{"data":{"slug":"nameetp-pdfmux","name":"pdfmux","tagline":"PDF extraction that checks its own work. #2 reading order accuracy — zero AI, zero GPU, zero cost.","github_url":"https://github.com/NameetP/pdfmux","owner":"NameetP","repo":"pdfmux","owner_avatar_url":"https://avatars.githubusercontent.com/u/93118951?v=4","primary_language":"Python","stars":74,"forks":12,"topics":["ai-agent","docling","document-parsing","llm","mcp","ocr","opendataloader","pdf","pdf-extraction","pdf-to-json","pdf-to-markdown","python","rag","self-healing","structured-extraction"],"archived":false,"github_pushed_at":"2026-07-07T14:04:29+00:00","maintenance_label":"Very active","url":"https://www.graphcanon.com/tools/nameetp-pdfmux","markdown_url":"https://www.graphcanon.com/tools/nameetp-pdfmux.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/nameetp-pdfmux","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=nameetp-pdfmux","description":"PDF extraction that checks its own work. #2 reading order accuracy — zero AI, zero GPU, zero cost.","homepage_url":"https://pdfmux.com","license":"MIT","open_issues":6,"watchers":0,"ai_summary":null,"readme_excerpt":"## Install\n\n```bash\npip install pdfmux\n```\n\nThat handles digital PDFs. **For any real-world batch, install `pdfmux[ocr]` too** — almost every directory of PDFs has at least one scan, and without OCR those pages return empty text:\n\n```bash\npip install \"pdfmux[ocr]\"             # ⭐ recommended — RapidOCR for scanned pages (~200MB, CPU)\n```\n\nOther backends, by document type:\n\n```bash\npip install \"pdfmux[tables]\"          # Docling — table-heavy docs (~500MB)\npip install \"pdfmux[opendataloader]\"  # OpenDataLoader — complex layouts (Java 11+)\npip install \"pdfmux[marker]\"          # Marker — neural extraction for academic papers\npip install \"pdfmux[llm]\"             # Gemini fallback (default LLM)\npip install \"pdfmux[llm-claude]\"      # Claude (Sonnet / Opus)\npip install \"pdfmux[llm-openai]\"      # GPT-4o family\npip install \"pdfmux[llm-ollama]\"      # Ollama (any local model)\npip install \"pdfmux[llm-mistral]\"     # Mistral OCR API ($0.002/page)\npip install \"pdfmux[llm-all]\"         # all LLM providers (incl. Gemma 4 via Gemini key)\npip install \"pdfmux[watch]\"           # `pdfmux watch <dir>` auto-convert on change\npip install \"pdfmux[all]\"             # everything\n```\n\nRequires Python 3.11+.\n\n---\n\n# cost-aware extraction with budget cap\npdfmux convert report.pdf --mode economy --budget 0.50\n\n---\n\n# predict cost before running anything\npdfmux estimate big-report.pdf --llm-provider gemini\n\n---\n\n# │ Extractor        │ Status      │ Version │ Install                          │\n\n---\n\n# │ Docling          │ missing     │ --      │ pip install pdfmux[tables]       │\n\n---\n\n# │ Surya            │ missing     │ --      │ pip install pdfmux[ocr-heavy]    │\n\n---\n\n# {\"event\":\"classified\",\"page_count\":312,\"plan\":\"pymupdf+gemini-fallback\"}\n\n---\n\n# Default install — already includes python-bidi for RTL reordering\npip install pdfmux\n\n---\n\n## Cost Modes\n\n| Mode | Behavior | Typical cost |\n|------|----------|-------------|\n| economy | Rule-based backends only. No LLM calls. | $0/page |\n| balanced | LLM only for pages that fail rule-based extraction. | ~$0.002/page avg |\n| premium | LLM on every page for maximum quality. | ~$0.01/page |\n\nSet a hard budget cap: `--budget 0.50` stops LLM calls when spend reaches $0.50 per document.","github_created_at":"2026-03-03T16:32:24+00:00","created_at":"2026-07-11T10:49:25.858071+00:00","updated_at":"2026-07-11T10:49:29.055493+00:00","categories":[{"slug":"ai-agents","name":"AI Agents","url":"https://www.graphcanon.com/categories/ai-agents","markdown_url":"https://www.graphcanon.com/categories/ai-agents.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/ai-agents"},{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"},{"slug":"vector-databases","name":"Vector Databases","url":"https://www.graphcanon.com/categories/vector-databases","markdown_url":"https://www.graphcanon.com/categories/vector-databases.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/vector-databases"}],"tags":[{"slug":"docling","name":"docling"},{"slug":"pdf","name":"pdf"},{"slug":"llm","name":"llm"},{"slug":"opendataloader","name":"opendataloader"},{"slug":"ocr","name":"ocr"},{"slug":"document-parsing","name":"document-parsing"},{"slug":"mcp","name":"mcp"},{"slug":"ai-agent","name":"ai-agent"}],"trust":{"provenance":{"is_fork":false,"github_id":1171815558,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-07-11T10:49:26.611Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":7,"days_since_push":3,"last_release_at":"2026-06-15T11:27:44Z"},"security_summary":{"status":"findings","scanner":"mcp_manifest@v1","low_count":0,"high_count":0,"last_scan_at":"2026-07-11T10:49:27.415Z","medium_count":1,"scan_profile":"mcp_manifest","critical_count":0}},"capability_facts":{"mcp":{"source":"repo_scan","observed_at":"2026-07-11T10:49:27.033Z","server_manifest":false},"scan":{"source":"repo_scan","observed_at":"2026-07-11T10:49:27.033Z"},"deploy":{"source":"dockerfile:Dockerfile","self_host":true,"observed_at":"2026-07-11T10:49:27.033Z","managed_saas":false},"has_cli":{"value":true,"source":"pyproject.toml:[project.scripts]","observed_at":"2026-07-11T10:49:27.033Z"},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-07-11T10:49:27.033Z"},"has_docker":{"value":true,"source":"dockerfile:Dockerfile","observed_at":"2026-07-11T10:49:27.033Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-07-11T10:49:27.033Z"}}}}