I-Orchestrating AI Agents nge-LangChain: Ukwakha Izicelo Ezihlakaniphile ku-Python | B4N1

I-Orchestrating AI Agents nge-LangChain: Ukwakha Izicelo Ezihlakaniphile ku-Python

9 months ago · b4n1 Tiempo de lectura: 3 min

Ukuhlela ama-AI Agents nge-LangChain: Ukwakha Izicelo Ezihlakaniphile ku-Python

Isingeniso

Ukuhlanganiswa kwe-Artificial Intelligence (AI) kanye Nokufunda Komshini (ML) ezinhlelweni zesofthiwe kuguqule indlela esibhekana ngayo nokuxazulula izinkinga. Kodwa-ke, njengoba ubunkimbinkimbi bezinhlelo ze-AI bukhula, siyanda nesidingo sokucula nokuphatha ngendlela efanele. Yilapho i-LangChain iqala khona ukudlala - uhlaka olunamandla lokwakha izinhlelo zokusebenza ezihlakaniphile kuPython. Kulesi sihloko, sizongena emhlabeni we-LangChain, sihlole amakhono ayo, izimo zokusetshenziswa komhlaba wangempela, amasu okusebenzisa, kanye nemikhuba engcono kakhulu yokuthuthukisa ukukhiqiza konjiniyela kanye nobuhlakani bohlelo lokusebenza.

Iyini i-LangChain?

I-LangChain iwuhlaka lomthombo ovulekile olwakhiwe yi-Meta AI oluvumela ukudalwa kwezinhlelo zokusebenza ezihlakaniphile ngokuhlela ama-agent e-AI. Inikeza isixhumi esibonakalayo esihlanganisiwe sokuhlanganisa amamodeli e-AI ahlukahlukene, imithombo yedatha, nezinsizakalo, okwenza kube lula ukwakha amasistimu e-AI ayinkimbinkimbi. I-LangChain isekela izilimi eziningi zokuhlela, okuhlanganisa i-Python, Rust, ne-Go, okuvumela abathuthukisi ukuba bakhethe ulimi oluvumelana kangcono nezidingo zabo.

Izici ezibalulekile ze-LangChain

  1. I-Architecture Esekelwe Kumenzeli: I-LangChain isebenzisa i-architecture esekelwe kumenzeli, lapho i-ejenti ngayinye imelela imodeli ethile ye-AI noma isevisi. Lokhu kuvumela ukwakheka okulula nokuhlelwa kwama-ejenti amaningi ukuze kwakhe amasistimu e-AI ayinkimbinkimbi.
  2. Isikhombikubona Esihlanganisiwe: I-LangChain inikeza isixhumi esibonakalayo esihlanganisiwe sokuhlanganisa amamodeli e-AI ahlukahlukene, imithombo yedatha, namasevisi, okwenza kube lula ukwakha amasistimu e-AI ayinkimbinkimbi.
  3. Ukusekelwa Kwezilimi Eziningi: I-LangChain isekela izilimi eziningi zokuhlela, ezihlanganisa i-Python, Rust, ne-Go, okuvumela abathuthukisi ukuba bakhethe ulimi oluvumelana kangcono nezidingo zabo.
  4. Ilabhulali Ebanzi Yama-ejenti Akhiwe Ngaphambili: I-LangChain iza nomtapo wolwazi obanzi wama-ejenti akhelwe kusengaphambili wamamodeli namasevisi e-AI ahlukahlukene, okwenza kube lula ukuqalisa ngokwakha izinhlelo zokusebenza ezihlakaniphile.

Izimo Zokusetshenziswa Komhlaba Wangempela

  1. Ama-Chatbots: I-LangChain ingasetshenziselwa ukwakha ama-chatbots ahlanganisa amamodeli e-AI amaningi, njengokuqonda ulimi, ukuqashelwa kwenhloso, nokukhiqizwa kokuphendula.
  2. Izinhlelo Zokuncoma: I-LangChain ingasetshenziselwa ukwakha izinhlelo zokuncoma ezihlanganisa amamodeli e-AI amaningi, njengokuhlunga ngokubambisana, ukuhlunga okusekelwe kokuqukethwe, nokuhlunga okusekelwe kugrafu yolwazi.
  3. Abasizi Ababonakalayo: I-LangChain ingasetshenziselwa ukwakha abasizi ababonakalayo abahlanganisa amamodeli e-AI amaningi, njengokuqaphela inkulumo, ukuqonda kolimi lwemvelo, nokwenza umsebenzi.
  4. Isizukulwane Sokuqukethwe: I-LangChain ingasetshenziselwa ukwakha amasistimu okukhiqiza okuqukethwe ahlanganisa amamodeli e-AI amaningi, njengokukhiqiza ulimi, ukukhiqizwa kwezithombe, nokukhiqizwa kwevidiyo.

Amaqhinga Okusebenzisa

  1. Qala Ngekesi Lokusebenzisa Elilula: Qala ngokwakha uhlelo lokusebenza lwe-AI olulula usebenzisa i-LangChain, njenge-chatbot noma isistimu yokuncoma.
  2. Khetha Ama-ejenti Afanele: Khetha ama-ejenti afanele wecala lakho lokusebenzisa, ngokusekelwe kumamodeli we-AI namasevisi adingekayo.
  3. Sebenzisa Isixhumi Esibonakalayo Esihlanganisiwe: Sebenzisa isixhumi esibonakalayo esihlanganisiwe esinikezwe i-LangChain ukuze uhlanganise ama-ejenti amaningi futhi wakhe amasistimu e-AI ayinkimbinkimbi.
  4. Linga futhi Uphindaphinde: Linga ngama-ejenti ahlukene kanye nezilungiselelo ukuze uthole indlela engcono kakhulu yekesi lakho lokusebenzisa.

