Abaabulka Horumarinta Software-ka Awoodda leh ee LangChain iyo DSPy | B4N1

Abaabulka Horumarinta Software-ka Awoodda leh ee LangChain iyo DSPy

6 months ago · b4n1 Tiempo de lectura: 6 min

** Abaabulka Horumarinta Software-ka Awoodda leh ee LangChain iyo DSPy ***

hordhac

Muuqaalka horumarinta software ayaa si degdeg ah u kobcaya, iyadoo qalabyada AI ku shaqeeya iyo teknoolajiyada ay ka ciyaarayaan door caan ah oo sii kordheysa ee DevOps automation iyo qaab dhismeedka software. Laba ciyaaryahan oo caan ah oo booskan ku jira waa LangChain iyo DSPy, kuwaas oo bixiya awoodo abaabul oo awood leh oo lagu dhisayo tuubooyinka horumarinta software-ka ee AI ay wado. Maqaalkan, waxaan u dhexgeli doonaa aduunka LangChain iyo DSPy, sahaminta awoodooda, faa'iidooyinka, iyo codsiyada la taaban karo ee horumarinta software-ka ee AI ku shaqeeya.

Waa maxay LangChain?

LangChain waa il-furan, qaab-dhismeedka Python-ku-saleysan ee lagu dhisayo codsiyada AI wada-hadalka. Waxay bixisaa qalab adag oo loogu talagalay habaynta luqadda dabiiciga ah (NLP), barashada mashiinka (ML), iyo horumarinta software, taasoo ka dhigaysa doorasho ku habboon tuubooyinka horumarinta software-ka ee AI ku shaqeeya. Astaamaha xudunta u ah LangChain waxaa ka mid ah:

  • ** Wadahadal AI ***: LangChain wuxuu u sahlayaa horumariyeyaasha inay dhisaan is dhex galka wada hadalka, sida chatbots iyo kaaliyeyaasha codka, iyagoo isticmaalaya farsamooyinka NLP iyo ML. ** Horumarinta Software ***: LangChain wuxuu bixiyaa qalabyo kala duwan oo loogu talagalay horumarinta software, oo ay ku jiraan soo saarista koodka, khaladka, iyo tijaabinta.
  • ** Orchestration ***: Awoodaha abaabulka ee LangChain waxay u ogolaataa horumariyeyaasha inay otomaatig u sameeyaan qulqulka shaqada ee adag iyo dhuumaha, taasoo sahlaysa in la maareeyo mashaariicda horumarinta software ee baaxadda leh.

waa maxay DSPy?

DSPy waa qaab-dhismeedka Python-ku-saleysan ee lagu dhisayo sayniska xogta iyo dhuumaha barashada mashiinka. Waxay bixisaa qalabyo kala duwan oo loogu talagalay diyaarinta xogta, injineernimada muuqaalka, tababarka moodeelka, iyo geynta. Astaamaha asaasiga ah ee DSPy waxaa ka mid ah:

** Sayniska Xogta ***: DSPy waxay u saamaxdaa horumariyayaasha inay dhisaan dhuumaha sayniska xogta, oo ay ku jiraan xogta xogta, habaynta, iyo falanqaynta. ** Barashada Mashiinka ***: DSPy waxay bixisaa qalab kala duwan oo loogu talagalay barashada mashiinka, oo ay ku jiraan tababarka moodeelka, hagaajinta, iyo geynta. ** Orchestration ***: Awoodaha abaabulka ee DSPy waxay u ogolaataa horumariyayaasha inay otomaatig u sameeyaan qulqulka shaqada ee adag iyo dhuumaha, taasoo sahlaysa in la maareeyo sayniska xogta baaxada leh iyo mashaariicda mashiinka barashada.

