4 Commits (2aba6418e6885b9eefeda12bb0079512053a04b4)

Author SHA1 Message Date
I Luk Kim 2395a0c0c3 feat: PEAD mid-cap strategy + pipeline hardening + README cleanup
- Implement PEAD 7% Long+Short strategy with mid-cap universe expansion
- Add Stock Oracle screener/company clients, text sentiment features
- Enhance backtest engine: short-side execution, walk-forward CV, MFE/MAE analysis
- Harden pipeline: sequential Oracle API calls, scoring recalibration (event_quality 65%)
- Add experiment configs for 60+ strategy variants and journal tracking
- Add review/analysis CLI tools
- Remove obsolete dev/phase0-4 design documents and analysis scripts
- Clean README to reflect only implemented features (remove unbuilt adapters/engines)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
5 months ago
I Luk Kim 9d3427e24e fix: disable Qwen3.5 thinking mode and switch OllamaClient to sync httpx
- Add `think: False` and `num_ctx: 8192` to Ollama payload:
  Qwen3.5 extended thinking mode generated 1300+ internal reasoning
  tokens before each response, adding 30-60s latency per LLM call.
  Disabling it reduces parse time from 600s timeout to ~13s.

- Rewrite OllamaClient to use sync httpx.Client inside asyncio.to_thread():
  Async httpx inside an active asyncpg SQLAlchemy session context on
  Python 3.13 hung indefinitely. Synchronous httpx in a thread pool
  completely isolates Ollama I/O from the asyncio event loop.

- Fix filing_poller to set issuer_id/symbol_id on Document records:
  Missing FK caused feature_builder to reject all events with
  event_no_symbol warning. Now looks up IssuerMaster/SymbolMaster
  by ticker before creating Document rows.

- Update test_llm_client to mock _sync_call instead of _client attr.
- Raise ollama_timeout default to 600s for large document processing.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
5 months ago
I Luk Kim bbe0e31150 feat: implement Phase 3 -- LLM enrichment, labeler, review queue, dataset export
- libs/llm/: OllamaClient (httpx async, retry), LLMCacheStore (SHA-256 DB cache),
  prompt registry (event_classifier_v1), LLMParser (cache→prompt→validate→repair)
- libs/parser/merger.py: rule+LLM canonical merge with provenance tracking,
  conflict detection (both confident + disagree), should_queue_for_review()
- libs/db/models.py: LLMCallCache, ReviewItem, EventLabel 3개 ORM 모델 추가
- libs/db/migrations/versions/0002_phase3_tables.py: Phase 3 Alembic migration
- libs/labeler/: filing_time_bucket→reaction_date, 1D/3D/5D fwd return, MFE/MAE
- libs/review/queue.py: create(dedup)/resolve/list ReviewItem
- libs/export/snapshot_export.py: temporal split + Parquet + manifest.json
- apps/: label_generator, dataset_export, review CLI, gold set evaluator
- 42개 신규 테스트 추가 (unit 32 + integration 4 + replay 1) — 152/152 통과
- libs/common/config.py: OLLAMA_URL/MODEL/TIMEOUT 설정 추가
- libs/common/logging.py: bugfix — add_logger_name incompatible with PrintLoggerFactory

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
5 months ago
I Luk Kim 0471018dd8 feat: implement ACE-F v1 Phase 1 -- Stock Oracle 기반 이벤트 파이프라인
Stock Oracle (localhost:18001)을 단일 데이터 소스로 사용하는 미국 주식
이벤트 스윙 트레이딩 시스템의 Phase 1 구현체.

주요 구성:
- libs/oracle_client/: Stock Oracle REST 클라이언트 (filings, price, financial, fred, finra)
- libs/common/: config, logging, time_utils, ids, retries, file_store
- libs/db/: SQLAlchemy 2.0 모델 12개 + Alembic 마이그레이션 0001
- libs/parser/: 규칙 기반 파서 (텍스트 정규화, JSON Schema 검증, LLM 스텁)
- libs/features/: 시장/이벤트 피처 계산기
- apps/pipeline/: filing_poller → filing_fetcher → event_parser → feature_builder
- apps/sync/: macro_sync (FRED), short_volume_sync (FINRA), issuer_sync
- tests/: 단위 81개 + 리플레이 5개 전체 통과, lint clean

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
5 months ago