Traceable dataset sampler for AI agents avatar

Traceable dataset sampler for AI agents

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Traceable dataset sampler for AI agents

Traceable dataset sampler for AI agents

Create a deterministic, representative, token-bounded context package from an Apify dataset while preserving row-level provenance and omission accounting.

Pricing

Pay per usage

Rating

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Developer

Abdulrahman Baidaq

Abdulrahman Baidaq

Maintained by Community

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Monthly active users

19 days ago

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This Actor converts an Apify dataset into a deterministic context package under an explicit complete-artifact transport estimate. It preserves configured provenance fields, suppresses duplicate identities, reserves coverage across configured strata, records why each row was selected, and accounts for every omission.

The size rule is ceil(complete CONTEXT.md UTF-8 bytes / 3.5), not an exact count or guaranteed upper bound for a specific model tokenizer. The Actor does not summarize, rewrite, or invent source values.

Local tests

python -m unittest discover -s tests -v

Output

  • Dataset row 1: context_manifest
  • Remaining rows: selected records with _context metadata
  • Key-value store: REQUEST, MANIFEST, and CONTEXT.md