Ukuhlela i-AI-Powered Software Development nge-LangChain ne-DSPy | B4N1

Ukuhlela i-AI-Powered Software Development nge-LangChain ne-DSPy

6 months ago · b4n1 Tiempo de lectura: 4 min

Ukuhlela i-AI-Powered Software Development nge-LangChain ne-DSPy

Isingeniso

Ukwakheka kwesoftware kuthuthuka ngokushesha, ngamathuluzi nobuchwepheshe obunamandla e-AI budlala indima egqamayo ku-automation ye-DevOps kanye nesoftware yokwakha. Abadlali ababili abaphawulekayo kulesi sikhala i-LangChain ne-DSPy, enikeza amakhono anamandla okucula okwakha amapayipi okuthuthukisa isofthiwe aqhutshwa yi-AI. Kulesi sihloko, sizongena emhlabeni we-LangChain ne-DSPy, sihlole amakhono abo, izinzuzo, kanye nezinhlelo zokusebenza ezingokoqobo ekuthuthukisweni kwesofthiwe enikwe amandla yi-AI.

Iyini i-LangChain?

I-LangChain iwumthombo ovulekile, uhlaka olusekelwe kuPython lokwakha izinhlelo zokusebenza ze-AI zengxoxo. Ihlinzeka ngesethi eqinile yamathuluzi okucubungula ulimi lwemvelo (i-NLP), ukufunda ngomshini (ML), nokuthuthukiswa kwesofthiwe, okuyenza ibe inketho efanelekile yamapayipi okuthuthukisa isofthiwe anikwe amandla yi-AI. Izici eziyinhloko ze-LangChain zifaka:

  • I-AI Yengxoxo: I-LangChain inika amandla onjiniyela ukuthi bakhe izixhumanisi zengxoxo, njengama-chatbots nabasizi bezwi, besebenzisa amasu e-NLP ne-ML.
  • Ukuthuthukiswa Kwesofthiwe: I-LangChain ihlinzeka ngohlu lwamathuluzi okuthuthukiswa kwesofthiwe, okuhlanganisa ukukhiqizwa kwekhodi, ukulungisa iphutha, nokuhlola.
  • I-Orchestration: Amakhono omculo we-LangChain avumela abathuthukisi ukuthi bazenzele ngokuzenzakalelayo ukuhamba komsebenzi okuyinkimbinkimbi namapayipi, okwenza kube lula ukuphatha amaphrojekthi amakhulu okuthuthukiswa kwesofthiwe.

Iyini i-DSPy?

I-DSPy iwuhlaka olusekelwe kuPython lokwakha isayensi yedatha namapayipi okufunda ngomshini. Ihlinzeka ngebanga lamathuluzi okucubungula ngaphambili kwedatha, ubunjiniyela besici, ukuqeqeshwa kwamamodeli, kanye nokusetshenziswa. Izici eziyinhloko ze-DSPy zihlanganisa:

  • Isayensi Yedatha: I-DSPy inika amandla onjiniyela ukuthi bakhe amaphayiphi esayensi yedatha, okuhlanganisa ukungeniswa kwedatha, ukucutshungulwa, nokuhlaziya.
  • Ukufunda Ngomshini: I-DSPy ihlinzeka ngebanga lamathuluzi okufunda ngomshini, okuhlanganisa ukuqeqeshwa okuyimodeli, ukushuna, kanye nokusetshenziswa.
  • I-Orchestration: Amakhono omculo we-DSPy avumela onjiniyela ukuthi bazenzele ngokuzenzakalelayo ukugeleza komsebenzi okuyinkimbinkimbi namapayipi, okwenza kube lula ukuphatha isayensi yedatha enkulu kanye namaphrojekthi okufunda komshini.

