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# Build a WeChat AI Agent with nanobot
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This guide connects nanobot to WeChat through the `weixin` channel. The channel
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uses HTTP long polling with QR-code login through the supported upstream API.
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## What this guide builds
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- the `weixin` channel enabled in nanobot
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- a QR-code login session
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- one allowed WeChat sender
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- a running gateway for message delivery
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## Prerequisites
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- A working local nanobot reply:
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```bash
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nanobot agent -m "Hello!"
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```
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- A WeChat account that can complete QR-code login.
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- The sender ID from logs for `allowFrom`, or a temporary private test setup.
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## Install nanobot
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```bash
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python -m pip install nanobot-ai
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nanobot onboard --wizard
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```
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## Enable the WeChat channel
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Install the optional channel dependency:
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```bash
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nanobot plugins enable weixin
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```
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Merge this snippet into `~/.nanobot/config.json`:
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```json
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{
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"channels": {
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"weixin": {
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"enabled": true,
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"allowFrom": ["YOUR_WECHAT_USER_ID"]
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}
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}
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}
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```
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Log in:
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```bash
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nanobot channels login weixin
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```
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Use `--force` if you need to discard saved login state and authenticate again.
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## Run nanobot gateway
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```bash
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nanobot channels status
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nanobot gateway
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```
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## Test a message
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Send a private WeChat message from the allowed account and watch gateway logs for
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the sender ID and reply.
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## Security notes
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- Keep `allowFrom` narrow after you identify the sender ID.
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- Treat saved login state as sensitive account access.
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- Avoid connecting personal accounts to untrusted workspaces or broad tool
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permissions.
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## Troubleshooting
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- If login fails, rerun `nanobot channels login weixin --force`.
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- If messages arrive but are ignored, update `allowFrom` with the sender ID
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shown in logs.
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- If polling disconnects, restart the gateway and check network reachability to
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the upstream service.
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## Next: memory, automations, MCP tools
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- [Chat Apps reference](../chat-apps.md)
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- [AI Agent Memory](./ai-agent-memory.md)
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- [Secure local AI agent](./secure-local-ai-agent.md)
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- [Deployment](../deployment.md)
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