** Orchestrating Agentic AI na DevOps Pipeline nwere DSPy na LangChain maka emelitere ZeroOps ***
** Okwu mmalite**
Ntinye aka nke Artificial Intelligence (AI) na pipeline DevOps agbanweela ka esi emepụta, nwale, na ibunye ngwanrọ. AI Agentic, akụkụ nke AI nke na-enyere aka ịme mkpebi na ime ihe n'onwe ya, nwere ike ịkwalite arụmọrụ na ịdị irè nke usoro DevOps. N'isiokwu a, anyị ga-enyocha echiche nke nhazi AI AI na DevOps pipeline site na iji DSPy na LangChain, ma tụlee uru nke ụzọ a iji nweta ZeroOps.
Gịnị bụ AI?
AI Agentic na-ezo aka n'ụdị AI nke nwere ikike ime mkpebi na ime ihe n'onwe ya, na-enweghị enyemaka mmadụ. A na-enweta nke a site n'iji igwe mmụta algọridim dị elu, nhazi asụsụ eke, na ihe nleba anya. Usoro AI nke AI nwere ike ịmụta site na ahụmahụ, ime mgbanwe n'ọnọdụ ọhụrụ, ma soro ụmụ mmadụ na-emekọrịta ihe n'ụzọ dị mma na nke nghọta.
Gịnị bụ ZeroOps?
ZeroOps bụ nkà ihe ọmụma DevOps nke na-achọ iwepụ mkpa ọ dị maka itinye aka mmadụ na mmepe ngwanrọ, mbugharị na mmezi. A na-enweta nke a site na iji automation, orchestration, na ime mkpebi nke AI na-edu. ZeroOps na-enyere ndị otu aka ibuga sọftụwia ngwa ngwa, nwere ogo dị elu yana ọnụ ala dị ala.
** Ndị na-ahazi AI na-arụ ọrụ na pipeline DevOps ***
Iji hazie AI AI na-arụ ọrụ na pipeline DevOps, anyị kwesịrị ijikọ mkpebi AI na-eme na ime ihe n'ime pipeline. Enwere ike nweta nke a site na iji DSPy na LangChain, usoro abụọ a ma ama maka iwulite na ibuga ngwa AI na-ebugharị.
DSPy
DSPy bụ usoro Python maka iwulite na ibuga ngwa AI na-achụ. Ọ na-enye ọtụtụ ngwaọrụ na ọba akwụkwọ maka nhazi data, mmụta igwe, na nhazi asụsụ eke. Emebere DSPy ka ọ rụọ ọrụ n'enweghị nsogbu yana usoro ndị ama ama dịka LangChain na FastAPI.
** LangChain ***
LangChain bụ usoro Python maka iwulite na ibuga ngwa AI na-ebugharị. Ọ na-enye ọtụtụ ngwaọrụ na ọba akwụkwọ maka nhazi asụsụ eke, mmụta igwe, na ihe nleba anya. Emebere LangChain ka ọ rụọ ọrụ n'enweghị nsogbu yana usoro ndị ama ama dịka DSPy na FastAPI.
** Mmejuputa nka na ụzụ ***
Iji gosipụta mmejuputa teknụzụ nke nhazi AI na DevOps pipeline site na iji DSPy na LangChain, ka anyị tụlee otu ihe atụ dị mfe. Ka e were ya na anyị chọrọ ịmegharị ntinye nke ngwa weebụ site na iji pipeline DevOps. Anyị nwere ike iji DSPy wuo usoro mkpebi mkpebi AI nke na-ekpebi atụmatụ ntinye kacha mma dabere na ihe ndị dị ka arụmọrụ ngwa, nzaghachi onye ọrụ, na akụrụngwa sistemụ.
"Python mbubata dspy si langchain mbubata LLM
def deployment_strategy(app_performance, user_feedback, system_resources): # Jiri DSPy hazie data wee mee mkpebi data = dspy.Data(app_performance, user_feedback, system_resources) mkpebi = dspy.DecisionMaker(data)
# Jiri LangChain mepụta atụmatụ mbugharị
llm = LLM ("ederede-davinci-003")
plan = llm.generate_text(f"Bufee {app_performance} na {user_feedback} na {system_resources} akụrụngwa)
atụmatụ nloghachi
Kọwaa pipeline DevOps
pipeline def (app_performance, user_feedback, system_resources): # Jiri DSPy hazie pipeline pipeline = dspy.Pipeline() pipeline.add_task (deployment_strategy, app_performance, user_feedback, system_resources) pipeline.add_task(dspytasks.Deploy, plan)
# Gbaa pipeline
pipeline.run ()
Gbaa pipeline
ọkpọkọ (90, 4.5, 80) ``
** Iwu 5-10 Kachasị Eji mee ihe
Nke a bụ iwu/snippets 5-10 kacha eji eme ihe maka DSPy na LangChain:
dspy.Data(): Na-emepụta ihe data maka nhazi na ime mkpebi.- `dspy.DecisionMaker()': Na-eme mkpebi dabere na data na ọnọdụ.
LLM.generate_text(): Na-emepụta ederede dabere na ntinye ntinye.dspytasks.Deploy(): Na-ebuga ngwa dabere na atụmatụ ntinye.dspy.Pipeline(): Na-ahazi pipeline DevOps.- `pipeline.add_task()': Na-agbakwunye ọrụ na pipeline.
pipeline.run(): Na-agba ọsọ ọkpọkọ.dspy.Data.process(): Na-ahazi data maka ime mkpebi.dspy.DecisionMaker.decide(): Na-eme mkpebi dabere na data na ọnọdụ.- `LLM.generate_text(prompt):': Na-emepụta ederede dabere na ntinye ntinye.
** Nlegharị anya ***
Nke a bụ nleba anya nke ọkpọkọ DevOps na-ebugharị AI na-eji Chart.js: Json { "ụdị": "ogwe", "data": { "labels": ["Nhazi data", "Mkpebi ime", "Nkwanye"], "datasets": [ { "label": "Agent AI", "data": [10, 20, 30], "backgroundColor": "rgba(255, 99, 132, 0.2)", "BorderColor": "rgba(255, 99, 132, 1)", "BorderWiidth": 1 } ] }, "Nhọrọ": { "ọnụego": { "yAxes": [ { "akara aka": { "beginAtZero": eziokwu } } ] } } } `` Ọhụụ a na-egosi usoro atọ nke ọkpọkọ DevOps nke AI na-arụ ọrụ: nhazi data, ime mkpebi, na ibuga.
Mkpebi
N'isiokwu a, anyị nyochara echiche nke nhazi AI AI na DevOps pipeline site na iji DSPy na LangChain. Anyị gosipụtara ihe atụ dị mfe nke otu esi emegharị ntinye nke ngwa weebụ site na iji usoro ime mkpebi nke AI na-ebute. Anyị nyekwara ọhụụ nke ọkpọkọ DevOps nke AI na-ebugharị site na iji Chart.js. Site na ijikọ AI na-arụ ọrụ n'ime pipeline DevOps, òtù dị iche iche nwere ike nweta ZeroOps ma bukwaa ngwanrọ ngwa ngwa, yana ịdị elu dị elu, yana ọnụ ala dị ala.