feat: Phase 5 – PDF/Bild-Beleg-Import (lokal, Tesseract-OCR)
Backend: - services/ocr: PDF-Text via PyMuPDF, OCR (Tesseract) für Scans/Bilder, heuristischer Parser (Datum + Betrag je Zeile, CH/DE/US-Beträge). - routers/documents: /documents/preview (Upload -> Text -> Kandidaten -> gemeinsame Prüf-/Buchungslogik des CSV-Imports). csv_import refaktoriert: detect_rows() von CSV und Beleg gemeinsam genutzt. - requirements: PyMuPDF, pytesseract, pillow; install.sh installiert tesseract-ocr (+ deu). pytest: Heuristik-Parser und PDF-Vorschau. Frontend: - Import-Seite: CSV/PDF-Umschalter; PDF-Modus mit Beleg-Auslesen, extrahiertem Text zur Kontrolle und Best-Effort-Hinweis; gleiche Prüfansicht + Buchen. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
This commit is contained in:
Guido
Claude Opus 4.8
@@ -24,6 +24,7 @@ from .routers import (
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budgets,
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categories,
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dashboard,
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documents,
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imports,
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rates,
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settings as settings_router,
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@@ -105,6 +106,7 @@ api.include_router(transactions.router)
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api.include_router(budgets.router)
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api.include_router(dashboard.router)
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api.include_router(imports.router)
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api.include_router(documents.router)
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api.include_router(rates.router)
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app.include_router(api)
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@@ -0,0 +1,34 @@
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"""PDF-/Bild-Beleg-Import (Phase 5, lokal). Nutzt die Prüf-/Buchungslogik des CSV-Imports."""
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from fastapi import APIRouter, Depends, File, Form, HTTPException, UploadFile
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from sqlalchemy.orm import Session
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from ..database import get_db
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from ..deps import get_current_user, get_owned
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from ..models import Account, User
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from ..services import csv_import, ocr
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router = APIRouter(prefix="/documents", tags=["documents"])
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@router.post("/preview")
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async def preview(
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file: UploadFile = File(...),
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account_id: int = Form(...),
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db: Session = Depends(get_db),
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user: User = Depends(get_current_user),
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) -> dict:
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account = get_owned(db, Account, account_id, user)
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data = await file.read()
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try:
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text = ocr.extract_text(data, file.filename or "", file.content_type or "")
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except ocr.ExtractionError as exc:
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raise HTTPException(status_code=400, detail=str(exc))
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candidates = ocr.parse_transactions(text)
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rows = csv_import.detect_rows(db, user, account, candidates)
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return {
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"rows": rows,
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"text": text[:8000],
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"count": len(rows),
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"filename": file.filename or "",
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}
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@@ -153,16 +153,45 @@ def _apply_rules(rules: list[CategorizationRule], payee: str, purpose: str) -> i
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return None
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def build_preview(db: Session, user: User, account: Account, template: ImportTemplate, data: bytes) -> list[dict]:
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def parse_file_to_candidates(data: bytes, template: ImportTemplate) -> list[dict]:
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"""Zerlegt die Datei anhand des Templates in rohe Kandidaten-Zeilen."""
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cmap = json.loads(template.column_map or "{}")
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def col(field: str) -> int | None:
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idx = cmap.get(field)
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return idx if isinstance(idx, int) and idx >= 0 else None
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rows = read_rows(data, template)
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out: list[dict] = []
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for r in read_rows(data, template):
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def cell(field: str) -> str:
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c = col(field)
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return r[c].strip() if c is not None and c < len(r) else ""
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# Identifikatoren aller Konten des Nutzers -> Konto-ID (für Transfer-Erkennung).
