MattssonandClaude Opus 4.7
1af977950b
* Refactor bookkeeping error handling and introduce new error classes - Introduced new error classes for better error categorization: - JournalEntryNotBalancedError - FiscalPeriodNotFoundError - EntryDateOutsideFiscalPeriodError - JournalEntryNotFoundError - CannotReverseNonPostedError - CannotCorrectNonPostedError - EntryAlreadyReversedError - CurrencyRevaluationAlreadyExistsError - InvalidMappingResultError - BookkeepingDatabaseError - Updated existing functions in engine.ts and transaction-entries.ts to throw specific errors instead of generic ones. - Enhanced error response handling in get-error-message.ts to provide localized messages for new error types. - Added unit tests for new error classes and error handling functions to ensure correctness and coverage. * feat(ai): implement AI proposal application and persistence - Add apply.ts to handle the application of AI proposals, including match and booking steps. - Introduce persist.ts for inserting and managing AI requests and proposals, ensuring unique constraints. - Create re-validate.ts for validating proposals before acceptance, checking for stale conditions. - Define database migrations for ai_requests and ai_proposals tables, including constraints and indexes. - Enhance journal_entries with AI provenance tracking, linking entries to AI proposals. - Update categorization_templates to distinguish AI-corrected templates. - Add company settings for toggling AI flow and managing backfill processes. - Extend processing_history to include AI-related events for better tracking. * feat: add uncategorized transactions API and UI for transaction selection - Implemented a new API endpoint for fetching uncategorized transactions with pagination and filtering options. - Created ChangeTransactionDialog component for selecting alternative transactions based on AI proposals. - Developed ReceiptDetailDialog to display detailed information about receipts, including upload functionality. - Added TransactionDetailDialog for viewing transaction details with links to the transaction list. - Introduced receipt quality assessment logic to evaluate extracted receipt data. - Implemented feature flagging for the AI bookkeeping agent to control availability in different environments. * feat: add manual receipt extraction dialog and integrate AWS Textract for expense analysis - Added ManualExtractDialog component for user input when AI fails to extract receipt data. - Implemented ReceiptsList component to manage and display uploaded receipts, including upload and rescan functionalities. - Introduced Textract integration for analyzing expenses, extracting fields like total, vendor, and date. - Updated package.json to include @aws-sdk/client-textract dependency. * fix(ai): handle livsmedel VAT transition (12% → 6%) in booking prompt and re-validate guard Add date-aware guidance to BOOKING_SYSTEM_PROMPT for the temporary livsmedel VAT cut (Prop. 2025/26:55, 2026-04-01 to 2027-12-31), with restaurang/servering carve-out at 12%. Add a re-validate safety net that rejects clearly-stale rate labels for grocery-chain merchants relative to the entry date. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
78 lines
3.0 KiB
SQL
78 lines
3.0 KiB
SQL
-- ai_requests: structured asks from the AI agent to the user.
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--
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-- When the AI agent cannot produce a proposal because something is missing or
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-- ambiguous (blurry receipt, no candidate transactions, uncertain VAT), it
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-- creates an ai_requests row instead of an ai_proposals row. The UI renders
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-- these as actionable cards with typed forms.
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--
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-- One open request per (subject, request_type) enforced by a partial unique
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-- index so the orchestrator can safely re-issue on retries without creating
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-- duplicates.
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CREATE TABLE IF NOT EXISTS public.ai_requests (
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id uuid PRIMARY KEY DEFAULT uuid_generate_v4(),
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company_id uuid NOT NULL REFERENCES public.companies(id) ON DELETE CASCADE,
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-- What the request is about
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subject_type text NOT NULL
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CHECK (subject_type IN ('inbox_item')),
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subject_id uuid NOT NULL,
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-- What the AI is asking for
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request_type text NOT NULL
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CHECK (request_type IN (
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'reupload_document',
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'pick_transaction',
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'specify_vat',
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'clarify_business_private',
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'needs_manual'
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)),
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message text NOT NULL,
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required_fields jsonb,
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options jsonb,
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-- Lifecycle
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status text NOT NULL DEFAULT 'open'
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CHECK (status IN ('open', 'resolved', 'dismissed')),
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response_json jsonb,
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resolved_at timestamptz,
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resolved_by_user_id uuid REFERENCES auth.users(id) ON DELETE SET NULL,
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-- Provenance
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model text,
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prompt_version text,
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created_at timestamptz NOT NULL DEFAULT now(),
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updated_at timestamptz NOT NULL DEFAULT now()
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);
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-- Only one open request per (subject, request_type) at a time
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CREATE UNIQUE INDEX IF NOT EXISTS idx_ai_requests_one_open_per_subject_type
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ON public.ai_requests (subject_type, subject_id, request_type)
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WHERE status = 'open';
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-- Lookup by company
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CREATE INDEX IF NOT EXISTS idx_ai_requests_company_status
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ON public.ai_requests (company_id, status);
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-- Lookup by subject (for cascading when the inbox item is processed)
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CREATE INDEX IF NOT EXISTS idx_ai_requests_subject
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ON public.ai_requests (subject_type, subject_id);
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-- RLS: company-scoped using user_company_ids()
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ALTER TABLE public.ai_requests ENABLE ROW LEVEL SECURITY;
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CREATE POLICY "ai_requests_select" ON public.ai_requests
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FOR SELECT USING (company_id IN (SELECT public.user_company_ids()));
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CREATE POLICY "ai_requests_insert" ON public.ai_requests
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FOR INSERT WITH CHECK (company_id IN (SELECT public.user_company_ids()));
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CREATE POLICY "ai_requests_update" ON public.ai_requests
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FOR UPDATE USING (company_id IN (SELECT public.user_company_ids()));
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-- updated_at trigger
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CREATE TRIGGER ai_requests_updated_at
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BEFORE UPDATE ON public.ai_requests
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FOR EACH ROW EXECUTE FUNCTION public.update_updated_at_column();
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NOTIFY pgrst, 'reload schema';
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