# Sitemap to RAG Dataset (`ghostgrid/sitemap-to-rag-dataset`) Actor Convert any website sitemap into an LLM-ready dataset for RAG pipelines. - **URL**: https://apify.com/ghostgrid/sitemap-to-rag-dataset.md - **Developed by:** [GhostGrid](https://apify.com/ghostgrid) (community) - **Categories:** AI, Developer tools, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.80 / 1,000 page extracteds 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 ## Sitemap to RAG Dataset Feed it a sitemap URL (or just a homepage), get back clean text content from every page, formatted for RAG pipelines and LLM training. ### What it does - Parses sitemap.xml files (including sitemap indexes, gzipped sitemaps, and auto-discovery from robots.txt) - Crawls each page and strips out navigation, footers, sidebars, ads, and other boilerplate - Outputs clean text and markdown versions of the main content - Extracts metadata (title, description, keywords, Open Graph image) - Detects page language and counts words - Splits content into RAG-ready chunks with stable chunk IDs (UUID5 based on URL + index) - Estimates token counts per chunk (len/4 heuristic) - Computes SHA-256 content hashes for pages and chunks - Supports diff mode to detect new, changed, and removed pages between crawls ### Input | Parameter | Type | Default | Description | |---|---|---|---| | `sitemap_url` | string | *required* | URL to a sitemap.xml or a website homepage (auto-detects sitemap) | | `max_pages` | integer | 100 | Max pages to crawl (1 - 10,000) | | `include_linked_pages` | boolean | false | Also crawl pages linked from sitemap pages | | `chunk_strategy` | string | fixed_size | How to split text: `fixed_size`, `sentence`, or `paragraph` | | `chunk_token_limit` | integer | 512 | Max tokens per chunk (100 - 4,096) | | `diff_mode` | boolean | false | Compare with previous crawl, report new/changed/removed pages | | `include_chunks` | boolean | true | Output RAG chunks as separate dataset items | ### Output The dataset contains two types of records: #### Page records (`type: "page"`) One per crawled page: | Field | Type | Description | |---|---|---| | `type` | string | Always `"page"` | | `url` | string | Page URL | | `title` | string | Page title | | `text` | string | Clean main content as plain text | | `markdown` | string | Content formatted as markdown | | `content_hash` | string | SHA-256 hex digest of the page text | | `metadata` | object | Description, keywords, OG image, canonical URL | | `crawled_at` | string | ISO 8601 timestamp | | `word_count` | integer | Word count of the extracted text | | `language` | string | Detected language code (e.g. en) | #### Chunk records (`type: "chunk"`) One per RAG chunk (when `include_chunks` is true): | Field | Type | Description | |---|---|---| | `type` | string | Always `"chunk"` | | `url` | string | Source page URL | | `title` | string | Source page title | | `chunk_id` | string | Stable UUID5 (based on url:chunk_index) | | `chunk_index` | integer | 0-based index within the page | | `total_chunks` | integer | Total chunks for this page | | `text` | string | The chunk text | | `start_char` | integer | Character offset in full page text | | `end_char` | integer | End character offset | | `token_estimate` | integer | Estimated tokens (len/4) | | `content_hash` | string | SHA-256 of the chunk text | | `page_content_hash` | string | SHA-256 of the full page text | | `language` | string | Page language code | #### Diff records (`type: "diff"`) One per run when `diff_mode` is true: | Field | Type | Description | |---|---|---| | `type` | string | Always `"diff"` | | `new` | list | URLs found in this crawl but not the previous one | | `changed` | list | URLs present in both but with different content hash | | `removed` | list | URLs in the previous crawl but not this one | | `crawl_time` | string | ISO 8601 timestamp of this crawl | | `previous_crawl_time` | string | ISO 8601 timestamp of the previous crawl | | `total_new` | integer | Count of new URLs | | `total_changed` | integer | Count of changed URLs | | `total_removed` | integer | Count of removed URLs | ### How to use Run locally: ```bash apify run --input '{"sitemap_url": "https://example.com/sitemap.xml"}' ```` With chunking and diff mode: ```bash apify run --input '{"sitemap_url": "https://example.com/sitemap.xml", "max_pages": 50, "chunk_strategy": "paragraph", "chunk_token_limit": 256, "diff_mode": true}' ``` Deploy to Apify: ```bash apify push ``` ### Pricing This actor uses pay-per-event (PPE) pricing. You are charged 1 event per page successfully crawled and extracted. Chunk records and diff records do not incur additional charges. # Actor input Schema ## `sitemap_url` (type: `string`): URL to a sitemap.xml file or a website homepage (we will auto-detect the sitemap). ## `max_pages` (type: `integer`): Maximum number of pages to crawl from the sitemap. ## `include_linked_pages` (type: `boolean`): Also crawl pages linked from sitemap pages. ## `chunk_strategy` (type: `string`): How to split page text into RAG chunks. ## `chunk_token_limit` (type: `integer`): Maximum tokens per chunk (tokens estimated as characters / 4). ## `diff_mode` (type: `boolean`): Compare with previous crawl and report new/changed/removed pages. ## `include_chunks` (type: `boolean`): Output RAG chunks as separate dataset items alongside raw pages. ## Actor input object example ```json { "sitemap_url": "https://example.com/sitemap.xml", "max_pages": 100, "include_linked_pages": false, "chunk_strategy": "fixed_size", "chunk_token_limit": 512, "diff_mode": false, "include_chunks": true } ``` # 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 = { "sitemap_url": "https://example.com/sitemap.xml" }; // Run the Actor and wait for it to finish const run = await client.actor("ghostgrid/sitemap-to-rag-dataset").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 = { "sitemap_url": "https://example.com/sitemap.xml" } # Run the Actor and wait for it to finish run = client.actor("ghostgrid/sitemap-to-rag-dataset").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 '{ "sitemap_url": "https://example.com/sitemap.xml" }' | apify call ghostgrid/sitemap-to-rag-dataset --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ghostgrid/sitemap-to-rag-dataset", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Sitemap to RAG Dataset", "description": "Convert any website sitemap into an LLM-ready dataset for RAG pipelines.", "version": "0.2", "x-build-id": "lESKJzvg5OOZ9bVmv" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ghostgrid~sitemap-to-rag-dataset/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ghostgrid-sitemap-to-rag-dataset", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/ghostgrid~sitemap-to-rag-dataset/runs": { "post": { "operationId": "runs-sync-ghostgrid-sitemap-to-rag-dataset", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/ghostgrid~sitemap-to-rag-dataset/run-sync": { "post": { "operationId": "run-sync-ghostgrid-sitemap-to-rag-dataset", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "sitemap_url" ], "properties": { "sitemap_url": { "title": "Sitemap URL", "type": "string", "description": "URL to a sitemap.xml file or a website homepage (we will auto-detect the sitemap)." }, "max_pages": { "title": "Max Pages", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of pages to crawl from the sitemap.", "default": 100 }, "include_linked_pages": { "title": "Include Linked Pages", "type": "boolean", "description": "Also crawl pages linked from sitemap pages.", "default": false }, "chunk_strategy": { "title": "Chunk Strategy", "enum": [ "fixed_size", "sentence", "paragraph" ], "type": "string", "description": "How to split page text into RAG chunks.", "default": "fixed_size" }, "chunk_token_limit": { "title": "Chunk Token Limit", "minimum": 100, "maximum": 4096, "type": "integer", "description": "Maximum tokens per chunk (tokens estimated as characters / 4).", "default": 512 }, "diff_mode": { "title": "Diff Mode", "type": "boolean", "description": "Compare with previous crawl and report new/changed/removed pages.", "default": false }, "include_chunks": { "title": "Include Chunks", "type": "boolean", "description": "Output RAG chunks as separate dataset items alongside raw pages.", "default": true } } }, "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 } } } } } } } } } } ```