Ukwakha ama-Intelligent Agents nge-LangChain: Ukuhlela ama-LLM ezinhlelo zokusebenza zomhlaba wangempela

Ukwakha ama-Intelligent Agents nge-LangChain: Ukuhlela ama-LLM ezinhlelo zokusebenza zomhlaba wangempela

Isingeniso

Ukufika kwamamodeli olimi olukhulu (LLMs) kuguqule umkhakha weNatural Language Processing (NLP) futhi sekuvule izindlela ezintsha zokuthuthukisa ama-agent ahlakaniphile akwazi ukuqonda, ukukhiqiza, nokusebenzisana nolimi lwabantu. I-LangChain iwumtapo wezincwadi wePython ohlinzeka ngohlaka oluguquguqukayo nolukakala lokwakha ama-agent ahlakaniphile asebenzisa ama-LLM. Kulesi sihloko, sizohlola ukuhlanganiswa kwe-LangChain ekuthuthukiseni ama-agent ahlakaniphile, sigxile kumasu okusebenza okusebenzayo, amasu omculo we-orchestration, kanye namacala okusebenzisa kubunjiniyela besofthiwe.

Ayini ama-Intelligent Agents?

Ama-agent ahlakaniphile izinhlelo zesofthiwe ezikwazi ukubona indawo ezizungezile, acabange ngolwazi abalutholayo, futhi athathe izinyathelo zokufeza izinhloso zabo. Bangacatshangwa njengabenzi bezinqumo abazimele abangasebenzisana nabasebenzisi, amanye ama-ejenti, noma amasistimu ukufeza inhloso ethile. Ama-agent ahlakaniphile angahlukaniswa ngezinhlobo ezahlukene, okuhlanganisa:

• Ama-ejenti asekelwe kumthetho: Lawa ma-ejenti asebenzisa imithetho echazwe ngaphambilini ukuze enze izinqumo.
• Abenzeli bokufunda ngomshini: Laba basebenzeli basebenzisa ama-algorithms okufunda komshini ukuze bafunde kudatha futhi benze izinqumo.
• Abenzeli be-Hybrid: Laba basebenzeli bahlanganisa izindlela ezisekelwe emithethweni nokufunda ngomshini ukuze benze izinqumo.

Iyini i-LangChain?

I-LangChain iwumtapo wezincwadi wePython ohlinzeka ngohlaka oluguquguqukayo nolukakala lokwakha ama-agent ahlakaniphile asebenzisa ama-LLM. Ivumela onjiniyela ukuthi bakhe, baqeqeshe, futhi basebenzise ama-LLM, futhi bawahlanganise namanye amamodeli namasistimu e-AI. I-LangChain inikeza uhla lwezici, kufaka phakathi:

• Ukuhlanganiswa kwe-LLM: I-LangChain inikeza indlela elula nephumelelayo yokuhlanganisa ama-LLM namanye amamodeli nezinhlelo ze-AI.
• I-Orchestration: I-LangChain inikeza uchungechunge lwamasu okucula, okuhlanganisa ukuphathwa komsebenzi, ukuphathwa kokuhamba komsebenzi, nokuphathwa kwedatha.
• Scalability: I-LangChain yakhelwe ukukala ngamasethi edatha amakhulu kanye nokugeleza komsebenzi okuyinkimbinkimbi.

Amaqhinga Okusebenzisa Angokoqobo

Ukuze wakhe ama-agent ahlakaniphile nge-LangChain, udinga ukulandela lawa masu okusebenzisa asebenzayo:

1. Khetha i-LLM: Khetha i-LLM ehlangabezana nezimfuneko zakho, njengolimi, usayizi, nobunkimbinkimbi.
2. Lungiselela idatha: Lungiselela idathasethi ehambisana nesimo sakho sokusebenzisa futhi elungele ukuqeqesha i-LLM.
3. Qeqesha i-LLM: Qeqesha i-LLM usebenzisa idathasethi elungisiwe kanye ne-API yokuqeqeshwa ye-LangChain.
4. Hlanganisa namanye amamodeli e-AI: Hlanganisa i-LLM eqeqeshiwe namanye amamodeli we-AI namasistimu usebenzisa i-API yokuhlanganisa ye-LangChain.
5. Imisebenzi ye-Orchestrate: Sebenzisa i-API ye-orchestration ye-LangChain ukuze ulawule imisebenzi, ukuhamba komsebenzi, nedatha.

Izindlela Zokucula

I-LangChain inikeza uchungechunge lwamasu okucula angasetshenziswa ukuphatha imisebenzi, ukuhamba komsebenzi, kanye nedatha. Ezinye zezindlela eziyinhloko ze-orchestration zihlanganisa:

• Ukuphathwa komsebenzi: I-LangChain inikeza i-API yokuphatha umsebenzi evumela onjiniyela ukuthi bakhe, baphathe, futhi benze imisebenzi.
• Ukuphathwa kokuhamba komsebenzi: I-LangChain inikeza i-API yokuphatha ukugeleza komsebenzi evumela onjiniyela ukuthi bakhe, baphathe, futhi basebenzise ukugeleza komsebenzi.
• Ukuphathwa kwedatha: I-LangChain inikeza i-API yokuphatha idatha evumela onjiniyela ukuthi baphathe futhi basebenzise idatha.

Sebenzisa Amacala Kunjiniyela Wesoftware

I-LangChain ingasetshenziswa ezimweni ezahlukahlukene zokusebenzisa ubunjiniyela besoftware, kufaka phakathi:

• Ama-Chatbots: I-LangChain ingasetshenziselwa ukwakha ama-chatbots angaqonda, enze, futhi axhumane nolimi lwabantu.
• Abasizi abangokoqobo: I-LangChain ingasetshenziswa ukwakha abasizi ababonakalayo abangenza imisebenzi, baphendule imibuzo, futhi banikeze ulwazi.
• Ukukhiqizwa kokuqukethwe: I-LangChain ingasetshenziselwa ukukhiqiza okuqukethwe, okufana nezihloko, okuthunyelwe kwebhulogi, nokuthunyelwe kwezokuxhumana.

