Back to Catalog

Extract transactions from images using unli.dev Vision API & Telegram

Khairul MuhtadinKhairul Muhtadin
221 views
2/3/2026
Official Page

unli.dev + n8n + Telegram

Image Analyzer turns images sent to your Telegram bot into clean, Markdown-formatted transaction text using unli.dev Vision API. Instead of typing numbers and dates manually, the workflow downloads the photo, converts it to base64, analyzes it via API, and replies in-chat with extracted details, saving time and reducing errors.

๐Ÿ’ก Why Use Image Analyzer?

  • Save time: Process images in seconds, cutting manual entry by up to 90%.
  • Solve pain points: No more blurry screenshot frustration; get clean Markdown transactions.
  • Faster outcomes: Per-image turnaround under 15s.
  • Competitive edge: Give staff/customers structured feedback instantly

โšก Perfect For

  • Small business owners: Capture receipts/payments quickly.
  • Accountants/bookkeepers: Intake client receipts with fewer typos.
  • Ops/support teams: Turn messy screenshots into actionable records.

๐Ÿ”ง How It Works

  1. Trigger: Telegram bot receives photo.
  2. Process: Convert to base64 & prepare request.
  3. Smart Logic: Call unli.dev Vision API for text extraction.
  4. Output: Send Markdown result back to Telegram.
  5. Optional: Save structured data to Google Sheets, Airtable, or DB.

๐Ÿ›  Quick Setup

  1. Import workflow JSON to your n8n instance.
  2. Add credentials: Telegram bot + unli.dev API key.
  3. Customize the system prompt (default: extract the transaction in Markdown).
  4. Test by sending a real photo to your bot.

๐Ÿงฉ Youโ€™ll Need

Made by: Khaisa Studio
Category: Image Analysis

Contact: Get in touch

Extract Transactions from Images using UnliDev Vision API and Telegram

This n8n workflow automates the process of extracting transaction details from images using the UnliDev Vision API and then sends the extracted information to a Telegram chat. It's designed to simplify expense tracking or data entry from receipts and other transactional documents.

What it does

  1. Listens for new images on Telegram: The workflow is triggered whenever a new image is sent to a configured Telegram bot.
  2. Prepares image for API: It takes the received image file and converts it into a base64 encoded string, which is required by the UnliDev Vision API.
  3. Sends image to UnliDev Vision API: The base64 encoded image is sent as a POST request to the UnliDev Vision API's /extract/transactions endpoint for OCR and transaction data extraction.
  4. Processes API response: The workflow receives the JSON response from the UnliDev Vision API, which contains the extracted transaction details.
  5. Formats output for Telegram: It then formats the extracted data into a human-readable message.
  6. Sends extracted data to Telegram: Finally, the formatted transaction details are sent back to the Telegram chat where the image was originally received.

Prerequisites/Requirements

  • n8n Instance: A running instance of n8n.
  • Telegram Bot: A Telegram bot token and a chat ID to listen for messages and send responses.
  • UnliDev Vision API Key: An API key for the UnliDev Vision API to access its /extract/transactions endpoint.

Setup/Usage

  1. Import the workflow: Import the provided JSON into your n8n instance.
  2. Configure Telegram Trigger:
    • Open the "Telegram Trigger" node.
    • Select or create a new Telegram API credential. You'll need your Telegram Bot Token.
    • Ensure the bot is added to the chat where you intend to send images.
  3. Configure "Edit Fields (Set)" node: This node is likely used to prepare the image data for the API. You might need to adjust how the image file is extracted from the Telegram message and converted to base64. The current setup implies it's handling the file_id from the Telegram message.
  4. Configure "HTTP Request" node:
    • Open the "HTTP Request" node.
    • Set the URL to your UnliDev Vision API endpoint (e.g., https://api.unlidev.com/vision/extract/transactions).
    • Set the Method to POST.
    • Add a Header for Authorization with your UnliDev Vision API Key (e.g., Bearer YOUR_UNLIDEV_API_KEY).
    • Configure the Body to send the base64 encoded image data. This will likely involve referencing the output of the "Edit Fields (Set)" node.
  5. Configure "Code" node: This node is responsible for parsing the API response and formatting the message. You may need to adjust the JavaScript code within this node to match the exact structure of the UnliDev Vision API response and your desired output format for Telegram.
  6. Configure Telegram node:
    • Open the "Telegram" node.
    • Select the same Telegram API credential used in the trigger.
    • Set the Chat ID to the ID of the Telegram chat where you want to send the extracted information. This can often be dynamically pulled from the trigger node's output.
    • Configure the Text field to use the output of the "Code" node, which contains the formatted transaction details.
  7. Activate the workflow: Once all credentials and nodes are configured, activate the workflow.

