LangBot Docs
Gemini

Build a DingTalk AI Bot with Gemini

Step-by-step guide to running a Gemini-powered AI bot on DingTalk with LangBot: model setup, bot credentials, networking, testing and troubleshooting.

This recipe puts a Gemini model behind a DingTalk bot. LangBot receives messages from DingTalk, runs them through a pipeline, and sends the answer back, so you do not write any platform code.

Use Google's Gemini models with LangBot's built-in Agent, including image input when the model supports vision.

What you need

  • A running LangBot instance: LangBot Cloud (no server needed) or a self-hosted deployment with Docker or uvx langbot.
  • A Gemini account or server you can call from LangBot.
  • A DingTalk app robot (Client ID and Client Secret). The one-click setup fills both after you authorize on your phone.

Networking

In Stream Mode LangBot connects out to DingTalk, so no public callback URL is needed.

1. Add the Gemini model

  1. Create an API key in the Google Gemini console.
  2. In LangBot, open Models, add an LLM model with the provider set to Google Gemini, then paste the API key and the model ID.
  3. Enable Tool Use if the model supports function calling; MCP tools, Skills and the sandbox need it.
  4. Create the key in Google AI Studio. Enable Vision on the model if you want the bot to read images.

2. Create a pipeline

Open Pipelines in the LangBot WebUI, create a pipeline (or edit the default one) and set AI as follows.

FieldValue
RunnerLocal Agent (built-in Agent)
ModelThe model you just added. You can add fallback models.
PromptInstructions: who the bot is, tone, what it must not do.
Knowledge BasesOptional. Attach a knowledge base so answers come from your documents.

3. Create the DingTalk bot

  1. Create a bot with the DingTalk adapter and use One-Click Setup, or create the robot manually and enter its credentials.
  2. Use Stream Mode for event delivery. For streaming replies, import LangBot's dingtalk_stream_card.json card template, enable Use Card Replies and paste the Card Template ID.

4. Bind and test

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

Message the robot directly, then add it to a group and @mention it.

Troubleshooting

  • Images are ignored: enable Vision on the model and check that the platform adapter forwards images.
  • Replies arrive as plain text instead of streaming: the card template is not imported or Use Card Replies is off.
  • Messages do not arrive: publish the app version and check that Stream Mode is selected under event subscriptions.
  • 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 DingTalk?

No. In Stream Mode LangBot connects out to DingTalk, so no public callback URL is needed.

Does the DingTalk bot support streaming replies?

Yes. Enable streaming on the bot; the AI back end must also stream. See the platform feature matrix for details.

Can the same Gemini setup serve other platforms too?

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

Build a Lark (Feishu) AI Bot with Gemini

Step-by-step guide to running a Gemini-powered AI bot on Lark (Feishu) with LangBot: model setup, bot credentials, networking, testing and troubleshooting.

Build a WeCom (internal app) AI Bot with Gemini

Step-by-step guide to running a Gemini-powered AI bot on WeCom (internal app) with LangBot: model setup, bot credentials, networking, testing and troubleshooting.

On this page

What you needNetworking1. Add the Gemini model2. Create a pipeline3. Create the DingTalk bot4. Bind and testTroubleshootingFAQDo I need a server with a public IP for DingTalk?Does the DingTalk bot support streaming replies?Can the same Gemini setup serve other platforms too?Related guides