Курнат Андрей
53 lines
1.7 KiB
Python
53 lines
1.7 KiB
Python
from __future__ import annotations
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from crypto_spot_bot.llm_advisor import LlmAdvisor, _extract_json
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from crypto_spot_bot.storage import Storage
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def test_extract_json_from_fenced_response() -> None:
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data = _extract_json(
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"""
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```json
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{"market_regime":"range","risk_level":"low","confidence_adjustment":0.02}
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```
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"""
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)
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assert data["market_regime"] == "range"
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assert data["confidence_adjustment"] == 0.02
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def test_llm_advisor_parse_clamps_adjustment(make_settings, tmp_path) -> None:
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settings = make_settings(tmp_path, llm_advisor_max_adjustment=0.05)
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advisor = LlmAdvisor(settings, Storage(settings.database_path))
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advice = advisor._parse(
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"BTCUSDT",
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'{"market_regime":"breakout","risk_level":"high","confidence_adjustment":0.5,'
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'"block_entry":true,"grid_suitable":false,"reason_ru":"тест"}',
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)
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assert advice.model == "gemma4:e4b"
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assert advice.market_regime == "breakout"
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assert advice.risk_level == "high"
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assert advice.confidence_adjustment == 0.05
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assert advice.block_entry is True
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def test_storage_records_llm_advice(make_settings, tmp_path) -> None:
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settings = make_settings(tmp_path)
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storage = Storage(settings.database_path)
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storage.insert_llm_advice(
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symbol="BTCUSDT",
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model="gemma4:e4b",
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prompt_json={"symbol": "BTCUSDT"},
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response_text='{"confidence_adjustment":0}',
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advice_json={"confidence_adjustment": 0.0, "reason_ru": "нейтрально"},
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)
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items = storage.recent_llm_advice(limit=1)
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assert items[0]["model"] == "gemma4:e4b"
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assert items[0]["prompt"]["symbol"] == "BTCUSDT"
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assert items[0]["advice"]["reason_ru"] == "нейтрально"
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