0057de4d12
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Add API-efficient daily trading mode for Gemini Free tier compatibility: ## Features - **Batch Decisions**: GeminiClient.decide_batch() analyzes multiple stocks in a single API call using compressed JSON format - **Daily Trading Mode**: run_daily_session() executes N sessions per day at configurable intervals (default: 4 sessions, 6 hours apart) - **Mode Selection**: TRADE_MODE env var switches between daily (batch) and realtime (per-stock) modes - **Requirements Log**: docs/requirements-log.md tracks user feedback chronologically for project evolution ## Configuration - TRADE_MODE: "daily" (default) | "realtime" - DAILY_SESSIONS: 1-10 (default: 4) - SESSION_INTERVAL_HOURS: 1-24 (default: 6) ## API Efficiency - 2 markets × 4 sessions = 8 API calls/day (within Free tier 20 calls) - 3 markets × 4 sessions = 12 API calls/day (within Free tier 20 calls) ## Testing - 9 new batch decision tests (all passing) - All existing tests maintained (298 passed) ## Documentation - docs/architecture.md: Trading Modes section with daily vs realtime - CLAUDE.md: Requirements Management section - docs/requirements-log.md: Initial entries for API efficiency needs Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
273 lines
11 KiB
Python
273 lines
11 KiB
Python
"""TDD tests for brain/gemini_client.py — written BEFORE implementation."""
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from __future__ import annotations
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from src.brain.gemini_client import GeminiClient
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# ---------------------------------------------------------------------------
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# Response Parsing
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# ---------------------------------------------------------------------------
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class TestResponseParsing:
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"""Gemini responses must be parsed into validated TradeDecision objects."""
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def test_valid_buy_response(self, settings):
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client = GeminiClient(settings)
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raw = '{"action": "BUY", "confidence": 90, "rationale": "Strong momentum"}'
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decision = client.parse_response(raw)
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assert decision.action == "BUY"
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assert decision.confidence == 90
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assert decision.rationale == "Strong momentum"
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def test_valid_sell_response(self, settings):
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client = GeminiClient(settings)
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raw = '{"action": "SELL", "confidence": 85, "rationale": "Overbought RSI"}'
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decision = client.parse_response(raw)
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assert decision.action == "SELL"
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def test_valid_hold_response(self, settings):
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client = GeminiClient(settings)
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raw = '{"action": "HOLD", "confidence": 95, "rationale": "Sideways market"}'
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decision = client.parse_response(raw)
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assert decision.action == "HOLD"
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# ---------------------------------------------------------------------------
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# Confidence Threshold Enforcement
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# ---------------------------------------------------------------------------
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class TestConfidenceThreshold:
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"""If confidence < 80, the action MUST be forced to HOLD."""
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def test_low_confidence_buy_becomes_hold(self, settings):
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client = GeminiClient(settings)
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raw = '{"action": "BUY", "confidence": 65, "rationale": "Weak signal"}'
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decision = client.parse_response(raw)
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assert decision.action == "HOLD"
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assert decision.confidence == 65
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def test_low_confidence_sell_becomes_hold(self, settings):
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client = GeminiClient(settings)
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raw = '{"action": "SELL", "confidence": 79, "rationale": "Uncertain"}'
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decision = client.parse_response(raw)
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assert decision.action == "HOLD"
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def test_exactly_threshold_is_allowed(self, settings):
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client = GeminiClient(settings)
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raw = '{"action": "BUY", "confidence": 80, "rationale": "Just enough"}'
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decision = client.parse_response(raw)
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assert decision.action == "BUY"
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# ---------------------------------------------------------------------------
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# Malformed JSON Handling
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# ---------------------------------------------------------------------------
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class TestMalformedJsonHandling:
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"""Gemini may return garbage — the parser must not crash."""