Imikhuba Engcono Kakhulu

  1. Landela Imibhalo Ye-LangChain: Landela imibhalo ye-LangChain ukuze uqinisekise ukuthi usebenzisa uhlaka ngendlela efanele nangempumelelo.
  2. Sebenzisa Ama-ejenti Akhiwe Ngaphambili: Sebenzisa ama-ejenti akhelwe kusengaphambili anikezwe i-LangChain ukuze wonge isikhathi nomzamo.
  3. Hlola Kahle: Hlola isicelo sakho se-AI ngokucophelela ukuze uqinisekise ukuthi sisebenza njengoba kulindelekile.
  4. Qapha Ngokuqhubekayo futhi Uthuthukise: Qhubeka uqaphe uhlelo lwakho lokusebenza lwe-AI futhi ulithuthukise ngokusekelwe kumpendulo yomsebenzisi namamethrikhi okusebenza.

Imiyalo/Amazwibela Aphezulu Okuyi-5-10

Python


ngenisa i-langchain

# Dala i-ejenti entsha ye-LangChain
i-ejenti = langchain.Agent(
    igama="umenzeli_wami",
    incazelo="Umenzeli wami we-AI",
    ulimi="python",
    framework="langchain"
)

# Dala umsebenzi omusha we-LangChain
umsebenzi = langchain.Task(
    igama="umsebenzi_wami",
    incazelo="Umsebenzi wami we-AI",
    input_data={"text": "Sawubona, mhlaba!"}
)

# Yenza umsebenzi usebenzisa i-ejenti
umphumela = i-agent.run(umsebenzi)

# Phrinta umphumela
phrinta(umphumela)

Ukugqwala

// Ngenisa umtapo wezincwadi we-LangChain
sebenzisa i-langchain::{Agent, Task};

// Dala i-ejenti entsha ye-LangChain
vumela i-ejenti = Umenzeli ::omusha(
    "i-ejenti_yami",
    "Umenzeli wami we-AI",
    "ukugqwala",
    "langchain"
);

// Dala umsebenzi omusha we-LangChain
vumela umsebenzi = Umsebenzi::okusha(
    "umsebenzi_wami",
    "Umsebenzi wami we-AI",
    vec!["umbhalo".to_string()],
    vec![String::from("Sawubona, mhlaba!")]
);

// Qalisa umsebenzi usebenzisa i-ejenti
vumela umphumela = i-agent.run(umsebenzi);

// Phrinta umphumela
println!("{}", umphumela);

Hamba

// Ngenisa umtapo wezincwadi we-LangChain
iphakethe main

ngenisa (
    "fmt"
    "github.com/langchain/langchain-go"
)

// Dala i-ejenti entsha ye-LangChain
func main() {
    umenzeli := langchain.NewAgent(
        "i-ejenti_yami",
        "Umenzeli wami we-AI",
        "hamba",
        "langchain"
    )

    // Dala umsebenzi omusha we-LangChain
    umsebenzi := langchain.NewTask(
        "umsebenzi_wami",
        "Umsebenzi wami we-AI",
        []uchungechunge{"umbhalo"},
        []uchungechunge{"Sawubona, mhlaba!"}
    )

    // Qalisa umsebenzi usebenzisa i-ejenti
    umphumela := i-ejenti.Run(umsebenzi)

    // Phrinta umphumela
    fmt.Println(umphumela)
}

Ukubona

{
    uhlobo: 'ibha',
    idatha: {
        amalebula: ['Umenzeli 1', 'Umenzeli 2', 'Umenzeli 3'],
        idathasethi: [{
            ilebula: 'Ukunemba',
            idatha: [0.8, 0.9, 0.7],
            Umbala wangemuva: [
                'rgba(255, 99, 132, 0.2)',
                'rgba(54, 162, 235, 0.2)',
                'rgba(255, 206, 86, 0.2)'
            ],
            Umbala womngcele: [
                'rgba(255, 99, 132, 1)',
                'rgba(54, 162, 235, 1)',
                'rgba(255, 206, 86, 1)'
            ],
            Ububanzi bomngcele: 1
        }]
    },
    izinketho: {
        isikali: {
            yAxes: [{
                imikhaza: {
                    startAtZero: kuyiqiniso
                }
            }]
        }
    }
}

Leli shadi libonisa ukunemba kwama-ejenti amathathu ahlukene e-AI esimweni esithile sokusetshenziswa.

Isiphetho

I-LangChain iwuhlaka olunamandla lokwakha izinhlelo zokusebenza ezihlakaniphile kuPython. Isakhiwo sayo esisekelwe kumenzeli, isixhumi esibonakalayo esihlanganisiwe, nokusekelwa kwezilimi eziningi kuyenza ibe inketho ekahle kubathuthukisi abafuna ukwakha amasistimu e-AI ayinkimbinkimbi. Ngokulandela izinqubo ezingcono kakhulu ezichazwe kulesi sihloko kanye nokusebenzisa ama-ejenti akhiwe ngaphambilini kanye nesixhumi esibonakalayo esihlanganisiwe esinikezwe i-LangChain, abathuthukisi bangakha izinhlelo zokusebenza ezihlakaniphile ezisebenza kahle, ezihlanjululwe, nezilula ukuzinakekela.


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