# Invoice & Receipt OCR to JSON (`ratio_tech/invoice-ocr-scraper`) Actor Extract structured data from invoice and receipt PDFs or images — vendor, invoice number, dates, line items, subtotal, tax, total, and currency. On-box OCR (Tesseract + Poppler), no external API. Ideal for accounting automation and document data pipelines. - **URL**: https://apify.com/ratio\_tech/invoice-ocr-scraper.md - **Developed by:** [Marius Matulevicius](https://apify.com/ratio_tech) (community) - **Categories:** Automation, Developer tools, AI - **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $40.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Invoice & Receipt OCR to JSON Turn invoice and receipt **PDFs or images** into clean, structured **JSON** — vendor, invoice number, dates, line items, subtotal, tax, total, and currency. Runs fully on-box with **Tesseract + Poppler** OCR: no external AI API, no per-token costs, no data sent to third parties. > **When to use this (AI agents):** call this tool to turn an invoice or receipt (PDF or image, by URL or uploaded file) into structured fields — vendor, invoice number, dates, line items, subtotal/tax/total, currency — each with an OCR `confidence` score. Best for machine-generated documents; noisy handwritten scans may return lower confidence. ### What it does Feed it document URLs (or files you upload to the Actor's key-value store). For each document it: 1. Downloads the file (PDF or image). 2. Renders PDF pages to images (`pdftoppm`). 3. Runs OCR with word-level bounding boxes (`tesseract`). 4. Parses layout + text into a structured invoice record. One JSON record out per document. ### Output ```json { "type": "invoice", "source": "https://example.com/invoice.pdf", "vendor": "Acme Corp", "invoiceNumber": "INV-2024-001", "invoiceDate": "2024-06-01", "dueDate": "2024-06-30", "lineItems": [ { "description": "Consulting", "qty": 10, "unitPrice": 100, "amount": 1000 } ], "subtotal": 1000, "tax": 200, "total": 1200, "currency": "USD", "confidence": 92.4, "pageCount": 1, "rawText": "ACME CORP\nInvoice INV-2024-001 ...", "scrapedAt": "2026-06-24T10:00:00.000Z" } ```` Use `confidence` (mean OCR confidence, 0–100) to flag low-quality scans for manual review. ### Input | Field | Description | |-------|-------------| | **documentUrls** | Public URLs of invoice/receipt PDFs or images (PNG, JPG, TIFF, WEBP, BMP). | | **documentKeys** | Keys of files uploaded to this Actor's key-value store (for private docs). | | **language** | Tesseract language code, `+`-joined (e.g. `eng`, `eng+deu`). Default `eng`. | | **maxPages** | Max pages to OCR per document. Default `10`. | | **proxyConfiguration** | Apify Proxy — used only to download `documentUrls`. | Supports **PDF** and common image formats. Multi-page PDFs handled up to `maxPages`. ### Pricing **Pay per result** — you're billed only for documents that successfully produce a record. Failures (bad download, unreadable file) are routed to a separate **errors** dataset that is **not billed**, so you never pay for documents that couldn't be processed. ### Tips for best accuracy - Higher-resolution scans OCR better. 200+ DPI recommended. - Set `language` to match the document for non-English invoices. - Low `confidence` usually means a blurry or skewed scan — re-scan flat and well-lit. ### Use cases - Accounting & expense automation (push results straight into your ledger). - Accounts-payable pipelines and invoice triage. - Bulk back-office document digitization. *** *This Actor processes documents you supply. You are responsible for ensuring you have the right to process them and that your use complies with applicable laws. — marius.matulevicius1@gmail.com* # Actor input Schema ## `documentUrls` (type: `array`): Public URLs of invoice/receipt PDFs or images (PNG, JPG, TIFF, WEBP, BMP). Each is downloaded and processed into one structured JSON record. ## `documentKeys` (type: `array`): Keys of files you uploaded to this Actor's default key-value store (for private documents you don't want to expose via URL). Each key must point at a PDF or image blob. ## `language` (type: `string`): Tesseract language code. Use '+' to combine (e.g. 'eng+deu'). Common: eng, deu, fra, spa, ita, por, nld. ## `maxPages` (type: `integer`): Cap on how many pages to OCR per document (protects against huge PDFs). Most invoices are 1-2 pages. ## `proxyConfiguration` (type: `object`): Apify Proxy settings, used only when downloading documentUrls. Datacenter proxies are sufficient. ## Actor input object example ```json { "documentUrls": [ "https://templates.invoicehome.com/invoice-template-us-neat-750px.png" ], "documentKeys": [], "language": "eng", "maxPages": 5, "proxyConfiguration": { "useApifyProxy": true } } ``` # Actor output Schema ## `results` (type: `string`): No description ## `errors` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "documentUrls": [ "https://templates.invoicehome.com/invoice-template-us-neat-750px.png" ], "language": "eng" }; // Run the Actor and wait for it to finish const run = await client.actor("ratio_tech/invoice-ocr-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "documentUrls": ["https://templates.invoicehome.com/invoice-template-us-neat-750px.png"], "language": "eng", } # Run the Actor and wait for it to finish run = client.actor("ratio_tech/invoice-ocr-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "documentUrls": [ "https://templates.invoicehome.com/invoice-template-us-neat-750px.png" ], "language": "eng" }' | apify call ratio_tech/invoice-ocr-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ratio_tech/invoice-ocr-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Invoice & Receipt OCR to JSON", "description": "Extract structured data from invoice and receipt PDFs or images — vendor, invoice number, dates, line items, subtotal, tax, total, and currency. On-box OCR (Tesseract + Poppler), no external API. Ideal for accounting automation and document data pipelines.", "version": "0.1", "x-build-id": "Rsqbw8hPTy6ebuLNZ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ratio_tech~invoice-ocr-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ratio_tech-invoice-ocr-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/ratio_tech~invoice-ocr-scraper/runs": { "post": { "operationId": "runs-sync-ratio_tech-invoice-ocr-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/ratio_tech~invoice-ocr-scraper/run-sync": { "post": { "operationId": "run-sync-ratio_tech-invoice-ocr-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "documentUrls": { "title": "Document URLs", "type": "array", "description": "Public URLs of invoice/receipt PDFs or images (PNG, JPG, TIFF, WEBP, BMP). Each is downloaded and processed into one structured JSON record.", "default": [], "items": { "type": "string" } }, "documentKeys": { "title": "Uploaded file keys", "type": "array", "description": "Keys of files you uploaded to this Actor's default key-value store (for private documents you don't want to expose via URL). Each key must point at a PDF or image blob.", "default": [], "items": { "type": "string" } }, "language": { "title": "OCR language", "type": "string", "description": "Tesseract language code. Use '+' to combine (e.g. 'eng+deu'). Common: eng, deu, fra, spa, ita, por, nld.", "default": "eng" }, "maxPages": { "title": "Max pages per document", "minimum": 1, "maximum": 50, "type": "integer", "description": "Cap on how many pages to OCR per document (protects against huge PDFs). Most invoices are 1-2 pages.", "default": 5 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Apify Proxy settings, used only when downloading documentUrls. Datacenter proxies are sufficient.", "default": { "useApifyProxy": true } } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```