Kenyelletso
Phetoho ea DevOps e fetotse tsela eo software e hlahisoang ka eona, e tsamaisoang le ho tsamaisoa ka eona. Leha ho le joalo, ha ho rarahana ha litsamaiso tsa sejoale-joale tsa software ho ntse ho hola, ho joalo le ka tlhokahalo ea boiketsetso, ho latela melao, le scalability. Mona ke moo li-DevOps tse tsamaeang ka matla a AI li kenang - mokhoa oa ho fetola lipapali o sebelisang bohlale ba maiketsetso (AI) le ho ithuta ka mochini (ML) ho tsamaisa lipeipi tsa DevOps. Sehloohong sena, re tla hlahloba mokhoa oa ho hlophisa li-DevOps tse tsamaisoang ke AI ka LangChain le DSPy, meralo e 'meli e tsoetseng pele e nolofalletsang boiketsetso bo thehiloeng ho moemeli.
LangChain ke eng?
LangChain ke moralo oa mohloli o bulehileng o lumellang bahlahisi ho haha lits'ebetso tsa puisano tsa AI ba sebelisa meralo ea modular, scalable meralo. E fana ka sete ea likarolo tse hahiloeng esale pele le lisebelisoa tsa ho theha liakhente tsa AI tse ka sebelisanang le mehloli e fapaneng ea data, ho etsa mesebetsi le ho etsa liqeto. LangChain e hahiloe ka holim'a puo ea lenaneo la Rust 'me e ka sebelisoa le lipuo tse ling tse kang Python le Go.
DSPy ke eng?
DSPy ke laebrari ea Python e fanang ka sebopeho se bonolo, sa Pythonic ho moralo oa LangChain. E lumella batho ba ntlafatsang ho haha lisebelisuoa tsa AI ba sebelisa syntax e tloaelehileng le ho phalla ha mosebetsi, ho etsa hore ho be bonolo ho kopanya LangChain le liphaephe tse teng tsa Python-based DevOps.
Ho kopanya LangChain le DSPy le DevOps Pipelines
Ho kopanya LangChain le DSPy le liphaephe tsa DevOps, re hloka ho theha moemeli oa AI ea khonang ho etsa mesebetsi, ho etsa liqeto, le ho sebelisana le mehloli e sa tšoaneng ea data. Mona ke kakaretso ea boemo bo holimo ea ts'ebetso:
- ** Hlalosa Moemeli oa AI **: Etsa moemeli oa LangChain ea ka etsang mesebetsi, e kang ho romela khoutu, ho etsa liteko, le ho hlahloba ts'ebetso.
- Ikopanye le Lisebelisoa tsa DevOps: Kopanya moemeli oa AI ka lisebelisoa tsa DevOps, tse kang Jenkins, GitLab CI/CD, kapa Docker.
- Lokisa Moemeli oa AI: Lokisa moemeli oa AI hore a sebelisane le mehloli e fapaneng ea data, joalo ka li-database, li-API, kapa litsamaiso tsa lifaele.
- Koetlisa Moemeli oa AI: Koetlisa moemeli oa AI ka mokhoa oa ho ithuta ka mochine le lintlha tse tsoang ho lipeipi tsa DevOps.
Mohlala o sebetsang: Ho tsamaisa Khoutu ka LangChain le DSPy
Mona ke mohlala o bonolo oa mokhoa oa ho sebelisa khoutu u sebelisa LangChain le DSPy:
import langchain
ho tsoa ho langchain.agents import Agent
ho tsoa ho langchain.llms kenya LLM
# Theha moemeli oa LangChain
moemeli = Moemeli(
llm=LLM(
lebitso_la mohlala = "davinci",
max_tokens=2048,
mocheso=0.5,
),
ketane=[
langchain.Chain(
lebitso = "deploy_code",
mehato=[
langchain.Mohato(
lebitso = "git_clone",
func=lambda: git_clone("https://github.com/user/repo.git"),
),
langchain.Mohato(
lebitso = "build_code",
func=lambda: build_code(),
),
langchain.Mohato(
lebitso = "deploy_code",
func=lambda: deploy_code(),
),
],
),
],
)
# Kenya khoutu u sebelisa moemeli oa AI
agent.deploy_code()
Mohlala ona, re theha moemeli oa LangChain ea etsang mehato e meraro:
- E koala polokelo ea khoutu u sebelisa Git.
