mlx-swift#7
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♻️ Current situation & Problem
This PR ports key OpenTSLM components to Swift and integrates them into HealthyLLM’s local inference flow.
Adds an in-app OpenTSLM encoder/projector pipeline.
Adds ECG fetching from HealthKit and ECG-first prompt behavior.
Improves local model staging/startup so the app can run from bundled/local assets without manual setup.
Includes large model/tokenizer/checkpoint assets required for local execution.
Related issue(s): #
⚙️ Release Notes
Added Swift OpenTSLM modules (encoder, projector, sample pipeline, inference service).
Added ECG data fetch + voltage extraction and automatic ECG starter prompt.
Added model setup flow:
Local model detection/staging
Download fallback UI when assets are missing
Environment-variable overrides for local debugging
Added OpenTSLM Swift package, CLI runner, and test fixtures.
Updated ignore rules for local large artifacts/datasets used during development.
📚 Documentation
README updated with ECG inference behavior.
Added/updated inline docs around model/runtime configuration and OpenTSLM flow.
Added Swift package metadata and runner usage/help text.
✅ Testing
Added unit tests for:
TransformerCNNEncoder
MLPProjector
SoftPromptInterleaver
Added fixture-based numerical parity checks (Python vs Swift encoder output).
CI/CodeCov should validate overall coverage and integration behavior.
Code of Conduct & Contributing Guidelines
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I agree to follow the Code of Conduct and Contributing Guidelines.