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

High complexity🔗 Webhook24 nodes🏷️ Miscellaneous👁 2 viewsby Tomohiro Goto

Overview

🧠 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

Nodes used

HTTP RequestCodeBasic LLM ChainGoogle Gemini Chat Model

Workflow Preview

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

How it Works

  1. 1

    Trigger

    The workflow starts with a webhook trigger.

  2. 2

    Process

    Data flows through 24 nodes, connecting chainllm, code, httprequest.

  3. 3

    Output

    The workflow completes its automation and delivers the result to the configured destination.

Node Details (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

How to Import This Workflow

  1. 1Click Download JSON button on the right to save the workflow file.
  2. 2Open your n8n instance. Go to Workflows → New → Import from file.
  3. 3Select the downloaded automate-multilingual-slack-communication-ja-en-with-gemini-25-flash file and click Import.
  4. 4Set up credentials for each service node (API keys, OAuth, etc.).
  5. 5Click Test Workflow to verify everything works, then activate it.

Or paste directly in n8n → Import from JSON:

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

Integrations

chainllmcodehttprequestiflmchatgooglegeminirespondtowebhookswitchwebhook

Get This Workflow

Download and import in one click

Download JSONView on n8n.io
Nodes24
Complexityhigh
Triggerwebhook
Views2
CategoryMiscellaneous

Created by

Tomohiro Goto

Tomohiro Goto

@taoo

Tags

chainllmcodehttprequestiflmchatgooglegeminirespondtowebhookswitchwebhook
⚡

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