Extract Details from Receipts via Telegram with Tesseract and Llama — n8n Workflow

Medium complexity⚡ Trigger13 nodes🏷️ Invoice Processing👁 1,165 viewsby Khairul Muhtadin

Overview

Tesseract - Money Mate Workflow Description

Disclaimer: This template requires the n8n-nodes-tesseractjs community node, which is only available on self-hosted n8n instances. You’ll need a self-hosted n8n setup to use this workflow.

Who is this for? This workflow is designed for individuals, freelancers, or small business owners who want an easy way to track expenses using Telegram. It’s ideal for anyone looking to digitize receipts—whether from photos or text messages—using free tools, withou

Nodes used

HTTP RequestTelegramCodeBasic LLM ChainStructured Output ParserOpenRouter Chat Model

Workflow Preview

📲 Telegram Trigger
Receives user messages (text or photo) from Telegram to
🔍 Check for Image
Determines whether the input is an image or text to rou
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📬 Send Expense Summary
Sends a summary of the recognized receipt or input to t
📝 Extract Text Input
Handles plain text inputs when no image is provided by
📊 Parse Receipt Data
Converts AI output into structured JSON with store, tra
📦 Get Telegram File
Fetches the file ID of a receipt image uploaded via Tel
⬇️ Download Image
Downloads the receipt photo and prepares it for text ex
🖼️ Text Extractor
Extract text from given image
🧾 Format Message
Creates a clear summary of expenses with store, date, i
🧠 AI Categorizer
Uses AI to classify input into categories like income o
❗ Send Error Message
Sends a warning to the user if the input is invalid or
🚫 Check Invalid Input
Detects and flags incorrect or zero-value entries befor
🤖 OpenRouter AI Model
Configures the language model to extract structured inf
modelparser
Format Summary Message
Get Telegram File
Download Image
⚡
T
Telegram Trigger
AI Categorizer
C
Check Invalid Input
E
Extract Text Input
C
Check for Image
Receipt Parser
AI Analyzer
Send Error Message
Send Expense Summary
E
Extract Value From Image
13 nodes13 edges

How it Works

  1. 1

    Trigger

    The workflow starts with a trigger trigger.

  2. 2

    Process

    Data flows through 13 nodes, connecting chainllm, code, httprequest.

  3. 3

    Output

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

Node Details (13)

HT

HTTP Request

httpRequest

#1
TE

Telegram

telegram

#2
CO

Code

code

#3
BA

Basic LLM Chain

n8n-nodes-langchain.chainLlm

#4
ST

Structured Output Parser

n8n-nodes-langchain.outputParserStructured

#5
OP

OpenRouter Chat Model

n8n-nodes-langchain.lmChatOpenRouter

#6

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 extract-details-from-receipts-via-telegram-with-tesseract-and-llama 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": " Extract Details from Receipts via Telegram with Tesseract and Llama", "nodes": [...], ...}

Integrations

chainllmcodehttprequestiflmchatopenroutern8n-nodes-tesseractjs.tesseractnodeoutputparserstructuredsettelegramtelegramtrigger

Get This Workflow

Download and import in one click

Download JSONView on n8n.io
Nodes13
Complexitymedium
Triggertrigger
Views1,165
CategoryInvoice Processing

Created by

Khairul Muhtadin

Khairul Muhtadin

@khmuhtadin

Tags

chainllmcodehttprequestiflmchatopenroutern8n-nodes-tesseractjs.tesseractnodeoutputparserstructuredsettelegramtelegramtrigger
⚡

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🔗 Webhook·12 nodes