Tatala ZeroOps ma AI Agents ma Context Engineering: O se Faiga Faʻavae Faʻataʻitaʻiga i AI DevOps Automation e faʻaaoga ai StackGen ma LangChain | B4N1

Tatala ZeroOps ma AI Agents ma Context Engineering: O se Faiga Faʻavae Faʻataʻitaʻiga i AI DevOps Automation e faʻaaoga ai StackGen ma LangChain

8 months ago · b4n1 Tiempo de lectura: 6 min

Tatalaina o ZeroOps ma AI Agents ma Context Engineering: O se Faʻataʻitaʻiga Faʻavae i le AI DevOps Automation e faʻaaoga ai StackGen ma LangChain

Fa'atomuaga

I le faʻavavevave faʻaleleia o laufanua o le atinaʻeina o polokalama, o le manatu o ZeroOps ua tulaʻi mai o se faiga faʻafouina i le DevOps automation. ZeroOps e faʻamoemoe e faʻaumatia le manaʻoga mo le faʻaogaina o le tusi lesona i le faʻapipiʻiina ma le puleaina o polokalama faakomepiuta, e mafai ai e le au atinaʻe ona taulaʻi atu i galuega maualuga e pei o le faʻafouina ma le fatufatuaʻi. I lenei tusiga, o le a tatou suʻesuʻe i le lalolagi o ZeroOps ma suʻesuʻe pe faʻafefea ona faʻaogaina AI sui ma faʻainisinia faʻamatalaga e ausia ai lenei sini. O le a matou talanoaina foi le faʻatinoina o se faʻataʻitaʻiga faʻavae i le AI DevOps automation e faʻaaoga ai StackGen ma LangChain.

O le a le ZeroOps?

ZeroOps o se DevOps faʻataʻitaʻiga e taumafai e faʻatometi le faagasologa atoa o le atinaʻeina o polokalama, mai le atinaʻe i le faʻapipiʻiina ma le pulega. O le sini autu o ZeroOps o le faʻaumatiaina lea o le manaʻoga mo le faʻaogaina o le tusi lesona i le faʻapipiʻiina ma le puleaina o polokalama faakomepiuta, ma faʻaitiitia ai le ono mafai ona sese tagata ma faʻateleina le saoasaoa ma le lelei o le tuʻuina atu o polokalama.

AI Agents ma Context Engineering

AI sui ma fa'ainisinia fa'amatalaga e taua tele i le fa'atinoga o ZeroOps. O sui ole AI o polokalama faakomepiuta e mafai ona iloa lo latou siosiomaga ma faia ni gaioiga e ausia ai sini patino. Fa'ainisinia fa'amatalaga, i le isi itu, e aofia ai le mamanuina ma le fa'atinoina o faiga e mafai ona malamalama ma tali atu i le tala o lo'o fa'agaioi ai.

I le tulaga o ZeroOps, e mafai ona faʻaogaina sui ole AI e faʻaaogaina galuega eseese e pei o le faʻatulagaina, suʻega, ma le mataʻituina. E mafai ona fa'aoga le fa'ainisinia o fa'amatalaga e mamanu ai faiga e mafai ona malamalama ai i le tala'aga o lo'o fa'agaioi ai, e pei o le si'osi'omaga, le tagata fa'aoga, ma le galuega o lo'o i ai.

StackGen: O se Faiga Faʻavae Faʻataʻitaʻiga ile AI DevOps Automation

StackGen o se faʻavaʻa faʻapipiʻi e mafai ai e tagata atiaʻe ona faʻatinoina se faʻataʻitaʻiga faʻavae i le AI DevOps automation. StackGen o loʻo tuʻuina atu se seti o faʻataʻitaʻiga ma faʻataʻitaʻiga e mafai ona faʻaaogaina e faʻaaogaina ai galuega eseese e pei o le faʻapipiʻiina, suʻega, ma le mataʻituina.

StackGen o loʻo fausia i luga ole LangChain, o se faʻavae e mafai ai e le au atinaʻe ona fausia faiga faʻatalanoaga AI. LangChain o loʻo tuʻuina atu se seti o API ma meafaigaluega e mafai ona faʻaogaina e fausia ai faiga faʻatalanoaga AI e mafai ona malamalama ma tali atu i faʻaoga gagana masani.

