Add offline merchant category suggestions
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- [x] 4.1 Implement monthly dashboard aggregation services for totals, category breakdowns, and derived comparisons.
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- [x] 4.2 Implement the dashboard API route and render dashboard sections for month-to-date metrics and comparisons.
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- [ ] 4.3 Implement the `OpenAI` insight service with structured monthly snapshot input and sparse-month fallback logic.
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- [ ] 4.4 Implement insight generation and display in the dashboard, including persisted monthly insight records.
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- [ ] 4.3 Implement the offline `Ollama` insight service with structured monthly snapshot input and sparse-month fallback logic.
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- [ ] 4.4 Implement insight generation and display in the dashboard, including persisted monthly insight records and offline-runtime fallback messaging.
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## 5. Verification
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## 5. Offline categorization
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- [ ] 5.1 Add automated tests for validation, persistence, dashboard aggregates, and insight fallback behavior.
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- [ ] 5.2 Verify the primary user flows in the browser, including expense entry, paycheck entry, dashboard updates, and insight generation.
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- [x] 5.1 Implement deterministic merchant-to-category mapping for known merchants.
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- [x] 5.2 Implement a local-model category suggestion endpoint for unknown merchants.
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- [x] 5.3 Update the expense entry flow to auto-fill known merchants and require confirmation for model-generated suggestions.
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- [x] 5.4 Add local runtime availability handling so category suggestion falls back to manual selection without cloud calls.
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## 6. Verification
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- [ ] 6.1 Add automated tests for validation, persistence, dashboard aggregates, offline insight fallback behavior, and category suggestion rules.
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- [ ] 6.2 Verify the primary user flows in the browser, including expense entry, paycheck entry, dashboard updates, category suggestion, and insight generation.
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