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https://github.com/zhayujie/chatgpt-on-wechat.git
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feat(desktop): redirect writable data to ~/.cow for packaged app
Introduce get_data_root() driven by the COW_DATA_DIR env var so the packaged desktop build stores config.json, run.log, user data and WeChat credentials under ~/.cow — surviving app updates and keeping the app bundle read-only. Source deployments leave COW_DATA_DIR unset and fall back to the repo root, so existing behavior is unchanged.
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21
app.py
21
app.py
@@ -15,6 +15,11 @@ import threading
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_channel_mgr = None
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# Desktop mode: a lighter runtime for the packaged Electron client. The plugin
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# framework is still bundled (it's tiny and on the web channel's import path),
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# but we skip loading actual plugins and MCP tools to keep startup fast.
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DESKTOP_MODE = os.environ.get("COW_DESKTOP") == "1"
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def get_channel_manager():
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return _channel_mgr
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@@ -75,7 +80,7 @@ class ChannelManager:
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if self._primary_channel is None and channels:
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self._primary_channel = channels[0][1]
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if first_start:
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if first_start and not DESKTOP_MODE:
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PluginManager().load_plugins()
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# Cloud client is optional. It is only started when
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@@ -364,10 +369,18 @@ def run():
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_sync_builtin_skills()
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# Kick off MCP server loading in the background so first-message
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# latency isn't dominated by npx package downloads.
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_warmup_mcp_tools()
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# latency isn't dominated by npx package downloads. Skipped in desktop
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# mode (MCP relies on external npx/uvx runtimes that aren't bundled).
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if not DESKTOP_MODE:
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_warmup_mcp_tools()
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_warmup_scheduler()
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if DESKTOP_MODE:
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# Defer the (heavy) AgentBridge/scheduler warmup to a background
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# thread so the web API becomes available within a couple seconds.
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# The scheduler still starts; it just doesn't block UI readiness.
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threading.Thread(target=_warmup_scheduler, daemon=True).start()
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else:
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_warmup_scheduler()
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logger.info(f"[App] Starting channels: {channel_names}")
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