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Rag Embedding Generator

Generate vector embeddings from text or chunked datasets using OpenAI or Cohere. Chains with RAG Content Chunker for end-to-end RAG pipelines. Outputs raw vectors ready for any vector database.

Pricing

from $0.30 / 1,000 results

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Mick

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4 days ago

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Rag Embedding Generator API

Below, you can find a list of relevant HTTP API endpoints for calling the Rag Embedding Generator Actor. For this, you’ll need an Apify account. Replace <YOUR_API_TOKEN> in the URLs with your Apify API token, which you can find under Integrations in Apify Console. For details, see the API reference.

Run Actor

POST
https://api.apify.com/v2/acts/labrat011~rag-embedding-generator/runs?token=<YOUR_API_TOKEN>

Note: By adding the method=POST query parameter, this API endpoint can be called using a GET request and thus used in third-party webhooks. Please refer to our Run Actor API documentation.

Run Actor synchronously and get dataset items

POST
https://api.apify.com/v2/acts/labrat011~rag-embedding-generator/run-sync-get-dataset-items?token=<YOUR_API_TOKEN>

Note: This endpoint supports both POST and GET request methods. However, only the POST method allows you to pass input data. For more information, please refer to our Run Actor synchronously and get dataset items API documentation.

Get Actor

GET
https://api.apify.com/v2/acts/labrat011~rag-embedding-generator?token=<YOUR_API_TOKEN>

For more information, please refer to our Get Actor API documentation.

Actors can be used to scrape web pages, extract data, or automate browser tasks. Use the Rag Embedding Generator API programmatically via the Apify API.

You can choose from:

Rag Embedding Generator API in Python

Rag Embedding Generator API in JavaScript

Rag Embedding Generator API through CLI

Rag Embedding Generator OpenAPI definition

You can start Rag Embedding Generator with the Apify API by sending an HTTP POST request to the Run Actorendpoint. An Actor’s input and its content type can be passed as a payload of the POST request, and additional options can be specified using URL query parameters. The Rag Embedding Generator is identified within the API by its ID, which is the creator’s username and the name of the Actor.

When the Rag Embedding Generator run finishes you can list the data from its default dataset(storage) via the API or you can preview the data directly on Apify Console.

Rag Vector Store Writer

labrat011/rag-vector-store-writer

Apify Actor that writes embedding vectors to Pinecone or Qdrant vector databases. Chains directly with RAG Embedding Generator output or accepts raw vectors with metadata. Handles batching, retries, collection creation, metadata mapping, and ID generation. Bring your own vector DB API key.

Mick

Rag Content Chunker

labrat011/rag-content-chunker

Turn raw text, Markdown, or Apify datasets into token-perfect RAG chunks with deterministic IDs, source metadata, and a billing-ready summary—ready for embeddings or vector DBs without extra glue code.

Mick

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

Web Scraper RAG Ready

traorealexy/Web-Sraper-RAG-Ready

Turn any website into clean, token-efficient Markdown ready for RAG and LLM pipelines. Removes boilerplate, handles JavaScript rendering, and outputs structured JSON for LangChain, LlamaIndex, and vector databases.

Alexy Traore

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

Docs to Markdown + AI Embeddings → Vector DB Crawler

badruddeen/docs-to-markdown-ai-embeddings---vector-db-crawler

Turn any documentation site into clean Markdown, intelligently chunked content with embeddings (Azure/OpenAI), and directly upsert into MongoDB Atlas, Pinecone, Weaviate, Qdrant, or Milvus — ready for RAG, AI assistants, and semantic search in minutes.

Badruddeen Naseem

5.0

Rag Pipeline

labrat011/rag-pipeline

One-click RAG pipeline: chunks text, generates embeddings, and stores vectors in Pinecone or Qdrant. Provide your content and API keys -- the orchestrator handles the rest.

Mick

Universal RAG Web Scraper

express_kingfisher/rag-web-scraper

Turn any website into clean, LLM-ready Markdown. Automatically strips ads, navigation, and noise using Mozilla Readability. Perfect for feeding data to ChatGPT, Claude, or Vector Databases (RAG).