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d = parse_date(cell("date"), template.date_format)
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if template.amount_mode == AmountMode.debit_credit:
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debit = parse_amount(cell("debit"), template.decimal_sep)
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credit = parse_amount(cell("credit"), template.decimal_sep)
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amount = (credit or 0) - (abs(debit) if debit else 0)
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elif template.amount_mode == AmountMode.abs_expense:
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a = parse_amount(cell("amount"), template.decimal_sep)
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amount = -abs(a) if a is not None else None
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else:
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amount = parse_amount(cell("amount"), template.decimal_sep)
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out.append({
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"date": d.isoformat() if d else None,
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"amount_cents": amount,
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"payee": cell("payee") or None,
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"purpose": cell("purpose") or None,
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"counterparty_iban": normalize_iban(cell("counterparty_iban")) or None,
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})
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return out
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def detect_rows(db: Session, user: User, account: Account, candidates: list[dict]) -> list[dict]:
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"""Reichert Kandidaten an: Typ, Auto-Kategorie, interner Transfer, Duplikat.
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Wird von CSV- UND Beleg-Import genutzt (gleiche Prüf-/Buchungslogik)."""
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idents: dict[str, int] = {}
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for value_norm, acc_id in (
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db.query(AccountIdentifier.value_norm, AccountIdentifier.account_id)
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@@ -177,39 +206,25 @@ def build_preview(db: Session, user: User, account: Account, template: ImportTem
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.order_by(CategorizationRule.priority.desc(), CategorizationRule.hits.desc())
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.all()
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)
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existing = {
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h[0]
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for h in db.query(Transaction.import_hash).filter(
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Transaction.owner_id == user.id, Transaction.import_hash.isnot(None)
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)
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}
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seen_in_file: set[str] = set()
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seen: set[str] = set()
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out: list[dict] = []
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for i, r in enumerate(rows):
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def cell(field: str) -> str:
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c = col(field)
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return r[c].strip() if c is not None and c < len(r) else ""
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d = parse_date(cell("date"), template.date_format)
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if template.amount_mode == AmountMode.debit_credit:
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debit = parse_amount(cell("debit"), template.decimal_sep)
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credit = parse_amount(cell("credit"), template.decimal_sep)
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amount = (credit or 0) - (abs(debit) if debit else 0)
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elif template.amount_mode == AmountMode.abs_expense:
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a = parse_amount(cell("amount"), template.decimal_sep)
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amount = -abs(a) if a is not None else None
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else:
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amount = parse_amount(cell("amount"), template.decimal_sep)
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payee = cell("payee")
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purpose = cell("purpose")
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iban = normalize_iban(cell("counterparty_iban"))
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for i, cand in enumerate(candidates):
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d_iso = cand.get("date")
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amount = cand.get("amount_cents")
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payee = cand.get("payee")
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purpose = cand.get("purpose")
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iban = cand.get("counterparty_iban")
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d = date.fromisoformat(d_iso) if d_iso else None
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valid = d is not None and amount is not None and amount != 0
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ttype = "transfer" if False else ("expense" if (amount or 0) < 0 else "income")
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ttype = "expense" if (amount or 0) < 0 else "income"
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category_id: int | None = None
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to_account_id: int | None = None
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@@ -218,11 +233,11 @@ def build_preview(db: Session, user: User, account: Account, template: ImportTem
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ttype = "transfer"
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to_account_id = other
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else:
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category_id = _apply_rules(rules, payee, purpose)
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category_id = _apply_rules(rules, payee or "", purpose or "")
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h = import_hash(account.id, d, amount, payee)
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is_dup = h in existing or h in seen_in_file
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seen_in_file.add(h)
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is_dup = h in existing or h in seen
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seen.add(h)
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out.append({
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"index": i,
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@@ -242,6 +257,10 @@ def build_preview(db: Session, user: User, account: Account, template: ImportTem
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return out
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def build_preview(db: Session, user: User, account: Account, template: ImportTemplate, data: bytes) -> list[dict]:
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return detect_rows(db, user, account, parse_file_to_candidates(data, template))
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# --- Verbuchen -------------------------------------------------------------
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@@ -0,0 +1,127 @@
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"""PDF-/Bild-Belege lokal auslesen (kein Cloud-Dienst).
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- Digitale PDFs: Text direkt via PyMuPDF.
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- Gescannte PDFs / Bilder: OCR via Tesseract (pytesseract).
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Danach ein heuristischer Parser, der Zeilen mit Datum + Betrag findet. Das ist
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bewusst Best-Effort – das Ergebnis landet in derselben Prüfansicht wie der
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CSV-Import und wird dort korrigiert.
