Files
signal-platform/app/routers/ingestion.py
T
dennisthiessen d53ed972d1
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Add multi-factor conviction gate to activation
Make "qualified" mean an edge candidate, not just R:R + confidence.
The gate now also requires (all admin-configurable, defaults on):
- high conviction: recommended_action LONG_HIGH / SHORT_HIGH only
- clean read: risk_level Low (no contradicting signals)
- probable primary target: best target probability >= min (default 60)

- Shared predicate: app/services/qualification.py +
  frontend/src/lib/qualification.ts (mirrored)
- Activation config extended (min_target_probability,
  require_high_conviction, exclude_conflicts) with bool-aware
  get/update + validation
- /trades/performance switched to ?qualified_only=true, applying
  the full gate server-side; confidence breakdown stays unfiltered
- Dashboard "Qualified", Signals "Qualified only" toggle, and
  Track Record all use the one gate; Admin gains the new controls

Sentiment provider runtime config (prior change) included.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-06-13 11:50:42 +02:00

202 lines
7.6 KiB
Python

"""Ingestion router: trigger data fetches from the market data provider.
Provides both a single-source OHLCV endpoint and a comprehensive
fetch-all endpoint that collects OHLCV + sentiment + fundamentals
in one call with per-source status reporting.
"""
from __future__ import annotations
import logging
from datetime import date
from fastapi import APIRouter, Depends, Query
from sqlalchemy import delete, select
from sqlalchemy.ext.asyncio import AsyncSession
from app.config import settings
from app.dependencies import get_db, require_access
from app.exceptions import ProviderError
from app.models.ohlcv import OHLCVRecord
from app.models.settings import IngestionProgress
from app.models.ticker import Ticker
from app.models.user import User
from app.providers.alpaca import AlpacaOHLCVProvider
from app.providers.fundamentals_chain import build_fundamental_provider_chain
from app.services.rr_scanner_service import scan_ticker
from app.services.sentiment_provider_service import build_sentiment_provider
from app.schemas.common import APIEnvelope
from app.services import (
fundamental_service,
ingestion_service,
scoring_service,
sentiment_service,
sr_service,
)
logger = logging.getLogger(__name__)
router = APIRouter(tags=["ingestion"])
def _get_provider() -> AlpacaOHLCVProvider:
"""Build the OHLCV provider from current settings."""
if not settings.alpaca_api_key or not settings.alpaca_api_secret:
raise ProviderError("Alpaca API credentials not configured")
return AlpacaOHLCVProvider(settings.alpaca_api_key, settings.alpaca_api_secret)
@router.post("/ingestion/fetch/{symbol}", response_model=APIEnvelope)
async def fetch_symbol(
symbol: str,
start_date: date | None = Query(None, description="Start date (YYYY-MM-DD)"),
end_date: date | None = Query(None, description="End date (YYYY-MM-DD)"),
force_refetch: bool = Query(False, description="Delete existing OHLCV data and re-fetch split-adjusted history"),
_user: User = Depends(require_access),
db: AsyncSession = Depends(get_db),
):
"""Fetch all data sources for a ticker: OHLCV, sentiment, and fundamentals.
Returns a per-source breakdown so the frontend can show exactly what
succeeded and what failed.
"""
symbol_upper = symbol.strip().upper()
sources: dict[str, dict] = {}
# If force_refetch is requested, clear old OHLCV and ingestion progress
# so the backfill logic pulls a full year of fresh split-adjusted data.
if force_refetch:
try:
result = await db.execute(
select(Ticker).where(Ticker.symbol == symbol_upper)
)
ticker_obj = result.scalar_one_or_none()
if ticker_obj:
await db.execute(
