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feat: add deterministic text_retrieve workload across local execution, routing, and validation - #51
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Objective
Add a deterministic
text_retrieveworkload to the existing local-only prototype so the mesh can execute a realistic AI-adjacent ranking task end-to-end (runner -> scheduler -> validation -> ledger) while keeping the change local, testable, and auditable.This matters because it expands useful work types without introducing networking, rewards, or production infrastructure changes, and exercises the same local transport/validation contracts already in place.
What changed
text_retrievesupport inLocalRunnerwith strict payload validation, deterministic token extraction, overlap scoring, stable tie-break sorting, and deterministic output shaping.text_retrieveinto validation so expected results are recomputed locally and mismatches are rejected (including malformed payloads and incorrect contribution units).text_retrievein default local capabilities so manifest default nodes can advertise and accept the new job type.text_retrievejob to the default local batch example and updated README docs to document required fields, scoring semantics, and failure behavior.Validation
PYTHONDONTWRITEBYTECODE=1 PYTHONPATH=src python3 -m unittest discover -s tests -v(310 tests, all passed).run-local-flow --manifest examples/local-batch.json --output-dir <tmp-output-dir>and confirmed the added workload flowed end-to-end withprocessed_assignment_count=6,receipt_count=6, and matching ledger total contribution units.audit-local-flow --output-dir <tmp-output-dir>and confirmed flow artifacts validated successfully withok: trueand consistent counts.Safety notes