125f48377a
Replaces Enterprise's account_invoice_extract with a Fusion-native pipeline: Stage 1 (text extraction): Tesseract OCRs the bill attachment via pytesseract + pdf2image. Pluggable OCRProvider adapter pattern allows future Mindee / Google Document AI / Ollama-vision backends. Stage 2 (field parsing): The fusion_accounting_ai LLMProvider reads the raw OCR text and returns structured invoice fields (vendor, invoice number, dates, amounts, line items) as JSON. Draft invoice fields are auto-populated for empty-only fields (never overwriting user-entered data). Vendor matching by name against res.partner with supplier_rank > 0. Adds: - account.move.ocr_state (selection: not_requested/pending/processing/ done/failed/manual) - account.move.ocr_raw_text, ocr_extracted_data (Json), ocr_backend, ocr_confidence - fusion.ocr.log (audit trail per OCR run) - res.company.fusion_ocr_enabled / fusion_ocr_default_backend / auto_run - /fusion/ocr/request_for_invoice JSON-RPC endpoint Backend availability detected at runtime via OCRProvider.is_available() classmethods. Tesseract 5.3.4 + pytesseract 0.3.13 + pdf2image 1.17.0 are installed in the container. Tests: 13 (TesseractAdapter availability + image OCR; flow tests for draft autofill, no-attachment guard, customer-invoice guard, ref-not- overwritten; field parser empty/clean-json/markdown-fence/bad-JSON/ provider-exception). All pass on westin-v19 OrbStack VM. Made-with: Cursor
41 lines
1.1 KiB
Python
41 lines
1.1 KiB
Python
"""OCRProvider contract - every backend must conform.
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Mirrors the LLMProvider pattern in fusion_accounting_ai. Future adapters
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(Mindee, Google Document AI, Ollama-vision) drop in alongside the default
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tesseract adapter without touching account.move.
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"""
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from abc import ABC, abstractmethod
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from dataclasses import dataclass, field
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@dataclass
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class OCRResult:
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raw_text: str = ''
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confidence: float = 0.0 # 0.0–1.0
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pages: int = 0
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backend: str = ''
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error: str = ''
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metadata: dict = field(default_factory=dict)
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class OCRProvider(ABC):
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"""Abstract OCR backend. Subclasses implement extract()."""
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name: str = 'base'
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@abstractmethod
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def extract(self, image_or_pdf_bytes: bytes, *, mimetype: str = 'application/pdf') -> OCRResult:
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"""Extract text from raw bytes.
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``mimetype`` hints whether to PDF-render (poppler) or image-decode
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(PIL) the bytes. Implementations should still inspect the byte
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signature for safety.
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"""
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...
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@classmethod
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def is_available(cls) -> bool:
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"""Return True if the backend's runtime deps are present."""
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return True
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