Build Custom AI Agent with LangChain & Gemini (Self-Hosted) — Workflow n8n

Faible complexité⚡ Déclencheur4 nœuds🏷️ Miscellaneous👁 4,410 vuespar shepard

Aperçu

Overview
This workflow leverages the LangChain code node to implement a fully customizable conversational agent. Ideal for users who need granular control over their agent's prompts while reducing unnecessary token consumption from reserved tool-calling functionality (compared to n8n's built-in Conversation Agent).

Setup Instructions
Configure Gemini Credentials: Set up your Google Gemini API key (Get API key here if needed). Alternatively, you may use other AI provider nodes.
Interacti

Nœuds utilisés

LangChain CodeSimple MemoryGoogle Gemini Chat Model

Aperçu du workflow

👇 Prompt Engineering
- Define agent personality and conversation structur
- ⚠️ Template must preserve `{chat_history}` and
Setup Instructions
1. Configure Gemini Credentials: Set up your Google Gem
👆 Interface Settings
Configure chat UI elements (e.g., title) in the `When C
👆 Model Selection
Swap language models through the `language model` input
👆 Memory Control
Adjust conversation history length in the `Store Conver
modelmemorymemory
⚡
W
When chat message received
Google Gemini Chat Model
Store conversation history
Construct & Execute LLM …
4 nodes4 edges

Comment ça fonctionne

  1. 1

    Déclencheur

    Le workflow démarre avec un déclencheur déclencheur.

  2. 2

    Traitement

    Les données transitent par 4 nœuds, connecting chattrigger, code, lmchatgooglegemini.

  3. 3

    Sortie

    Le workflow termine son automatisation et livre le résultat à la destination configurée.

Détails des nœuds (4)

LA

LangChain Code

n8n-nodes-langchain.code

#1
SI

Simple Memory

n8n-nodes-langchain.memoryBufferWindow

#2
GO

Google Gemini Chat Model

n8n-nodes-langchain.lmChatGoogleGemini

#3

Comment importer ce workflow

  1. 1Cliquez sur le bouton Télécharger JSON à droite pour enregistrer le fichier du workflow.
  2. 2Ouvrez votre instance n8n. Accédez à Workflows → Nouveau → Importer depuis un fichier.
  3. 3Sélectionnez le fichier build-custom-ai-agent-with-langchain-gemini-self-hosted téléchargé et cliquez sur Importer.
  4. 4Configurez les identifiants pour chaque nœud de service (clés API, OAuth, etc.).
  5. 5Cliquez sur Tester le workflow pour vérifier que tout fonctionne, puis activez-le.

Ou collez directement dans n8n → Importer depuis JSON :

{ "name": "Build Custom AI Agent with LangChain & Gemini (Self-Hosted)", "nodes": [...], ...}

Intégrations

chattriggercodelmchatgooglegeminimemorybufferwindow

Obtenir ce workflow

Téléchargez et importez en un clic

Télécharger JSONVoir sur n8n.io
Nœuds4
Complexitélow
Déclencheurtrigger
Vues4,410
CatégorieMiscellaneous

Créé par

shepard

shepard

@shepard

Tags

chattriggercodelmchatgooglegeminimemorybufferwindow
⚡

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