Now, whenever you send an image to your configured Telegram bot, the workflow will process it, extract transaction details, and send them back to the chat.

Related Templates

Track competitor SEO keywords with Decodo + GPT-4.1-mini + Google Sheets

This workflow automates competitor keyword research using OpenAI LLM and Decodo for intelligent web scraping. Who this is for SEO specialists, content strategists, and growth marketers who want to automate keyword research and competitive intelligence. Marketing analysts managing multiple clients or websites who need consistent SEO tracking without manual data pulls. Agencies or automation engineers using Google Sheets as an SEO data dashboard for keyword monitoring and reporting. What problem this workflow solves Tracking competitor keywords manually is slow and inconsistent. Most SEO tools provide limited API access or lack contextual keyword analysis. This workflow solves that by: Automatically scraping any competitorโ€™s webpage with Decodo. Using OpenAI GPT-4.1-mini to interpret keyword intent, density, and semantic focus. Storing structured keyword insights directly in Google Sheets for ongoing tracking and trend analysis. What this workflow does Trigger โ€” Manually start the workflow or schedule it to run periodically. Input Setup โ€” Define the website URL and target country (e.g., https://dev.to, france). Data Scraping (Decodo) โ€” Fetch competitor web content and metadata. Keyword Analysis (OpenAI GPT-4.1-mini) Extract primary and secondary keywords. Identify focus topics and semantic entities. Generate a keyword density summary and SEO strength score. Recommend optimization and internal linking opportunities. Data Structuring โ€” Clean and convert GPT output into JSON format. Data Storage (Google Sheets) โ€” Append structured keyword data to a Google Sheet for long-term tracking. Setup Prerequisites If you are new to Decode, please signup on this link visit.decodo.com n8n account with workflow editor access Decodo API credentials OpenAI API key Google Sheets account connected via OAuth2 Make sure to install the Decodo Community node. Create a Google Sheet Add columns for: primarykeywords, seostrengthscore, keyworddensity_summary, etc. Share with your n8n Google account. Connect Credentials Add credentials for: Decodo API credentials - You need to register, login and obtain the Basic Authentication Token via Decodo Dashboard OpenAI API (for GPT-4o-mini) Google Sheets OAuth2 Configure Input Fields Edit the โ€œSet Input Fieldsโ€ node to set your target site and region. Run the Workflow Click Execute Workflow in n8n. View structured results in your connected Google Sheet. How to customize this workflow Track Multiple Competitors โ†’ Use a Google Sheet or CSV list of URLs; loop through them using the Split In Batches node. Add Language Detection โ†’ Add a Gemini or GPT node before keyword analysis to detect content language and adjust prompts. Enhance the SEO Report โ†’ Expand the GPT prompt to include backlink insights, metadata optimization, or readability checks. Integrate Visualization โ†’ Connect your Google Sheet to Looker Studio for SEO performance dashboards. Schedule Auto-Runs โ†’ Use the Cron Node to run weekly or monthly for competitor keyword refreshes. Summary This workflow automates competitor keyword research using: Decodo for intelligent web scraping OpenAI GPT-4.1-mini for keyword and SEO analysis Google Sheets for live tracking and reporting Itโ€™s a complete AI-powered SEO intelligence pipeline ideal for teams that want actionable insights on keyword gaps, optimization opportunities, and content focus trends, without relying on expensive SEO SaaS tools.

