# News & Announcements to Markdown for RAG (`nexgendata/news-announcements-rag-markdown`) Actor Convert press releases, corporate announcements & news articles into clean, chunked Markdown for RAG and LLM pipelines. Article URLs or RSS feeds. No login. - **URL**: https://apify.com/nexgendata/news-announcements-rag-markdown.md - **Developed by:** [NexGenData](https://apify.com/nexgendata) (community) - **Categories:** Business, AI, News - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $40.00 / 1,000 markdown chunks 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 ## 📰 News & Announcements to Markdown for RAG Turn press releases, corporate announcements, and news articles into clean, chunked Markdown for RAG and LLM pipelines. Feed it article URLs or RSS/Atom feeds and get LLM-ready text with citations. ### ⚡ What you get | Field | Description | |---|---| | `url` | Source article URL (citation) | | `title` | Article / release title | | `chunkIndex` / `totalChunks` | Position within the article | | `markdown` | Clean Markdown chunk | ### 🎯 Use cases 1. AI engineers building news/PR RAG copilots 2. Market & competitive intel feeding event data to an LLM 3. PR/IR teams building searchable announcement archives 4. Fintech/research products needing announcement text with citations ### 🚀 Sample inputs ```json { "rssFeeds": ["https://www.prnewswire.com/rss/news-releases-list.rss"], "maxPerFeed": 10 } ```` ```json { "urls": ["https://www.businesswire.com/news/home/.../en/..."], "chunkWords": 600 } ``` ### 📦 Sample output ```json { "url": "https://www.prnewswire.com/news-releases/...", "title": "Acme Raises $50M Series B", "chunkIndex": 0, "totalChunks": 6, "markdown": "## Acme Corp Raises $50M... ..." } ``` ### 📊 Sample Output ![Sample output](https://api.apify.com/v2/key-value-stores/8gLgXMBveEI1tTz1z/records/news-announcements-rag-markdown-output.png) ### 🛠 How it works 1. **Source** — fetches article URLs directly, or pulls latest items from RSS/Atom feeds. 2. **Extract** — isolates the main article (`
`/`
`), strips nav/ads/scripts. 3. **Convert** — HTML → ATX Markdown. 4. **Chunk** — ~`chunkWords`-word chunks for embedding. 5. **Schema** — one row per chunk, with the source URL as citation. ### 🔗 Related Actors - [PR Newswire Releases](https://apify.com/nexgendata/pr-newswire-press-releases-scraper?fpr=2ayu9b) - [SEC Filings to Markdown for RAG](https://apify.com/nexgendata/sec-filings-rag-markdown?fpr=2ayu9b) - [RAG Web Browser](https://apify.com/nexgendata/rag-web-browser?fpr=2ayu9b) - [Website Content Crawler](https://apify.com/nexgendata/website-content-crawler?fpr=2ayu9b) ### 💰 Pricing Example Pay-per-event: **$0.005 per run + $0.04 per Markdown chunk** (`document-record`). | Chunks | Cost | |---|---| | 100 | ~$4.00 | | 500 | ~$20.00 | | 2,000 | ~$80.00 | Apify's **$5 free credit** covers ~124 chunks. [Start free →](https://apify.com/?fpr=2ayu9b) ### ⚖️ Legal & data sources Fetches publicly-accessible articles/feeds with an identified User-Agent. Respect each publisher's terms for your downstream use; output includes source URLs for attribution. ### ❓ FAQ **URLs or feeds?** Either or both — feeds expand to their latest items. **Citations?** Yes — every chunk keeps its source URL. **Chunk size?** `chunkWords` (default 800). **Paywalled articles?** Only public content is reachable. **Fresh?** Pulled live at run time. **Dedup?** Repeated URLs in one run are skipped. ### 🆘 Troubleshooting - **Empty markdown** — the page may be JS-rendered or paywalled. - **Too much boilerplate** — the article wrapper wasn't detected; try a direct article URL. - **Feed returns nothing** — confirm it's a valid RSS/Atom URL. - **Huge output** — lower `maxPerFeed` or `chunkWords`. ### 🏷️ About NexGenData Structured public-data tools for analysts, developers, and operators. [thenextgennexus.com](https://thenextgennexus.com/actors-by-workflow/). # Actor input Schema ## `urls` (type: `array`): Direct URLs of press releases / news articles to convert. ## `rssFeeds` (type: `array`): Feed URLs; latest items are fetched and converted. ## `maxPerFeed` (type: `integer`): How many latest items to take from each feed. ## `chunkWords` (type: `integer`): Approx words per Markdown chunk for RAG. ## Actor input object example ```json { "urls": [ "https://www.apify.com/change-log" ], "rssFeeds": [], "maxPerFeed": 10, "chunkWords": 800 } ``` # 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 = { "urls": [ "https://www.apify.com/change-log" ], "rssFeeds": [], "maxPerFeed": 10, "chunkWords": 800 }; // Run the Actor and wait for it to finish const run = await client.actor("nexgendata/news-announcements-rag-markdown").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 = { "urls": ["https://www.apify.com/change-log"], "rssFeeds": [], "maxPerFeed": 10, "chunkWords": 800, } # Run the Actor and wait for it to finish run = client.actor("nexgendata/news-announcements-rag-markdown").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 '{ "urls": [ "https://www.apify.com/change-log" ], "rssFeeds": [], "maxPerFeed": 10, "chunkWords": 800 }' | apify call nexgendata/news-announcements-rag-markdown --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nexgendata/news-announcements-rag-markdown", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "News & Announcements to Markdown for RAG", "description": "Convert press releases, corporate announcements & news articles into clean, chunked Markdown for RAG and LLM pipelines. Article URLs or RSS feeds. No login.", "version": "0.0", "x-build-id": "JmoCZtWwbYUqo8io6" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nexgendata~news-announcements-rag-markdown/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nexgendata-news-announcements-rag-markdown", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nexgendata~news-announcements-rag-markdown/runs": { "post": { "operationId": "runs-sync-nexgendata-news-announcements-rag-markdown", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nexgendata~news-announcements-rag-markdown/run-sync": { "post": { "operationId": "run-sync-nexgendata-news-announcements-rag-markdown", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "urls": { "title": "Article URLs", "type": "array", "description": "Direct URLs of press releases / news articles to convert.", "items": { "type": "string" } }, "rssFeeds": { "title": "RSS / Atom feeds", "type": "array", "description": "Feed URLs; latest items are fetched and converted.", "items": { "type": "string" } }, "maxPerFeed": { "title": "Max items per feed", "type": "integer", "description": "How many latest items to take from each feed." }, "chunkWords": { "title": "Chunk size (words)", "type": "integer", "description": "Approx words per Markdown chunk for RAG." } } }, "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 } } } } } } } } } } ```