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"""
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import io
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import re
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from datetime import datetime
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from decimal import Decimal, InvalidOperation
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try: # PyMuPDF (Text + Rendern)
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import fitz # type: ignore
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except Exception: # noqa: BLE001
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fitz = None
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try: # OCR
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import pytesseract # type: ignore
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from PIL import Image # type: ignore
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except Exception: # noqa: BLE001
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pytesseract = None
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Image = None
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class ExtractionError(RuntimeError):
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pass
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def _image_to_text(data: bytes) -> str:
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if pytesseract is None or Image is None:
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raise ExtractionError("OCR nicht verfügbar (pytesseract/Pillow/Tesseract fehlen).")
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img = Image.open(io.BytesIO(data))
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return pytesseract.image_to_string(img, lang="deu+eng")
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def _pdf_to_text(data: bytes) -> str:
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if fitz is None:
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raise ExtractionError("PDF-Verarbeitung nicht verfügbar (PyMuPDF fehlt).")
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parts: list[str] = []
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with fitz.open(stream=data, filetype="pdf") as doc:
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for page in doc:
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txt = page.get_text()
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if txt and txt.strip():
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parts.append(txt)
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elif pytesseract is not None and Image is not None:
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pix = page.get_pixmap(dpi=200)
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img = Image.open(io.BytesIO(pix.tobytes("png")))
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parts.append(pytesseract.image_to_string(img, lang="deu+eng"))
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return "\n".join(parts)
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def extract_text(data: bytes, filename: str, content_type: str) -> str:
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name = (filename or "").lower()
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if name.endswith(".pdf") or content_type == "application/pdf":
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return _pdf_to_text(data)
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return _image_to_text(data)
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# --- Heuristischer Zeilen-Parser -------------------------------------------
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DATE_RE = re.compile(r"\b(\d{4}-\d{2}-\d{2}|\d{1,2}[./]\d{1,2}[./]\d{2,4})\b")
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# Betrag: entweder mit Tausender-Gruppen (1'234.56 / 1.234,56) oder schlicht (3000.00).
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AMOUNT_RE = re.compile(r"[-+]?(?:\d{1,3}(?:['.,\s]\d{3})+|\d+)[.,]\d{2}(?!\d)")
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_DATE_FORMATS = ["%Y-%m-%d", "%d.%m.%Y", "%d.%m.%y", "%d/%m/%Y", "%d/%m/%y"]
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def _norm_date(token: str):
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for fmt in _DATE_FORMATS:
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try:
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return datetime.strptime(token, fmt).date()
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except ValueError:
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continue
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return None
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def _parse_amount_auto(s: str) -> int | None:
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"""Betrag mit automatisch erkanntem Dezimaltrenner (CH/DE/US) -> Cent."""
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s = s.strip()
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neg = s.startswith("-") or (s.startswith("(") and s.endswith(")"))
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m = re.search(r"[.,](\d{2})$", s)
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if not m:
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return None
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int_digits = re.sub(r"\D", "", s[: m.start()])
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frac = m.group(1)
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try:
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val = Decimal(f"{int_digits or '0'}.{frac}")
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except InvalidOperation:
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return None
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cents = int(val * 100)
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return -cents if neg else cents
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def parse_transactions(text: str) -> list[dict]:
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"""Findet Zeilen mit Datum + Betrag und macht daraus Kandidaten-Buchungen."""
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rows: list[dict] = []
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for line in text.splitlines():
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line = line.strip()
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if len(line) < 6:
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continue
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dm = DATE_RE.search(line)
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if not dm:
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continue
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d = _norm_date(dm.group(0))
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if d is None:
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continue
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rest = f"{line[: dm.start()]} {line[dm.end():]}"
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amounts = AMOUNT_RE.findall(rest)
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if not amounts:
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continue
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amount = _parse_amount_auto(amounts[0])
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if amount is None or amount == 0:
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continue
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desc = rest
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for a in amounts:
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desc = desc.replace(a, " ")
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desc = re.sub(r"\s+", " ", desc).strip(" -–|;,.")
