WhatsApp Receipt OCR & AI Data Extraction with Twilio, LlamaParse & Gemini — n8n 워크플로

높음 복잡도🔗 Webhook35개의 노드🏷️ Invoice Processing작성자: Gabriela Macovei

개요

WhatsApp Receipt OCR & Data Extraction Suite
Categories: Accounting Automation • OCR Processing • AI Data Extraction • Business Tools

This workflow transforms WhatsApp into a fully automated receipt-processing system using advanced OCR, multi-model AI parsing, and structured data storage. By combining LlamaParse, Claude (OpenRouter), Gemini, Google Sheets, and Twilio, it eliminates manual data entry and delivers instant, reliable receipt digitization for any business.

What This Workflow Does

사용된 노드

Google SheetsHTTP RequestGoogle DriveCodeBasic LLM ChainStructured Output ParserGoogle Gemini Chat ModelOpenRouter Chat Model

워크플로 미리보기

Quick reply yes/no . SID from twilio
extracted values. no yes/no buttons
Try It Out!
This template shows how to automate the extraction of k
Send quick reply asking the user to confirm i
Contains yes / No buttons
You need to define the quick reply template inside Twil
Wait for WhatsApp to
OCR pooling mechanism using LlamaParse
Calculate tax if not specified on the receipt
modelmodelmodelparser
W
Webhook3
I
If5
W
Wait
HTTP Request28
HTTP Request29
HTTP Request17
HTTP Request18
HTTP Request30
OpenRouter Chat Model
HTTP Request5
Google Gemini Chat Model5
Upload file2
Append row in sheet2
Update row in sheet4
Update row in sheet5
HTTP Request6
Basic LLM Chain3
Structured Output Parser3
Code4
HTTP Request7
Code5
I
If
M
Merge2
M
Merge3
Share file1
HTTP Request19
S
Switch1
HTTP Request20
HTTP Request21
Update row in sheet9
Update row in sheet10
Update row in sheet11
HTTP Request22
HTTP Request24
Google Gemini Chat Model6
35 nodes37 edges

작동 원리

  1. 1

    트리거

    워크플로는 webhook 트리거로 시작합니다.

  2. 2

    처리

    데이터가 35개의 노드를 통해 흐릅니다, connecting chainllm, code, googledrive.

  3. 3

    출력

    워크플로가 자동화를 완료하고 구성된 대상에 결과를 전달합니다.

노드 세부 정보 (35)

GO

Google Sheets

googleSheets

#1
HT

HTTP Request

httpRequest

#2
GO

Google Drive

googleDrive

#3
CO

Code

code

#4
BA

Basic LLM Chain

n8n-nodes-langchain.chainLlm

#5
ST

Structured Output Parser

n8n-nodes-langchain.outputParserStructured

#6
GO

Google Gemini Chat Model

n8n-nodes-langchain.lmChatGoogleGemini

#7
OP

OpenRouter Chat Model

n8n-nodes-langchain.lmChatOpenRouter

#8

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 whatsapp-receipt-ocr-ai-data-extraction-with-twilio-llamaparse-gemini 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": "WhatsApp Receipt OCR & AI Data Extraction with Twilio, LlamaParse & Gemini", "nodes": [...], ...}

통합

chainllmcodegoogledrivegooglesheetshttprequestiflmchatgooglegeminilmchatopenroutermergeoutputparserstructuredswitchwaitwebhook

이 워크플로 가져오기

한 번의 클릭으로 다운로드 및 가져오기

JSON 다운로드n8n.io에서 보기
노드35
복잡도high
트리거webhook
카테고리Invoice Processing

제작자

Gabriela Macovei

Gabriela Macovei

@gabrielamacovei

태그

chainllmcodegoogledrivegooglesheetshttprequestiflmchatgooglegeminilmchatopenroutermergeoutputparserstructured

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🔗 Webhook·12 nodes