** Abaabulka Horumarinta Software-ka Awoodda leh ee LangChain iyo DSPy ***

Si loo muujiyo awoodda LangChain iyo DSPy ee horumarinta software-ka ku shaqeeya AI, aan tixgelinno tusaale fudud. Ka soo qaad in aan rabno in aan dhisno dhuumaha horumarinta software-ku-wada-hadalka AI ku shaqeeya oo otomaatig u ah hawlaha soo socda:

  1. Code Generation: U samee qoraal Python aasaasiga ah ee codsiga shabakada adoo isticmaalaya template.
  2. ** Dib u eegis koodhka ***: Dib u eeg koodka la sameeyay ee khaladaadka oo soo jeedi hagaajin.
  3. **Tijaabi ***: Ku samee tijaabooyin otomaatig ah koodka la sameeyay si aad u hubiso inuu buuxiyo heerarka loo baahan yahay.
  4. ** Hawlgelinta ***: Geli koodka la sameeyay meel daruur ku salaysan.

Waa kuwan furaha furaha fudud ee muujinaya sida loo isticmaalo LangChain iyo DSPy si loo toosiyo dhuumahaan: `` Python soo dejinta langchain ka langchain.chains soo dejinta ConversationalAI ka langchain.llms soo daji LLM

dhuunta = ConversationalAI ( llm=LLM("qoraalka-davinci-003"), silsilad=[ langchain.Tallaabada dhuumaha( magac = "Code Generation", func=lambda x: f"import flask\napp = flask.Flask(name)\n@app.route('/')\def index():\n soo celi 'Hello World!'", ), langchain.Tallaabada dhuumaha( name="Dib u eegis koodhka", func=lambda x: "Koodhka la soo saaray wuxuu u muuqdaa mid wanaagsan, laakiin tixgeli inaad ku darto maaraynta khaladka.", ), langchain.Tallaabada dhuumaha( name="Tijaabi", func=lambda x: "Tijaabooyin socda...\nPASS: index()", ), langchain.Tallaabada dhuumaha( name="Guurin", func=lambda x: "Dad geyneysa goobta daruuraha...\nGuusha!", ), ], )

Daadi dhuumaha

natiijada = pipeline.run

daabac(natiijo) `` Koodhkan koodka ah wuxuu muujinayaa sida loo isticmaalo LangChain iyo DSPy si otomaatig loogu sameeyo dhuumaha horumarinta software ee AI ku shaqeeya wada hadalka. Dhuunta waxay ka kooban tahay afar tillaabo: soo saarista code, dib u eegista code, tijaabinta, iyo geynta. Tallaabo kasta waxaa lagu fuliyaa iyadoo la adeegsanayo tallaabada dhuumaha LangChain, taas oo qeexaysa hawl gaar ah oo la qabanayo.

** Faa'iidooyinka LangChain iyo DSPy ***

Faa'iidooyinka isticmaalka LangChain iyo DSPy ee horumarinta software-ka ku shaqeeya AI waa badan yihiin:

** Automation ***: LangChain iyo DSPy waxay awood u siinayaan horumariyeyaasha inay otomaatig u sameeyaan qulqulka shaqada ee adag iyo dhuumaha, taasoo fududaynaysa maareynta mashaariicda horumarinta software ee baaxadda leh.

  • ** Hufnaanta ***: Iyaga oo otomaatig u ah hawlaha soo noqnoqda, horumariyayaashu waxay diiradda saari karaan hawlaha heerka sare ah ee u baahan hal-abuurnimo iyo xirfado xalinta mashaakilaadka.
  • ** Joogteynta ***: LangChain iyo DSPy waxay xaqiijiyaan joogtaynta hababka horumarinta software, yaraynta khatarta khaladaadka iyo hagaajinta tayada guud.
  • ** Scalability ***: LangChain iyo DSPy waxay awood u siiyaan horumariyayaasha inay cabbiraan tubooyinka horumarinta software si ay u daboolaan baahiyaha mashaariicda waaweyn.

