gavindiazandClaude Code
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Full project import for the self-hosted code hosting (https://code.aifunny.ltd/gavindiaz/my-NexusTradingForexBot.git). Includes the live-freshness + scaler-hash fixes for the permanent STALE dashboard (tick_pipeline now_utc stamps; infer_probabilities computes model_input_hash on the actual scaled 70D tensor), the data-fetch default-path fix, the g29 web-auth test fixes, and a Chinese user manual (使用手册.md) for the web dashboard. Scratch diagnostic scripts (check*.py, contain a live web-auth token) and the .kilo/ agent-worktree directory are gitignored, not committed. Co-Authored-By: Claude Code <noreply@anthropic.com>
55 lines
1.8 KiB
Python
55 lines
1.8 KiB
Python
"""Shared fixture helpers for the Agent-2 log-hygiene regression suite.
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Seeds UNKNOWN_PROVENANCE orphan rows into a real ExperienceLedger the same
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way the production sweep classifies them (no dispatch row + no gate signal
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=> honest unknown provenance).
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"""
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from __future__ import annotations
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from datetime import UTC, datetime
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def seed_unknown_orphans(ledger, *, count: int) -> None:
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"""Creates `count` executed+closed experiences with NO outcome and NO
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dispatch evidence -> evaluate_sample() == UNKNOWN_PROVENANCE."""
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from nexus_scalp.experience.models import (
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ExperienceRecord,
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FeatureSnapshot,
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StrategyContext,
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)
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base = datetime(2026, 8, 18, tzinfo=UTC)
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for i in range(count):
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rec = ExperienceRecord(
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experience_id=f"exp_orphan_{i:05d}",
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request_id=f"req_orphan_{i:05d}",
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idempotency_key=f"idem_orphan_{i:05d}",
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symbol="XAUUSD",
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timeframe="M1",
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decision_timestamp=base,
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strategy_id="strat_flood",
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strategy_version="1.0.0",
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context=StrategyContext(
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strategy_id="strat_flood",
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symbol="XAUUSD",
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session="LONDON",
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regime="TRENDING",
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volatility_regime="NORMAL",
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trend_state="BULLISH",
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),
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feature_snapshot=FeatureSnapshot(
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feature_schema_id="scalp_v1", feature_dimension=50, values=[0.0] * 50
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),
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action="BUY_LIMIT",
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entry_reason="SMC",
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model_probability=0.6,
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signal_confidence=0.6,
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proposed_entry=2000.0,
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stop_loss=1990.0,
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take_profit=2020.0,
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risk_reward_ratio=2.0,
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approved_volume=0.1,
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)
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ledger.record_experience(rec)
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