Ukuhlela i-AI-Powered Software Development nge-LangChain ne-DSPy

Ukukhombisa amandla e-LangChain ne-DSPy ekuthuthukisweni kwesoftware enikwe amandla yi-AI, ake sicabangele isibonelo esilula. Ake sithi sifuna ukwakha ipayipi lokuthuthukisa isofthiwe elinamandla e-AI elisebenzisa ngokuzenzakalelayo le misebenzi elandelayo:

  1. Ukwenziwa Kwekhodi: Khiqiza umbhalo wePython oyisisekelo wohlelo lokusebenza lwewebhu usebenzisa isifanekiso.
  2. Ukubuyekezwa Kwekhodi: Buyekeza ikhodi ekhiqiziwe ukuze uthole amaphutha futhi uphakamise ukuthuthukiswa.
  3. Ukuhlola: Yenza izivivinyo ezizenzakalelayo kukhodi ekhiqiziwe ukuze uqinisekise ukuthi ihlangabezana nezindinganiso ezidingekayo.
  4. Ukusetshenziswa: Sebenzisa ikhodi ekhiqiziwe endaweni yesikhulumi esisekelwe emafini.

Nali ibhulokhi yekhodi elula ekhombisa ukuthi isetshenziswa kanjani i-LangChain ne-DSPy ukwenza leli payipi libe ngokuzenzakalelayo:

ngenisa i-langchain
kusuka ku-langchain.chains ngenisa ConversationalAI
kusuka ku-langchain.llms ngenisa i-LLM


iphayiphi = ConversationalAI(
    llm=LLM("text-davinci-003"),
    iketango=[
        langchain.PipelineStep(
            igama="Isizukulwane Sekhodi",
            func=lambda x: f"import flask\napp = flask.Flask(__name__)\n@app.route('/')\ndef index():\n return 'Hello World!'",
        ),
        langchain.PipelineStep(
            igama="Ukubuyekezwa Kwekhodi",
            func=lambda x: "Ikhodi ekhiqiziwe ibukeka iyinhle, kodwa cabanga ukwengeza ukuphatha amaphutha.",
        ),
        langchain.PipelineStep(
            name="Ukuhlola",
            func=lambda x: "Isebenzisa izivivinyo...\nPASS: index()",
        ),
        langchain.PipelineStep(
            igama="Ukuthunyelwa",
            func=lambda x: "Ithumela kuplathifomu yamafu...\nImpumelelo!",
        ),
    ],
)

# Qalisa ipayipi
umphumela = pipeline.run(input="Yenza umbhalo oyisisekelo wePython wohlelo lokusebenza lwewebhu.")

phrinta(umphumela)

Lokhu kuvinjwa kwekhodi kukhombisa indlela yokusebenzisa i-LangChain ne-DSPy ukwenza ngokuzenzakalelayo ipayipi lokuthuthukisa isofthiwe elinamandla e-AI. Ipayipi linezinyathelo ezine: ukukhiqizwa kwekhodi, ukubuyekezwa kwekhodi, ukuhlola, nokusatshalaliswa. Isinyathelo ngasinye sisetshenziswa kusetshenziswa isinyathelo sepayipi le-LangChain, esichaza umsebenzi othile okufanele wenziwe.

Izinzuzo ze-LangChain ne-DSPy

Izinzuzo zokusebenzisa i-LangChain ne-DSPy ekuthuthukisweni kwesoftware enikwe amandla yi-AI ziningi:

  • I-Automation: I-LangChain ne-DSPy yenza abathuthukisi bakwazi ukwenza ngokuzenzakalelayo ukuhamba komsebenzi okuyinkimbinkimbi namapayipi, okwenza kube lula ukuphatha amaphrojekthi amakhulu okuthuthukiswa kwesofthiwe.
  • Ukusebenza kahle: Ngokuzenza ngokuzenzakalelayo imisebenzi ephindaphindwayo, onjiniyela bangagxila emisebenzini yezinga eliphezulu edinga ubuhlakani namakhono okuxazulula izinkinga.
  • Ukungaguquguquki: I-LangChain ne-DSPy iqinisekisa ukungaguquguquki ezinqubweni zokuthuthukiswa kwesofthiwe, inciphisa ingozi yamaphutha nokuthuthukisa ikhwalithi iyonke.
  • Scalability: I-LangChain ne-DSPy yenza abathuthukisi bakwazi ukukala amapayipi okuthuthukisa isofthiwe ukuze bahlangabezane nezidingo zamaphrojekthi amakhulu.

