Automate Multilingual Slack Communication (JA ⇄ EN) with Gemini 2.5 Flash — n8n 工作流

高 复杂度🔗 Webhook24 个节点🏷️ Miscellaneous👁 2 次查看作者：Tomohiro Goto

概览

🧠 How it works
This workflow automatically translates messages between Japanese and English inside Slack — perfect for mixed-language teams.
In our real-world use case, our 8-person team includes Arif, an English-speaking teammate from Indonesia, while the rest mainly speak Japanese.

Before using this workflow, our daily chat often included:
“Can someone translate this for Arif?”
“I don’t understand what Arif wrote — can someone summarize it in Japanese?”
“I need to post this announ

使用的节点

HTTP RequestCodeBasic LLM ChainGoogle Gemini Chat Model

工作流预览

Loading workflow preview...

工作原理

  1. 1

    触发器

    工作流由 webhook 触发器启动。

  2. 2

    处理

    数据流经 24 个节点, connecting chainllm, code, httprequest。

  3. 3

    输出

    工作流完成自动化并将结果发送到配置的目标。

节点详情 (24)

HT

HTTP Request

httpRequest

#1
CO

Code

code

#2
BA

Basic LLM Chain

n8n-nodes-langchain.chainLlm

#3
GO

Google Gemini Chat Model

n8n-nodes-langchain.lmChatGoogleGemini

#4

如何导入此工作流

  1. 1点击右侧 下载 JSON 按钮保存工作流文件。
  2. 2打开你的 n8n 实例，依次点击 工作流 → 新建 → 从文件导入。
  3. 3选择下载的 automate-multilingual-slack-communication-ja-en-with-gemini-25-flash 文件并点击导入。
  4. 4为每个服务节点配置 凭证（API 密钥、OAuth 等）。
  5. 5点击 测试工作流 验证一切正常，然后激活它。

或直接在 n8n → 从 JSON 导入 中粘贴：

{ "name": "Automate Multilingual Slack Communication (JA ⇄ EN) with Gemini 2.5 Flash", "nodes": [...], ...}

集成

chainllmcodehttprequestiflmchatgooglegeminirespondtowebhookswitchwebhook

获取此工作流

一键下载并导入

在 n8n.io 上查看
节点24
复杂度high
触发器webhook
查看次数2
分类Miscellaneous

创建者

Tomohiro Goto

Tomohiro Goto

@taoo

标签

chainllmcodehttprequestiflmchatgooglegeminirespondtowebhookswitchwebhook
⚡

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