Gudanar da Wakilan AI tare da LangChain da DSPy don Ƙirƙirar Ƙirƙirar Software | B4N1

Gudanar da Wakilan AI tare da LangChain da DSPy don Ƙirƙirar Ƙirƙirar Software

3 months ago · b4n1 Read time: 5 min

Gabatarwa

Ƙirƙirar tsarin software ya haifar da haɓakar gine-ginen AI wanda zai iya sarrafawa da kuma tsara ma'aikatan AI da yawa. LangChain da DSPy su ne ginshiƙai biyu masu ƙarfi waɗanda ke ba da damar ƙirƙirar ƙirar ƙirar software mai ƙarfi da juriya ta hanyar samar da dandamali mai ƙarfi don ƙungiyar ƙungiyar AI. A cikin wannan labarin, za mu bincika aiwatar da tsarin gine-ginen software na AI ta amfani da LangChain da DSPy, tare da mayar da hankali kan haɓakawa, haɓakawa, da haɗin kai tare da kayan aikin DevOps kamar Mai yiwuwa da AWS Kiro.

Menene LangChain da DSPy?

LangChain tsari ne na Python wanda ke ba da damar ƙirƙirar wakilai AI na tattaunawa ta amfani da dabarun sarrafa harshe na halitta (NLP) da dabarun koyon injin (ML). Yana ba da API mai sauƙi da fahimta don ginawa da haɗawa da wakilan AI tare da aikace-aikace da ayyuka daban-daban.

DSPy, a gefe guda, shine tsarin tushen tsatsa wanda ke ba da babban aiki da dandamali mai ƙima don ƙungiyar ƙungiyar AI. Yana ba da damar ƙirƙirar tsarin AI mai rikitarwa ta hanyar samar da ingantaccen gini mai sassauƙa don haɗa wakilai AI da yawa.

Fa'idodin Amfani da LangChain da DSPy

Amfani da LangChain da DSPy a cikin gine-ginen software na AI suna ba da fa'idodi da yawa, gami da:

  • ** Scalability ***: LangChain da DSPy suna ba da damar ƙirƙirar tsarin AI mai ƙima ta hanyar samar da ingantaccen dandamali don ƙungiyar ƙungiyar AI.
  • ** Resilience ***: Yin amfani da LangChain da DSPy yana tabbatar da cewa tsarin AI sun fi dacewa da kasawa da kurakurai, kamar yadda za'a iya sake daidaita su da sauƙi.
  • ** Haɗin kai ***: LangChain da DSPy suna ba da haɗin kai tare da kayan aikin DevOps daban-daban, ciki har da Mai yiwuwa da AWS Kiro, yana sauƙaƙa sarrafawa da ƙaddamar da tsarin AI.

Aiwatar da AI-Driven Software Architecture tare da LangChain da DSPy

Don aiwatar da gine-ginen software na AI ta amfani da LangChain da DSPy, muna buƙatar bin waɗannan matakan:

  1. ** Sanya LangChain da DSPy ***: Shigar da tsarin LangChain da DSPy ta amfani da pip da kaya, bi da bi.
  2. ** Ƙirƙirar AI Agents ***: Ƙirƙiri wakilai na AI ta amfani da LangChain da DSPy, da kuma haɗa su tare da aikace-aikace da ayyuka daban-daban.
  3. ** Orchestrate AI Agents ***: Yi amfani da DSPy don tsara wakilan AI da ƙirƙirar tsarin AI mai rikitarwa.
  4. ** Haɗa tare da kayan aikin DevOps ***: Haɗa LangChain da DSPy tare da kayan aikin DevOps kamar Mai yiwuwa da AWS Kiro don sarrafawa da ƙaddamar da tsarin AI.

Lambar Misali: Ƙirƙirar Wakilin AI tare da LangChain

`` Python shigo da langchain

Ƙirƙiri samfurin harshe

model = langchain.LMModel("harshen_model")

Ƙirƙiri wakilin AI na tattaunawa

wakili = langchain.ConversationalAgent (samfurin)

Ƙayyade aiki don sarrafa shigarwar mai amfani

def handle_input(input_text): # Yi amfani da wakilin AI don amsa shigar da mai amfani amsa = wakili. amsa (input_text) mayar da martani

Gwada wakilin AI

input_text = "Sannu, ya kuke?" amsa = handed_input(input_text) buga(amsa)


### Lambobin Misali: Ƙaddamar da Wakilan AI tare da DSPy

``tsatsa
amfani da dspy:: {Agent, Orchestration};

