Kenyelletso
Tšimo ea DevOps e bile le liphetoho tse kholo lilemong tsa morao tjena, 'me ho kopanngoa ha Artificial Intelligence (AI) le Machine Learning (ML) ho ntse ho hlahella le ho feta. E 'ngoe ea libaka tsa bohlokoa moo AI e nang le tšusumetso e kholo ke sebakeng sa othomathike. Ka ho sebelisa lisebelisoa tsa AI, mekhatlo e ka tsamaisa tšebetso ea eona ea ntlafatso ea software, ea fokotsa liphoso tsa matsoho, le ho ntlafatsa ts'ebetso e akaretsang.
Sehloohong sena, re tla hlahloba lefats'e la li-automation tsa DevOps tse tsamaisoang ke AI, re shebane le mekhoa ea LangChain le DSPy. Re tla hlahloba hore na lisebelisoa tsena li ka sebelisoa joang ho theha sistimi e sebetsang ea ho rarolla mathata le ho iketsetsa tšebetso ea ntlafatso ea software. Ho feta moo, re tla fana ka mohlala o sebetsang oa mokhoa oa ho hokahanya Mehlala ea Lipuo tse Kholo (LLMs) ho lipeipi tsa hau tsa DevOps.
LangChain le DSPy ke eng?
Pele re kenella ka har'a lintlha tsa automation ea DevOps e tsamaisoang ke AI, ha re hlahlobeng ka bokhuts'oane meralo ea LangChain le DSPy.
LangChain
LangChain ke moralo oa mohloli o bulehileng o nolofalletsang batho ba ntlafatsang ho haha lisebelisoa tsa puisano tsa AI ba sebelisa Mehlala e Meholo ea Lipuo (LLMs). E fana ka API e bonolo le e hlakileng bakeng sa ho sebelisana le LLMs, e lumellang batho ba ntlafatsang ho iketsetsa mekhoa e tloaelehileng ea lipuisano bakeng sa likopo tsa bona.
LangChain e ts'ehetsa mefuta e mengata ea LLM, ho kenyelletsa le mefuta e tsebahalang joalo ka LLaMA, BERT, le RoBERTa. E boetse e fana ka mefuta e mengata ea lisebelisoa bakeng sa ho hlophisa hantle le ho etsa li-LLM tsa hau ho lumellana le maemo a itseng a ts'ebeliso.
DSPy
DSPy ke laebrari ea Python e fanang ka mokhoa o bonolo le o sebetsang oa ho kopanya mefuta ea AI ho lipeipi tsa hau tsa DevOps. E ts'ehetsa mekhoa e mengata ea AI, ho kenyelletsa le LangChain, 'me e fana ka lisebelisoa tse ngata bakeng sa ho iketsetsa mosebetsi o tsamaisoang ke AI.
DSPy e etselitsoe ho sebetsa ntle le moroallo ka lisebelisoa tse tsebahalang tsa DevOps joalo ka Jenkins, GitLab, le Docker, e e etsa khetho e nepahetseng bakeng sa mekhatlo e batlang ho kopanya AI meahong ea eona e teng ea DevOps.
Ho hlophisa baemeli ba AI bakeng sa DevOps Automation
Kaha joale re na le kakaretso e khuts'oane ea LangChain le DSPy, ha re hlahlobeng hore na meralo ena e ka sebelisoa joang ho hlophisa liakhente tsa AI bakeng sa automation ea DevOps.
Tharollo e Tsoang Pele ea Taba
O mong oa melemo ea mantlha ea boits'oaro ba AI-driven DevOps ke bokhoni ba ho rarolla mathata pele e fetoha mathata a maholo. LangChain le DSPy li ka sebelisoa ho theha mekhoa ea puisano e tloaelehileng e sebelisanang le LLMs ho khetholla mathata a ka 'nang a hlaha le ho fana ka litlhahiso bakeng sa tharollo.
Mona ke mohlala o bonolo oa hore na sena se ka sebetsa joang:
import langchain
ho tsoa ho langchain.chat_models e kenya LLaMA
# Theha mofuta oa moqoqo oa LangChain
chat_model = LLaMA()
# Hlalosa tšebetso ea ho sebelisana le mofuta oa moqoqo
def interact_with_chat_model(prompt):
karabo = chat_model.run(prompt)
kgutlisa karabo
# Hlalosa ts'ebetso ho tseba mathata a ka bang teng
def supa_issues(khoutu):
prompt = f"Lemoha mathata a ka bang teng ka khouto e latelang: {code}"
karabo = interact_with_chat_model(ka potlako)
kgutlisa karabo
# Hlalosa tšebetso ho fana ka likhothaletso bakeng sa tharollo
def provide_recommendations(litaba):
prompt = f"Fana ka likhothaletso bakeng sa ho rarolla mathata a latelang: {litaba}"
karabo = interact_with_chat_model(ka potlako)
kgutlisa karabo
# Tšebeliso ea mohlala
khoutu = """
def eketsa(x, y):
khutla x + y
"""
litaba = khetholla_litaba(khoutu)
likhothaletso = provide_recommendations(litaba)
hatisa (likhothaletso)
Mohlaleng ona, re hlalosa ts'ebetso e bonolo interact_with_chat_model e sebelisanang le mohlala oa moqoqo oa LangChain ho fana ka karabelo ho potso e fanoeng. Ka mor'a moo re hlalosa mesebetsi e 'meli ea tlatsetso ho tseba_litaba le ho fana_likhothaletso tse sebelisang mokhoa oa ho qoqa ho tseba mathata a ka bang teng ho sampole ea khoutu le ho fana ka likhothaletso bakeng sa tharollo.
