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ci: fix lint baseline and stabilize failing main tests
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agentson
2026-03-01 20:17:13 +09:00
parent 6f047a6daf
commit 5730f0db2a
64 changed files with 1041 additions and 1380 deletions
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54
src/brain/gemini_client.py
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@@ -25,12 +25,12 @@ from typing import Any
from google import genai
from src.config import Settings
from src.data.news_api import NewsAPI, NewsSentiment
from src.data.economic_calendar import EconomicCalendar
from src.data.market_data import MarketData
from src.brain.cache import DecisionCache
from src.brain.prompt_optimizer import PromptOptimizer
from src.config import Settings
from src.data.economic_calendar import EconomicCalendar
from src.data.market_data import MarketData
from src.data.news_api import NewsAPI, NewsSentiment
logger = logging.getLogger(__name__)
@@ -159,16 +159,12 @@ class GeminiClient:
return ""
# Check for upcoming high-impact events
upcoming = self._economic_calendar.get_upcoming_events(
days_ahead=7, min_impact="HIGH"
)
upcoming = self._economic_calendar.get_upcoming_events(days_ahead=7, min_impact="HIGH")
if upcoming.high_impact_count == 0:
return ""
lines = [
f"Upcoming High-Impact Events: {upcoming.high_impact_count} in next 7 days"
]
lines = [f"Upcoming High-Impact Events: {upcoming.high_impact_count} in next 7 days"]
if upcoming.next_major_event is not None:
event = upcoming.next_major_event
@@ -180,9 +176,7 @@ class GeminiClient:
# Check for earnings
earnings_date = self._economic_calendar.get_earnings_date(stock_code)
if earnings_date is not None:
lines.append(
f" Earnings: {stock_code} on {earnings_date.strftime('%Y-%m-%d')}"
)
lines.append(f" Earnings: {stock_code} on {earnings_date.strftime('%Y-%m-%d')}")
return "\n".join(lines)
@@ -235,9 +229,7 @@ class GeminiClient:
# Add foreigner net if non-zero
if market_data.get("foreigner_net", 0) != 0:
market_info_lines.append(
f"Foreigner Net Buy/Sell: {market_data['foreigner_net']}"
)
market_info_lines.append(f"Foreigner Net Buy/Sell: {market_data['foreigner_net']}")
market_info = "\n".join(market_info_lines)
@@ -249,8 +241,7 @@ class GeminiClient:
market_info += f"\n\n{external_context}"
json_format = (
'{"action": "BUY"|"SELL"|"HOLD", '
'"confidence": <int 0-100>, "rationale": "<string>"}'
'{"action": "BUY"|"SELL"|"HOLD", "confidence": <int 0-100>, "rationale": "<string>"}'
)
return (
f"You are a professional {market_name} trading analyst.\n"
@@ -289,15 +280,12 @@ class GeminiClient:
# Add foreigner net if non-zero
if market_data.get("foreigner_net", 0) != 0:
market_info_lines.append(
f"Foreigner Net Buy/Sell: {market_data['foreigner_net']}"
)
market_info_lines.append(f"Foreigner Net Buy/Sell: {market_data['foreigner_net']}")
market_info = "\n".join(market_info_lines)
json_format = (
'{"action": "BUY"|"SELL"|"HOLD", '
'"confidence": <int 0-100>, "rationale": "<string>"}'
'{"action": "BUY"|"SELL"|"HOLD", "confidence": <int 0-100>, "rationale": "<string>"}'
)
return (
f"You are a professional {market_name} trading analyst.\n"
@@ -339,25 +327,19 @@ class GeminiClient:
data = json.loads(cleaned)
except json.JSONDecodeError:
logger.warning("Malformed JSON from Gemini — defaulting to HOLD")
return TradeDecision(
action="HOLD", confidence=0, rationale="Malformed JSON response"
)
return TradeDecision(action="HOLD", confidence=0, rationale="Malformed JSON response")
# Validate required fields
if not all(k in data for k in ("action", "confidence", "rationale")):
logger.warning("Missing fields in Gemini response — defaulting to HOLD")
# Preserve raw text in rationale so prompt_override callers (e.g. pre_market_planner)
# can extract their own JSON format from decision.rationale (#245)
return TradeDecision(
action="HOLD", confidence=0, rationale=raw
)
return TradeDecision(action="HOLD", confidence=0, rationale=raw)
action = str(data["action"]).upper()
if action not in VALID_ACTIONS:
logger.warning("Invalid action '%s' from Gemini — defaulting to HOLD", action)
return TradeDecision(
action="HOLD", confidence=0, rationale=f"Invalid action: {action}"
)
return TradeDecision(action="HOLD", confidence=0, rationale=f"Invalid action: {action}")
confidence = int(data["confidence"])
rationale = str(data["rationale"])
@@ -445,9 +427,7 @@ class GeminiClient:
# not a parsed TradeDecision. Skip parse_response to avoid spurious
# "Missing fields" warnings and return the raw response directly. (#247)
if "prompt_override" in market_data:
logger.info(
"Gemini raw response received (prompt_override, tokens=%d)", token_count
)
logger.info("Gemini raw response received (prompt_override, tokens=%d)", token_count)
# Not a trade decision — don't inflate _total_decisions metrics
return TradeDecision(
action="HOLD", confidence=0, rationale=raw, token_count=token_count
@@ -546,9 +526,7 @@ class GeminiClient:
# Batch Decision Making (for daily trading mode)
# ------------------------------------------------------------------
async def decide_batch(
self, stocks_data: list[dict[str, Any]]
) -> dict[str, TradeDecision]:
async def decide_batch(self, stocks_data: list[dict[str, Any]]) -> dict[str, TradeDecision]:
"""Make decisions for multiple stocks in a single API call.
This is designed for daily trading mode to minimize API usage