver/pysilk) 提供；pypi 上另有同名 `pysilk==0.0.1` 是无内容 的占位包，不可用。错误消息里 `pip install silk-python` 已经是对的， 但 reader 看到 `import pysilk` 仍会困惑，所以： - `_silk_to_wav` 的 import 处加一行注释，点名所用的是 synodriver 版本，并提醒 pypi 上还有 pilk / pysilk 两个同类包 - `decode_voice` / `transcribe_voice` 的 docstring 加 "依赖:" 行， 明确 "pip install silk-python (import 名为 pysilk)"，MCP 客户端 读 tool 描述就能看到正确的安装命令 未新增 requirements.txt 条目：voice 支持是可选功能（tool 内 try/except ImportError 懒加载），保持非必需依赖的语义。 Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>
This commit is contained in:
btc-z
4
.gitignore
vendored
4
.gitignore
vendored
@@ -23,3 +23,7 @@ __pycache__/
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# OS
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.DS_Store
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Thumbs.db
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# Compiled binaries and output
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find_all_keys_macos
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decoded_voices/
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16
Makefile
Normal file
16
Makefile
Normal file
@@ -0,0 +1,16 @@
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.PHONY: keys decrypt web build
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PYTHON ?= .venv/bin/python3
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build:
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cc -O2 -o find_all_keys_macos find_all_keys_macos.c -framework Foundation
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codesign -s - find_all_keys_macos
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keys:
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sudo ./find_all_keys_macos
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decrypt:
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$(PYTHON) main.py decrypt
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web:
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$(PYTHON) main.py
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@@ -12,9 +12,16 @@ def _load_impl():
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if system == "linux":
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import find_all_keys_linux as impl
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return impl
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if system == "darwin":
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raise RuntimeError(
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f"当前平台暂不支持通过 find_all_keys.py 提取密钥: {platform.system()}\n"
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f"macOS 请使用 find_all_keys_macos.c (C 版扫描器)"
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"macOS 请先运行 C 版扫描器提取密钥：\n"
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"\n"
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" sudo ./find_all_keys_macos\n"
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"\n"
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" 完成后再运行 python main.py decrypt"
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)
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raise RuntimeError(
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f"当前平台暂不支持通过 find_all_keys.py 提取密钥: {platform.system()}"
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)
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4
main.py
4
main.py
@@ -6,7 +6,9 @@ python main.py decrypt # 提取密钥 + 解密全部数据库
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"""
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import json
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import os
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import platform
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import sys
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import subprocess
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import functools
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print = functools.partial(print, flush=True)
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@@ -16,6 +18,8 @@ from key_utils import strip_key_metadata
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def check_wechat_running():
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"""检查微信是否在运行，返回 True/False"""
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if platform.system().lower() == "darwin":
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return subprocess.run(["pgrep", "-x", "WeChat"], capture_output=True).returncode == 0
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from find_all_keys import get_pids
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try:
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get_pids()
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222
mcp_server.py
222
mcp_server.py
@@ -5,7 +5,9 @@ Based on FastMCP (stdio transport), reuses existing decryption.
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Runs on Windows Python (needs access to D:\ WeChat databases).
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"""
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import io
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import os, sys, json, time, sqlite3, tempfile, struct, hashlib, atexit, re
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import wave
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import hmac as hmac_mod
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from contextlib import closing
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from datetime import datetime
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@@ -803,18 +805,19 @@ def _build_message_filters(start_ts=None, end_ts=None, keyword=''):
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return clauses, params
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def _query_messages(conn, table_name, start_ts=None, end_ts=None, keyword='', limit=20, offset=0):
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def _query_messages(conn, table_name, start_ts=None, end_ts=None, keyword='', limit=20, offset=0, oldest_first=False):
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if not _is_safe_msg_table_name(table_name):
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raise ValueError(f'非法消息表名: {table_name}')
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clauses, params = _build_message_filters(start_ts, end_ts, keyword)
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where_sql = f"WHERE {' AND '.join(clauses)}" if clauses else ''
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order = 'ASC' if oldest_first else 'DESC'
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sql = f"""
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SELECT local_id, local_type, create_time, real_sender_id, message_content,
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WCDB_CT_message_content
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FROM [{table_name}]
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{where_sql}
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ORDER BY create_time DESC
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ORDER BY create_time {order}
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"""
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if limit is None:
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return conn.execute(sql, params).fetchall()
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@@ -994,14 +997,14 @@ def _history_query_batch_size(candidate_limit):
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return min(candidate_limit, _HISTORY_QUERY_BATCH_SIZE)
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def _page_ranked_entries(entries, limit, offset):
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ordered = sorted(entries, key=lambda item: item[0], reverse=True)
