{"id":8999,"date":"2025-01-08T17:30:14","date_gmt":"2025-01-08T14:30:14","guid":{"rendered":"https:\/\/fatihsoysal.com\/blog\/langgraph-copilotkit-ve-tavily-ile-perplexity-kopyasi-detayli-bir-rehber\/"},"modified":"2025-01-08T17:30:14","modified_gmt":"2025-01-08T14:30:14","slug":"langgraph-copilotkit-ve-tavily-ile-perplexity-kopyasi-detayli-bir-rehber","status":"publish","type":"post","link":"https:\/\/fatihsoysal.com\/blog\/langgraph-copilotkit-ve-tavily-ile-perplexity-kopyasi-detayli-bir-rehber\/","title":{"rendered":"LangGraph, CopilotKit ve Tavily ile Perplexity Kopyas\u0131: Detayl\u0131 Bir Rehber"},"content":{"rendered":"

<\/p>\n

LangGraph, CopilotKit ve Tavily ile Perplexity Kopyas\u0131: Detayl\u0131 Bir Rehber<\/p>\n

Merhaba! Fatih Soysal olarak, bu makalede size LangGraph, CopilotKit, Tavily ve Next.js kullanarak Perplexity’nin g\u00fc\u00e7l\u00fc yanlar\u0131n\u0131 taklit eden bir arama motoru klonu olu\u015fturma s\u00fcrecinde ad\u0131m ad\u0131m rehberlik edece\u011fim. Bu proje, b\u00fcy\u00fck dil modelleri ve modern web geli\u015ftirme tekniklerinin g\u00fcc\u00fcn\u00fc birle\u015ftiriyor. \u00d6ncelikle, bu teknolojilerin her birinin ne i\u015fe yarad\u0131\u011f\u0131n\u0131 ve nas\u0131l bir araya geldi\u011fini inceleyelim.<\/p>\n

Teknolojileri Tan\u0131yal\u0131m<\/h2>\n

Ba\u015flang\u0131\u00e7 olarak, kullanaca\u011f\u0131m\u0131z teknolojilerin \u00f6zelliklerine k\u0131saca bakal\u0131m. LangGraph, b\u00fcy\u00fck dil modellerini (LLM) sorgulay\u0131p cevaplar\u0131 yap\u0131land\u0131ran g\u00fc\u00e7l\u00fc bir ara\u00e7t\u0131r. \u00d6te yandan, CopilotKit, geli\u015ftirme s\u00fcrecini h\u0131zland\u0131ran bir dizi ara\u00e7 sunar. Tavily ise, veri y\u00f6netimi ve veritaban\u0131 i\u015flemlerinde bize b\u00fcy\u00fck kolayl\u0131k sa\u011flar. Son olarak, Next.js, performansl\u0131 ve \u00f6l\u00e7eklenebilir React uygulamalar\u0131 olu\u015fturmak i\u00e7in m\u00fckemmel bir \u00e7er\u00e7evedir. Bu d\u00f6rt teknolojinin bir araya gelmesiyle, g\u00fc\u00e7l\u00fc ve etkili bir arama motoru olu\u015fturabiliriz.<\/p>\n

Proje Yap\u0131s\u0131 ve Kurulum<\/h2>\n

Projemizi Next.js ile ba\u015flataca\u011f\u0131z. \u0130lk ad\u0131m olarak, yeni bir Next.js projesi olu\u015fturuyoruz. Ard\u0131ndan, package.json<\/code> dosyam\u0131za LangGraph, CopilotKit ve Tavily paketlerini ekliyoruz. Bunun i\u00e7in npm veya yarn kullanabiliriz. Bu ad\u0131m\u0131n ard\u0131ndan, gerekli konfig\u00fcrasyonlar\u0131 yaparak uygulamay\u0131 \u00e7al\u0131\u015ft\u0131rmaya haz\u0131r hale getiririz. Detayl\u0131 kurulum ad\u0131mlar\u0131 i\u00e7in bu kayna\u011fa<\/a> g\u00f6z atabilirsiniz. Bu kaynak \u0130ngilizce olsa da, kod \u00f6rneklerini anlamak nispeten kolayd\u0131r. Ayr\u0131ca, bu ad\u0131mda kar\u015f\u0131la\u015fabilece\u011finiz sorunlar i\u00e7in Stack Overflow gibi platformlardan faydalanabilirsiniz.<\/p>\n