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rows.append({
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"date": d.isoformat(),
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"amount_cents": amount,
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"payee": desc[:120] or None,
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"purpose": None,
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"counterparty_iban": None,
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})
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return rows
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@@ -8,4 +8,9 @@ argon2-cffi==23.1.0
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python-multipart==0.0.20
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httpx==0.28.1
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python-dateutil==2.9.0.post0
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# PDF/Bild-Import (Phase 5): Text aus PDFs (PyMuPDF) und OCR (Tesseract) für Scans/Bilder.
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PyMuPDF==1.25.1
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pytesseract==0.3.13
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pillow==11.1.0
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pytest==8.3.4
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@@ -0,0 +1,55 @@
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import io
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import pytest
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fitz = pytest.importorskip("fitz")
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def _account(admin):
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r = admin.post("/api/accounts", json={"name": "Beleg", "type": "girokonto", "currency": "EUR"})
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assert r.status_code == 201
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return r.json()
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def _make_pdf() -> bytes:
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doc = fitz.open()
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page = doc.new_page()
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page.insert_text((50, 72), "15.03.2026 REWE Supermarkt Zuerich -50.00")
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page.insert_text((50, 96), "25.03.2026 Gehalt Firma AG 3000.00")
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page.insert_text((50, 120), "Kein Datum hier, nur Text 12.34")
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return doc.tobytes()
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def test_parse_transactions_heuristic():
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from app.services import ocr
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text = (
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"Kontoauszug März 2026\n"
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"15.03.2026 REWE Supermarkt -50,00\n"
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"2026-03-25 Gehalt 3'000.00\n"
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"Zwischensumme\n"
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)
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rows = ocr.parse_transactions(text)
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assert len(rows) == 2
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assert rows[0]["date"] == "2026-03-15"
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assert rows[0]["amount_cents"] == -5000
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assert "REWE" in rows[0]["payee"]
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assert rows[1]["date"] == "2026-03-25"
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assert rows[1]["amount_cents"] == 300000 # Schweizer Tausender-Apostroph
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def test_pdf_document_preview(admin):
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acc = _account(admin)
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pdf = _make_pdf()
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r = admin.post(
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"/api/documents/preview",
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files={"file": ("beleg.pdf", io.BytesIO(pdf), "application/pdf")},
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data={"account_id": str(acc["id"])},
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)
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assert r.status_code == 200, r.text
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body = r.json()
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assert body["count"] == 2
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rows = body["rows"]
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kinds = {(row["type"], row["amount_cents"]) for row in rows}
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assert ("expense", -5000) in kinds
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assert ("income", 300000) in kinds
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+2
-1
@@ -48,7 +48,8 @@ fi
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info "Installiere Systempakete (Python, Build-Tools, git, curl) …"
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export DEBIAN_FRONTEND=noninteractive
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apt-get update -y
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apt-get install -y python3 python3-venv python3-dev build-essential curl ca-certificates git
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apt-get install -y python3 python3-venv python3-dev build-essential curl ca-certificates git \
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tesseract-ocr tesseract-ocr-deu
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# --- Python-Version prüfen (3.11+ erforderlich) ------------------------------
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PY_VER="$(python3 -c 'import sys; print("%d.%d" % sys.version_info[:2])' 2>/dev/null || echo 0.0)"
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+3
-2
@@ -28,8 +28,9 @@ Bank-Templates (Trennzeichen/Dezimal/Datum/Spaltenmapping/Vorzeichen), lernende
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Auto-Kategorisierung, Prüfansicht, Duplikat-Erkennung, interne-Transfer-Erkennung
|
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via IBAN, Batch-Undo. Vorgefertigte Bank-Templates folgen aus Nutzer-Beispielen.
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## Phase 5 – PDF/Bild-Import (Stretch)
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Lokal (pdfplumber/pypdf + Tesseract-OCR), speist dieselbe Prüfansicht.
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## Phase 5 – PDF/Bild-Import (Stretch) ✅
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Lokal: PyMuPDF (PDF-Text) + Tesseract-OCR (Scans/Bilder), heuristischer
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Zeilen-Parser (Datum + Betrag), speist dieselbe Prüfansicht. Best-Effort.