Ho iketsetsa Ts'ebetso ea Tsoelo-pele ea Software
LangChain le DSPy le tsona li ka sebelisoa ho iketsetsa tšebetso ea ntlafatso ea software ka ho kopanya mefuta ea AI ho lipeipi tsa hau tse teng tsa DevOps.
Mona ke mohlala oa kamoo sena se ka sebetsang kateng:
kenya dspy
ho tsoa ho dSpy import Workflow
# Hlalosa mokhoa oa ho sebetsa oa DSPy
Mokhoa oa ho sebetsa = Mokhoa oa ho sebetsa()
# Hlalosa mosebetsi oa ho tsamaisa sesebelisoa sa tlhahlobo ea khoutu
def run_code_analysis(khoutu):
# Sebelisa sesebelisoa sa tlhahlobo ea khoutu ho tseba mathata a ka bang teng
litaba = []
#...
kgutlisa ditaba
# Hlalosa mosebetsi ho fana ka likhothaletso bakeng sa tharollo
def provide_recommendations(litaba):
# Sebelisa mofuta oa moqoqo oa LangChain ho fana ka likhothaletso
prompt = f"Fana ka likhothaletso bakeng sa ho rarolla mathata a latelang: {litaba}"
karabo = langchain.chat_model.run(prompt)
kgutlisa karabo
# Hlalosa mosebetsi oa ho tsamaisa khoutu
def deploy_code(khoutu):
# Kenya khoutu sebakeng sa tlhahiso
#...
# Hlalosa mokhoa oa ho sebetsa
workflow.add_task(run_code_analysis)
workflow.add_task( fana_commendations)
workflow.add_task(deploy_code)
# Kenya ts'ebetso ea ts'ebetso
workflow.run()
Mohlaleng ona, re hlalosa mokhoa o bonolo oa ho sebetsa oa DSPy o nang le mesebetsi e meraro: ho sebetsa sesebelisoa sa tlhahlobo ea khoutu, ho fana ka likhothaletso bakeng sa tharollo, le ho tsamaisa khoutu. Ebe re hlalosa mokhoa oa ho sebetsa ka ho eketsa mosebetsi o mong le o mong le ho o tsamaisa.
Top 5-10 Litaelo / Linotsoana tse Sebelisitsoeng ka ho Fetisisa
Mona ke tse ling tsa litaelo le likotlo tse sebelisoang haholo bakeng sa LangChain le DSPy:
LangChain
langchain.chat_models.LLaMA(): Theha mofuta oa moqoqo oa LangChain o sebelisa mofuta oa LLaMA.langchain.chat_model.run(prompt): Sebelisa mokhoa oa ho qoqa ka molaetsa o fanoeng.langchain.chat_model.interact_with(prompt): Sebelisana le mofuta oa moqoqo u sebelisa molaetsa o fanoeng.
DSPy
dspy.Workflow(): Theha mokhoa oa ho sebetsa oa DSPy.mosebetsi.add_task(mosebetsi): Eketsa mosebetsi mosebetsing.workflow.run(): Etsa mosebetsi oa ho sebetsa.
Ho bona pono
Mona ke pono e bonolo ea tšebetso e sebelisang Chart.js:
{
"type": "bar",
"data": {
"labels": ["Analysis ea Khoutu", "Likhothaletso", "Deployment"],
"lintlha tsa boitsebiso": [
{
"label": "Motsamao oa mosebetsi",
"data": [10, 20, 30],
"backgroundColour": [
"rgba(255, 99, 132, 0.2)",
"rgba(54, 162, 235, 0.2)",
"rgba(255, 206, 86, 0.2)"
],
"Mmala oa moeli": [
"rgba(255, 99, 132, 1)",
"rgba(54, 162, 235, 1)",
"rgba(255, 206, 86, 1)"
],
"borderWidth": 1
}
]
},
"likgetho": {
"sehlooho": {
"bontša": 'nete,
"text": "Tlhaloso ea mosebetsi"
},
"makala": {
"yAxes": [
{
"li-ticks": {
"beginAtZero": 'nete
}
}
]
}
}
}
Pono ena e bonts'a chate e bonolo ea bar e emelang phallo ea mosebetsi, e nang le mekoallo e meraro e emelang tlhahlobo ea khoutu, likhothaletso le mesebetsi ea ho tsamaisa.
Qetello
Sehloohong sena, re ile ra hlahloba lefats'e la li-automation tsa AI-driven DevOps ho sebelisa LangChain le DSPy. Re bone kamoo meralo ena e ka sebelisoang ho theha lits'ebetso tsa ho rarolla mathata le ho iketsetsa tšebetso ea ntlafatso ea software. Re boetse re fane ka mehlala e sebetsang ea mokhoa oa ho kopanya LLM ho lipeipi tsa hau tsa DevOps le ho bona ka mahlo a kelello ts'ebetso ea mosebetsi u sebelisa Chart.js.
Ka ho matlafatsa matla a AI le boiketsetso, mekhatlo e ka tsamaisa tšebetso ea eona ea ntlafatso ea software, ea fokotsa liphoso tsa matsoho, le ho ntlafatsa katleho ka kakaretso. Ebang u moenjiniere oa DevOps, moqapi oa software, kapa moetapele oa khoebo, LangChain le DSPy ke lisebelisoa tse matla tse ka u thusang ho finyella lipakane tsa hau.