fix: classifier robustness — schema in prompt, retries, kickoff fallback
The kickoff parse-and-confirm route was 500-ing intermittently because
Hermes-3 + Featherless's response_format={"type":"json_object"} only
guarantees JSON output, NOT a particular schema. The model was inventing
its own field names (sceneTime, entities, settingDetails) instead of
the KickoffParse fields, causing Pydantic validation to fail on both
classify() retries.
Three changes:
1. Include the Pydantic JSON schema in the system prompt so the model
knows exactly which keys to produce. Affects every classify() call
(kickoff parse, turn parse, scene-close detect, significance,
state-update, scene summarize). Strip ```json fences if the model
wraps its output. Bump retries 2 → 3 (model is stochastic; one extra
attempt closes most of the remaining gap).
2. parse_kickoff() now passes a default empty KickoffParse so the
route degrades to a fillable form instead of 500 when the classifier
ultimately fails. The confirm form is the human-in-the-loop; an
empty form is strictly better UX than a stack trace.
3. Tests updated: bumped canned-failure arrays from 2 → 3 entries to
match the new attempt count; renamed kickoff test from
"raises_when_classifier_fails_twice" to
"falls_back_to_empty_when_classifier_fails" reflecting the new
degraded-but-usable behavior.
Verified live with all 3 sample bots (maya/eli/sam) — kickoff route
returns 200 across multiple attempts. Full suite: 168 passed.
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@@ -74,7 +74,7 @@ async def test_parse_turn_empty_prose_short_circuits_without_classifier_call():
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@pytest.mark.asyncio
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async def test_parse_turn_raises_when_classifier_fails_twice():
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mock = MockLLMClient(canned=["nope", "still nope"])
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mock = MockLLMClient(canned=["nope", "still nope", "nope3"])
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with pytest.raises(RuntimeError):
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await parse_turn(
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mock,
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