Ranjan DailataBy Ranjan Dailata
161

Generate song lyrics and music from text prompts using OpenAI and Fal.ai Minimax

Spark your creativity instantly in any chatโ€”turn a simple prompt like "heartbreak ballad" into original, full-length lyrics and a professional AI-generated music track, all without leaving your conversation. ๐Ÿ“‹ What This Template Does This chat-triggered workflow harnesses AI to generate detailed, genre-matched song lyrics (at least 600 characters) from user messages, then queues them for music synthesis via Fal.ai's minimax-music model. It polls asynchronously until the track is ready, delivering lyrics and audio URL back in chat. Crafts original, structured lyrics with verses, choruses, and bridges using OpenAI Submits to Fal.ai for melody, instrumentation, and vocals aligned to the style Handles long-running generations with smart looping and status checks Returns complete song package (lyrics + audio link) for seamless sharing ๐Ÿ”ง Prerequisites n8n account (self-hosted or cloud with chat integration enabled) OpenAI account with API access for GPT models Fal.ai account for AI music generation ๐Ÿ”‘ Required Credentials OpenAI API Setup Go to platform.openai.com โ†’ API keys (sidebar) Click "Create new secret key" โ†’ Name it (e.g., "n8n Songwriter") Copy the key and add to n8n as "OpenAI API" credential type Test by sending a simple chat completion request Fal.ai HTTP Header Auth Setup Sign up at fal.ai โ†’ Dashboard โ†’ API Keys Generate a new API key โ†’ Copy it In n8n, create "HTTP Header Auth" credential: Name="Fal.ai", Header Name="Authorization", Header Value="Key [Your API Key]" Test with a simple GET to their queue endpoint (e.g., /status) โš™๏ธ Configuration Steps Import the workflow JSON into your n8n instance Assign OpenAI API credentials to the "OpenAI Chat Model" node Assign Fal.ai HTTP Header Auth to the "Generate Music Track", "Check Generation Status", and "Fetch Final Result" nodes Activate the workflowโ€”chat trigger will appear in your n8n chat interface Test by messaging: "Create an upbeat pop song about road trips" ๐ŸŽฏ Use Cases Content Creators: YouTubers generating custom jingles for videos on the fly, streamlining production from idea to audio export Educators: Music teachers using chat prompts to create era-specific folk tunes for classroom discussions, fostering interactive learning Gift Personalization: Friends crafting anniversary R&B tracks from shared memories via quick chats, delivering emotional audio surprises Artist Brainstorming: Songwriters prototyping hip-hop beats in real-time during sessions, accelerating collaboration and iteration โš ๏ธ Troubleshooting Invalid JSON from AI Agent: Ensure the system prompt stresses valid JSON; test the agent standalone with a sample query Music Generation Fails (401/403): Verify Fal.ai API key has minimax-music access; check usage quotas in dashboard Status Polling Loops Indefinitely: Bump wait time to 45-60s for complex tracks; inspect fal.ai queue logs for bottlenecks Lyrics Under 600 Characters: Tweak agent prompt to enforce fuller structures like [V1][C][V2][B][C]; verify output length in executions

