PDF kuenda kuMarkdown
Kushandiswa kwekutengesa OK
380 + mamodheru
Hapana mvura
Hapana kumbobvira kushanyira
Model:
+ GPT-5, Claude, Gemini
Drop a PDF — AI inoshandura kuita yakachena GitHub-yakasviba Markdown ine mazita, maparagiramu, zvinyorwa, mapepa, uye mablocks ekodzero ese akachengetwa. Powered by IBM Granite-Docling-258M (Apache 2.0).
Kubvisa layout-aware Markdown… ~ 5-10 sec / peji
_Zvirongwa
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Kugadzirisa yako mibvunzo...
Kushandura chero PDF mutsva GitHub- flavored Markdown nezita, tebhu, zvinyorwa, uye code blocks akachengetwa. Powered by IBM Granite-Docling. Free, unlimited, no signup.
Maitiro ekuisa PDF kuenda kuMarkdown
1
Sarudza yako input
Tinya meseji, wedzera faira, kana kuti nyora zvaunoda. Hapana account yaunoda.
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Tinya kuumba
Our AI inoongorora yako mibvunzo mumasekondi nekushandisa yakanakisa open-source mamodheru.
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Dhawunirodha & shandisa
Dhawunirodha, kopa kana kugovera yako mhinduro. Yemahara yemunhu uye yekutengesa kushandiswa.
Usashandisa iyi chirongwa kuburikidza neAPI
Automatize iyi chirongwa kubva yako pachako code. OpenAI-inowirirana REST endpoint, Bearer-token auth, hapana zvishoma SDK zvinodiwa. Token mutengo kusangana web interface.
curl -X POST https://api.free.ai/v1/chat/ \
-H "Authorization: Bearer sk-free-..." \
-H "Content-Type: application/json" \
-d '{"model": "qwen7b", "messages": [{"role": "user", "content": "Use the PDF kuenda kuMarkdown tool on: ..."}]}'Zvinoenderana neFree AI Tools
PDF kuenda kuMarkdown — FAQ
Kudonha mu chero PDF uye AI inoshandura kuita yakachena GitHub-yakasviba Markdown - zvinyorwa zvinyorwa zvinyorwa, mameseji mameseji mameseji, mazita ezita, mablocks ekodzero ekodzero. Inoenda kunze kwekubvisa kwechinyorwa; kugadzira kwechinyorwa chechinyorwa chinochengetwa kuitira kuti ugone kudonha mu output straight into a docs site, an LLM RAG pipeline, or a search index.
IBM Granite-Docling-258M (Apache 2.0). Tiny pfungwa-ku-sequence model fine-tuned for layout-aware document conversion — beats pdftotext + much faster + smarter than running a generic vision-language model on each page.
pdftotext imwechete dump - maparagiramu uye mameseji kusvikira muimba yemashoko. Adobe Export to Word inochengeta layout asi inogadzira.docx + mutengo ~ $ 15 / mo. Docling inochengeta SEMANTIC nharaunda (heading mativi, zvinyorwa sezvinyorwa, zvinyorwa seMarkdown zvinyorwa) uye inoburitsa format LLMs uye dev zviwanikwa zvinogonawo kusvikira natively.
LlamaParse uye unstructured vaviri vane zvibereko zvemahara asi cap mapeji / mwedzi uye zvinoda chiratidzo cheAPI. Docling-258M inofamba munzvimbo yedu GPU + ndeyekamwechete-yakachengetwa Apache 2.0, hapana peji peji, hapana chiratidzo chekunyora.
Yeah — mapepa anodzokera seakakodzera Markdown pipe-mapepa. Mapepa ane zvinyorwa zvakawanda / akaiswa mapepa anovharwa zvakasimba (a fundamental Markdown limitation, not the model's fault). Kuti tiwane tafura yakakwana, tinotsigirawo `format=html` kuburikidza neAPI iyo inochengeta rowspan/colspan.
Granite-Docling inoita OCR nhanho yacho — inoshanda pazvinyorwa zvedigital uye zvakashambadzwa zvakafanana. Yakashambadzwa paDPI yakaderera (<150) inorasikirwa nechokwadi chekunyora; edzazve kushambadza pa200+ DPI kuti uwane zvirinani.
Kune zvinyorwa zvedzidzo zvine mapepa anorema, isu tinopawo chirongwa chekubvisa mapepa (Nougat) icho chinogadzirirwa zvakananga equations nezita remunyori.
Pamusoro pe5-10 masekondi papeji paH200 yedu. 30-page report i ~ 3-5 maminitsi. Tiny model inoreva kuti mabhajeti emaPDF madiki anogara akasununguka muzuva nezuva.
200 tokens papeji, ne 500-token floor. A 5-peji chibvumirano = 1,000 tokens. A 30-peji ongororo = 6,000 tokens. The 5K zuva rega rega free pool inokodzera kushandiswa zvikuru.
PDF — born-digital + scanned both supported. Max 50 MB upload. Other document formats (DOCX, EPUB, HTML, etc.) are on the roadmap; for now upload-and-convert with the pdf-conversion tool first.
Kugadziriswazve, Markdown output inochengetwa (24h anony / 7d yakabhadharwa kugovera-link ku expire), iyo source PDF inogadziriswa mushure mekubvisa. Hapana kudzidziswa. /privacy/ for the full policy.
Yeah — POST a multipart `file` kuti /v1/document/pdf-to-markdown/. Returns {markdown_url, mapeji, preview, tokens, share_url}. Bearer auth (sk-free-…) inopa 10K vakasununguka tokens / mwedzi. /api/ ine curl muenzaniso.
Ungaishandisa sei iyi chirongwa?