Isici sokukhipha isibizo-sibizo
Ukusetshenziswa kwebhizinisi OK
Amamodeli angama-380+
Akukho phawu lwamanzi
Akukho ubhaliso olungenayo
Imodeli:
+ GPT-5, Claude, Gemini
Igama lokhiye elikhishwayo
Izinketho ezithuthukisiwe
Imiphumela
Ama-token aphansi.
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Kuqedwa isicelo sakho...
Thola amagama angukhiye kusuka kuwo wonke umbhalo nge-AI emahhala. Ucwaningo lwe-SEO kanye nokuhlaziywa kwesihloko kwenziwa lula.
Indlela Yokusetshenziswa Isici sokukhipha isibizo-sibizo
1
Faka umngenisi wakho
Bhala umbhalo, ulayishe ifayela, noma uchaza ofuna ukukwenza. Akukho akhawunti edingekayo.
2
Chofoza ukwakha
I-AI yethu isebenza isicelo sakho emaminithini usebenzisa amamodeli avulekile angcono kakhulu.
3
Layisha phezulu futhi uhlukanise
Layisha phezulu, kopela, noma uhlukanise imiphumela yakho. Imahhala ukusetshenziswa komuntu siqu nokwebhizinisi.
Sebenzisa lesi sisetshenziswa nge-API
Yenza lokhu sixhobo sisebenze ngokuzenzakalela kusuka kukhodi yakho. I-REST ehambisanayo ne-OpenAI, ukuqinisekisa i-token ye-bearer, akukho SDK edingekayo. Izindleko ze-token zifana ne-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": "Summarize this: ..."}]}'Isici sokukhipha isibizo-sibizo — FAQ
Ikhipha amagama abalulekile kakhulu kanye nezinhlamvu kusuka kunoma iyiphi ifomu lemibhalo ende (isihloko, i-blog post, i-transcript, incazelo yemikhiqizo). Amamodi okukhipha ahlanu: (1) ama-keywords we-SEO nge-search-intent tagging, (2) amasihloko aphezulu + amathegi, (3) izinhlangano ezibizwa ngegama — abantu/amandawo/amaqembu, (4) amathegi afana ne-tag-smallcase-hyphen-joined tags, (5) amathegi we-academic index terms. Izibalo ezitholakele 0-100 nge-TF-IDF, ukusakazwa okungekuhle, noma ukuhambisana kwe-semantic. Rhweba ngaphandle njenge-CSV, TXT, noma i-JSON.
Yebo — 1,500-word article extracts in ~350 tokens on the default Qwen 3 30B model, comfortably inside the 2,500 anonymous or 10,000 signed-up daily pool. No sign-up required for your first extraction.
Lawa mathuluzi asusa idatha yocwaningo oluphilayo lwegama elingukhiye owalinika ($ 99 + / mo). Le thuluzi lisebenza ngokuhlukile - likhipha amagama angukhiye akhethiwe kusuka ku-content yakho futhi lihlukanise ukucabanga kwabo kokufuna. Ukuhamba komsebenzi: sebenzisa lokhu ukuthola ukuthi iziphi izihloko isihloko sakho esivele siphawula, bese ufaka ezingeni le-Ahrefs / Semrush ukuhlola ubukhulu bokufuna ngenyanga.
Izigaba ezintathu ukukala: (1) TF-IDF (default) inikeza amagama obobabili ezivame kule ncwadi futhi evamile e isiNgisi jikelele - best for SEO njengoba lezi ziyimigomo ehlukene. (2) Raw ukusakazwa ibala izimo straight - best lapho ufuna ukubona ukuthi yini okusho kakhulu. (3) Semantic ukuxhumana amaphuzu ngokusondelana namaphepha isihloko eyinhloko ngisho uma amagama abonakala kuphela kabili - best for topical coherence.
I-n-gram iyingxenye ehambisanayo yegama eli-N. "ushintsho lwesimo sezulu" yigama eli-2. "imodeli yengqondo eyenziwe ngokwezifiso" yigama eli-3. Thola ama-chips ukuze ukhiphe kuphela ama-1-gram (amagama afanayo njenge "photosynthesis"), ama-2-gram (izwi eliphambili njenge "carbon footprint"), noma ama-3-gram (ikhanda elide njenge "carbon footprint calculator"). Amanye ama-SEO afuna ama-2+3-gram — amagama afanayo ajwayelekile kakhulu.
Yebo — uhlu lokuyeka oluzenzakalelayo lususa "i", "na", "ye", "yi", njll. ezilimi ezingu-14. Ungangeza ama-stopwords ajwayelekile nge-"Words to exclude" field — asetshenziswa ukuvimbela igama lakho le-brand, amakhodi wemikhiqizo, noma i-boilerplate legalese engeke i domine izimpendulo.
Google ihlukanise izicelo ngokuya ngenhloso yomsebenzisi: ulwazi ("yini i-X"), ukuzulazula ("isitolo esisemthethweni se-nike"), ukuhweba ("izicathulo ezihamba phambili 2026"), ukuthengiselana ("thenga i-air max online"). Ithuluzi liphawula amagama akho e-keyword akhishwayo ngenhloso engahleliwe ukuze ukwazi ukuthi ngabe incwadi yakho kufanele i Rank for researchers, shoppers, or direct-traffic lookups. Ibalulekile ukuhlela okuqukethwe ngezici ze-SERP.
99 izilimi nge-Qwen 2.5 model. Ubuningi obuphezulu ngesiNgisi, isiShayina, isiFrentshi, isiPutukezi, isiJalimane, isiSinansi, isiJalimane. Izilimi eziphansi-zomthombo zisebenza kodwa ukukhishwa kwe-3-gram kungase kube kungenakuthembeka — buyela emuva ku-1+2-grams ye-Arabic, Hindi, Turkish, njll.
The UI runs one text at a time. For bulk extraction wire the /v1/chat/ API into a Python script — iterate over your CMS export, POST each article body, dump the JSON. Bearer auth, 1,000 calls/hour on free accounts, higher limits on pro. Docs at /api/.
RAKE ne YAKE yi-algorithms ye-lexical ejwayelekile - ngokushesha kodwa iphansi ku-semantic nuance (ilahlekelwa yi- "tech startup" uma idokhumende lithi "i-tech startup" kodwa hhayi i- "tech" kuphela). I-KeyBERT isebenzisa i-BERT embeddings - ikhwalithi engcono ye-semantic kodwa ihamba kancane futhi idinga ukufakwa. I-TextRank isekelwe ku-graph. Indlela yethu isebenzisa i-7B-parameter LLM eyenza yonke i-zero-shot engezansi kanye nohlobo lokusesha-ukuze-kuhlolwe - kuhamba kancane nge-call kodwa i-zero setup, yamahhala, futhi akukho ML engineering edingekayo.
In frequency and TF-IDF modes, yes — every keyword is derivable from the source text verbatim or with minimal inflection change. In semantic-relevance mode the model may return a controlled-vocabulary version ("pulmonology" even if your text says "lung doctor visit"). The academic-terms mode intentionally prefers controlled vocabulary.
Yebo — POST ku /v1/chat/ ngendlela efanayo yokufaka isicelo le khasi liyivula (bheka i-template source yesicelo esifanele). Ibuyisela i-JSON eyenziwe kahle. Engcono kuma-dashboards wesimo se-isizinda noma ama-plugins we-CMS. Ugunyazo lomthwalo, ama-limits anyanga zonke. Amadokhumende ku /api/.
Ungayilinganisela kanjani lethuluzi?