delete(OHLCVRecord).where(OHLCVRecord.ticker_id == ticker_obj.id)
)
await db.execute(
delete(IngestionProgress).where(IngestionProgress.ticker_id == ticker_obj.id)
)
await db.commit()
logger.info("force_refetch: cleared OHLCV and progress for %s", symbol_upper)
except Exception as exc:
logger.error("force_refetch cleanup failed for %s: %s", symbol_upper, exc)
# --- OHLCV ---
try:
provider = _get_provider()
result = await ingestion_service.fetch_and_ingest(
db, provider, symbol_upper, start_date, end_date
)
sources["ohlcv"] = {
"status": "ok" if result.status in ("complete", "partial") else "error",
"records": result.records_ingested,
"message": result.message,
}
except Exception as exc:
logger.error("OHLCV fetch failed for %s: %s", symbol_upper, exc)
sources["ohlcv"] = {"status": "error", "records": 0, "message": str(exc)}
# --- Sentiment ---
try:
sent_provider = await build_sentiment_provider(db)
except ProviderError as exc:
sent_provider = None
sources["sentiment"] = {"status": "skipped", "message": str(exc)}
if sent_provider is not None:
try:
data = await sent_provider.fetch_sentiment(symbol_upper)
await sentiment_service.store_sentiment(
db,
symbol=symbol_upper,
classification=data.classification,
confidence=data.confidence,
source=data.source,
timestamp=data.timestamp,
reasoning=data.reasoning,
citations=data.citations,
)
sources["sentiment"] = {
"status": "ok",
"classification": data.classification,
"confidence": data.confidence,
"message": None,
}
except Exception as exc:
logger.error("Sentiment fetch failed for %s: %s", symbol_upper, exc)
sources["sentiment"] = {"status": "error", "message": str(exc)}
# --- Fundamentals ---
if settings.fmp_api_key or settings.finnhub_api_key or settings.alpha_vantage_api_key:
try:
fundamentals_provider = build_fundamental_provider_chain()
fdata = await fundamentals_provider.fetch_fundamentals(symbol_upper)
await fundamental_service.store_fundamental(
db,
symbol=symbol_upper,
pe_ratio=fdata.pe_ratio,
revenue_growth=fdata.revenue_growth,
earnings_surprise=fdata.earnings_surprise,
market_cap=fdata.market_cap,
unavailable_fields=fdata.unavailable_fields,
)
sources["fundamentals"] = {"status": "ok", "message": None}
except Exception as exc:
logger.error("Fundamentals fetch failed for %s: %s", symbol_upper, exc)
sources["fundamentals"] = {"status": "error", "message": str(exc)}
else:
sources["fundamentals"] = {
"status": "skipped",
"message": "No fundamentals provider key configured",
}
# --- Derived pipeline: S/R levels ---
try:
levels = await sr_service.recalculate_sr_levels(db, symbol_upper)
sources["sr_levels"] = {
"status": "ok",
"count": len(levels),
"message": None,
}
except Exception as exc:
logger.error("S/R recalc failed for %s: %s", symbol_upper, exc)
sources["sr_levels"] = {"status": "error", "message": str(exc)}
# --- Derived pipeline: scores ---
try:
score_payload = await scoring_service.get_score(db, symbol_upper)
sources["scores"] = {
"status": "ok",
"composite_score": score_payload.get("composite_score"),
"missing_dimensions": score_payload.get("missing_dimensions", []),
"message": None,
}
except Exception as exc:
logger.error("Score recompute failed for %s: %s", symbol_upper, exc)
sources["scores"] = {"status": "error", "message": str(exc)}
# --- Derived pipeline: scanner ---
try:
setups = await scan_ticker(
db,
symbol_upper,
rr_threshold=settings.default_rr_threshold,
)
sources["scanner"] = {
"status": "ok",
"setups_found": len(setups),
"message": None,
}
except Exception as exc:
logger.error("Scanner run failed for %s: %s", symbol_upper, exc)
sources["scanner"] = {"status": "error", "message": str(exc)}
# Always return success — per-source breakdown tells the full story
return APIEnvelope(
status="success",
data={"symbol": symbol_upper, "sources": sources},
error=None,
)