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def test_empty_string_returns_hold(self, settings):
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client = GeminiClient(settings)
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decision = client.parse_response("")
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assert decision.action == "HOLD"
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assert decision.confidence == 0
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def test_plain_text_returns_hold(self, settings):
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client = GeminiClient(settings)
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decision = client.parse_response("I think you should buy Samsung stock")
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assert decision.action == "HOLD"
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assert decision.confidence == 0
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def test_partial_json_returns_hold(self, settings):
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client = GeminiClient(settings)
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decision = client.parse_response('{"action": "BUY", "confidence":')
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assert decision.action == "HOLD"
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assert decision.confidence == 0
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def test_json_with_missing_fields_returns_hold(self, settings):
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client = GeminiClient(settings)
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decision = client.parse_response('{"action": "BUY"}')
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assert decision.action == "HOLD"
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assert decision.confidence == 0
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def test_json_with_invalid_action_returns_hold(self, settings):
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client = GeminiClient(settings)
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decision = client.parse_response(
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'{"action": "YOLO", "confidence": 99, "rationale": "moon"}'
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)
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assert decision.action == "HOLD"
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assert decision.confidence == 0
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def test_json_wrapped_in_markdown_code_block(self, settings):
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"""Gemini often wraps JSON in ```json ... ``` blocks."""
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client = GeminiClient(settings)
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raw = '```json\n{"action": "BUY", "confidence": 92, "rationale": "Good"}\n```'
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decision = client.parse_response(raw)
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assert decision.action == "BUY"
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assert decision.confidence == 92
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# ---------------------------------------------------------------------------
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# Prompt Construction
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# ---------------------------------------------------------------------------
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class TestPromptConstruction:
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"""The prompt sent to Gemini must include all required market data."""
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def test_prompt_contains_stock_code(self, settings):
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client = GeminiClient(settings)
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market_data = {
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"stock_code": "005930",
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"current_price": 72000,
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"orderbook": {"asks": [], "bids": []},
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"foreigner_net": -50000,
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}
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prompt = client.build_prompt_sync(market_data)
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assert "005930" in prompt
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def test_prompt_contains_price(self, settings):
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client = GeminiClient(settings)
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market_data = {
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"stock_code": "005930",
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"current_price": 72000,
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"orderbook": {"asks": [], "bids": []},
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"foreigner_net": -50000,
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}
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prompt = client.build_prompt_sync(market_data)
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assert "72000" in prompt
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def test_prompt_enforces_json_output_format(self, settings):
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client = GeminiClient(settings)
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market_data = {
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"stock_code": "005930",
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"current_price": 72000,
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"orderbook": {"asks": [], "bids": []},
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"foreigner_net": 0,
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}
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prompt = client.build_prompt_sync(market_data)
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assert "JSON" in prompt
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assert "action" in prompt
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assert "confidence" in prompt
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# ---------------------------------------------------------------------------
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# Batch Decision Making
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# ---------------------------------------------------------------------------
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class TestBatchDecisionParsing:
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"""Batch response parser must handle JSON arrays correctly."""