// Ƙirƙiri wakilai AI
bari wakili1 = Wakili :: sabon ("wakili1");
bari wakili2 = Wakili :: sabon ("wakili2");

// Ƙirƙiri misalin ƙungiyar makaɗa
bari ƙungiyar makaɗa = Orchestration :: sabo();

// Ƙara wakilan AI zuwa ƙungiyar makaɗa
orchestration.add_agent (wakili1);
orchestration.add_agent (wakili2);

// Ƙayyade aiki don sarrafa shigarwar mai amfani
fn handle_input (input_text: String) -> igiya {
    // Yi amfani da misalin ƙungiyar makaɗa don amsa shigar da mai amfani
    bari amsa = orchestration.respond(input_text);
    amsa
}

// Gwada ƙungiyar makaɗa
bari input_text = "Sannu, ya kuke?".to_string();
bari amsa = handle_input(input_text);
println!("{}", amsa);

Manyan Dokoki 5-10 da Akafi Amfani da su/Snippets

Anan akwai manyan umarni 5-10 da aka fi amfani da su/snippets don LangChain da DSPy:

  1. langchain.LMModel("samfurin_harshe"): Yana ƙirƙira misalin samfurin harshe.
  2. ** langchain.ConversationalAgent (samfurin)**: Yana ƙirƙira misalin wakilin AI na tattaunawa.
  3. ** dspy:: Wakili:: sabon("wakili1")**: Yana ƙirƙira misalin wakilin AI.
  4. dspy::Orchestration::sabon(): Samar da misalin kungiyar kade-kade.
  5. ** orchestration.add_agent (wakili1)**: Yana ƙara wakilin AI zuwa ƙungiyar makaɗa.
  6. ** Orchestration.respond(input_text)**: Yana amsa shigar da mai amfani ta amfani da ƙungiyar makaɗa.
  7. langchain.model.respond(input_text): Yana amsa shigar da mai amfani ta amfani da ƙirar harshe.
  8. ** dspy :: Wakili :: amsa(input_text)**: Amsa shigar da mai amfani ta amfani da wakilin AI.
  9. langchain.ConversationalAgent.handle_input(input_text): Yana sarrafa shigarwar mai amfani ta amfani da wakilin AI na tattaunawa.
  10. dspy::Orchestration.handle_input(input_text): Yana sarrafa shigarwar mai amfani ta amfani da ƙungiyar makaɗa.

Kallon gani

Anan ga hangen nesa na LangChain da gine-ginen DSPy ta amfani da Chart.js: Json { "type": "bar", "data": { "labels": ["LangChain", "DSPy"], "datasets": [ { "label": "Scalability", "bayanai": [8, 9], "backgroundColor": ["rgba (255, 99, 132, 0.2)", "rgba (54, 162, 235, 0.2)"], "BorderColor": ["rgba (255, 99, 132, 1)", "rgba (54, 162, 235, 1)"], "BorderWidth": 1 }, { "label": "Resilience", "bayanai": [9, 8], "backgroundColor": ["rgba (255, 99, 132, 0.2)", "rgba (54, 162, 235, 0.2)"], "BorderColor": ["rgba (255, 99, 132, 1)", "rgba (54, 162, 235, 1)"], "BorderWidth": 1 }, { "label": "Haɗin kai", "bayanai": [8, 9], "backgroundColor": ["rgba (255, 99, 132, 0.2)", "rgba (54, 162, 235, 0.2)"], "BorderColor": ["rgba (255, 99, 132, 1)", "rgba (54, 162, 235, 1)"], "BorderWidth": 1 } ] }, "zaɓi": { "ma'auni": { "yAxes": [ { "zama": { "beginAtZero": gaskiya } } ] } } }

Wannan hangen nesa yana nuna haɓaka, juriya, da damar haɗin kai na LangChain da DSPy.

## Kammalawa

A ƙarshe, LangChain da DSPy su ne ginshiƙai masu ƙarfi waɗanda ke ba da damar ƙirƙirar ƙirar ƙira da juriya na kayan aikin software ta hanyar samar da dandamali mai ƙarfi don ƙungiyar ƙungiyar AI. Ta amfani da LangChain da DSPy, masu haɓakawa na iya ƙirƙirar tsarin AI mai rikitarwa waɗanda suke da inganci, daidaitawa, da juriya. Amfani da LangChain da DSPy kuma yana ba da damar haɗin kai tare da kayan aikin DevOps daban-daban, yana sauƙaƙa sarrafawa da ƙaddamar da tsarin AI.

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