# Connect Langflow to WeCom Customer Service

Source: https://langbot.app/docs/en/recipes/langflow/wecomcs

Step-by-step guide to running your Langflow app as a WeCom Customer Service bot with LangBot: Langflow setup, bot credentials, networking, testing and troubleshooting.

This recipe puts your Langflow app behind a WeCom Customer Service bot. LangBot receives messages from WeCom Customer Service, runs them through a pipeline, and sends the answer back, so you do not write any platform code.

Langflow builds agents and flows with a drag-and-drop editor. LangBot runs a flow through the Langflow API for every message.

## What you need

- A running LangBot instance: [LangBot Cloud](https://space.langbot.app/cloud) (no server needed) or a [self-hosted deployment](https://langbot.app/docs/en/deploy/langbot/docker.md) with Docker or `uvx langbot`.
- A Langflow account or instance that LangBot can reach over the network.
- WeCom Customer Service (WeChat Kefu) with API access: **Corporate ID**, **Secret**, and a callback **Token** and **EncodingAESKey**.

## Networking

Customer Service delivers events to a callback URL, so LangBot needs a public HTTPS address. LangBot Cloud includes one.

## 1. Prepare Langflow

1. Build a flow in Langflow (the Simple Agent template is a good start).
2. Create an API key under **Settings**.
3. Copy the **Flow ID** from **Share → API access**.

## 2. Create a pipeline

Open **Pipelines** in the LangBot WebUI, create a pipeline (or edit the default one) and set **AI** as follows. If the runner is not listed, install the official runner plugin from **Plugins** or the [LangBot Space marketplace](https://space.langbot.app/market).

| Field    | Value                                                |
| -------- | ---------------------------------------------------- |
| Runner   | **Langflow** (official Langflow Agent runner plugin) |
| Base URL | Your Langflow address, reachable from LangBot        |
| API Key  | The Langflow API key                                 |
| Flow ID  | The flow to run                                      |

## 3. Create the WeCom Customer Service bot

1. In WeCom Customer Service **Developer Settings**, generate the Token and EncodingAESKey and enter them with the Corporate ID in a bot using the **WeCom Customer Service** adapter.
2. Enable the bot, paste its webhook callback URL into the admin console, then fill in the Secret and restart the bot. Generate the customer service link or QR code users will open.

## 4. Bind and test

Open the bot, select the pipeline you created, save and make sure the bot is enabled.

Open the customer service link or scan the QR code in WeChat and send a message.

## Troubleshooting

- Connection refused: `http://localhost:7860` only works when Langflow runs on the same host and network namespace as LangBot.
- Welcome messages can only be sent when WeChat supplies a `welcome_code`, and only once before it expires.
- Check **Monitoring** in the WebUI: every message, pipeline run and error is recorded there.

## FAQ

### Do I need a server with a public IP for WeCom Customer Service?

Yes, or use LangBot Cloud. Customer Service delivers events to a callback URL, so LangBot needs a public HTTPS address. LangBot Cloud includes one.

### Does the WeCom Customer Service bot support streaming replies?

Check the [platform feature matrix](https://langbot.app/docs/en/insight/platform-features.md) for what this platform supports. Replies are delivered once the AI back end has finished.

### Can the same Langflow setup serve other platforms too?

Yes. A pipeline can be bound to many bots, so one configuration can answer on several platforms at once.

## Related guides

- [Full WeCom Customer Service setup guide](https://langbot.app/docs/en/usage/platforms/wecom/wecomcs.md)
- [Full Langflow runner guide](https://langbot.app/docs/en/usage/pipelines/langflow.md)
- Other AI back ends on WeCom Customer Service: [Dify](https://langbot.app/docs/en/recipes/dify/wecomcs.md) · [n8n](https://langbot.app/docs/en/recipes/n8n/wecomcs.md) · [Coze](https://langbot.app/docs/en/recipes/coze/wecomcs.md) · [DeepSeek](https://langbot.app/docs/en/recipes/deepseek/wecomcs.md) · [OpenAI (ChatGPT models)](https://langbot.app/docs/en/recipes/openai/wecomcs.md)
- Langflow on other platforms: [Telegram](https://langbot.app/docs/en/recipes/langflow/telegram.md) · [Discord](https://langbot.app/docs/en/recipes/langflow/discord.md) · [Slack](https://langbot.app/docs/en/recipes/langflow/slack.md) · [Lark (Feishu)](https://langbot.app/docs/en/recipes/langflow/lark.md) · [DingTalk](https://langbot.app/docs/en/recipes/langflow/dingtalk.md) · [WeCom (internal app)](https://langbot.app/docs/en/recipes/langflow/wecom.md)