{ "openapi": "3.0.1", "info": { "title": "Advanced Product Matcher Pro", "description": "A powerful AI Apify Actor that intelligently matches products between two datasets using advanced machine learning algorithms and configurable similarity scoring. Perfect for e-commerce catalog matching, product deduplication, and inventory reconciliation.", "version": "0.0", "x-build-id": "n4fsdaq29FfegfcF4" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/datawhisperers~advanced-product-matcher-pro/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-datawhisperers-advanced-product-matcher-pro", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/datawhisperers~advanced-product-matcher-pro/runs": { "post": { "operationId": "runs-sync-datawhisperers-advanced-product-matcher-pro", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/datawhisperers~advanced-product-matcher-pro/run-sync": { "post": { "operationId": "run-sync-datawhisperers-advanced-product-matcher-pro", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "dataFormat", "dataSource", "dataset1", "dataset1PrimaryKey", "dataset2", "dataset2PrimaryKey", "threshold", "attributes" ], "properties": { "dataFormat": { "title": "Data Format", "enum": [ "csv", "json" ], "type": "string", "description": "Choose between CSV or JSON format", "default": "json" }, "csvSeparator": { "title": "CSV Separator", "type": "string", "description": "CSV separator (only applies to CSV Data Format)", "default": "," }, "dataSource": { "title": "Data Source", "enum": [ "keyvaluestore", "datasets" ], "type": "string", "description": "Choose between KeyValueStore files or Datasets", "default": "datasets" }, "keyValuestoreNameOrId": { "title": "Name or ID of KeyValueStore", "type": "string", "description": "If sourcing data from a KeyValueStore, enter the name or Id of the store" }, "dataset1": { "title": "Dataset 1 Key/Dataset 1 ID", "type": "string", "description": "Data Soure = KeyValueStore > KV store key name where first dataset is stored. For Data Source = Dataset > Apify dataset ID containing data" }, "dataset1Name": { "title": "Name of dataset 1", "type": "string", "description": "Friendly name for dataset 1 - used as a prefix to fields output from dataset 1 for easier identification in the matched results", "default": "Dataset1" }, "dataset1PrimaryKey": { "title": "Name of primary row identifier in dataset 1", "type": "string", "description": "Must match the actual data record, is used to form a match with dataset 2", "default": "ProductId" }, "dataset2": { "title": "Dataset 2 Key/Dataset 2 ID", "type": "string", "description": "Data Soure = KeyValueStore > KV store key name where second dataset is stored. For Data Source = Dataset > Apify dataset ID containing data" }, "dataset2Name": { "title": "Name of dataset 2", "type": "string", "description": "Friendly name for dataset 2 - used as a prefix to fields output from dataset 2 for easier identification in the matched results", "default": "Dataset2" }, "dataset2PrimaryKey": { "title": "Name of primary row identifier in dataset 2", "type": "string", "description": "Must match the actual data record, is used to form a match with dataset 1", "default": "ProductId" }, "attributes": { "title": "Matching Attributes", "type": "array", "description": "Configure attributes for matching with simple or advanced cleaning options", "default": [ { "name": "title", "weight": 1, "useForMatching": true, "wordsToRemove": [ "new", "used", "refurbished" ], "wordReplacements": { "&": "and", "w/": "with" } }, { "name": "brand", "weight": 0.8, "useForMatching": true, "wordsToRemove": [ "inc", "llc", "ltd", "corp" ], "wordReplacements": { "apple": "apple inc", "samsung": "samsung electronics" } }, { "name": "description", "jsonPath": "product.description", "weight": 0.6, "useForMatching": true, "wordsToRemove": [ "brand new", "excellent condition", "fast shipping" ], "regex": "\\b(color|colour):\\s*\\w+\\b", "normalizationRegex": "[^a-zA-Z0-9\\s]", "normalizationReplacement": "" }, { "name": "model", "weight": 0.9, "useForMatching": true, "wordsToRemove": [ "model", "version" ], "wordReplacements": { "v1": "version 1", "v2": "version 2" } }, { "name": "price", "weight": 1, "useForMatching": false, "regex": "\\D" } ] }, "threshold": { "title": "Matching Threshold", "type": "string", "description": "Minimum similarity score for matches (0.0 to 1.0)", "default": "0.5" }, "maxMatches": { "title": "Max Matches per Item", "minimum": 1, "maximum": 5, "type": "integer", "description": "Maximum number of matches to return for each item", "default": 2 }, "groupByAttribute": { "title": "Group By Attribute", "type": "string", "description": "Attribute to group by for more efficient matching (optional)", "default": "" }, "language": { "title": "Language/Model", "enum": [ "en", "multilingual", "es", "fr", "de", "it", "pt", "nl" ], "type": "string", "description": "Language of your data to select appropriate embedding model", "default": "en" }, "includeOriginalValues": { "title": "Include Original Values", "type": "boolean", "description": "Include all original attribute values in output", "default": true }, "dataset1OutputFields": { "title": "Output Fields Dataset 1", "type": "array", "description": "If not including all fields in the output, specifiy individual fields from dataset 1 data to include in output", "default": [] }, "dataset2OutputFields": { "title": "Output Fields Dataset 2", "type": "array", "description": "If not including all fields in the output, specifiy individual fields from dataset 2 data to include in output", "default": [] } } }, "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": 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} } } } } } } } }