feat: productionize local service — fix signal pipeline, lower thresholds, add company-name ticker extraction
- Point Ollama to local instance via host.docker.internal, use gemma3 model - Remove Docker Ollama service (using host's Ollama instead) - Add company-name-to-ticker mapping (Apple→AAPL, Tesla→TSLA, etc.) for RSS articles - Lower signal thresholds for faster feedback with paper trading: - FinBERT confidence: 0.6→0.4, signal strength: 0.3→0.15 - News strategy: article_count 2→1, confidence 0.5→0.3, score ±0.3→±0.15 - Fix market data BarSet access bug (BarSet.__contains__ returns False incorrectly) - Fix market data SIP feed error by switching to IEX feed for free Alpaca accounts - Fix nginx proxy routing for /api/auth/* to api-gateway /auth/* - Add seed_sample_data script - Update tests for new thresholds and alpaca mock modules
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18 changed files with 749 additions and 185 deletions
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@ -188,9 +188,10 @@ class TestTradesListEndpoint:
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trade.signal_id = None
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trade.created_at = datetime(2024, 1, 1, tzinfo=timezone.utc)
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# session.execute will be called twice: count + data
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# session.execute is called twice: count + data (now returns tuples)
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count_result = _make_execute_result([], scalar=1)
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data_result = _make_execute_result([trade])
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data_result = MagicMock()
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data_result.all.return_value = [(trade, None)] # (Trade, strategy_name)
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session.execute = AsyncMock(side_effect=[count_result, data_result])
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resp = client.get("/api/trades")
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@ -242,8 +243,11 @@ class TestStrategiesEndpoint:
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strategy.active = True
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strategy.created_at = datetime(2024, 1, 1, tzinfo=timezone.utc)
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# First call: list strategies; subsequent calls: trades per strategy
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strategies_result = _make_execute_result([strategy])
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trades_result = _make_execute_result([]) # no trades
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session.execute = AsyncMock(
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return_value=_make_execute_result([strategy])
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side_effect=[strategies_result, trades_result]
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)
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resp = client.get("/api/strategies")
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@ -97,6 +97,9 @@ def _install_alpaca_mocks():
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historical_mod = ModuleType("alpaca.data.historical")
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historical_mod.StockHistoricalDataClient = MagicMock
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enums_mod = ModuleType("alpaca.data.enums")
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enums_mod.DataFeed = MagicMock()
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# Build the package hierarchy
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alpaca_mod = sys.modules.get("alpaca") or ModuleType("alpaca")
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data_mod = sys.modules.get("alpaca.data") or ModuleType("alpaca.data")
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@ -106,6 +109,7 @@ def _install_alpaca_mocks():
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sys.modules["alpaca.data.timeframe"] = timeframe_mod
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sys.modules["alpaca.data.requests"] = requests_mod
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sys.modules["alpaca.data.historical"] = historical_mod
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sys.modules["alpaca.data.enums"] = enums_mod
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# Install mocks before importing from market_data.main
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@ -271,17 +271,17 @@ class TestNewsDrivenStrategy:
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@pytest.mark.asyncio
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async def test_news_driven_no_signal_low_confidence(self, strategy: NewsDrivenStrategy) -> None:
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"""No signal when avg_confidence is too low (<=0.5)."""
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"""No signal when avg_confidence is too low (<=0.3)."""
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market = _market()
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sentiment = _sentiment(avg_score=0.8, avg_confidence=0.4, article_count=5)
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sentiment = _sentiment(avg_score=0.8, avg_confidence=0.2, article_count=5)
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signal = await strategy.evaluate("AAPL", market, sentiment)
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assert signal is None
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@pytest.mark.asyncio
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async def test_news_driven_no_signal_few_articles(self, strategy: NewsDrivenStrategy) -> None:
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"""No signal when article_count < 2."""
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"""No signal when article_count < 1."""
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market = _market()
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sentiment = _sentiment(avg_score=0.8, avg_confidence=0.7, article_count=1)
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sentiment = _sentiment(avg_score=0.8, avg_confidence=0.7, article_count=0)
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signal = await strategy.evaluate("AAPL", market, sentiment)
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assert signal is None
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@ -311,7 +311,7 @@ class TestNewsDrivenStrategy:
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@pytest.mark.asyncio
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async def test_news_driven_neutral_score(self, strategy: NewsDrivenStrategy) -> None:
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"""No signal when avg_score is between -0.3 and 0.3 (neutral)."""
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"""No signal when avg_score is between -0.15 and 0.15 (neutral)."""
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market = _market()
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sentiment = _sentiment(avg_score=0.1, avg_confidence=0.9, article_count=10)
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signal = await strategy.evaluate("AAPL", market, sentiment)
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@ -319,9 +319,9 @@ class TestNewsDrivenStrategy:
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@pytest.mark.asyncio
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async def test_news_driven_boundary_confidence(self, strategy: NewsDrivenStrategy) -> None:
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"""No signal when avg_confidence is exactly 0.5 (threshold is >0.5)."""
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"""No signal when avg_confidence is exactly 0.3 (threshold is >0.3)."""
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market = _market()
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sentiment = _sentiment(avg_score=0.8, avg_confidence=0.5, article_count=5)
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sentiment = _sentiment(avg_score=0.8, avg_confidence=0.3, article_count=5)
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signal = await strategy.evaluate("AAPL", market, sentiment)
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assert signal is None
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