Imiyalo/Amazwibela Aphezulu Okuyi-5-10

Nansi imiyalo/ amazwibela asetshenziswa kakhulu angu-5-10 e-LangChain ne-DSPy:

  1. langchain.PipelineIsinyathelo: Ichaza umsebenzi othize okufanele wenziwe ngokuqhubekayo.
pipeline_step = langchain.PipelineStep(
    igama="Isizukulwane Sekhodi",
    func=lambda x: f"import flask\napp = flask.Flask(__name__)\n@app.route('/')\ndef index():\n return 'Hello World!'",
)
  1. langchain.ConversationalAI: Ichaza ipayipi le-AI lengxoxo.
iphayiphi = langchain.ConversationalAI(
    llm=LLM("text-davinci-003"),
    iketango=[pipeline_step],
)
  1. DSPy.DataPipeline: Ichaza ipayipi lesayensi yedatha.
iphayiphi = DSPy.DataPipeline(
    idatha_source="https://example.com/data.csv",
    idatha_transformer=lambda x: x["ikholomu1"] + x["ikholomu2"],
)
  1. DSPy.ModelPipeline: Ichaza ipayipi lokufunda umshini.
iphayiphi = DSPy.ModelPipeline(
    imodeli="ukwehla_komugqa",
    idatha_source="https://example.com/data.csv",
    idatha_transformer=lambda x: x["ikholomu1"] + x["ikholomu2"],
)
  1. langchain.LLM: Ichaza imodeli yolimi.
llm = langchain.LLM("text-davinci-003")
  1. DSPy.DataTransformer: Ichaza isiguquli sedatha.
isiguquli = DSPy.DataTransformer(lambda x: x["column1"] + x["column2"])
  1. DSPy.ModelTrainer: Ichaza umqeqeshi oyimodeli.
umqeqeshi = DSPy.ModelTrainer(imodeli="linear_regression")
  1. langchain.Pipeline: Ichaza ipayipi.
iphayiphi = langchain.Pipeline(
    iketango=[pipeline_step],
)
  1. DSPy.DataLoader: Ichaza isilayishi sedatha.
isilayishi = DSPy.DataLoader(data_source="https://example.com/data.csv")
  1. DSPy.ModelDeployer: Ichaza imodeli ephakelayo.
umqambi = DSPy.ModelDeployer(imodeli="linear_regression")

Ukubona

Nakhu okubonwayo kwepayipi le-LangChain ne-DSPy kusetshenziswa i-Chart.js:

{
  "type": "bar",
  "idatha": {
    "labels": ["Ukwenziwa Kwekhodi", "Ukubuyekezwa Kwekhodi", "Ukuhlola", "Ukuthunyelwa"],
    "idathasethi": [
      {
        "label": "LangChain",
        "idatha": [10, 8, 12, 15],
        "backgroundColor": "rgba(255, 99, 132, 0.2)",
        "borderColor": "rgba(255, 99, 132, 1)",
        "BorderWidth": 1
      },
      {
        "label": "DSPy",
        "idatha": [8, 10, 12, 15],
        "backgroundColor": "rgba(54, 162, 235, 0.2)",
        "borderColor": "rgba(54, 162, 235, 1)",
        "BorderWidth": 1
      }
    ]
  },
  "izinketho": {
    "isihloko": {
      "Display": iqiniso,
      "text": "LangChain ne-DSPy Pipeline"
    },
    "izikali": {
      "yAxes": [
        {
          "imikhaza": {
            "beginAtZero": kuyiqiniso
          }
        }
      ]
    }
  }
}

Lokhu kubukwa kukhombisa inani lemisebenzi eyenziwa yi-LangChain kanye ne-DSPy emgqeni. I-eksisi ka-x imele imisebenzi, kanti i-eksisi ka-y imele inani lemisebenzi eyenziwe.

Isiphetho

I-LangChain ne-DSPy zinikeza amandla okucula anamandla okwakha amapayipi okuthuthukisa isofthiwe aqhutshwa yi-AI. Ngokwenza ngokuzenzakalela ukuhamba komsebenzi okuyinkimbinkimbi namapayipi, abathuthukisi bangagxila emisebenzini yezinga eliphezulu edinga ubuhlakani namakhono okuxazulula izinkinga. Izinzuzo zokusebenzisa i-LangChain ne-DSPy zifaka i-automation, ukusebenza kahle, ukungaguquguquki, nokuqina. Nge-LangChain ne-DSPy, abathuthukisi bangakha amapayipi okuthuthukisa isofthiwe anamandla e-AI ahlangabezana nezidingo zamaphrojekthi amakhulu.

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