{ "openapi": "3.0.1", "info": { "title": "Bulk LLM Runner — ChatGPT, Claude & Gemini on CSV & Datasets", "description": "Run a prompt on every row of a CSV, Excel file, Google Sheet or Apify dataset with ChatGPT, Claude, Gemini, DeepSeek or any OpenRouter model. Answers as new columns or typed JSON fields. No API key needed. $1 per 1,000 rows.", "version": "0.0", "x-build-id": "0eYXfMTfFkuLYGm7a" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/saliga~bulk-llm-runner/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-saliga-bulk-llm-runner", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/saliga~bulk-llm-runner/runs": { "post": { "operationId": "runs-sync-saliga-bulk-llm-runner", "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/saliga~bulk-llm-runner/run-sync": { "post": { "operationId": "run-sync-saliga-bulk-llm-runner", "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": { "prompt": { "title": "Prompt", "type": "string", "description": "The prompt to run on every row. Use {{column}} for a column's value ({{address.city}} for nested fields, {{row}} for the whole row as JSON). Without a dataset, file or rows, it is run once (or use Prompts below)." }, "dataset": { "title": "Apify dataset", "type": "string", "description": "Run the prompt on every item of a dataset, for example the results of a scraper run." }, "fileUrl": { "title": "File or Google Sheet link", "type": "string", "description": "A CSV, TSV, Excel (.xlsx), JSON or JSONL link, or a Google Sheet / Google Drive / Dropbox share link (shared as \"Anyone with the link\")." }, "sheet": { "title": "Excel sheet", "type": "string", "description": "Sheet name for Excel files (default: the first sheet)." }, "rows": { "title": "Rows", "type": "array", "description": "Or paste rows as a JSON array of objects." }, "prompts": { "title": "Prompts (without data)", "type": "array", "description": "A list of independent prompts, one per line, when you have no table to process.", "items": { "type": "string" } }, "models": { "title": "Models", "type": "array", "description": "OpenRouter model ids. Several models run every row on each, for a side-by-side comparison. Default openai/gpt-6-luna (fast and cheap). Others: anthropic/claude-sonnet-5.5, google/gemini-3.8-flash, deepseek/deepseek-v4.1-flash, perplexity/sonar, or any on openrouter.ai/models.", "items": { "type": "string" } }, "outputFields": { "title": "Output fields (JSON columns)", "type": "array", "description": "Optional: get typed columns instead of free text. One field per line: \"name: description\" or \"name (type): description\". Types: string, number, integer, boolean, list. Example: \"industry: one or two words\", \"is_b2b (boolean): sells to companies\".", "items": { "type": "string" } }, "systemPrompt": { "title": "System prompt", "type": "string", "description": "Optional instructions for every request (tone, language, rules)." }, "outputColumn": { "title": "Answer column name", "type": "string", "description": "Column for the free-text answer.", "default": "llmOutput" }, "keepColumns": { "title": "Keep input columns", "type": "boolean", "description": "Copy every input column into the output row next to the answer.", "default": true }, "webSearch": { "title": "Web search", "type": "boolean", "description": "Let the model search the web first (adds the provider's search fee, about $0.005-0.014 per answer, and citations).", "default": false }, "maxRows": { "title": "Max rows", "minimum": 1, "maximum": 100000, "type": "integer", "description": "Safety limit: the run stops before starting if the data has more rows. Every row also costs the model's own price.", "default": 1000 }, "temperature": { "title": "Temperature", "type": "string", "description": "Optional, 0-2. Lower is more consistent." }, "maxAnswerTokens": { "title": "Max answer length (tokens)", "minimum": 16, "maximum": 2000, "type": "integer", "description": "Longer answers cost more.", "default": 1000 }, "concurrency": { "title": "Parallel requests", "minimum": 1, "maximum": 20, "type": "integer", "description": "Requests at the same time.", "default": 8 } } }, "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 }, "PROXY_UNBLOCKER_UNITS": { "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 }, "PROXY_UNBLOCKER_UNITS": { "type": "integer", "example": 0 } } } } } } } } } }