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

Hoch Komplexität🔗 Webhook24 Knoten🏷️ Miscellaneous👁 2 Aufrufevon Tomohiro Goto

Übersicht

🧠 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

Verwendete Knoten

HTTP RequestCodeBasic LLM ChainGoogle Gemini Chat Model

Workflow-Vorschau

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

So funktioniert es

  1. 1

    Auslöser

    Der Workflow startet mit einem webhook-Auslöser.

  2. 2

    Verarbeitung

    Die Daten fließen durch 24 Knoten, connecting chainllm, code, httprequest.

  3. 3

    Ausgabe

    Der Workflow schließt seine Automatisierung ab und liefert das Ergebnis an das konfigurierte Ziel.

Knotendetails (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

So importieren Sie diesen Workflow

  1. 1Klicken Sie rechts auf die Schaltfläche JSON herunterladen, um die Workflow-Datei zu speichern.
  2. 2Öffnen Sie Ihre n8n-Instanz. Gehen Sie zu Workflows → Neu → Aus Datei importieren.
  3. 3Wählen Sie die heruntergeladene Datei automate-multilingual-slack-communication-ja-en-with-gemini-25-flash und klicken Sie auf Importieren.
  4. 4Richten Sie Anmeldedaten für jeden Dienstknoten ein (API-Schlüssel, OAuth usw.).
  5. 5Klicken Sie auf Workflow testen, um zu überprüfen, ob alles funktioniert, und aktivieren Sie es dann.

Oder direkt in n8n → Aus JSON importieren einfügen:

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

Integrationen

chainllmcodehttprequestiflmchatgooglegeminirespondtowebhookswitchwebhook

Diesen Workflow holen

Herunterladen und mit einem Klick importieren

JSON herunterladenAuf n8n.io ansehen
Knoten24
Komplexitäthigh
Auslöserwebhook
Aufrufe2
KategorieMiscellaneous

Erstellt von

Tomohiro Goto

Tomohiro Goto

@taoo

Tags

chainllmcodehttprequestiflmchatgooglegeminirespondtowebhookswitchwebhook
⚡

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