32 lines
1.6 KiB
Markdown
32 lines
1.6 KiB
Markdown
# Pending Guideline Fixes (September 2025)
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## Overview
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The following gaps violate our "no stubs, no synthetic data" policy and must
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be resolved before the dashboard can operate in production. Inline TODOs with
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matching wording have been added in the codebase.
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## Items
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1. **Prediction aggregation** – `TradingOrchestrator._get_all_predictions` still
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raises until the real ModelManager integration is written. The decision loop
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intentionally skips synthetic fallback signals.
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2. **Device handling for CNN checkpoints** – the orchestrator references
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`self.device` while loading weights; define and manage the device before the
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load occurs.
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3. **Trading balance access** – `TradingExecutor.get_balance` is currently
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`NotImplementedError`. Provide a real balance snapshot (simulation and live).
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4. **Fallback pricing** – `_get_current_price` now raises when no market price
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is available. Implement a real degraded-mode data path instead of hardcoded
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ETH/BTC prices.
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5. **Pivot context prerequisites** – ensure pivot bounds exist (or are freshly
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calculated) before requesting normalized pivot features.
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6. **Decision-fusion training features** – the dashboard still relies on random
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vectors for decision fusion. Replace them with real feature tensors derived
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from market data.
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## Next Steps
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- Prioritise restoring real prediction outputs so the orchestrator can resume
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trading decisions without synthetic stand-ins.
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- Sequence the remaining work so that downstream components (dashboard panels,
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executor feedback) receive genuine data once more.
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