Hordhac

Beerta DevOps waxa ay soo martay isbedelo la taaban karo sanadihii ugu dambeeyay, iyada oo is dhexgalka Sirdoonka Artificial (AI) iyo Barashada Mashiinka (ML) ay noqdeen kuwo caan ah. Mid ka mid ah meelaha ugu muhiimsan ee AI ay ku sameyneyso saameyn la taaban karo ayaa ku jirta goobta otomaatiga. Iyaga oo ka faa'iidaysanaya wakiilada AI, ururadu waxay hagaajin karaan socodka shaqadooda horumarinta software, yaraynta khaladaadka gacanta, iyo hagaajinta waxtarka guud.

Maqaalkan, waxaan u dhexgeli doonaa adduunka AI-driven DevOps automation, oo diiradda saaraya qaabdhismeedka LangChain iyo DSPy. Waxaan sahamin doonaa sida qalabkan loogu isticmaali karo si loo abuuro habab xallinta arrimaha firfircoon iyo toosinta socodka socodka shaqada ee horumarinta software. Intaa waxaa dheer, waxaan ku siin doonaa tusaale wax ku ool ah oo ku saabsan sida loogu dari karo Moodooyinka Luuqadaha Waaweyn (LLMs) ee dhuumahaaga DevOps.

Waa maxay LangChain iyo DSPy?

Ka hor inta aynaan u gelin faahfaahinta Automation-ka DevOps ee AI ay wado, aan si kooban u eegno qaab-dhismeedka LangChain iyo DSPy.

LangChain

LangChain waa qaab-dhismeedka il furan oo awood u siinaya horumariyeyaasha inay dhisaan codsiyada AI wada-hadalka iyagoo isticmaalaya Moodooyinka Luuqadaha waaweyn (LLMs). Waxay siisaa API fudud oo dareen leh si ay ula falgalaan LLMs, taasoo u oggolaanaysa horumariyeyaasha inay abuuraan is-dhexgal wada-hadal oo caado u ah codsiyadooda.

LangChain waxay taageertaa noocyo kala duwan oo LLM ah, oo ay ku jiraan moodooyinka caanka ah sida LLAMA, BERT, iyo RoBERTa. Waxa kale oo ay bixisaa qalabyo kala duwan oo loogu talagalay hagaajinta iyo habaynta LLMs si ay ugu habboonaato kiisaska isticmaalka gaarka ah.

DSPy

DSPy waa maktabad Python oo bixisa hab fudud oo hufan oo lagu dhex daro moodooyinka AI ee dhuumahaaga DevOps. Waxay taageertaa qaabab kala duwan oo AI ah, oo ay ku jiraan LangChain, waxayna bixisaa qalabyo kala duwan oo loogu talagalay socodsiinta shaqada AI ay wado.

DSPy waxaa loogu talagalay inay si aan kala go 'lahayn ula shaqeyso aaladaha caanka ah ee DevOps sida Jenkins, GitLab, iyo Docker, taasoo ka dhigaysa doorasho ku habboon ururada doonaya inay ku dhex daraan AI kaabayaasha jira ee DevOps.

Abaabulka Wakiilada AI ee DevOps Automation

Hadda oo aan hayno dulmar kooban oo ku saabsan LangChain iyo DSPy, aan sahamno sida qaab-dhismeedkan loogu isticmaali karo in lagu abaabulo wakiilada AI ee Automation-ka DevOps.

Xallinta Arrinta Firfircoon

Mid ka mid ah faa'iidooyinka muhiimka ah ee Automation-ka DevOps ee AI ay wado waa awoodda si firfircoon loo xalliyo arrimaha ka hor intaysan noqon dhibaatooyin waaweyn. LangChain iyo DSPy waxaa loo isticmaali karaa in lagu abuuro is-dhexgal wada-sheekeysi oo caadi ah oo la falgala LLM-yada si loo aqoonsado arrimaha suurtagalka ah iyo bixinta talooyinka xallinta.

Waa kuwan tusaale fudud oo ku saabsan sida tani u shaqayn karto:

`` Python soo dejinta langchain ka langchain.chat_models ka soo daji LLMA

Samee qaab sheekeysi LangChain

chat_model = LLAMA()

Qeex shaqada si aad ula falgasho qaabka sheekaysiga

def interact_with_chat_model (degdeg): jawaab = chat_model.run( degdeg ah) jawaab celin

Qeex hawl si loo aqoonsado arrimaha iman kara

def aqoonsiga_assues(code): degdeg = f"Ceex arrimaha suurtagalka ah ee summada soo socota: {code}" jawaab = interact_with_chat_model (degdeg ah) jawaab celin

Qeex hawl si aad u bixiso talooyinka xallinta

def provide_talooyinka(arrimaha): degdeg = f" Bixi talooyinka xalinta arrimaha soo socda: {arrimaha}" jawaab = interact_with_chat_model (degdeg ah) jawaab celin

Tusaale isticmaalka

code = """ def add(x, y): soo noqo x + y """ arimaha = aqoonsiga_arimaha(code) talooyinka = bixinta_talooyin(arrimo) daabac(talooyinka) ``

Tusaalahan, waxaanu ku qeexnay hawl fudud 'isdhexgal_with_model_chat_model' kaas oo la falgala qaabka sheekaysiga LangChain si loo bixiyo jawaab degdeg ah. Waxaan markaa qeexnay laba hawlood oo dheeri ah 'aqoonsiga_arrimaha' iyo 'bixinta_talooyin' ee adeegsada qaabka wada sheekaysiga si loo aqoonsado arrimaha suurtagalka ah ee kood muunada qaarkood oo bixiya talooyinka xallinta.

