Skill: tristanmanchester/extracting-mistral-ocr (version 1.0.0)

--- name: extracting-mistral-ocr description: >- Extracts text, tables, and images from PDFs (including scanned PDFs) using the Mistral OCR API. Use when user asks to OCR a PDF/image, extract text from a PDF, parse a scanned document, convert a PDF to Markdown, or extract structured fields from a document. compatibility: >- Requires network access and a MISTRAL_API_KEY environment variable. Expects Python 3.9+ and the mistralai package. allowed-tools: "Read,Write,Bash(python:*)" metadata: author: generated-by-chatgpt version: 0.1.0 api: mistral default-model: mistral-ocr-latest --- # Mistral OCR PDF extraction ## Quick start (default) Run the bundled script to OCR a local PDF and write Markdown + JSON outputs: ```bash python {baseDir}/scripts/mistral_ocr_extract.py --input path/to/file.pdf --out out/ocr ``` Output directory layout: - `combined.md` (all pages concatenated) - `pages/page-000.md` (per-page markdown) - `raw_response.json` (full OCR response) - `images/` (decoded embedded images, if requested) - `tables/` (separate tables, if requested) ## Workflow 1. **Pick input mode** - **Local PDF** (most common): upload via Files API, then OCR via `file_id`. - **Public URL**: OCR directly via `document_url`. 2. **Choose output fidelity** (defaults are safe for RAG) - Keep `table_format=inline` unless the user explicitly wants tables split out. - Set `--include-image-base64` when the user needs figures/diagrams extracted. - Use [REDACTED_SECRET] if header/footer noise hurts downstream search. 3. **Run OCR** - Use `scripts/mistral_ocr_extract.py` to produce a deterministic on-disk artefact set. 4. **(Optional) Structured extraction from the whole document** - If the user wants fields (invoice totals, contract parties, etc.), provide an annotation prompt. - The OCR API can return a document-level `document_annotation` in addition to page markdown. Example: ```bash python {baseDir}/scripts/mistral_ocr_extract.py \ --input invoice.pdf \ --out out/invoice \ --annotation-prompt "Extract supplier_name, invoice_number, invoice_date (ISO-8601), currency, total_amount. Return JSON." \ --annotation-format json_object ``` ## Decision rules - **If the PDF is local and not publicly accessible**, upload it (the script does this automatically). - **If the PDF URL is private or requires authentication**, do not pass it as `document_url`; upload instead. - **If output quality is critical**, prefer `table_format=html` for downstream parsing over brittle regex. ## Common failure modes - **Missing `MISTRAL_API_KEY`**: set it in the environment before running. - **URL OCR fails**: the URL likely is not publicly accessible; upload the file. - **Large files**: upload supports large files, but very large PDFs may need page selection (`--pages`) or batch processing. ## References - API + parameters: `references/mistral_ocr_api.md` - Output mapping rules (placeholders to extracted images/tables): `references/output_mapping.md` - Example annotation prompts for common document types: `references/annotation_prompts.md`


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