# OCR – PDF to Word (Arabic and all other languages) (`mshshakir/ocr-arabic`) Actor Convert Arabic PDFs to Word with Google Cloud Vision OCR. Optimized for manuscripts and books, it highlights low-confidence words in red for easy review. Get a clean, editable .docx file ready for publishing. Works for other languages too—fast, accurate, and reliable. - **URL**: https://apify.com/mshshakir/ocr-arabic.md - **Developed by:** [Mufaddal Shakir](https://apify.com/mshshakir) (community) - **Categories:** AI, Integrations, Automation - **Stats:** 1 total users, 1 monthly users, 50.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $30.00 / 1,000 page processeds This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ## Arabic OCR – PDF to Word Convert Arabic PDF files into fully editable Word documents using Google Cloud Vision OCR — with automatic highlighting of low-confidence words for easy human review. --- ### ⬇️ How to Download Your Output After the Actor finishes running: 1. Open the completed run 2. Click the **Storage** tab (top of the run page) 3. Click **Key-value store** 4. Find the key named **OUTPUT** 5. Click the **Download** button next to it Your `.docx` file will download immediately. Open it in Microsoft Word or Google Docs. > **Note:** The "Dataset" tab only shows billing records (one row per page processed). Your actual Word document is always in the Key-value store under the OUTPUT key. --- ### What This Actor Does 1. **Downloads** your PDF from a public URL 2. **Runs** Google Cloud Vision OCR (industry-leading Arabic accuracy) 3. **Compiles** all pages into a single `.docx` Word file 4. **Highlights** uncertain words in red so you can review them quickly 5. **Outputs** the DOCX file to the key-value store for download --- ### Why Use This Instead of Generic OCR? - ✅ **Arabic-first** — built specifically for Arabic, not an afterthought - ✅ **Manuscript support** — works on classical Arabic script, not just modern print - ✅ **Confidence highlighting** — low-confidence words appear in red in the output document - ✅ **Custom page numbering** — set the real-world starting page number of your PDF --- ### Input Parameters | Parameter | Required | Default | Description | |-----------|----------|---------|-------------| | `pdfUrl` | ✅ Yes | — | Direct public URL to your PDF | | `fileLabel` | No | `document` | Short name for the output file (no spaces) | | `startingPageNumber` | No | `1` | Real-world page number of the first page | | `confidenceThreshold` | No | `0.9` | Words below this confidence are highlighted red (0.0–1.0) | | `gcsBucketName` | No | `kutub-scanning` | GCS bucket (leave as default) | --- ### Supported PDF URLs Your PDF must be publicly accessible. Supported sources: - **Direct URL** — any public `https://` link ending in `.pdf` - **Google Drive** — share the file as "Anyone with the link", paste the share URL - **Dropbox** — paste the share link (the Actor converts it automatically) --- ### Pricing | Pages | Estimated Cost | |-------|----------------| | 10 | ~$0.80 | | 50 | ~$2.00 | | 100 | ~$3.50 | | 500 | ~$15.50 | Pricing = $0.50 Actor start fee + $0.03 per page processed. --- ### Example Use Cases - Digitizing Islamic manuscript collections - Converting scanned Arabic books for academic research - Archiving Arabic legal or historical documents - Bulk digitization for libraries and institutions --- ### Notes - Your PDF must be **publicly accessible** via URL - Very large PDFs (500+ pages) may take several minutes — this is normal - Password-protected PDFs are not supported - For best results, use high-resolution scans (300 DPI or above) - The red-highlighted words in the output indicate lower OCR confidence — review these manually # Actor input Schema ## `pdfUrl` (type: `string`): Direct URL to the PDF file you want to process. Must be publicly accessible. ## `fileLabel` (type: `string`): A short name for this file (no spaces). Used to name the output DOCX. ## `startingPageNumber` (type: `integer`): The real-world page number of the first page in your PDF (e.g. if your PDF starts at page 45 of a book, enter 45). ## `confidenceThreshold` (type: `number`): Words with OCR confidence below this value will be highlighted in red in the output DOCX. Range: 0.0 to 1.0. ## `gcsBucketName` (type: `string`): Your Google Cloud Storage bucket name. Leave as default if you are using the managed service. ## Actor input object example ```json { "pdfUrl": "https://example.com/arabic-document.pdf", "fileLabel": "kitab-al-ilm", "startingPageNumber": 1, "confidenceThreshold": 0.85, "gcsBucketName": "kutub-scanning" } ```` # Actor output Schema ## `docxFile` (type: `string`): Download your Arabic OCR output as an editable .docx file. Low-confidence words are highlighted in red. ## `pages` (type: `string`): Dataset records showing each page processed, used for billing. # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("mshshakir/ocr-arabic").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 = {} # Run the Actor and wait for it to finish run = client.actor("mshshakir/ocr-arabic").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 '{}' | apify call mshshakir/ocr-arabic --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=mshshakir/ocr-arabic", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "OCR – PDF to Word (Arabic and all other languages)", "description": "Convert Arabic PDFs to Word with Google Cloud Vision OCR. Optimized for manuscripts and books, it highlights low-confidence words in red for easy review. Get a clean, editable .docx file ready for publishing. Works for other languages too—fast, accurate, and reliable.", "version": "0.0", "x-build-id": "mELQl0XayqVgLrGvj" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/mshshakir~ocr-arabic/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-mshshakir-ocr-arabic", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/mshshakir~ocr-arabic/runs": { "post": { "operationId": "runs-sync-mshshakir-ocr-arabic", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/mshshakir~ocr-arabic/run-sync": { "post": { "operationId": "run-sync-mshshakir-ocr-arabic", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "pdfUrl" ], "properties": { "pdfUrl": { "title": "PDF URL", "type": "string", "description": "Direct URL to the PDF file you want to process. Must be publicly accessible." }, "fileLabel": { "title": "File Label", "type": "string", "description": "A short name for this file (no spaces). Used to name the output DOCX.", "default": "document" }, "startingPageNumber": { "title": "Starting Page Number", "minimum": 1, "type": "integer", "description": "The real-world page number of the first page in your PDF (e.g. if your PDF starts at page 45 of a book, enter 45).", "default": 1 }, "confidenceThreshold": { "title": "Confidence Threshold", "minimum": 0, "maximum": 1, "type": "number", "description": "Words with OCR confidence below this value will be highlighted in red in the output DOCX. Range: 0.0 to 1.0.", "default": 0.9 }, "gcsBucketName": { "title": "GCS Bucket Name", "type": "string", "description": "Your Google Cloud Storage bucket name. Leave as default if you are using the managed service.", "default": "kutub-scanning" } } }, "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 } } } } } } } } } } ```