Daniel NkenchoBy Daniel Nkencho
601

Automate invoice processing with OCR, GPT-4 & Salesforce opportunity creation

PDF Invoice Extractor (AI) End-to-end pipeline: Watch Drive โžœ Download PDF โžœ OCR text โžœ AI normalize to JSON โžœ Upsert Buyer (Account) โžœ Create Opportunity โžœ Map Products โžœ Create OLI via Composite API โžœ Archive to OneDrive. --- Node by node (what it does & key setup) 1) Google Drive Trigger Purpose: Fire when a new file appears in a specific Google Drive folder. Key settings: Event: fileCreated Folder ID: google drive folder id Polling: everyMinute Creds: googleDriveOAuth2Api Output: Metadata { id, name, ... } for the new file. --- 2) Download File From Google Purpose: Get the file binary for processing and archiving. Key settings: Operation: download File ID: ={{ $json.id }} Creds: googleDriveOAuth2Api Output: Binary (default key: data) and original metadata. --- 3) Extract from File Purpose: Extract text from PDF (OCR as needed) for AI parsing. Key settings: Operation: pdf OCR: enable for scanned PDFs (in options) Output: JSON with OCR text at {{ $json.text }}. --- 4) Message a model (AI JSON Extractor) Purpose: Convert OCR text into strict normalized JSON array (invoice schema). Key settings: Node: @n8n/n8n-nodes-langchain.openAi Model: gpt-4.1 (or gpt-4.1-mini) Message role: system (the strict prompt; references {{ $json.text }}) jsonOutput: true Creds: openAiApi Output (per item): $.message.content โ†’ the parsed JSON (ensure itโ€™s an array). --- 5) Create or update an account (Salesforce) Purpose: Upsert Buyer as Account using an external ID. Key settings: Resource: account Operation: upsert External Id Field: taxid_c External Id Value: ={{ $json.message.content.buyer.tax_id }} Name: ={{ $json.message.content.buyer.name }} Creds: salesforceOAuth2Api Output: Account record (captures Id) for downstream Opportunity. --- 6) Create an opportunity (Salesforce) Purpose: Create Opportunity linked to the Buyer (Account). Key settings: Resource: opportunity Name: ={{ $('Message a model').item.json.message.content.invoice.code }} Close Date: ={{ $('Message a model').item.json.message.content.invoice.issue_date }} Stage: Closed Won Amount: ={{ $('Message a model').item.json.message.content.summary.grand_total }} AccountId: ={{ $json.id }} (from Upsert Account output) Creds: salesforceOAuth2Api Output: Opportunity Id for OLI creation. --- 7) Build SOQL (Code / JS) Purpose: Collect unique product codes from AI JSON and build a SOQL query for PricebookEntry by Pricebook2Id. Key settings: pricebook2Id (hardcoded in script): e.g., 01sxxxxxxxxxxxxxxx Source lines: $('Message a model').first().json.message.content.products Output: { soql, codes } --- 8) Query PricebookEntries (Salesforce) Purpose: Fetch PricebookEntry.Id for each Product2.ProductCode. Key settings: Resource: search Query: ={{ $json.soql }} Creds: salesforceOAuth2Api Output: Items with Id, Product2.ProductCode (used for mapping). --- 9) Code in JavaScript (Build OLI payloads) Purpose: Join lines with PBE results and Opportunity Id โžœ build OpportunityLineItem payloads. Inputs: OpportunityId: ={{ $('Create an opportunity').first().json.id }} Lines: ={{ $('Message a model').first().json.message.content.products }} PBE rows: from previous node items Output: { body: { allOrNone:false, records:[{ OpportunityLineItem... }] } } Notes: Converts discount_total โžœ per-unit if needed (currently commented for standard pricing). Throws on missing PBE mapping or empty lines. --- 10) Create Opportunity Line Items (HTTP Request) Purpose: Bulk create OLIs via Salesforce Composite API. Key settings: Method: POST URL: https://<your-instance>.my.salesforce.com/services/data/v65.0/composite/sobjects Auth: salesforceOAuth2Api (predefined credential) Body (JSON): ={{ $json.body }} Output: Composite API results (per-record statuses). --- 11) Update File to One Drive Purpose: Archive the original PDF in OneDrive. Key settings: Operation: upload File Name: ={{ $json.name }} Parent Folder ID: onedrive folder id Binary Data: true (from the Download node) Creds: microsoftOneDriveOAuth2Api Output: Uploaded file metadata. --- Data flow (wiring) Google Drive Trigger โ†’ Download File From Google Download File From Google โ†’ Extract from File โ†’ Update File to One Drive Extract from File โ†’ Message a model Message a model โ†’ Create or update an account Create or update an account โ†’ Create an opportunity Create an opportunity โ†’ Build SOQL Build SOQL โ†’ Query PricebookEntries Query PricebookEntries โ†’ Code in JavaScript Code in JavaScript โ†’ Create Opportunity Line Items --- Quick setup checklist ๐Ÿ” Credentials: Connect Google Drive, OneDrive, Salesforce, OpenAI. ๐Ÿ“‚ IDs: Drive Folder ID (watch) OneDrive Parent Folder ID (archive) Salesforce Pricebook2Id (in the JS SOQL builder) ๐Ÿง  AI Prompt: Use the strict system prompt; jsonOutput = true. ๐Ÿงพ Field mappings: Buyer tax id/name โ†’ Account upsert fields Invoice code/date/amount โ†’ Opportunity fields Product name must equal your Product2.ProductCode in SF. โœ… Test: Drop a sample PDF โ†’ verify: AI returns array JSON only Account/Opportunity created OLI records created PDF archived to OneDrive --- Notes & best practices If PDFs are scans, enable OCR in Extract from File. If AI returns non-JSON, keep โ€œReturn only a JSON arrayโ€ as the last line of the prompt and keep jsonOutput enabled. Consider adding validation on parsing.warnings to gate Salesforce writes. For discounts/taxes in OLI: Standard OLI fields donโ€™t support per-line discount amounts directly; model them in UnitPrice or custom fields. Replace the Composite API URL with your orgโ€™s domain or use the Salesforce nodeโ€™s Bulk Upsert for simplicity.

Le NguyenBy Le Nguyen
942