- Ushintsho oluvela kubunjiniyela obusheshayo obulula luye ekwakhiweni komongo ophelele ukuze kuqedwe ukungaboni kahle kanye nokubola komongo.
- Izindlela zamasu zokuphatha iwindi lomongo we-LLM ngokubhala, ukukhetha, ukucindezela, nokuhlukanisa ulwazi.
- Ukuhlanganiswa kwamagrafu enkumbulo ahlelekile kanye nolwazi ukuze kuhlinzekwe ama-ejenti ngolwazi lwezimo kanye nokucabanga okuchazekayo.
Okwesikhashana manje, impikiswano emphakathini we-AI yayimayelana nobunjiniyela obusheshayo—ubuciko bokuthola amagama omlingo okwenza i-chatbot isebenze kahle. Kodwa ake sibe ngokoqobo: njengoba saqala ukwakha imikhiqizo yangempela esikhundleni se-demos epholile nje, safika odongeni. Saqaphela ukuthi ukulungisa nje izichasiso ezimbalwa ku-prompt kwakunganele ukuvimba imodeli ekulahlekelweni umzila wayo wokucabanga noma amaqiniso angaqondakali emsebenzini oyinkimbinkimbi. Yilapho ubunjiniyela bomongo buqala khona ukusebenza, ukushintsha ukugxila endleleni esibuza ngayo umbuzo kuye kulwazi oluqondile imodeli enalo “enkumbuloni yayo yokusebenza” lapho iphendula.
Cabanga nge-LLM njenge-CPU enamandla kanye nefasitela lomongo njenge-RAM yayo. Kungakhathaliseki ukuthi imodeli ihlakaniphe kangakanani, uma i-RAM igcwele udoti noma idatha ebalulekile engekho, uhlelo luyaphahlazeka noma luphazamiseke. Ubunjiniyela bomongo ngokuyisisekelo buyindlela eyinkimbinkimbi yokuhlelwa kwale ndawo yokusebenza , okuqinisekisa ukuthi amathokheni anesignali ephezulu kakhulu akhona ngesikhathi esifanele adingeka ngaso. Umehluko phakathi kokunikeza umfundi imiyalelo engacacile nokumnika incwadi ekhethiwe, umshini wokubala, kanye nesethi yamanothi enemininingwane ngaphambi kokuhlolwa.
Ngale Kwezisekelo: Kungani Ukunxusa Kunganele
Ubunjiniyela bokushesha buhle kakhulu emisebenzini eyenzeka kanye nje njengokufingqa isigaba noma ukushintsha ithoni ye-imeyili. Lokhu ukuxhumana okuzimele lapho imodeli incike ekuqeqeshweni kwayo kwangaphambi kwesikhathi. Kodwa-ke, uma uthuthela endaweni ye-ejensi—lapho i-AI kufanele ihlele khona, isebenzise amathuluzi, futhi ikhumbule izinto ngezinyathelo eziyishumi ezahlukene—ukusheshisa okujwayelekile kuba buthakathaka. Ugcina “unomongo wokubola,” lapho imodeli ikhungathekiswa khona umsindo omningi noma imane ikhohlwe umgomo wokuqala ngoba ingxoxo ibe yinde kakhulu.
Igebe langempela liwukuthi izikhuthazo aziguquki, kodwa imisebenzi yokukhiqiza iyashintshashintsha . I-ejenti idinga ukwazi usuku lwamanje, isimo esithile se-akhawunti yomsebenzisi, kanye nomphumela wethuluzi elilibize ngemizuzu emibili edlule. Ubunjiniyela bokuqukethwe kuxazulula lokhu ngokwakha ipayipi lokuhlanganisa ulwazi , ukunquma ukuthi yini okufanele ilandwe, yini okufanele ifinyezwe, nokuthi yini okufanele ilahlwe ngesikhathi sangempela ukuze kugcinwe imodeli iqinile futhi isebenza kahle.
Izinsika Zesu Lomqondo Oqinile
Ukuze uqonde kahle ubunjiniyela bomongo, kufanele ububheke ngamalensi amane ayinhloko: ukubhala, ukukhetha, ukucindezela, nokuhlukanisa. Okokuqala, ukubhala umongo kuhilela ukudala “ama-scratchpad” noma izinkumbulo zangaphandle. Esikhundleni sokuthemba ukuthi imodeli ikhumbula uhlelo, i-ejenti ibhala ngokucacile lolo hlelo entweni ethile noma efayeleni, iqinisekisa ukuthi uhlelo alulahleki lapho ifasitela ligcwele.
Bese kuba ukukhetha umongo . Awukwazi nje ukufaka yonke idokhumenti ku-prompt. Izinhlelo ezithuthukisiwe zisebenzisa i-GraphRAG noma usesho lwe-semantic ukudonsa kuphela izingcezu zedatha ezifanele kakhulu. Lokhu akubandakanyi umbhalo kuphela, kodwa nezincazelo zamathuluzi athile. Uma i-ejenti inamathuluzi ayi-100, ukunikeza zonke izincazelo eziyi-100 kuzoyidida; esikhundleni salokho, uhlelo kufanele lufake kuphela amathuluzi ayi-5 anengqondo ngempela kulesi sinyathelo samanje.
