Civitai Models Scraper
Pricing
from $2.99 / 1,000 results
Extract Civitai AI image models, ratings, download counts, and images into clean CSV, JSON, or Excel datasets without needing logins or proxies. Search checkpoints or LoRAs by keyword, lookup model IDs, and export structured results easily for your research and workflow.
You can access the Civitai Models Scraper programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in API & Integrations in Apify Console.
{ "openapi": "3.0.1", "info": { "version": "0.0", "x-build-id": "jRl3fMZ5qr069CQWS" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/b2b_lead_generation~civitai-models-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-b2b_lead_generation-civitai-models-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/b2b_lead_generation~civitai-models-scraper/runs": { "post": { "operationId": "runs-sync-b2b_lead_generation-civitai-models-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/b2b_lead_generation~civitai-models-scraper/run-sync": { "post": { "operationId": "run-sync-b2b_lead_generation-civitai-models-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", "required": [ "mode" ], "properties": { "mode": { "title": "Mode", "enum": [ "search_models", "model_details", "images", "tags" ], "type": "string", "description": "Which public Civitai feed to read: model search, one model by ID, the images feed, or the tags list.", "default": "search_models" }, "query": { "title": "Search text", "type": "string", "description": "Search text sent as query on model search and on the tags list. Leave blank to omit the query parameter.", "default": "anime" }, "modelIds": { "title": "Model IDs", "type": "array", "description": "Numeric Civitai model IDs, one per line. Required for model details. On the images feed, each ID is sent as modelId. Ignored for search and tags.", "items": { "type": "string" } }, "types": { "title": "Model types", "type": "array", "description": "Model types for search, one per line. Each value is sent as a types parameter. Example values: Checkpoint, LORA, TextualInversion. Leave empty to skip the filter.", "default": [], "items": { "type": "string" } }, "sort": { "title": "Sort", "enum": [ "Highest Rated", "Most Downloaded", "Newest" ], "type": "string", "description": "Sort order for model search. Verified values are Highest Rated, Most Downloaded, and Newest.", "default": "Highest Rated" }, "period": { "title": "Period", "enum": [ "AllTime", "Year", "Month", "Week", "Day" ], "type": "string", "description": "Time window for model search. Verified values are AllTime, Year, Month, Week, and Day.", "default": "AllTime" }, "includeNsfw": { "title": "Include NSFW", "type": "boolean", "description": "When checked, model search sends nsfw=true. When unchecked, model search sends nsfw=false. Default is off.", "default": false }, "maxItems": { "title": "Max items", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum data rows to save this run. Error rows do not count toward the cap. Hard maximum is 1000.", "default": 100 }, "requestDelaySecs": { "title": "Delay between requests (seconds)", "minimum": 0, "type": "number", "description": "Seconds to wait after each completed request before the next one. Default is 1 second because Civitai does not publish a rate limit.", "default": 1 }, "userAgent": { "title": "User-Agent", "type": "string", "description": "User-Agent header sent on every request. Include an app name and a contact address so the source can identify the client.", "default": "BigiByteActorResearch/1.0 (contact: research@bigibyte.com)" }, "timeoutSecs": { "title": "Actor timeout (seconds)", "minimum": 1, "maximum": 3600, "type": "integer", "description": "Maximum seconds for the whole run. The actor stops and flushes rows already collected when this elapses.", "default": 300 }, "requestTimeoutSecs": { "title": "Request timeout (seconds)", "minimum": 1, "maximum": 120, "type": "integer", "description": "Maximum seconds to wait for a single HTTP response before retrying or recording an error row.", "default": 30 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Optional proxy for Civitai requests. Leave useApifyProxy off to call the API directly. Turn it on only if your IP is blocked.", "default": { "useApifyProxy": false } } } }, "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 } } } } } } } } }}OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.
OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.
By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.
You can download the OpenAPI definitions for Civitai Models Scraper from the options below:
If you’d like to learn more about how OpenAPI powers GPTs, read our blog post.
You can also check out our other API clients: