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Applies to:


Summary Issue: Online scorers don’t re-trigger for all feedback calls when multiple feedback API calls update the same span’s expected field in quick succession, and only the last feedback value is scored. Cause: Scoring requests are deduplicated by row_id within write-ahead log (WAL) processing batches, so only one scoring invocation executes per span per batch. Resolution: Space out feedback API calls to ensure they process in separate WAL batches, or restructure your application to send only one feedback update per span.

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How Deduplication Works

When feedback calls arrive in quick succession:
  1. First feedback call updates expected, generates scoring request with token A
  2. Second feedback call updates expected again, generates scoring request with token B
  3. Both requests enter the same WAL batch
  4. Second request overwrites the first (same row_id key)
  5. Only one scoring invocation triggers (with token B’s data)
This is intentional behavior to prevent redundant scoring invocations.

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Resolution Steps

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Option 1: Space out feedback calls

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Introduce a delay between feedback API calls for the same span.

import time
from braintrust import update_span

# First feedback update
update_span(span_id, expected={"patient": None})

# Wait for first update to process
time.sleep(1)

# Second feedback update
update_span(span_id, expected={"customer": "9d50173e18664h91ab"})

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Option 2: Consolidate feedback updates

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Queue feedback updates and send only the final state per span.

from braintrust import update_span

# Instead of multiple calls, determine final state first
final_expected = {"customer": "9d50173e18664h91ab"}

# Single feedback update
update_span(span_id, expected=final_expected)