Uma umlando uba mude kakhulu, ukucindezela umongo kuba yinto ebalulekile. Lokhu akukhona nje ukususa imiyalezo emidala, kodwa nokusebenzisa ukufingqa okuphindaphindayo ukuze kuhlanganiswe umzila omude wemicimbi ibe amaphuzu ambalwa abalulekile. Okokugcina, ukuhlukanisa umongo kusho ukusebenzisa ukwakheka kwama-ejenti amaningi. Ngokuhlukanisa umsebenzi omkhulu phakathi kwama-ejenti amancane akhethekile, ngalinye lithola ifasitela lalo lomongo elihlanzekile, okuvimbela "ukuphazamiseka" okwenzeka lapho imodeli eyodwa izama ukwenza konke ngesikhathi esisodwa.
Amandla Ememori Ehlelekile kanye Negrafu Yolwazi
I-RAG yendabuko ivame ukuthembela ekufaneni kwe-vector, okuyisisekelo "sokuthola umbhalo ozwakala kanje." Kodwa kuma-ejenti ebanga lebhizinisi, lokho akwanele ngoba akunalo ulwazi lwezimo . Yingakho amagrafu olwazi eshintsha umdlalo. Ngokumapha izinhlangano kanye nobudlelwano bazo (isb., "Isevisi A incike kusevisi B"), i-ejenti ingenza ukucabanga kwe-multi-hop , idlula kugrafu ukuthola imbangela yenkinga kunokumane iqagele ngokusekelwe ekufanisweni kwamagama angukhiye.
Ukuhlanganisa imiphumela ehlelekile nakho kusiza ekuhlanzeni i-loop. Ngokuphoqa imodeli ukuthi ikhiphe i-JSON noma ama-schema athile, ungayifaka leyo datha ehlelekile emuva kumongo wesinyathelo esilandelayo ngaphandle kolimi olungenamsebenzi. Lokhu kugcina isabelomali sethokheni sigxile ekuqondeni kunokuhlonipha noma emazwini agcwalisayo.
Ukuqaliswa Okusebenzayo kanye Nomklamo Wokuhamba Komsebenzi
Ukufaka lokhu esenzweni kudinga ukusuka engqondweni egxile kumodeli uye kwegxile kumklamo. Uqala ngokuchaza i -Minimum Viable Context (MVC) : inani elincane kakhulu lolwazi oludingwa yimodeli ukuze iphumelele. Lokhu kuvame ukufaka umgomo womsebenzisi, isifinyezo senkumbulo esihlanganisiwe, izincazelo zamathuluzi ezidingekayo kuphela, kanye nezibonelo ezimbalwa zekhwalithi ephezulu (ukukhuthaza okumbalwa).
Ukusebenzisa izinhlaka zokuhlelwa kwemisebenzi njengeLangGraph nePython kuvumela abathuthukisi ukuthi bakhe imisebenzi eqhutshwa yimicimbi . Esikhundleni sesicelo esisodwa esikhulu, wakha uchungechunge lwama-node lapho isinyathelo ngasinye sinomongo okhethekile. Isibonelo, i-node ethi “Search Planner” idinga kuphela umbuzo kanye namathuluzi okusesha atholakalayo, kuyilapho i-node ethi “Report Generator” idinga okutholakele okuhlanganisiwe kanye neziqondiso zokufometha. Lokhu kuhlukaniswa kwamasu yikho okuvimbela ukubona izinto ezingekho futhi kuqinisekisa ukuthi i-ejenti ihlala isendleleni.
Isethi Yamakhono Eguqukayo Yonjiniyela We-AI
Indima yomthuthukisi we-AI iyashintsha. Akusekho ngokuba "ngumuntu ohlebayo" owazi amagama angukhiye afanele, kodwa ngokuba umakhi wesistimu . Ukwazi kahle le nsimu kudinga inhlanganisela yokumodela igrafu, ukulungiswa kokuthola kabusha, kanye nokuqonda okujulile kokuthi ama-transformer anakekela kanjani ulwazi. Umsele wezinhlelo zokusebenza ze-AI zesikhathi esizayo ngeke ube yimodeli uqobo—njengoba lezo sezithengiswa—kodwa yizindlela zokuqukethwe ezizimele ezenza i-ejenti ithembeke endaweni engcolile, yangempela.
Ukwakha uhlelo lwe-AI oluthembekile ekugcineni kuncike ekuphatheni ifasitela lomongo njengomthombo onqabile noyigugu . Ngokuhlanganisa ukubuyisa okunamandla, inkumbulo ehlelekile, kanye nokucindezela okuhlakaniphile, ungaguqula i-LLM ejwayelekile ibe ithuluzi elinembile eliqonda kahle ukuthi ikuphi nokuthi yini okudingeka iyenze. Ukuqhubekela phambili ekubunjweni komongo kuqinisekisa ukuthi njengoba amamodeli ekhula ngamandla, ikhono lethu lokuwaqondisa lihlala linembile, lingandiswa, futhi ngaphezu kwakho konke, lisekelwe eqinisweni.
