Kuronga Agentic AI muDevOps Mapaipi ane DSPy uye LangChain yeEnhanced ZeroOps

Kuronga Agentic AI muDevOps Mapaipi ane DSPy uye LangChain yeEnhanced ZeroOps

Introduction

Kubatanidzwa kweArtificial Intelligence (AI) mumapaipi eDevOps kwakashandura nzira yekugadzira, kuedzwa, uye kutumirwa kwesoftware. Agentic AI, chikamu cheAI chinogonesa kuzvitonga kwekuita sarudzo uye kutora-chiito, ine mukana wekuwedzera kusimudzira nekubudirira kweDevOps maitiro. Muchikamu chino, tichaongorora pfungwa yekuronga agent AI mumapaipi eDevOps tichishandisa DSPy neLangChain, uye tokurukura zvakanakira nzira iyi mukuwana ZeroOps.

Chii chinonzi Agent AI?

Agentic AI inoreva rudzi rweAI ine kugona kuita sarudzo uye kuita zviito zvakazvimiririra, pasina kupindira kwevanhu. Izvi zvinowanikwa kuburikidza nekushandiswa kweyepamusoro muchina kudzidza algorithms, mitauro yechisikigo kugadzirisa, uye cognitive zvivakwa. Agentik AI masisitimu anogona kudzidza kubva pane zvakaitika, kujairana nemamiriro matsva, uye kudyidzana nevanhu mune yakasarudzika uye intuitive nzira.

Chii chinonzi ZeroOps?

ZeroOps ihuzivi hweDevOps ine chinangwa chekubvisa kudiwa kwekupindira kwevanhu mukuvandudza software, kutumira, uye kugadzirisa. Izvi zvinowanikwa kuburikidza nekushandisa otomatiki, orchestration, uye AI-inotungamirwa kuita sarudzo. ZeroOps inogonesa masangano kuendesa software nekukurumidza, nemhando yepamusoro, uye nemutengo wakaderera.

Kuronga Agenti AI muDevOps Pipelines

Kuronga agentic AI mumapaipi eDevOps, tinoda kubatanidza kuita sarudzo kunotungamirwa neAI uye kutora-kuita mupombi. Izvi zvinogona kuwanikwa kuburikidza nekushandiswa kweDSPy neLangChain, maitiro maviri anozivikanwa ekuvaka uye kutumira maapplication anofambiswa neAI.

DSPy

DSPy chirongwa chePython chekuvaka uye kutumira maapplication anofambiswa neAI. Inopa seti yezvishandiso uye maraibhurari ekugadzirisa data, kudzidza muchina, uye kugadzirwa kwemutauro wechisikigo. DSPy yakagadzirirwa kushanda isina musono nemafuremu akakurumbira akadai seLangChain uye FastAPI.

LangChain

LangChain iPython framework yekuvaka uye kutumira maAI-driven applications. Inopa seti yezvishandiso uye maraibhurari ekugadzirisa mutauro wechisikigo, kudzidza muchina, uye yekuziva zvivakwa. LangChain yakagadzirirwa kushanda isina musono nemafuremu akakurumbira akadai seDSPy uye FastAPI.

Technical Implementation

Kuratidza tekinoroji yekumisikidza kwe orchestrating agent AI muDevOps mapaipi uchishandisa DSPy neLangChain, ngatifungei muenzaniso wakapusa. Ngatitii isu tinoda kugadzirisa kutumira kwewebhu application tichishandisa pombi yeDevOps. Isu tinogona kushandisa DSPy kuvaka iyo AI-inotyairwa sarudzo-yekuita sisitimu inotaridza iyo yakakwana yekuendesa zano zvichienderana nezvinhu zvakaita sekuita kwekushandisa, mhinduro yemushandisi, uye zviwanikwa zvehurongwa.

import dspy
kubva ku langchain import LLM


def deployment_strategy(app_performance, user_feedback, system_resources):
    # Shandisa DSPy kugadzirisa data uye kuita sarudzo
    data = dspy.Data(app_performance, user_feedback, system_resources)
    Sarudzo = dSpy.DecisionMaker(data)
    
    # Shandisa LangChain kugadzira chirongwa chekuendesa
    llm = LLM("chinyorwa-davinci-003")
    plan = llm.generate_text(f"Deploy {app_performance} ine {user_feedback} uye {system_resources} zviwanikwa")
    
    chirongwa chekudzoka

# Tsanangura iyo DevOps pombi
def pombi (app_performance, user_feedback, system_resources):
    # Shandisa DSPy kuronga pombi
    pombi = dSpy.Pipeline()
    pipeline.add_task(deployment_strategy, app_performance, user_feedback, system_resources)
    pipeline.add_task(dspytasks.Deploy, plan)
    
    # Mhanya pombi
    pipeline.run()

# Mhanya pombi
pombi (90, 4.5, 80)

Pamusoro 5-10 Inonyanya Kushandiswa Mirairo/Zvidimbu

Heano epamusoro 5-10 anonyanya kushandiswa mirairo/zvimedu zveDSPy uye LangChain:

dspy.Data(): Inogadzira chinhu chedata chekugadzirisa uye kuita sarudzo.
dspy.DecisionMaker(): Inoita sarudzo zvichienderana nedata uye mamiriro.
LLM.generate_text(): Inogadzira zvinyorwa zvichibva pane zvinopinza.
dspytasks.Deploy(): Inotumira chikumbiro zvichienderana nehurongwa hwekutumira.
dspy.Pipeline(): Inoronga pombi yeDevOps.
pipeline.add_task(): Inowedzera basa kune pombi.
pipeline.run(): Inomhanyisa pombi.
dspy.Data.process(): Inogadzirisa data pakuita sarudzo.
dspy.DecisionMaker.decide(): Inoita sarudzo zvichienderana nedata uye mamiriro.
LLM.generate_text(prompt): Inogadzira zvinyorwa zvichibva pazvinoitwa.

Kuona

Heino tarisiro yeagentic AI-inofambiswa neDevOps pombi uchishandisa Chart.js:

{
  "type": "bha",
  "data": {
    "labels": ["Data Processing", "Kuita Sarudzo", "Deployment"],
    "datasets": [
      {
        "label": "Agentic AI",
        "data": [10, 20, 30],
        "backgroundColor": "rgba(255, 99, 132, 0.2)",
        "borderColor": "rgba(255, 99, 132, 1)",
        "borderWidth": 1
      }
    ]
  },
  "sarudzo": {
    "zvikero": {
      "yAxes": [
        {
          "zvikwekwe": {
            "beginAtZero": chokwadi
          }
        }
      ]
    }
  }
}

Kuona uku kunoratidza matanho matatu eiyo agent AI-inotyairwa DevOps pombi: kugadzirisa data, kuita sarudzo, uye kutumira.

Mhedziso

Muchikamu chino, takaongorora pfungwa yekuronga agent AI muDevOps mapaipi uchishandisa DSPy uye LangChain. Takaratidza muenzaniso wakapfava wekuita otomatiki kutumira kwewebhu application uchishandisa AI-inotyairwa kuita sarudzo system. Isu takapawo maonero eiyo agentic AI-inotyairwa DevOps pombi tichishandisa Chart.js. Nekubatanidza agent AI mumapaipi eDevOps, masangano anogona kuwana ZeroOps uye kuendesa software nekukurumidza, nemhando yepamusoro, uye nemitengo yakaderera.

Kuronga Agentic AI muDevOps Mapaipi ane DSPy uye LangChain yeEnhanced ZeroOps

Have Questions?