Socodka Shaqo ee Horumarinta Software-ka Atoomatiga ah

LangChain iyo DSPy waxaa sidoo kale loo isticmaali karaa in lagu habeeyo socodka shaqada horumarinta software iyadoo la isku darayo moodooyinka AI ee dhuumahaaga jira ee DevOps.

Waa kuwan tusaale sida tani u shaqayn karto:

`` Python soo dejinta dspy ka soo dejinta dspy socodka shaqada

Qeex socodka shaqada DSPy

socodka shaqada = socodka shaqada ()

Qeex hawsha si aad u socodsiiso qalabka falanqaynta kood

def run_code_analysis(kood): # Samee aalad falanqaynta kood si aad u ogaatid arrimaha suurtagalka ah arrimaha = [] #... arimaha soo noqoshada

Qeex hawsha si aad u bixiso talooyinka xallinta

def provide_talooyinka(arrimaha): # Isticmaal qaabka wada sheekeysiga LangChain si aad u bixiso talooyin degdeg = f" Bixi talooyinka xalinta arrimaha soo socda: {arrimaha}" jawaab = langchain.chat_model.run( degdeg ah) jawaab celin

Qeex hawsha lagu geynayo koodka

def deploy_code(kood): # Geli koodka deegaanka wax soo saarka #...

Qeex socodka shaqada

workflow.add_task (run_code_analysis) workflow.add_task (bixi_talooyinka) workflow.add_task(deploy_code)

socodsii socodka shaqada

workflow.run() ``

Tusaalahan, waxaan ku qeexeynaa shaqo fudud oo DSPy ah oo ka kooban seddex hawlood: socodsiinta aaladda falanqaynta code, bixinta talooyinka xallinta, iyo geynta koodka. Kadibna waxaynu qeexnaa hab-socodka shaqada anagoo ku darayna hawl kasta oo wadnaa.

5-10ka amar ee ugu badan ee la isticmaalo

Waa kuwan qaar ka mid ah amarada sida caadiga ah loo isticmaalo iyo qaybo yaryar oo loogu talagalay LangChain iyo DSPy:

LangChain

• langchain.chat_models.LLaMA(): Samee qaab sheekeysi LangChain adiga oo isticmaalaya qaabka LLama.
• langchain.chat_model.run(degdeg): Ku socodsii moodeelka wada sheekaysiga degdeg la bixiyay.
• langchain.chat_model.interact_with(degdeg): La falgeli qaabka wada sheekeysiga adigoo isticmaalaya deg deg.

DSPy

• `dspy. Socodka shaqada()': Samee socodka shaqada DSPy.
• `socodka shaqada
• workflow.run(): socodsii socodka shaqada.

Muuqaalka

Halkan waxaa ah muuqaal sahlan oo socodka shaqada iyadoo la adeegsanayo Chart.js:

json { "type": "bar", "xogta": { "labels": ["Code Analysis", "Talooyin", "Diritaan"], "datasets": [ { "label": "socodka shaqada", "xogta": [10, 20, 30], "backgroundColor": [ "rgba(255, 99, 132, 0.2)", "rgba (54, 162, 235, 0.2)", "rgba(255, 206, 86, 0.2)" ], "BorderColor": [ "rgba(255, 99, 132, 1)", "rgba (54, 162, 235, 1)", "rgba (255, 206, 86, 1)" ], "BorderWidth": 1 } ] }, "ikhtiyaar": { "ciwaan": { "muujin": run, "text": "socodka shaqada" }, "Miisaanka": { "yAxes": [ { "ticks": { "beginAtZero": run } } ] } } }

Aragtidaani waxay muujinaysaa jaantus fudud oo ka dhigan socodka shaqada, oo leh saddex baarar oo matalaya falanqaynta koodhka, talooyinka, iyo hawlaha geynta.

Gabagabo

Maqaalkan, waxaan sahaminay aduunka AI-driven DevOps automation anagoo adeegsanayna LangChain iyo DSPy. Waxaan aragnay sida qaab-dhismeedkan loo isticmaali karo si loo abuuro habab xallinta arrimaha firfircoon iyo toosinta socodka shaqada horumarinta software. Waxaan sidoo kale bixinay tusaalooyin wax ku ool ah oo ku saabsan sida loogu dhex dari karo LLM-yada dhuumahaaga DevOps oo aan sawiro socodka shaqada iyadoo la adeegsanayo Chart.js.

Iyaga oo ka faa'iidaysanaya awoodda AI iyo automation-ka, ururradu waxay hagaajin karaan socodka shaqadooda horumarinta software, yaraynta khaladaadka gacanta, iyo hagaajinta waxtarka guud. Haddii aad tahay Injineer DevOps, horumariye software ah, ama hoggaamiye ganacsi, LangChain iyo DSPy waa aalado awood leh oo kaa caawin kara inaad gaarto yoolalkaaga.