extracting-mistral-ocr
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.
Quellinformationen
- Repository
- tristanmanchester/agent-skills
- Letzte Quellaktivität
- 21. Februar 2026 um 11:57
- Erkannte Sprache von SKILL.md
- Englisch
- Sterne
- 3
- Forks
- 2
Installationsoptionen
Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.
Quelldateien prüfen
Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.
Datei-Explorer
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SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau- 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 `--extract-header/--extract-footer` 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`
Auf GitHub ansehen