\n\/\/ package.json'a ekleyece\u011finiz paketler (\u00f6rnek)\n\"dependencies\": {\n  \"next\": \"latest\",\n  \"react\": \"latest\",\n  \"react-dom\": \"latest\",\n  \"langgraph\": \"latest\",\n  \"copilotkit\": \"latest\",\n  \"tavily\": \"latest\"\n}\n<\/code><\/pre>\n
API Ba\u011flant\u0131s\u0131 ve Veri \u0130\u015fleme<\/h2>\n
\u015eimdi, LangGraph API’sini entegre etme zaman\u0131.  Kullan\u0131c\u0131 sorgular\u0131n\u0131 LangGraph’a iletecek ve sonu\u00e7lar\u0131 i\u015fleyece\u011fiz.  CopilotKit’in bize sundu\u011fu ara\u00e7lar, bu i\u015flemleri daha kolay ve verimli hale getirecektir.  Tavily’nin veri y\u00f6netim yetenekleri, sonu\u00e7lar\u0131n saklanmas\u0131 ve d\u00fczenlenmesi konusunda b\u00fcy\u00fck kolayl\u0131k sa\u011flayacakt\u0131r.   Sonu\u00e7lar\u0131n kullan\u0131c\u0131 aray\u00fcz\u00fcnde do\u011fru bir \u015fekilde g\u00f6sterilmesi i\u00e7in, verileri uygun bir formata d\u00f6n\u00fc\u015ft\u00fcrmemiz gerekecektir.  Bu ad\u0131mda, hata y\u00f6netimi ve performans optimizasyonu olduk\u00e7a \u00f6nemlidir.  Zira, b\u00fcy\u00fck miktarda veri ile \u00e7al\u0131\u015f\u0131rken performans sorunlar\u0131 ya\u015famamak i\u00e7in dikkatli olmak \u015fartt\u0131r.<\/p>\n
Kullan\u0131c\u0131 Aray\u00fcz\u00fc Tasar\u0131m\u0131<\/h2>\n
Son olarak, kullan\u0131c\u0131 dostu bir aray\u00fcz tasarlamam\u0131z gerekiyor.  Next.js’in sundu\u011fu bile\u015fen tabanl\u0131 mimari, bu noktada bize olduk\u00e7a yard\u0131mc\u0131 olacakt\u0131r.  Arama \u00e7ubu\u011fu, sonu\u00e7lar\u0131n g\u00f6r\u00fcnt\u00fclendi\u011fi alan ve belki de ek \u00f6zellikler (\u00f6rne\u011fin, sonu\u00e7lar\u0131n filtrelenmesi) gibi unsurlar\u0131 d\u00fc\u015f\u00fcnmemiz gerekiyor.  Modern ve temiz bir aray\u00fcz, kullan\u0131c\u0131 deneyimini iyile\u015ftirecektir.  Bu a\u015famada, tasar\u0131m ilkelerini ve kullan\u0131c\u0131 deneyimini g\u00f6z \u00f6n\u00fcnde bulundurmak olduk\u00e7a \u00f6nemlidir.<\/p>\n
Sonu\u00e7<\/h2>\n
Bu makalede, LangGraph, CopilotKit, Tavily ve Next.js kullanarak Perplexity benzeri bir arama motoru olu\u015fturman\u0131n temel ad\u0131mlar\u0131n\u0131 ele ald\u0131k.  Bu proje, yapay zeka ve web geli\u015ftirme konular\u0131nda tecr\u00fcbe kazanman\u0131z i\u00e7in harika bir f\u0131rsatt\u0131r.  Umar\u0131m bu rehber size yard\u0131mc\u0131 olmu\u015ftur.  Ba\u015fka sorular\u0131n\u0131z veya \u00f6nerileriniz varsa, l\u00fctfen benimle ileti\u015fime ge\u00e7mekten \u00e7ekinmeyin. Daha fazla bilgi i\u00e7in kendi web sitemi fatihsoysal.com<\/a> adresini ziyaret edebilirsiniz.<\/p>\n
#Etiketler: Perplexity, LangGraph, CopilotKit, Tavily, Next.js, yapay zeka, b\u00fcy\u00fck dil modeli, arama motoru, klon, tutorial, rehber, makale, Fatih Soysal<\/p>\n
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Fatih Soysal olarak, bu makalede size LangGraph, CopilotKit, Tavily ve Next.js kullanarak Perplexity'nin g\u00fc\u00e7l\u00fc yanlar\u0131n\u0131 taklit eden bir arama motoru klonu olu\u015fturma s\u00fcrecinde ad\u0131m ad\u0131m rehberlik edece\u011fim. Bu proje, b\u00fcy\u00fck dil modelleri ve modern web geli\u015ftirme tekniklerinin g\u00fcc\u00fcn\u00fc birle\u015ftiriyor. \u00d6ncelikle, bu teknolojilerin her birinin ne i\u015fe yarad\u0131\u011f\u0131n\u0131 ve nas\u0131l bir araya geldi\u011fini inceleyelim.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/fatihsoysal.com\/blog\/langgraph-copilotkit-ve-tavily-ile-perplexity-kopyasi-detayli-bir-rehber\/\" \/>\n<meta property=\"og:locale\" content=\"tr_TR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"LangGraph, CopilotKit ve Tavily ile Perplexity Kopyas\u0131: Detayl\u0131 Bir Rehber\" \/>\n<meta property=\"og:description\" content=\"Merhaba! Fatih Soysal olarak, bu makalede size LangGraph, CopilotKit, Tavily ve Next.js kullanarak Perplexity'nin g\u00fc\u00e7l\u00fc yanlar\u0131n\u0131 taklit eden bir arama motoru klonu olu\u015fturma s\u00fcrecinde ad\u0131m ad\u0131m rehberlik edece\u011fim. 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