LangChain: Fausiaina Faiga Fa'amatalaga AI

LangChain o se faʻavae e mafai ai e le au atinaʻe ona fausia faiga faʻatalanoaga AI. LangChain o loʻo tuʻuina atu se seti o API ma meafaigaluega e mafai ona faʻaogaina e fausia ai faiga faʻatalanoaga AI e mafai ona malamalama ma tali atu i faʻaoga gagana masani.

LangChain o loʻo fausia i luga o le tele o tekonolosi faʻamatalaga, e aofia ai TensorFlow ma PyTorch. LangChain o loʻo tuʻuina atu se seti o API ma meafaigaluega e mafai ona faʻaogaina e fausia ai faiga faʻatalanoaga AI e mafai ona malamalama ma tali atu i faʻaoga gagana masani.

Faʻatinoina ZeroOps ma StackGen ma LangChain

Ina ia faʻatinoina ZeroOps ma StackGen ma LangChain, e manaʻomia ona tatou mulimulitaʻi i ni laasaga:

  1. ** Faʻamatala le AI Agent **: O le laasaga muamua i le faʻatinoina o ZeroOps o le faʻamalamalamaina lea o le sui AI o le a faʻaaogaina e faʻaaogaina ai galuega eseese. E mafai ona faʻamalamalamaina le sui sooupu AI e faʻaaoga ai le tele o faʻataʻitaʻiga ma faʻataʻitaʻiga na saunia e StackGen.
  2. Design the Context Engine: O le isi laasaga o le mamanuina o le anotusi afi o le a faʻaaogaina e malamalama ai ma tali atu i le tala o loʻo galue ai le sui AI. E mafai ona mamanuina le afi afi e faʻaaoga ai le tele o API ma meafaigaluega na tuʻuina atu e LangChain.
  3. ** Faʻatinoina le AI Agent **: A maeʻa ona faʻamalamalamaina le sui AI ma le afi faʻamatalaga, o le isi laasaga o le faʻaaogaina lea o le sui AI e faʻaaoga ai le tele o API ma meafaigaluega na saunia e StackGen ma LangChain.
  4. Su'ega ma Fa'atino: O le laasaga mulimuli o le fa'ata'ita'i ma fa'apipi'i le sui sooupu AI i se siosiomaga gaosiga.

** Fa'ata'ita'iga Fa'ailoga: Fa'atinoina o se Faigofie AI Agent fa'aaoga StackGen ma LangChain**

O se faʻataʻitaʻiga poloka poloka e faʻaalia ai le faʻaogaina o se sui AI faigofie e faʻaaoga ai StackGen ma LangChain:

faaulufale mai le langchain
mai langchain.chains faaulufale mai LLMChain
mai langchain.llms faaulufale mai LLM


ai_agent = LLMChain(
    llm=LLM(
        model_name="davinci:3-batch",
        vevela=0.5,
        max_tokens=100,
    ),
    input_format="text",
    output_format="text",
)

# Fa'amatala le afi fa'amatalaga
context_engine = langchain.ContextEngine(
    llm=LLM(
        model_name="davinci:3-batch",
        vevela=0.5,
        max_tokens=100,
    ),
    input_format="text",
    output_format="text",
)

# Faʻatino le sui sooupu AI
ai_agent.implement(
    context_engine=context_engine,
    input_text="Talofa, o a mai oe?",
)

# Suʻe ma faʻapipiʻi le sui AI
ai_agent.test_and_deploy(
    input_text="Talofa, o a mai oe?",
)

O lenei poloka code o loʻo faʻaalia ai le faʻaogaina o se sui AI faigofie e faʻaaoga ai StackGen ma LangChain. O le sui sooupu AI o loʻo faʻamatalaina e faʻaaoga ai le tele o faʻataʻitaʻiga ma faʻataʻitaʻiga na saunia e StackGen. O le afi faʻamatalaga ua mamanuina e faʻaaoga ai le tele o API ma meafaigaluega na saunia e LangChain. O le sui AI o loʻo faʻatinoina e faʻaaoga ai le tele o API ma meafaigaluega na tuʻuina atu e StackGen ma LangChain. Mulimuli ane, o le sui sooupu AI e tofotofoina ma faʻapipiʻiina i se siosiomaga gaosiga.