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def test_parse_valid_batch_response(self, settings):
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client = GeminiClient(settings)
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stocks_data = [
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{"stock_code": "AAPL", "current_price": 185.5},
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{"stock_code": "MSFT", "current_price": 420.0},
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]
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raw = """[
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{"code": "AAPL", "action": "BUY", "confidence": 85, "rationale": "Strong momentum"},
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{"code": "MSFT", "action": "HOLD", "confidence": 50, "rationale": "Wait for earnings"}
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]"""
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decisions = client._parse_batch_response(raw, stocks_data, token_count=100)
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assert len(decisions) == 2
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assert decisions["AAPL"].action == "BUY"
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assert decisions["AAPL"].confidence == 85
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assert decisions["MSFT"].action == "HOLD"
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assert decisions["MSFT"].confidence == 50
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def test_parse_batch_with_markdown_wrapper(self, settings):
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client = GeminiClient(settings)
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stocks_data = [{"stock_code": "AAPL", "current_price": 185.5}]
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raw = """```json
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[{"code": "AAPL", "action": "BUY", "confidence": 90, "rationale": "Good"}]
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```"""
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decisions = client._parse_batch_response(raw, stocks_data, token_count=100)
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assert decisions["AAPL"].action == "BUY"
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assert decisions["AAPL"].confidence == 90
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def test_parse_batch_empty_response_returns_hold_for_all(self, settings):
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client = GeminiClient(settings)
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stocks_data = [
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{"stock_code": "AAPL", "current_price": 185.5},
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{"stock_code": "MSFT", "current_price": 420.0},
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]
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decisions = client._parse_batch_response("", stocks_data, token_count=100)
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assert len(decisions) == 2
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assert decisions["AAPL"].action == "HOLD"
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assert decisions["AAPL"].confidence == 0
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assert decisions["MSFT"].action == "HOLD"
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def test_parse_batch_malformed_json_returns_hold_for_all(self, settings):
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client = GeminiClient(settings)
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stocks_data = [{"stock_code": "AAPL", "current_price": 185.5}]
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raw = "This is not JSON"
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decisions = client._parse_batch_response(raw, stocks_data, token_count=100)
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assert decisions["AAPL"].action == "HOLD"
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assert decisions["AAPL"].confidence == 0
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def test_parse_batch_not_array_returns_hold_for_all(self, settings):
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client = GeminiClient(settings)
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stocks_data = [{"stock_code": "AAPL", "current_price": 185.5}]
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raw = '{"code": "AAPL", "action": "BUY", "confidence": 90, "rationale": "Good"}'
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decisions = client._parse_batch_response(raw, stocks_data, token_count=100)
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assert decisions["AAPL"].action == "HOLD"
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assert decisions["AAPL"].confidence == 0
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def test_parse_batch_missing_stock_gets_hold(self, settings):
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client = GeminiClient(settings)
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stocks_data = [
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{"stock_code": "AAPL", "current_price": 185.5},
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{"stock_code": "MSFT", "current_price": 420.0},
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]
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# Response only has AAPL, MSFT is missing
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raw = '[{"code": "AAPL", "action": "BUY", "confidence": 85, "rationale": "Good"}]'
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decisions = client._parse_batch_response(raw, stocks_data, token_count=100)
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assert decisions["AAPL"].action == "BUY"
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assert decisions["MSFT"].action == "HOLD"
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assert decisions["MSFT"].confidence == 0
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def test_parse_batch_invalid_action_becomes_hold(self, settings):
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client = GeminiClient(settings)
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stocks_data = [{"stock_code": "AAPL", "current_price": 185.5}]
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raw = '[{"code": "AAPL", "action": "YOLO", "confidence": 90, "rationale": "Moon"}]'
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decisions = client._parse_batch_response(raw, stocks_data, token_count=100)
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assert decisions["AAPL"].action == "HOLD"
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def test_parse_batch_low_confidence_becomes_hold(self, settings):
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client = GeminiClient(settings)
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stocks_data = [{"stock_code": "AAPL", "current_price": 185.5}]
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raw = '[{"code": "AAPL", "action": "BUY", "confidence": 65, "rationale": "Weak"}]'
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decisions = client._parse_batch_response(raw, stocks_data, token_count=100)
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assert decisions["AAPL"].action == "HOLD"
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assert decisions["AAPL"].confidence == 65
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def test_parse_batch_missing_fields_gets_hold(self, settings):
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client = GeminiClient(settings)
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stocks_data = [{"stock_code": "AAPL", "current_price": 185.5}]
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raw = '[{"code": "AAPL", "action": "BUY"}]' # Missing confidence and rationale
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decisions = client._parse_batch_response(raw, stocks_data, token_count=100)
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assert decisions["AAPL"].action == "HOLD"
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assert decisions["AAPL"].confidence == 0
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