Three root causes fixed:
1. docker-compose.yml — celery-worker and celery-beat missing PYTHONPATH=/app
ForkPoolWorker processes inherit sys.path with '' (CWD), but fork can change
CWD so lazy imports like `from db.session import ...` raised ModuleNotFoundError.
Adding PYTHONPATH=/app ensures /app is always explicit in the path.
2. provider_config.py — lmstudio SUPPORTS_JSON_MODE set to False
LM Studio only accepts response_format type 'json_schema' or 'text', not
'json_object'. GenericOpenAIProvider now omits response_format for lmstudio
and relies on parse_classification() fallback (same path as Gemini).
3. generic_openai_provider.py — max_tokens raised 1024→4096 (classify) / 256→1024 (suggest)
Qwen3 thinking models (like qwen/qwen3.5-9b) consume reasoning tokens from the
same budget. With max_tokens=1024 the model exhausts the budget in the thinking
trace, leaving content=''. 4096 gives room for both thinking and the JSON output.
Also updates lmstudio PROVIDER_DEFAULTS model to qwen/qwen3.5-9b (confirmed loaded
in LM Studio) and context_chars to 32_000 (Qwen3 context window).
Tested: classify(invoice_text, ['Finance','Legal','HR']) → topics=['Finance'] ✓
Backend tests: 376 passed ✓
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
