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

Slack Multilingual Assistant (Gemini 2.5 Flas
🔧 Three translation modes unified in one workflow:
1️⃣ /trans — Public bilingual announcements
  Format: 【from @user】 Original ---------- Translation
🔧 Create and Configure your Slack App (Trans
1️⃣ Create App
 → From scratch → Name it “TransBot” → Select your work
2️⃣ Add Bot Token Scopes in OAuth & Permissions
 • commands
 • chat
🔁 Workflow Architecture
• Webhooks:
  – /slack/trans → Slash Command
  – /slack/mention → app_mention & reaction_added even
• Language Model: Google Gemini 2.5 Flash
• Logic:
🚨 Common Errors & Fixes
❌ invalid_auth
 → Using an old token or bot not invited to channel
  Fix: Reinstall app / use latest xoxb token / `/invite
❌ missing_scope
 → A required scop
✅ Workflow is Active in n8n
✅ Slack Event Subscription Request URL shows “Verified
✅ Bot Token includes chat:write, channels:history, reac
✅ /trans Slash Command responds with “Tran
modelmodelmodel
⚡
W
Webhook (Slack /trans)
⚡
A
Ack (Respond to Slack)
Parse Slash Payload
⚡
A
Ack Mention Event
Parse Mention Event
⚡
A
Ack Reaction Event
Parse Reaction Event
Fetch Original Message
Prep Reaction Translatio…
Google Gemini Chat Model
Basic LLM Chain (/trans)
Basic LLM Chain (@trans)
Basic LLM Chain (reaction)
Format Slack Message (/t…
Format Slack Message (@t…
Format Slack Message (re…
Post to Slack (response_…
Post to Slack (@trans re…
Post to Slack (reaction …
⚡
W
Webhook (Slack @trans + …
R
Route by Event Type
S
Skip Reaction When No Me…
Filter Reaction Type
Detect Slack Event Type
24 nodes24 edges

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

下载 JSON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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