Qalisa ama-LLM endaweni ku-Flutter nge-latency engu-<200ms

\u003ch2\u003eQalisa ama-LLM endaweni ku-Flutter nge-<200ms latency\u003c/h2\u003e \u003cp\u003eLe khosombe ye-GitHub yomthombo ovulekile imele umnikelo obalulekile ku-ecosystem kanjiniyela. Le phrojekthi ibonisa izinqubo zesimanje zokuthuthukisa kanye nokubhala ngekhodi okuhlanganyelwe.\u003c/p\u003e \u003ch3\u003eIzici zobuchwepheshe\u003c/h3\u003e \u003cp\u003eInqolobane kungenzeka ihlanganisa:\u003c/p\u003e \u003cul\u003e \u003cli\u003eHlanza, ikhodi ebhalwe kahle\u003c/li\u003e \u003cli\u003eI-README ebanzi enezibonelo zokusetshenziswa\u003c/li\u003e \u003cli\u003eIziqondiso zokulandela umkhondo nomnikelo\u003c/li\u003e \u003cli\u003eIzibuyekezo ezivamile nokulungiswa\u003c/li\u003e \u003c/ul\u003e \u003ch3\u003eUmthelela Womphakathi\u003c/h3\u003e \u003cp\u003eAmaphrojekthi womthombo ovulekile njengalena ekhuthaza ukwabiwa kolwazi futhi asheshise ukusungula izinto ezintsha zobuchwepheshe ngekhodi efinyelelekayo nokuthuthukiswa kokuhlanganyela.\u003c/p\u003e

Imibuzo Evame Ukubuzwa

Kusho ukuthini ukusebenzisa i-LLM endaweni ku-Flutter?

Ukuqalisa i-LLM endaweni kusho ukuthi imodeli isebenza ngokuphelele kudivayisi yomsebenzisi — awekho amakholi we-API, akukho ukuncika kwamafu, akukho inthanethi edingekayo. Ku-Flutter, lokhu kufinyelelwa ngokuhlanganisa imodeli enamanani amaningi kanye nokusebenzisa izibopho zomdabu (nge-FFI noma iziteshi zeplathifomu) ukuze kunxeshezelwe ngokuqondile kudivayisi. Umphumela uwukukwazi okugcwele okungaxhunyiwe ku-inthanethi, ukukhathazeka ngobumfihlo bedatha, kanye nokubambezeleka kwempendulo okungahle kwehle ngaphansi kuka-200ms kuhadiwe yesimanje yeselula.

Imaphi ama-LLM amancane ngokwanele ukuthi angasebenza kumakhalekhukhwini?

Amamodeli kububanzi bepharamitha ye-1B–3B ane-4-bit noma 8-bit quantization ayindawo emnandi yeselula. Izinketho ezidumile zifaka i-Gemma 2B, i-Phi-3 Mini, ne-TinyLlama. Lawa mamodeli ngokuvamile athatha u-500MB–2GB wesitoreji futhi asebenza kahle kumadivayisi e-Android ne-iOS ebangeni elimaphakathi. Uma wakha umkhiqizo obanzi one-AI-powered, izinkundla ezifana Mewayz (amamojula angu-207, $19/mo) akuvumela ukuthi uhlanganise okuqondiwe okukudivayisi nokugeleza komsebenzi okubuyela emuva kwefu kalula.

Ingatholakala kanjani i-sub-200ms ukubambezeleka ocingweni?

Ukufinyelela ngaphansi kokungu-200ms kudinga izinto ezintathu ezisebenza ndawonye: imodeli enenani elikhulu, isikhathi sokusebenza esilungiselelwe ama-CPU/NPUs eselula (njenge-llama.cpp noma i-MediaPipe LLM), kanye nokuphathwa kwememori okuphumelelayo ukuze imodeli ihlale ifudumele ku-RAM phakathi kwezingcingo. Ukuhlanganisa amathokheni okwaziswa, ukufaka kunqolobane isimo senani elingukhiye, nokukhomba ukubambezeleka kwethokheni yokuqala kunokubambezeleka okulandelanayo okugcwele amasu ayinhloko aphusha izikhathi zokuphendula kububanzi obungama-sub-200ms ukuze uthole ukwaziswa okufushane.

Ingabe ukucabangela kwe-LLM kwasendaweni kungcono kunokusebenzisa i-API yefu yezinhlelo zokusebenza ze-Flutter?

Kuncike esimweni sakho sokusebenzisa. Ukucatshangelwa kwendawo kuwina ngobumfihlo, ukusekela ungaxhunyiwe ku-inthanethi, kanye neziro zezindleko zesicelo ngasinye - ilungele idatha ebucayi noma ukuxhumeka kwesikhashana. I-Cloud APIs iwina ngamandla kanye nobusha bemodeli. Izinhlelo zokusebenza eziningi zokukhiqiza zisebenzisa indlela ehlanganisiwe: zisingatha imisebenzi engasindi ekudivayisi futhi yenze imibuzo eyinkimbinkimbi eya emafini. Uma ufuna isixazululo esigcwele isitaki esinazo zombili izinketho ezihlanganiswe ngaphambilini, Mewayz ihlanganisa lokhu ngenkundla yayo yamamojula angu-207 eqala ku-$19/mo.