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def _page_ranked_entries(entries, limit, offset, oldest_first=False):
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ordered = sorted(entries, key=lambda item: item[0], reverse=not oldest_first)
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paged = ordered[offset:offset + limit]
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paged.sort(key=lambda item: item[0])
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return paged
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def _collect_chat_history_lines(ctx, names, start_ts=None, end_ts=None, limit=20, offset=0):
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def _collect_chat_history_lines(ctx, names, start_ts=None, end_ts=None, limit=20, offset=0, oldest_first=False):
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collected = []
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failures = []
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candidate_limit = _candidate_page_size(limit, offset)
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@@ -1022,6 +1025,7 @@ def _collect_chat_history_lines(ctx, names, start_ts=None, end_ts=None, limit=20
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end_ts=end_ts,
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limit=batch_size,
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offset=fetch_offset,
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oldest_first=oldest_first,
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)
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if not rows:
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break
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@@ -1042,7 +1046,7 @@ def _collect_chat_history_lines(ctx, names, start_ts=None, end_ts=None, limit=20
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except Exception as e:
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failures.append(f"{table_ctx['db_path']}: {e}")
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paged = _page_ranked_entries(collected, limit, offset)
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paged = _page_ranked_entries(collected, limit, offset, oldest_first=oldest_first)
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return [line for _, line in paged], failures
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@@ -1348,7 +1352,7 @@ def get_recent_sessions(limit: int = 20) -> str:
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@mcp.tool()
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def get_chat_history(chat_name: str, limit: int = 50, offset: int = 0, start_time: str = "", end_time: str = "") -> str:
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def get_chat_history(chat_name: str, limit: int = 50, offset: int = 0, start_time: str = "", end_time: str = "", oldest_first: bool = False) -> str:
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"""获取指定聊天的消息记录。
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Args:
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@@ -1357,6 +1361,7 @@ def get_chat_history(chat_name: str, limit: int = 50, offset: int = 0, start_tim
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offset: 分页偏移量，默认0
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start_time: 起始时间，支持 YYYY-MM-DD / YYYY-MM-DD HH:MM / YYYY-MM-DD HH:MM:SS
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end_time: 结束时间，支持 YYYY-MM-DD / YYYY-MM-DD HH:MM / YYYY-MM-DD HH:MM:SS
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oldest_first: 为 True 时返回最早的消息（默认 False 返回最新消息）
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"""
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try:
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_validate_pagination(limit, offset, limit_max=None)
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@@ -1378,6 +1383,7 @@ def get_chat_history(chat_name: str, limit: int = 50, offset: int = 0, start_tim
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end_ts=end_ts,
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limit=limit,
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offset=offset,
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oldest_first=oldest_first,
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)
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if not lines:
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@@ -1734,5 +1740,207 @@ def get_chat_images(chat_name: str, limit: int = 20) -> str:
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return f"{display_name} 的 {len(lines)} 张图片:\n\n" + "\n".join(lines)
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# ============ 语音解密 ============
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DECODED_VOICE_DIR = os.path.join(SCRIPT_DIR, "decoded_voices")
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# media DB 与 message DB 同样会分片（media_0.db、media_1.db…），
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# 每个分片各有独立的 Name2Id / VoiceInfo 表。
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MEDIA_DB_KEYS = sorted([
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k for k in ALL_KEYS
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if any(v.startswith("message/") for v in key_path_variants(k))
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and any(re.search(r"media_\d+\.db$", v) for v in key_path_variants(k))
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])
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def _iter_media_db_paths():
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for rel_key in MEDIA_DB_KEYS:
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path = _cache.get(rel_key)
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if path:
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yield path
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def _get_chat_name_id(conn, username):
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row = conn.execute(
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"SELECT rowid FROM Name2Id WHERE user_name = ?", (username,)
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).fetchone()
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return row[0] if row else None
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def _fetch_voice_row(username, local_id):
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"""遍历所有 media DB 分片，返回 (voice_data, create_time)；找不到返回 None。"""
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for media_db in _iter_media_db_paths():
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with closing(sqlite3.connect(media_db)) as conn:
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chat_name_id = _get_chat_name_id(conn, username)
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if chat_name_id is None:
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continue
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row = conn.execute(
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"SELECT voice_data, create_time FROM VoiceInfo "
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"WHERE chat_name_id = ? AND local_id = ?",
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(chat_name_id, local_id),
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).fetchone()
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if row:
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return row
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return None
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def _silk_to_wav(voice_data, create_time, username, local_id):
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"""Decode SILK voice blob to WAV file, return output path."""