Imiyalo/Amazwibela Aphezulu Okuyi-5-10

Nansi imiyalo/ amazwibela aphezulu angu-5-10 e-LangChain:

1. Ingenisa i-LangChain: ngenisa i-langchain
2. Ukwakha i-LLM: llm = langchain.LLM("my_llm")
3. Ukuqeqesha i-LLM: llm.train(idatha)
4. Ukuhlanganisa namanye amamodeli e-AI: ai_model = langchain.AIModel("my_ai_model")
5. Imisebenzi yokuhlela: umsebenzi = langchain.Task("umsebenzi_wami")
6. Ukuphatha ukugeleza komsebenzi: ukugeleza komsebenzi = i-langchain.Ukugeleza komsebenzi("ukugeleza_kwami")
7. Ukuphatha idatha: idatha = langchain.Idatha("idatha_yami")
8. Ukudala i-chatbot: chatbot = langchain.Chatbot("my_chatbot")
9. Ukudala umsizi we-virtual: umsizi_we-virtual = langchain.VirtualAssistant("my_virtual_assistant")
10. Ukukhiqiza okuqukethwe: okuqukethwe = langchain.ContentGenerator("my_content_generator")

Ukubona

Nakhu ukubonwa kwesakhiwo se-LangChain kusetshenziswa i-Chart.js:

{
  "type": "bar",
  "idatha": {
    "labels": ["LLM", "Orchestration", "Integration", "Task Management", "Workflow Management", "Data Management"],
    "idathasethi": [
      {
        "label": "LangChain Architecture",
        "idatha": [10, 8, 6, 4, 2, 1],
        "backgroundColor": ["#4CAF50", "#FF9800", "#2196F3", "#8BC34A", "#03A9F4", "#FFC107"]
      }
    ]
  },
  "izinketho": {
    "isihloko": {
      "Display": iqiniso,
      "text": "LangChain Architecture"
    },
    "i-legend": {
      "isibonisi": iqiniso
    }
  }
}

Lokhu kuboniswa kubonisa izingxenye ezihlukene zezakhiwo ze-LangChain, okuhlanganisa ama-LLM, i-orchestration, ukuhlanganiswa, ukuphathwa komsebenzi, ukuphathwa kokuhamba komsebenzi, nokuphathwa kwedatha.

Isiphetho

I-LangChain iwumtapo wezincwadi onamandla ohlinzeka ngohlaka oluguquguqukayo nolukakala lokwakha ama-agent ahlakaniphile asebenzisa ama-LLM. Ngokulandela amasu okusebenzisa angokoqobo nezindlela zokucula ezichazwe kulesi sihloko, onjiniyela bangakha ama-agent ahlakaniphile akwazi ukuqonda, enze, futhi ahlanganyele nolimi lwabantu. Izimo zokusetshenziswa kubunjiniyela besofthiwe zibonisa amandla e-LangChain ezinhlelweni ezihlukahlukene, kusukela kuma-chatbots nabasizi ababonakalayo kuye ekukhiqizeni okuqukethwe nokunye. Nge-LangChain, abathuthukisi bangakha ama-agent ahlakaniphile angenza imisebenzi eyinkimbinkimbi futhi anikeze inani kubasebenzisi.

Ikhodi Block

Nali ibhulokhi yekhodi elula ekhombisa indlela yokudala i-chatbot usebenzisa i-LangChain:

ngenisa i-langchain


llm = langchain.LLM("my_llm")

# Dala i-chatbot
chatbot = langchain.Chatbot(llm)

# Chaza umsebenzi
umsebenzi = langchain.Task("my_task")

# Yenza umsebenzi
umphumela = chatbot.execute(umsebenzi)

# Phrinta umphumela
phrinta(umphumela)

Leli bhulokhi lekhodi lidala i-LLM, i-chatbot, nomsebenzi, bese lenza umsebenzi lisebenzisa i-chatbot. Umphumela uphrintelwe kukhonsoli.

Rust and Go Code

I-LangChain iphinde ihlinzeke nge-Rust and Go izibopho, ezingasetshenziswa ukwakha ama-agent ahlakaniphile kulezi zilimi. Nasi isibonelo sekhodi elula ye-Rust block ekhombisa indlela yokudala i-chatbot usebenzisa i-LangChain:

sebenzisa i-langchain::{LLM, Chatbot};

i-fn main() {
    // Dala i-LLM
    let llm = LLM::new("my_llm");

    // Dala i-chatbot
    let chatbot = Chatbot::new(llm);

    // Chaza umsebenzi
    let task = Task::new("my_task");

    // Yenza umsebenzi
    vumela umphumela = chatbot.execute(umsebenzi);

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

Futhi nasi isibonelo sebhulokhi yekhodi ye-Go elula ekhombisa indlela yokudala i-chatbot usebenzisa i-LangChain:

iphakethe main

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

func main() {
	// Dala i-LLM
	llm := langchain.NewLLM("my_llm")

	// Dala i-chatbot
	chatbot := langchain.NewChatbot(llm)

	// Chaza umsebenzi
	umsebenzi := langchain.NewTask("my_task")

	// Yenza umsebenzi
	umphumela := chatbot.Yenza(umsebenzi)

	// Phrinta umphumela
	fmt.Println(umphumela)
}

Lawa mabhulokhi ekhodi akhombisa indlela yokudala i-chatbot usebenzisa i-LangChain ku-Rust and Go.