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

낮음 복잡도⚡ 트리거4개의 노드🏷️ Miscellaneous👁 4,410회 조회작성자: shepard

개요

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

사용된 노드

LangChain CodeSimple MemoryGoogle Gemini Chat Model

워크플로 미리보기

👇 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

작동 원리

  1. 1

    트리거

    워크플로는 트리거 트리거로 시작합니다.

  2. 2

    처리

    데이터가 4개의 노드를 통해 흐릅니다, connecting chattrigger, code, lmchatgooglegemini.

  3. 3

    출력

    워크플로가 자동화를 완료하고 구성된 대상에 결과를 전달합니다.

노드 세부 정보 (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

이 워크플로 가져오는 방법

  1. 1오른쪽의 JSON 다운로드 버튼을 클릭하여 워크플로 파일을 저장합니다.
  2. 2n8n 인스턴스를 열고 워크플로 → 새로 만들기 → 파일에서 가져오기로 이동합니다.
  3. 3다운로드된 build-custom-ai-agent-with-langchain-gemini-self-hosted 파일을 선택하고 가져오기를 클릭합니다.
  4. 4각 서비스 노드에 대한 자격 증명（API 키, OAuth 등）을 설정합니다.
  5. 5워크플로 테스트를 클릭하여 모든 것이 작동하는지 확인한 후 활성화합니다.

또는 n8n → JSON에서 가져오기에 직접 붙여넣기:

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

통합

chattriggercodelmchatgooglegeminimemorybufferwindow

이 워크플로 가져오기

한 번의 클릭으로 다운로드 및 가져오기

JSON 다운로드n8n.io에서 보기
노드4
복잡도low
트리거trigger
조회수4,410
카테고리Miscellaneous

제작자

shepard

shepard

@shepard

태그

chattriggercodelmchatgooglegeminimemorybufferwindow
⚡

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