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# pypi 上有多个 SILK 相关包名（silk-python / pysilk / pilk），
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# 这里用的是 synodriver/pysilk —— 安装包名 silk-python，import 名 pysilk
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import pysilk
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data = bytes(voice_data)
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silk_data = data[1:] if data[0] == 0x02 else data
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os.makedirs(DECODED_VOICE_DIR, exist_ok=True)
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time_str = datetime.fromtimestamp(create_time).strftime('%Y%m%d_%H%M%S')
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out_path = os.path.join(DECODED_VOICE_DIR, f"{username}_{time_str}_{local_id}.wav")
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inp = io.BytesIO(silk_data)
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out = io.BytesIO()
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pysilk.decode(inp, out, 24000)
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pcm = out.getvalue()
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with wave.open(out_path, 'wb') as wf:
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wf.setnchannels(1)
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wf.setsampwidth(2)
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wf.setframerate(24000)
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wf.writeframes(pcm)
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return out_path, len(pcm)
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@mcp.tool()
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def get_voice_messages(chat_name: str, limit: int = 20) -> str:
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"""列出某个聊天中的语音消息。
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返回语音的时间、local_id 和大小，可配合 decode_voice 工具解码。
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Args:
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chat_name: 聊天对象的名字、备注名或wxid
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limit: 返回数量，默认20
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"""
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username = resolve_username(chat_name)
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if not username:
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return f"找不到聊天对象: {chat_name}"
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names = get_contact_names()
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display_name = names.get(username, username)
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if not MEDIA_DB_KEYS:
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return "找不到 media DB"
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# 从每个分片各取最多 limit 条后合并再截断：分片若有时间重叠也不会漏最新消息
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rows = []
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for media_db in _iter_media_db_paths():
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with closing(sqlite3.connect(media_db)) as conn:
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chat_name_id = _get_chat_name_id(conn, username)
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if chat_name_id is None:
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continue
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rows.extend(conn.execute(
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"SELECT local_id, create_time, length(voice_data) FROM VoiceInfo "
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"WHERE chat_name_id = ? ORDER BY create_time DESC LIMIT ?",
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(chat_name_id, limit),
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).fetchall())
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if not rows:
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return f"{display_name} 无语音消息"
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rows.sort(key=lambda r: r[1], reverse=True)
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rows = rows[:limit]
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lines = []
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for local_id, create_time, size in rows:
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time_str = datetime.fromtimestamp(create_time).strftime('%Y-%m-%d %H:%M')
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lines.append(f"[{time_str}] local_id={local_id} {size/1024:.0f}KB")
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return f"{display_name} 的 {len(lines)} 条语音消息:\n\n" + "\n".join(lines)
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@mcp.tool()
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def decode_voice(chat_name: str, local_id: int) -> str:
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"""解码微信语音消息为 WAV 文件。
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先用 get_voice_messages 获取 local_id，再用此工具解码。
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输出文件保存在 decoded_voices/ 目录。
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依赖: pip install silk-python (import 名为 pysilk)
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Args:
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chat_name: 聊天对象的名字、备注名或wxid
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local_id: 语音消息的 local_id（从 get_voice_messages 获取）
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"""
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try:
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import pysilk # noqa: F401
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except ImportError:
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return "缺少依赖: pip install silk-python"
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username = resolve_username(chat_name)
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if not username:
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return f"找不到聊天对象: {chat_name}"
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row = _fetch_voice_row(username, local_id)
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if row is None:
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return f"找不到 local_id={local_id} 的语音消息"
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voice_data, create_time = row
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out_path, pcm_len = _silk_to_wav(voice_data, create_time, username, local_id)
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duration_s = pcm_len / (24000 * 2)
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return (
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f"解码成功!\n"
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f" 文件: {out_path}\n"
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f" 时长: {duration_s:.1f}秒\n"
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f" 大小: {os.path.getsize(out_path):,} bytes"
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)
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_whisper_model = None
|
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|
||||
def _get_whisper_model(model_size="base"):
|
||||
global _whisper_model
|
||||
if _whisper_model is None:
|
||||
import whisper
|
||||
_whisper_model = whisper.load_model(model_size)
|
||||
return _whisper_model
|
||||
|
||||
|
||||
@mcp.tool()
|
||||
def transcribe_voice(chat_name: str, local_id: int) -> str:
|
||||
"""将微信语音消息转录为文字（自动检测语言，保留原语言）。
|
||||
|
||||
会先解码 SILK 语音为 WAV，再用 Whisper 转录。
|
||||
首次运行会下载 Whisper 模型（约 145MB）。
|
||||
|
||||
依赖: pip install silk-python openai-whisper (silk-python 的 import 名为 pysilk)
|
||||
|
||||
Args:
|
||||
chat_name: 聊天对象的名字、备注名或wxid
|
||||
local_id: 语音消息的 local_id（从 get_voice_messages 获取）
|
||||
"""
|
||||
try:
|
||||
import whisper # noqa: F401
|
||||
except ImportError:
|
||||
return "缺少依赖: pip install openai-whisper"
|
||||
try:
|
||||
import pysilk # noqa: F401
|
||||
except ImportError:
|
||||
return "缺少依赖: pip install silk-python"
|
||||
|
||||
username = resolve_username(chat_name)
|
||||
if not username:
|
||||
return f"找不到聊天对象: {chat_name}"
|
||||
|
||||
row = _fetch_voice_row(username, local_id)
|
||||
if row is None:
|
||||
return f"找不到 local_id={local_id} 的语音消息"
|
||||
|
||||
voice_data, create_time = row
|
||||
wav_path, _ = _silk_to_wav(voice_data, create_time, username, local_id)
|
||||
|
||||
model = _get_whisper_model()
|
||||
result = model.transcribe(wav_path)
|
||||
lang = result.get("language", "unknown")
|
||||
text = result.get("text", "").strip()
|
||||
|
||||
time_label = datetime.fromtimestamp(create_time).strftime('%Y-%m-%d %H:%M')
|
||||
return f"[{time_label}] ({lang})\n{text}"
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
mcp.run()
|
||||
|
||||
Reference in New Issue
Block a user