Validate a RAG dataset before re-indexing
Created by
Sebastián S
Actor
RAG Dataset Linter
Catch broken chunk sequences, missing provenance, duplicates, and overlap before a scheduled RAG re-index replaces your production vectors.
RAG Dataset Lintersebastian-actors/rag-dataset-linter
Gate
Action
Source type
Source ID
+9 fieldsTextNumberBooleanListObject
Input
Minimum tokens:10
Maximum tokens:2000
Near-duplicate similarity:0.95
Maximum adjacent overlap ratio:0.35
Inline records
chunkId:release-0+2
documentId:release-notes+1
sourceUrl:https://example.com/releases+1
chunkIndex:0+2
title:Release notes+2
headingPath
chunkText:Create a repeatable quality gate before each scheduled re-index. Stable chunk identifiers and ordered indexes make regressions visible across ingestion runs.+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
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.