** 5-10ka ugu sarreeya amarada/Qodobka ugu Isticmaalka badan**

Waa kuwan 5-10-ka amarrada ugu badan ee la isticmaalo ee LangChain iyo DSPy:

  1. langchain.PipelineTallaabo: Wuxuu qeexayaa hawl gaar ah oo lagu qabanayo dhuumaha. Python pipeline_step = langchain.Pipeline Step ( magac = "Code Generation", func=lambda x: f"import flask\napp = flask.Flask(__name__)\n@app.route('/')\def index():\n soo celi 'Hello World!'", )
  2. langchain.ConversationalAI: Wuxuu qeexayaa dhuumaha AI wada hadalka. Python dhuumaha = langchain.ConversationalAI ( llm=LLM("qoraalka-davinci-003"), silsilad = [tubo-tallaabo], )
  3. ** DSPy.DataPipeline**: Wuxuu qeexayaa dhuumaha sayniska xogta. Python dhuumaha = DSPy.DataPipeline ( xogta_source = "https://example.com/data.csv", data_transformer=lambda x: x["column1"] + x["column2"], )
  4. **DSPy.ModelPipeline ***: Qeexee dhuumaha barashada mashiinka. Python dhuumaha = DSPy.ModelPipeline ( model="linear_regression", xogta_source = "https://example.com/data.csv", data_transformer=lambda x: x["column1"] + x["column2"], )
  5. langchain.LLM: Wuxuu qeexayaa qaabka luqadda. Python llm = langchain.LLM("qoraalka-davinci-003")
  6. ** DSPy.DataTransformer**: Wuxuu qeexayaa xog beddelka xogta. Python transformer = DSPy.DataTransformer(lambda x: x["column1"] + x["column2")
  7. ** DSPy.ModelTrainer**: Wuxuu qeexayaa tababaraha moodeelka. Python Tababaraha = DSPy.ModelTrainer (model = "linear_regression")
  8. **langchain.Pipeline: Qeexee dhuumaha. Python dhuumaha = langchain. silsilad = [tubo-tallaabo], )
  9. ** DSPy.DataLoader ***: Qeexaya xog-qaade Python xamuulka = DSPy.DataLoader(xogta_source = "https://example.com/data.csv")
  10. ** DSPy.ModelDeployer**: Wuxuu qeexayaa soo-dejiyaha moodeelka. Python diraye = DSPy.ModelDeployer (model = "linear_regression") Muuqaalka

Halkan waxaa ah muuqaalka LangChain iyo dhuumaha DSPy iyadoo la adeegsanayo Chart.js: json { "type": "bar", "xogta": { "labels": ["Koodhka Jiilka", "Dib u eegis koodhka", "Tijaabinta", "Diritaan"], "datasets": [ { "label": "LangChain", "xogta": [10, 8, 12, 15], "backgroundColor": "rgba(255, 99, 132, 0.2)", "BorderColor": "rgba(255, 99, 132, 1)", "BorderWidth": 1 }, { "label": "DSPy", "xogta": [8, 10, 12, 15], "backgroundColor": "rgba(54, 162, 235, 0.2)", "BorderColor": "rgba(54, 162, 235, 1)", "BorderWidth": 1 } ] }, "ikhtiyaar": { "ciwaan": { "muujin": run, "text": "LangChain iyo DSPy Pipeline" }, "Miisaanka": { "yAxes": [ { "ticks": { "beginAtZero": run } } ] } } } Aragtidani waxay muujinaysaa tirada hawlaha ay sameeyeen LangChain iyo DSPy ee dhuumaha. dhidibka x waxa uu u taagan yahay hawlaha, dhidibka y-na waxa uu u taagan yahay tirada hawlaha la qabtay.

** Gabagabo**

LangChain iyo DSPy waxay bixiyaan awoodo abaabul oo xoog leh si loo dhiso tuubooyinka horumarinta software-ka ee AI ay wado. Iyaga oo otomaatig u ah socodka shaqada adag iyo dhuumaha, horumariyayaashu waxay diiradda saari karaan hawlaha heerka sare ah ee u baahan hal-abuurnimo iyo xirfado xalinta mashaakilaadka. Faa'iidooyinka isticmaalka LangChain iyo DSPy waxaa ka mid ah automation, hufnaan, joogtayn, iyo miisaan. Iyadoo LangChain iyo DSPy, horumariyayaashu waxay dhisi karaan wadahadalka AI ku shaqeeya tubooyinka horumarinta software kaas oo buuxiya shuruudaha mashaariicda waaweyn.

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