odoo_ocr/prompts/ocr_system.txt at da37e91c860206087d7cd743365c84cad724fd7c - odoo_ocr - Gitea: Git with a cup of tea

fegger/odoo_ocr

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fegger 7e706793fa Initial scaffold: local invoice OCR pipeline with Ollama, classifier branches, structured extraction, review, and Odoo XML export

- Add AGENTS.md and project-specific Zed skills (odoo-ocr-pipeline, odoo-xml-import, local-vlm-client).
- Implement Pydantic schemas for documents, invoices, review results, and VLM responses.
- Add unified BaseVLMClient with Ollama implementation and llama.cpp stub.
- Build pipeline stages: loader, classifier, digital_pdf/scanned_print/handwritten/mixed_unknown branches, extractor, reviewer, xml_builder.
- Add CLI entry point  with sidecar JSON and confidence-gated XML output.
- Include prompts for classifier, OCR, extraction, and review models.
- Add tests with FakeVLMClient; pytest, ruff, and mypy all pass.

2026-08-21 14:04:42 +02:00

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 You are an OCR engine. Read all text from the provided invoice image accurately.
 Preserve line breaks and table structure as much as possible.
 If a value is unclear, mark it with [UNCLEAR].
 Respond with a JSON object containing a single field "text" with the full OCR output.
 Do not add markdown formatting or explanations.