Split text into clean, overlapping chunks ready for embeddings, vector databases, RAG and LLM context. Configurable size, overlap, and split strategy.

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.

Clean and chunk scraped text for RAG and LLM pipelines. Strips HTML, collapses whitespace, splits into overlapping chunks ready for embedding. Works standalone or chained after any scraper. Per-row billing.

Text Cleaner For RAG

junipr/text-cleaner-for-rag

Clean web text for RAG by removing boilerplate, normalizing whitespace, and producing chunk-ready text.

AI / RAG Web Crawler

groupoject/ai-rag-web-crawler

Crawl any website and extract clean, LLM-ready Markdown chunks to feed AI agents, chatbots, and RAG pipelines. One row per embeddable chunk.

Rag Embedding Generator

labrat011/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.

RAG-Ready Markdown Converter & Chunker

foxpink/apify-rag-markdown-chunker

Convert raw HTML/text into clean Markdown and split into ready-to-ingest chunks for RAG pipelines, Vector DBs, and LLM fine-tuning workflows.

Convert PDFs into token-bounded Markdown chunks for RAG, embeddings, and vector databases (Pinecone, Chroma, Weaviate, Qdrant). Set maxTokens + overlap; get clean chunks with page number, token count, and SHA-256 content hash for dedup. JSON dataset ready for any LLM pipeline.

RAG Docs Extractor - Documentation to Chunks

ambitious_door/ragdocs-extractor

Turn any documentation site into clean, RAG-ready chunks in a single call. Semantic boundaries, preserved structure, per-chunk metadata.

Search the web and extract content for AI/RAG pipelines. Returns clean text ready for LLM ingestion.