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## Querschnitt – Backup/Export
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DB-Backup-Download + Export je Entität (CSV/JSON); dokumentierte LXC-Sicherung.
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@@ -198,4 +198,7 @@ export const api = {
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importCommit: (body) => request("/imports/commit", { method: "POST", body }),
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importBatches: () => request("/imports/batches"),
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undoImportBatch: (id) => request(`/imports/batches/${id}`, { method: "DELETE" }),
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|
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// PDF/Bild-Beleg
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documentPreview: (formData) => request("/documents/preview", { method: "POST", formData }),
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};
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@@ -560,3 +560,14 @@ tr.row-invalid {
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tr.row-dup {
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opacity: 0.55;
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}
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.doc-text {
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max-height: 240px;
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overflow: auto;
|
||||
font-size: 0.78rem;
|
||||
white-space: pre-wrap;
|
||||
color: var(--muted);
|
||||
background: var(--surface-2);
|
||||
padding: var(--sp-3);
|
||||
border-radius: var(--radius-sm);
|
||||
margin-top: var(--sp-2);
|
||||
}
|
||||
|
||||
@@ -197,13 +197,18 @@
|
||||
"targetAccount": "Zielkonto"
|
||||
},
|
||||
"import": {
|
||||
"title": "CSV-Import",
|
||||
"title": "Import",
|
||||
"modeCsv": "CSV",
|
||||
"modeDoc": "PDF · Bild",
|
||||
"readDoc": "Beleg auslesen",
|
||||
"docHint": "PDF-/Bild-Erkennung ist Best-Effort — bitte jede Zeile prüfen und ggf. korrigieren.",
|
||||
"extractedText": "Extrahierter Text (zur Kontrolle)",
|
||||
"step1": "1 · Konto & Datei",
|
||||
"step2": "2 · Format",
|
||||
"step3": "3 · Spalten zuordnen",
|
||||
"step4": "4 · Prüfen & buchen",
|
||||
"account": "Zielkonto",
|
||||
"file": "CSV-Datei",
|
||||
"file": "Datei",
|
||||
"preset": "Bank-Vorlage (vorgefertigt)",
|
||||
"template": "Eigene Vorlage",
|
||||
"templateManual": "Manuell einstellen",
|
||||
|
||||
@@ -197,13 +197,18 @@
|
||||
"targetAccount": "Target account"
|
||||
},
|
||||
"import": {
|
||||
"title": "CSV import",
|
||||
"title": "Import",
|
||||
"modeCsv": "CSV",
|
||||
"modeDoc": "PDF · Image",
|
||||
"readDoc": "Read document",
|
||||
"docHint": "PDF/image recognition is best-effort — please check and fix every row.",
|
||||
"extractedText": "Extracted text (for reference)",
|
||||
"step1": "1 · Account & file",
|
||||
"step2": "2 · Format",
|
||||
"step3": "3 · Map columns",
|
||||
"step4": "4 · Review & import",
|
||||
"account": "Target account",
|
||||
"file": "CSV file",
|
||||
"file": "File",
|
||||
"preset": "Bank preset",
|
||||
"template": "My template",
|
||||
"templateManual": "Configure manually",
|
||||
|
||||
@@ -41,11 +41,13 @@ export default function Import() {
|
||||
const [presets, setPresets] = useState([]);
|
||||
const [batches, setBatches] = useState([]);
|
||||
|
||||
const [mode, setMode] = useState("csv"); // "csv" | "doc"
|
||||
const [accountId, setAccountId] = useState("");
|
||||
const [file, setFile] = useState(null);
|
||||
const [config, setConfig] = useState(defaultConfig());
|
||||
const [raw, setRaw] = useState(null);
|
||||
const [rows, setRows] = useState(null);
