Work#25
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…me details, and workflow controls ### Motivation - Improve robustness of AI inference runs by pre-validating the Cerebrium predict endpoint and tolerating alternate endpoint shapes, and make workflow runs more flexible for core/AI-only invocations. - Surface AI runtime metadata and the performance period start in email reports to aid triage and visibility of model/backend choices. - Simplify manager-produced reasoning in email output and enable a soft-cash neutral breakout path so the AI can opportunistically deploy capital when conditions warrant. ### Description - Updated GitHub Actions workflow `/.github/workflows/daily_trading_bot.yml` to add a `disable_core_trading` input, gate the core job on it, add a `Verify Cerebrium predict endpoint` preflight step, and wire that step into AI-run and fallback logic so inference is only attempted when the predict endpoint check succeeds. - Simplified email rationale handling in `email_notifier.py` by returning model-provided `decision_reason`/`reason` directly for both entry and close reasons, added inclusion of `performance_period_start` and an `AI RUNTIME` summary block for AI-tagged emails, and adjusted pipeline reporting logic to avoid duplicated content. - Extended candidate scoring behavior in `llm_trader.py` to support "neutral breakout" overrides and a soft-cash deployment heuristic that can convert sufficiently strong directional probabilities into a non-neutral score when no open AI positions exist. - Added `get_performance_period_start` to `positions.py` to provide a best-effort period start date used in reports. - Plumbed performance period and richer AI backend/model/fallback info into the reports in `main.py` and formatted AI runtime summary text that is included in the AI email. - Improved resilience of HTTP prediction calls in `trained_model_client.py` by attempting an alternate prediction URL on `404`, skipping strict `/health` probing for some Cerebrium endpoint shapes that return `404`, and exposing the alternate URL logic via `_alternate_prediction_url`. ### Testing - Ran the repository unit test suite with `pytest`; tests passed. - Ran linter checks with `flake8`; no new lint errors were reported. - Validated the workflow YAML via a CI workflow/linters; the workflow syntax and added conditional paths validated successfully.
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