Audit RAG chunks before Pinecone

Validate RAG chunk structure, provenance, duplicate content, and overlap before uploading embeddings to a Pinecone index.

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RAG Dataset Linter
RAG Dataset Lintersebastian-actors/rag-dataset-linter
Gate
Action
Source type
Source ID
+9 fields
Text
Number
Boolean
List
Object

Input

Minimum tokens:10
Maximum tokens:2000
Near-duplicate similarity:0.95
Maximum adjacent overlap ratio:0.35
Inline records
chunkId:pinecone-guide-0+2
documentId:pinecone-guide+2
sourceUrl:https://example.com/pinecone-guide+2
chunkIndex:0+2
title:Pinecone ingestion guide+2
headingPath
chunkText:Validate chunk identifiers, document provenance, source URLs, and retrieval context before uploading vectors to Pinecone. A pre-ingestion quality gate prevents malformed records from entering the production index.+2
Maximum chunks:1000

Output fields

Gate
Action
Source type
Source ID
Audited
Findings
Errors
Warnings
Exact duplicate rate
Near duplicate rate
Estimated wasted tokens
Truncated
Finished

How it works

Sign up on Apify01

Create your Apify account to access the RAG Dataset Linter.

Start the run02

The Actor will start running based on the input automatically.

Receive the output03

Monitor the progress in real-time. You will be notified as soon as your dataset is complete and ready for review.

Integrate into your workflow04

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow.

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