|
||||
const [docText, setDocText] = useState("");
|
||||
const [busy, setBusy] = useState(false);
|
||||
const [saveName, setSaveName] = useState("");
|
||||
|
||||
@@ -117,6 +119,19 @@ export default function Import() {
|
||||
} catch (e) { toast(e.message, "error"); } finally { setBusy(false); }
|
||||
}
|
||||
|
||||
async function loadDoc() {
|
||||
if (!file || !accountId) { toast(t("import.needFileAccount"), "error"); return; }
|
||||
setBusy(true);
|
||||
try {
|
||||
const fd = new FormData();
|
||||
fd.append("file", file);
|
||||
fd.append("account_id", accountId);
|
||||
const res = await api.documentPreview(fd);
|
||||
setRows(res.rows.map((r) => ({ ...r })));
|
||||
setDocText(res.text || "");
|
||||
} catch (e) { toast(e.message, "error"); } finally { setBusy(false); }
|
||||
}
|
||||
|
||||
async function commit() {
|
||||
setBusy(true);
|
||||
try {
|
||||
@@ -168,7 +183,15 @@ export default function Import() {
|
||||
|
||||
return (
|
||||
<div>
|
||||
<h1>{t("import.title")}</h1>
|
||||
<div className="page-head">
|
||||
<h1>{t("import.title")}</h1>
|
||||
<div className="seg" style={{ width: 240, marginBottom: 0 }}>
|
||||
<button type="button" className={`seg-btn${mode === "csv" ? " active" : ""}`}
|
||||
onClick={() => { setMode("csv"); setRows(null); setRaw(null); setDocText(""); }}>{t("import.modeCsv")}</button>
|
||||
<button type="button" className={`seg-btn${mode === "doc" ? " active" : ""}`}
|
||||
onClick={() => { setMode("doc"); setRows(null); setRaw(null); setDocText(""); }}>{t("import.modeDoc")}</button>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{/* Schritt 1: Konto + Datei */}
|
||||
<div className="card">
|
||||
@@ -182,11 +205,20 @@ export default function Import() {
|
||||
</label>
|
||||
<label className="grow">
|
||||
<span>{t("import.file")}</span>
|
||||
<input ref={fileRef} type="file" accept=".csv,text/csv,text/plain"
|
||||
onChange={(e) => { setFile(e.target.files?.[0] || null); setRaw(null); setRows(null); }} />
|
||||
<input ref={fileRef} type="file"
|
||||
accept={mode === "doc" ? ".pdf,application/pdf,image/*" : ".csv,text/csv,text/plain"}
|
||||
onChange={(e) => { setFile(e.target.files?.[0] || null); setRaw(null); setRows(null); setDocText(""); }} />
|
||||
</label>
|
||||
</div>
|
||||
<div className="row">
|
||||
{mode === "doc" && (
|
||||
<>
|
||||
<button className="btn primary" onClick={loadDoc} disabled={busy || !file}>
|
||||
<Icon name="search" size={15} /> {t("import.readDoc")}
|
||||
</button>
|
||||
<p className="muted small" style={{ marginTop: "var(--sp-2)" }}>{t("import.docHint")}</p>
|
||||
</>
|
||||
)}
|
||||
<div className="row" style={{ display: mode === "csv" ? undefined : "none" }}>
|
||||
{presets.length > 0 && (
|
||||
<label className="grow">
|
||||
<span>{t("import.preset")}</span>
|
||||
@@ -208,7 +240,8 @@ export default function Import() {
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{/* Schritt 2: Format */}
|
||||
{/* Schritt 2: Format (nur CSV) */}
|
||||
{mode === "csv" && (
|
||||
<div className="card">
|
||||
<h2>{t("import.step2")}</h2>
|
||||
<div className="row">
|
||||
@@ -266,6 +299,17 @@ export default function Import() {
|
||||
<Icon name="search" size={15} /> {t("import.readFile")}
|
||||
</button>
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* Extrahierter Text (PDF/Bild) */}
|
||||
{mode === "doc" && docText && (
|
||||
<div className="card">
|
||||
<details>
|
||||
<summary className="muted">{t("import.extractedText")}</summary>
|
||||
<pre className="doc-text">{docText}</pre>
|
||||
</details>
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* Schritt 3: Spaltenzuordnung */}
|
||||
{raw && (
|
||||
|
||||
Reference in New Issue
Block a user