Pricing

Pay per usage

Rag

Interviews RAG — An Actor that answers questions about customer meeting notes using RAG. It searches a Pinecone vector store for relevant transcript chunks, ranks results by semantic similarity and recency, then generates answers. Runs in Standby mode as an HTTP service, exposing a /query endpoint.

Pricing

Pay per usage

Rating

0.0

(0)

Developer

Jan Ženíšek

Actor stats

Bookmarked

Total users

Monthly active users

21 hours ago

Last modified

Actor uses Standby mode

Beta

The Standby mode is a new, lightweight method for using Actors. Instead of starting an Actor for each input and waiting for results, the Actor remains ready in the background to handle arbitrary HTTP requests, just like any web or API server.

Actor URL

Send a HTTP request to the this URL, and wait for the response. To call the Actor, you need to have an Apify account. Replace <YOUR_API_TOKEN> with your API token, which you can find under Settings > Integrations in Apify Console.Learn more.

To view the specific endpoint of this Actor, go to README.

https://zenisjan--rag.apify.actor?token=<YOUR_API_TOKEN>

Max requests per run

maxRequestsPerActorRunnumber

The maximum number of concurrent HTTP requests a single standby Actor run can accept. If this limit is exceeded, the system starts a new Actor run to handle the request, which will take a few seconds.

Default value of this property is 4

Desired requests per run

desiredRequestsPerActorRunnumber

The desired number of concurrent HTTP requests a single standby Actor run can handle. If this limit is exceeded, the system preemptively starts a new Actor run to handle additional requests.

Default value of this property is 2

Memory (MB)

memoryMbytesnumber

The amount of memory (RAM) allocated for the Actor standby run, in megabytes. With more memory, the Actor can typically handle more requests in parallel, but the number of compute units consumed and the cost also grow.

Default value of this property is 256

Idle timeout (seconds)

idleTimeoutSecsnumber

If a standby Actor run doesn’t receive any HTTP requests in this amount of time, the system will finish the run. When a new request comes, the system might need to start a new standby Actor run to handle it, which will take a few seconds. Higher idle timeout increases the responsiveness but increases the costs as the Actor needs to keep running longer.

Default value of this property is 1800

Build

buildenum

Build version of the Actor that will be used for the standby run.

Default value of this property is "latest"

RAG Web Browser

apify/rag-web-browser

Web browser for OpenAI Assistants, RAG pipelines, or AI agents, similar to a web browser in ChatGPT. It queries Google Search, scrapes the top N pages, and returns their content as Markdown for further processing by an LLM. It can also scrape individual URLs.

Apify

18K

2.5

(17)

RAG Browser

visita/rag-browser

This Actor provides essential web browsing and content extraction functionality for AI Agents, LLM applications, and Retrieval-Augmented Generation (RAG) pipelines. It functions similarly to the web search feature in popular LLM chatbots, providing fresh, contextualized data directly from the web.

Visita Intelligence

Rag Knowledge Graph Builder

cspnair/rag-knowledge-graph-builder

Transform websites into RAG-ready datasets. Crawls pages, chunks content into semantic segments (500-1000 tokens), and generates hypothetical questions for each chunk. No API key needed with native mode. Output: pre-indexed JSON optimized for AI retrieval with 3x better accuracy than raw text.

csp

5.0

(8)

Quick Website Content Scraper ( Extract Text for RAG & LLMs )

automateitplease/ai-web-content-scraper-extract-text-for-rag-llms

Extract clean text from any website for AI/LLM applications. Supports both static and JavaScript-rendered sites (React, Vue, Angular). Perfect for RAG systems, chatbot training, and content analysis.

AutomateItPlease Workflow And Automaton Ops

AI Context Fetcher: Clean Text for RAG

sarvesh_bijawe/ai-context-fetcher-clean-text-for-rag

Instantly extracts clean, ad-free text from any URL. Designed for AI Agents, RAG pipelines, and LLM context windows.

Sarvesh Bijawe

AI RAG Feeder V2

mickeywmoore/ai-rag-feeder-v2

Turn any website into AI-ready Markdown. Scrapes entire domains, removes ads/clutter, and formats text specifically for RAG pipelines and LLM training data.

Mickey Moore

Docs Markdown Rag Ready Crawler

devwithbobby/docs-markdown-rag-ready-crawler

Turn any documentation site or website into clean, structured markdown—ready for RAG, embeddings, and AI agents.

Dev with Bobby

Web-to-Markdown Generator for AI & RAG Pipelines

profitstack/web-to-markdown-generator-for-ai-rag-pipelines

Convert any website into clean, heading-based chunking, LLM-ready Markdown for RAG and AI agents.

Manas Mantri

Docs To Rag

gabrielaxy/docs-to-rag

Transform documentation websites into RAG-ready chunks with semantic understanding, quality scoring, and direct vector database integration.

Gabriel Antony Xaviour

RAG Markdown Cleaner

cooldev/rag-markdown-cleaner

Transform web pages into RAG-ready Markdown with smart chunking, metadata, code detection & quality scoring. Production-tested deduplication. Fully open-source (Apache 2.0)—review code, contribute, or self-host. Turn messy HTML into embedding-ready knowledge instantly.