# AI Menu Parser — Flat Price per Menu, No API Key (`nomad-agent/ai-menu-parser-flat`) Actor One flat price per menu, charged only on success — no API key, no per-item metering. Menu photos in, structured dishes out: translated names, prices, atomic ingredients, EU-14 allergens, dietary type, nutrition estimates. 15 languages. - **URL**: https://apify.com/nomad-agent/ai-menu-parser-flat.md - **Developed by:** [Nomad.Dev](https://apify.com/nomad-agent) (community) - **Categories:** AI, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $990.00 / 1,000 menu parseds 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 ## AI Menu Parser — Flat Price per Menu **One flat charge per menu. Charged only when parsing succeeds. No API key.** Send up to 10 photos of a menu, get the whole menu back as **structured JSON** — one record per dish, however many dishes it has. A 12-dish café card and a 60-dish restaurant board cost exactly the same. Each dish record includes: - `name` (translated to your language) + `originalName` (as printed) - `category`, `price` (with currency, as shown) - `ingredients` — atomic base ingredients, each with an English database name, translated display name, and **EU-14 allergens with confidence** - `dietaryType` — Vegan / Vegetarian / Pescetarian / Other, with explanation - `nutritionInfo` — estimated serving size, calories, protein, fat, carbs - `story` — origin story / cultural significance - `isAlcoholic` for beverages 15 output languages. The prompt is the production pipeline of a dietary-restrictions travel app — battle-tested on real menus worldwide. ### Why flat pricing You know the cost before you run: one menu, one price. No per-dish metering, no bill surprises on dense menus. If the parse fails or the photos are unreadable, you are not charged — a non-billed diagnostic row explains what went wrong instead. Prefer usage-based pricing or your own Gemini key? The same parser is also listed as [ai-menu-parser](https://apify.com/nomad-agent/ai-menu-parser) (bring your own key, per dish) and [ai-menu-parser-managed](https://apify.com/nomad-agent/ai-menu-parser-managed) (no key, per dish). ### Input example ```json { "imageUrls": ["https://example.com/menu-page-1.jpg", "https://example.com/menu-page-2.jpg"], "language": "en" } ```` ### Notes - Up to 10 images per run, parsed together as **one** menu. One run = one menu — for several restaurants, start one run each. - Unreadable items are skipped rather than guessed; empty results produce a non-billed diagnostic row explaining why. # Actor input Schema ## `imageUrls` (type: `array`): Direct, publicly reachable URLs of the menu's photos (JPEG/PNG/WebP). All images are parsed as ONE menu — up to 10 per run. Prefilled with a sample menu photo so you can try the actor immediately. ## `language` (type: `string`): Language for dish names, descriptions, stories and allergen summaries (ingredient database names stay English). ## Actor input object example ```json { "imageUrls": [ "https://raw.githubusercontent.com/Exdenta/nomads-eat-support/main/docs/assets/menu-demo.jpg" ], "language": "en" } ``` # Actor output Schema ## `items` (type: `string`): The run's dataset items (see the dataset schema for the field-by-field structure). # 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 = { "imageUrls": [ "https://raw.githubusercontent.com/Exdenta/nomads-eat-support/main/docs/assets/menu-demo.jpg" ] }; // Run the Actor and wait for it to finish const run = await client.actor("nomad-agent/ai-menu-parser-flat").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 = { "imageUrls": ["https://raw.githubusercontent.com/Exdenta/nomads-eat-support/main/docs/assets/menu-demo.jpg"] } # Run the Actor and wait for it to finish run = client.actor("nomad-agent/ai-menu-parser-flat").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 '{ "imageUrls": [ "https://raw.githubusercontent.com/Exdenta/nomads-eat-support/main/docs/assets/menu-demo.jpg" ] }' | apify call nomad-agent/ai-menu-parser-flat --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nomad-agent/ai-menu-parser-flat", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "AI Menu Parser — Flat Price per Menu, No API Key", "description": "One flat price per menu, charged only on success — no API key, no per-item metering. Menu photos in, structured dishes out: translated names, prices, atomic ingredients, EU-14 allergens, dietary type, nutrition estimates. 15 languages.", "version": "0.1", "x-build-id": "ySFu5RUNycHSIk3Zt" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nomad-agent~ai-menu-parser-flat/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nomad-agent-ai-menu-parser-flat", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nomad-agent~ai-menu-parser-flat/runs": { "post": { "operationId": "runs-sync-nomad-agent-ai-menu-parser-flat", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nomad-agent~ai-menu-parser-flat/run-sync": { "post": { "operationId": "run-sync-nomad-agent-ai-menu-parser-flat", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "imageUrls" ], "properties": { "imageUrls": { "title": "Menu photo URLs", "type": "array", "description": "Direct, publicly reachable URLs of the menu's photos (JPEG/PNG/WebP). All images are parsed as ONE menu — up to 10 per run. Prefilled with a sample menu photo so you can try the actor immediately.", "items": { "type": "string" } }, "language": { "title": "Output language", "enum": [ "en", "es", "fr", "de", "it", "pt", "ru", "zh", "ja", "ko", "ar", "hi", "uk", "ka", "eu" ], "type": "string", "description": "Language for dish names, descriptions, stories and allergen summaries (ingredient database names stay English).", "default": "en" } } }, "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 } } } } } } } } } } ```