Poloaiga/Snippets pito i luga 5-10 Fa'aaogaina

O le pito i luga 5-10 pito sili ona faʻaaogaina poloaiga / snippets mo StackGen ma LangChain:

  1. langchain.LLMChain(): Fausia se mea fou filifili LLM.
  2. langchain.ContextEngine(): Fausia se mea fou afi afi.
  3. LLM(model_name="davinci:3-batch", temperature=0.5, max_tokens=100): Fausia se mea fou LLM ma le igoa fa'ata'ita'i fa'apitoa, vevela, ma fa'ailoga maualuga.
  4. ai_agent.implement(context_engine=context_engine, input_text="Talofa, o a mai oe?"): Faʻaaogaina le sui AI e faʻaaoga ai le afi faʻamatalaga maʻoti ma tusitusiga faʻapipiʻi.
  5. ai_agent.test_and_deploy(input_text="Talofa, o a mai oe?"): Suʻega ma faʻapipiʻi le sui AI e faʻaaoga ai tusitusiga faʻapipiʻi.
  6. langchain.llms.LLM(): Fausia se mea fou LLM.
  7. langchain.chains.LLMChain(): Fausia se mea fou filifili LLM.
  8. langchain.ContextEngine(llm=LLM(model_name="davinci:3-batch", temperature=0.5, max_tokens=100)): Fausia se mea fa'ainitaneti fou e fa'aaoga ai le mea fa'apitoa LLM.
  9. ai_agent.context_engine = langchain.ContextEngine(llm=LLM(model_name="davinci:3-batch", temperature=0.5, max_tokens=100)): Seti le afi fa'asinomaga o le sui sooupu AI i le mea fa'atatau o le afi.
  10. ai_agent.input_text = "Talofa, o a mai oe?": Seti le tusitusiga o lo'o i totonu o le sui sooupu AI i le tusitusiga fa'amautu.

Va'aiga

Ole fa'aaliga lea ole fausaga ole ZeroOps ile fa'aogaina ole Chart.js:

{
  "type": "pa",
  "fa'amatalaga": {
    "labels": ["AI Agent", "Context Engine", "StackGen", "LangChain"],
    "fa'amaumauga": [
      {
        "label": "Faigafale",
        "faamatalaga": [10, 8, 6, 4],
        "Lulu lanu": ["#FF6384", "#36A2EB", "#FFCE56", "#4BC0C0"]
      }
    ]
  },
  "filifiliga": {
    "igoa": {
      "fa'aaliga": moni,
      "text": "ZeroOps Architecture"
    },
    "talatu'u": {
      "faʻaalia": moni
    },
    "fua": {
      "yAxes": [
        {
          "tiki": {
            "beginAtZero": moni
          }
        }
      ]
    }
  }
}

O lenei faʻaaliga faʻaalia o loʻo faʻaalia ai le fausaga o le ZeroOps system, e aofia ai le sui AI, faʻamatalaga afi, StackGen, ma LangChain.

Fa'ai'uga

ZeroOps o se faiga faʻafouina i le DevOps automation lea e taumafai e faʻaumatia le manaʻomia mo le faʻaogaina o le tusi lesona i le faʻapipiʻiina ma le puleaina o polokalama faakomepiuta. AI sui ma fa'ainisinia fa'asinomaga e taua tele i le fa'atinoga o ZeroOps, ma StackGen ma LangChain e tu'uina atu se fa'ata'ita'iga fa'avae ile AI DevOps automation. E ala i le faʻatinoina o se sui AI faigofie e faʻaaoga ai StackGen ma LangChain, e mafai ona tatou faʻaogaina galuega eseese e pei o le faʻapipiʻiina, suʻega, ma le mataʻituina. O loʻo tuʻuina atu foʻi le 5-10 pito sili ona faʻaaogaina tulafono / snippets mo StackGen ma LangChain, faʻatasi ai ma se faʻaaliga o le faʻaogaina o le ZeroOps e faʻaaoga ai le Chart.js.


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