Joseph Doherty
49be3cf4b9
The turn endpoint was 500ing in multi-bot scenes whenever the classifier provider hiccuped on parse_turn — particularly visible after a guest was added and bots started exchanging turns. The traceback was 'classify failed for schema ParsedTurn with no default' because parse_turn was the only classify caller without a default. Two changes: - chat/services/turn_parse.py: parse_turn now passes a default that wraps the whole prose as one 'dialogue' segment. The narrative still fires on the prose; we lose finer-grained segment kinds (action vs dialogue vs ooc) on this turn, but the request returns cleanly. Updated the existing test that pinned the old RuntimeError contract. - chat/llm/classify.py: when retries are exhausted, log a WARNING with the schema name, last error type, and a snippet of the last raw text the model returned. Surfaces flapping classifiers in the uvicorn log for diagnosis without taking down the request. Suite: 471 passed in 11.7s.
98 lines
3.2 KiB
Python
98 lines
3.2 KiB
Python
import json
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import pytest
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from chat.llm.mock import MockLLMClient
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from chat.services.turn_parse import (
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ParsedTurn,
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TurnSegment,
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parse_turn,
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)
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@pytest.mark.asyncio
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async def test_parse_turn_three_segment_happy_path():
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canned = json.dumps(
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{
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"segments": [
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{"kind": "action", "text": "walks over"},
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{"kind": "dialogue", "text": "Hey."},
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{"kind": "ooc", "text": "player note"},
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]
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}
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)
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mock = MockLLMClient(canned=[canned])
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result = await parse_turn(
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mock,
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model="m",
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prose='*walks over* "Hey." ((player note))',
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)
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assert isinstance(result, ParsedTurn)
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assert len(result.segments) == 3
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kinds = [s.kind for s in result.segments]
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assert kinds == ["action", "dialogue", "ooc"]
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texts = [s.text for s in result.segments]
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assert texts == ["walks over", "Hey.", "player note"]
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assert all(isinstance(s, TurnSegment) for s in result.segments)
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@pytest.mark.asyncio
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async def test_parse_turn_pure_dialogue_single_segment():
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canned = json.dumps(
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{
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"segments": [
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{"kind": "dialogue", "text": "Hello there"},
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]
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}
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)
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mock = MockLLMClient(canned=[canned])
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result = await parse_turn(
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mock,
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model="m",
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prose='"Hello there"',
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)
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assert isinstance(result, ParsedTurn)
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assert len(result.segments) == 1
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assert result.segments[0].kind == "dialogue"
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assert result.segments[0].text == "Hello there"
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@pytest.mark.asyncio
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async def test_parse_turn_empty_prose_short_circuits_without_classifier_call():
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# No canned responses provided — if classify() is invoked it will raise
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# IndexError on the empty list. The short-circuit must prevent that.
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mock = MockLLMClient(canned=[])
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result = await parse_turn(mock, model="m", prose="")
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assert isinstance(result, ParsedTurn)
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assert result.segments == []
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# Whitespace-only prose must also short-circuit.
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result_ws = await parse_turn(mock, model="m", prose=" \n\t ")
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assert isinstance(result_ws, ParsedTurn)
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assert result_ws.segments == []
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@pytest.mark.asyncio
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async def test_parse_turn_falls_back_to_whole_prose_when_classifier_fails():
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"""A flapping classifier (3 invalid responses) no longer 500s the
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request. ``parse_turn`` returns the original prose as a single
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``dialogue`` segment so the turn flow can keep moving — the
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narrative will still fire on the prose, just without finer-grained
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segment classification.
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The old contract was ``RuntimeError`` (no default), but in
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production that took down the whole turn endpoint with a 500 the
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moment any classifier provider hiccuped — particularly painful in
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multi-bot scenes where every user turn pays the parse_turn cost.
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"""
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mock = MockLLMClient(canned=["nope", "still nope", "nope3"])
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result = await parse_turn(
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mock,
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model="m",
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prose='*shrugs* "whatever"',
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)
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assert len(result.segments) == 1
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assert result.segments[0].kind == "dialogue"
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assert result.segments[0].text == '*shrugs* "whatever"'
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assert result.intent == "narrative"
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