Isilinganisi se-sentiment
Ukusetshenziswa kwebhizinisi OK
579 amamodeli
Akukho phawu lwamanzi
Akukho ubhaliso odingekayo
Imodeli:
+ GPT-5, Claude, Gemini
Izinga eliphelele
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Umbala
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-100 kuya ku-+100
Ukwethembeka
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Isiqephu
Izinketho ezithuthukisiwe
Imiphumela
Ama-token aphansi.
Thola okuningi
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Ubhalise
Kuqedwa isicelo sakho...
Hlola umbhalo wesimo nge-AI emahhala. Thola izithonjana ezilungile, ezibi, nezingenalutho.
Indlela yokusetshenziswa Isilinganisi se-sentiment
1
Faka isingeniso sakho
Bhala umbhalo, thumela ihele, noma chaza ofuna ukukwenza. Akukho akhawunti edingekayo.
2
Chofoza ukudala
I-AI yethu isebenza isicelo sakho emaminithini ambalwa usebenzisa amamodeli angcono kakhulu avulekile.
3
Layisha phezulu futhi uhlukanise
Layisha phezulu, kopela, noma uhlukanise imiphumela yakho. Imahhala ukusebenziseka komuntu siqu nebhizinisi.
Sebenzisa lesi sisetshenziswa nge-API
Yenza lokhu sixhobo sisebenze ngokuzenzakalela kusuka kukhodi yakho. I-REST ehambisanayo ne-OpenAI, ubufakazi be-token, 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: ..."}]}'Amathuluzi ahlobene ne-AI emahhala
Isilinganisi se-sentiment - FAQ
Izinto eziyisithupha, ngokuya ngendlela okhetha ngayo: (1) ubukhulu be-polarity - i-100 kuya ku-100 isilinganiso esiqiniseke kakhulu; (2) imizwa engu-6-dimensional - ukuthula, ubuhlungu, ubuhlungu, ukukhathazeka; (3) i-aspect-based - iqoqa izici ezibizwa ngokuthi noma izimo futhi i scores ngayinye ngokuhlukile; (4) u-sarcasm / subtext - i-flips surface polarity on detected irony; (5) per-sentence - tags every sentence individually. Khetha indlela efana nesimo sakho sokusetshenziswa.
Yebo - i-200-word review ejwayelekile iqhuba imodeli ejwayelekile ye-Qwen 3 30B ku-~200 tokens, ekhululekile ngaphakathi kwe-6,000 anonymous noma i-30,000 ebhalisiwe-up pool. Ucwaningo lwe-forensic-depth aspect kumagama ade kakhulu kubiza ~600 tokens. Akukho ubhaliso odingekayo ukuzama ambalwa.
Ulinganise ngokugcwele ukuxhumana (~ 85% ukuvumelana nabantu abalinganisi ku-text ecacile-cut), ngemuva Google ku-subject-classification precision, ngaphambili kweningi ku-sarcasm ngoba sinikeza imodeli ecacile sarcasm-detection prompts. Enterprise abahlinzeki ukukhokha $ 1-4 ngayinye 1,000 amayunithi. Usizo lwethu: emotion radar + aspect-based output in one call, free, akukho API key to provision.
Yebo - shintsha ku "Isikhashana + isiqephu" indlela. I-system prompt iqondisa ngokucacile imodeli ukuthi ishintshe ubuso bomhlaba lapho ithola khona ukucasuka ("Oh, ngcono, enye iphutha" ithola amaphuzu aphansi naphezu kokuvela kwegama elilungile). Ukunemba ku-sarcasm ecacile yi ~80%; ubuhlungu obuncane obungenalutho bunzima kunanoma yisiphi imodeli. I-"Mixed" isinqumo + isilinganiso esiphansi sokuzithemba yi-flag yakho yokufundela umbhalo ngokwakho.
Instead of one verdict for the whole text, you get separate scores for each entity or feature mentioned. Example: "The hotel was beautiful but the breakfast was cold and the wifi was terrible" yields {hotel: +80, breakfast: -50, wifi: -70}. Ideal for product reviews, restaurant feedback, and NPS comments where customers mix praise and complaints in one paragraph.
99 izilimi. Izinhlamvu ezingu-6 zemizwa zivela ku-Ekman basic-emotion research futhi ziguqulwe emhlabeni wonke. Ukunemba kuphezulu kakhulu ku-English, Spanish, French, Portuguese, German, Chinese, Japanese; izilimi eziphansi-zomthombo zisebenza kodwa zingadala amaphuzu aphansi okuthembela.
Yebo - lokhu kuyinye yezinkinga zayo eziphezulu kakhulu. Sebenzisa ama-tickets afika nge- "Support ticket" imode yendawo; ama-tickets athola ama-polari angaphansi kuka-50 nge-high anger-dimension ahamba ku-support queue yakho ephakeme, ama-tickets a positive-verdict ahamba ku-self-service. Ukukhishwa kwe-JSON nge-download button ne-wire into Zendesk / Freshdesk automations.
Yebo - UTHOMBELA ku /v1/incoko/ ngendlela efanayo yohlelo lokucela le khasi lisebenzisa (bheka umsuka wesicelo esifanele). Ibuyisela iJSON eyenziwe kahle. Engcono kuma-dashboards athatha amawaka ebuyekezo nsuku zonke. Ubufakazi bomuntu ophethe, ama-limits anyanga zonke. Amadokhumende ku /api/.
Ukuphepha kukhombisa ukuphepha kwemodeli, hhayi ukuphepha kwakho. Izingeniso ezincane (<20 amagama), umbhalo ocacile, kanye nezingcezu ezixhumene-zobubanzi zithola isilinganiso esiphansi. Ukuphepha okuphansi okuphumelelayo akulona ukulahlekelwa okuthembekile - "Angazi". Yamukela noma yikuphi ukuphumelela ngezansi kwe-50 njengedinga ukuhlolwa komuntu.
I-UI iqhuba umbhalo owodwa ngasikhathi sinye. Ubukhulu, i-JSON+CSV download ikuvumela ukuthi uxhume i-API kwi-Python noma i-Node script ephindayo i-dataset yakho. Izilimi: 20,000 izibonakaliso ngasinye, 100 izilimi/ihora ngalinye le-IP kubasebenzisi abangaziwayo, 1,000/ihora ku-akhawunti ezibhalisiwe. Izilimi ze-Enterprise rate zikhona - xhumana nathi.
Lexalytics kanye Repustate ikhokhisa $ 500-5,000 / mo for elinganayo aspect-based + emotion ukuhlola. Ithuluzi lethu limahhala kuningi umsebenzi; premium models (GPT-5, Claude Sonnet) etholakalayo per-call for the highest-stakes use cases like earnings-call transcripts.
Umbhalo uphathwa ngaphakathi kwememori ku-GPU yethu, awugcinwanga kwidiski kubasebenzisi abangaziwayo. Abasebenzisi ababhalisiwe babona izixhumanisi ku-dashboard yabo iminyaka engu-7. Asikwazi ukuhlukanisa umbhalo namanye amaqembu noma ukuwusebenzisa ukuqeqeshwa. Ukulandelana kwe-zero-log sebenzisa indawo yakho ye-API-key-gated endpoint - xhumana nathi nge-enterprise SLAs.
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