- E haha khoutu ka ho sebelisa sesebelisoa sa ho haha.
- E sebelisa khoutu e sebelisa sesebelisoa sa ho tsamaisa.
Moemeli oa AI o sebelisa mohlala oa puo (LLM) ho etsa liqeto le ho etsa mesebetsi.
Top 5-10 Litaelo / Linotsoana tse Sebelisitsoeng ka ho Fetisisa
Mona ke tse ling tsa litaelo le likonopo tse sebelisoang haholo bakeng sa LangChain le DSPy:
- Theha moemeli oa LangChain:
agent = Moemeli(llm=LLM(model_name="davinci", max_tokens=2048, mocheso=0.5), ketane=[langchain.Chain(name="deploy_code", steps=[langchain.Step(name="git_clambc: func", git_clone("https://github.com/user/repo.git")])]) - Kenya khoutu u sebelisa moemeli oa AI:
agent.deploy_code() - Koetlisa moemeli oa AI:
agent.train(data=[{"input": "deploy code", "output": "deployed code"}]) - Ikopanye le lisebelisoa tsa DevOps:
agent.integrate_with_jenkins() - Beakanya moemedi wa AI:
agent.configure(llm=LLM(model_name="davinci", max_tokens=2048, thempereichara=0.5)) - Fumana boemo ba moemeli oa AI:
agent.status() - Fumana litlaleho tsa moemeli oa AI:
agent.logs() - Nchafatsa tlhophiso ya moemedi wa AI:
agent.update_config(llm=LLM(model_name="davinci", max_tokens=2048, thempereichara=0.5)) - Hlakola moemeli oa AI:
moemeli.hlakola() - Fumana metrics ea moemeli oa AI:
agent.metrics()
Ho bona pono
Mona ke pono ea meralo ea LangChain le DSPy e sebelisang Chart.js:
{
"type": "bar",
"data": {
"labels": ["LangChain", "DSPy"],
"lintlha tsa boitsebiso": [
{
"label": "Likaroloana",
"data": [10, 5],
"backgroundColor": ["#4CAF50", "#FF9800"],
"borderColor": ["#3e8e41", "#ff9900"],
"borderWidth": 1
}
]
},
"likgetho": {
"sehlooho": {
"bontša": 'nete,
"text": "LangChain le DSPy Architecture"
},
"tšōmo": {
"pontšo": 'nete
},
"makala": {
"yAxes": [
{
"li-ticks": {
"beginAtZero": 'nete
}
}
]
}
}
}
Pontšo ena e bonts'a palo ea likarolo tsa LangChain le DSPy.
Qetello
Sehloohong sena, re ile ra hlahloba mokhoa oa ho hlophisa li-DevOps tse tsamaisoang ke AI ka LangChain le DSPy, meralo e 'meli e tsoetseng pele e nolofalletsang boiketsetso bo thehiloeng ho moemeli. Re buisane ka melemo ea AI-powered DevOps, ho kenyeletsoa boits'oaro bo ntlafalitsoeng, ho latela melao le ho hlaka. Hape re fane ka mohlala o sebetsang oa ho tsamaisa khoutu ho sebelisa LangChain le DSPy, hammoho le lethathamo la litaelo tse sebelisoang ka ho fetisisa le li-snippets. Qetellong, re ile ra bona meralo ea LangChain le DSPy ka ho sebelisa Chart.js. Ka LangChain le DSPy, bahlahisi ba ka haha liphaephe tsa DevOps tse sebetsang hantle, tse senyehang, le tse ikemetseng tse phahamisang matla a AI le ho ithuta ka mochini.