Overview
LangChain inzvimbo yakavhurika-sosi (uye kambani) yekuvaka zvikumbiro zvinofambiswa nemhando dzemitauro mikuru. Inopa zvivakwa zvekuvaka zvinogoneka zvekubatanidza LLM mafoni, kubatanidza kune data uye maturusi, uye kuronga akawanda-nhanho vamiririri.
LangChain inonzwisiswa zvakanyanya mumamiriro ehurongwa, kuwana muenzaniso, sarudzo dzepuratifomu, uye kudyidzana kwe ecosystem.
Deep Dive
Yakatangwa naHarrison Chase muna Gumiguru 2022, kwangosara nguva ye ChatGPT boom, LangChain yakave iyo inonyanya kufarirwa chimiro cheWiring LLMs mukushandisa chaiko. Chimiro chayo ndechekuti inobatsira LLM maapplication haawanzo kukurumidza kamwe chete; vanofona modhi yeketani, kutora magwaro, kufonera APIs, kuburitsa zvinobuda, uye kuchengetedza ndangariro. LangChain inomisa zvidimbu izvi nezvisungo zvekukurudzira, modhi, zvidzoreso, zvishandiso, uye 'ngetani.' Iyo LangChain Expression Mutauro (LCEL) inoita kuti vanogadzira vagadzire zvikamu zvine pombi-style syntax. Iyo kambani yakawedzera kuita chigadzirwa suite: LangGraph yekuvaka stateful, controllable agent workflows semagirafu; LangSmith yekutsvaga, kugadzirisa, uye kuongorora LLM mapurogiramu mukugadzira; uye LangServe kuti iendeswe. Inowanikwa muPython neJavaScript, ine makumi ezviuru zveGitHub nyeredzi uye yakafara bhizinesi kutorwa, kunyangwe vamwe vatsoropodzi vachipokana kuti mabatiro ayo anowedzera kuomarara kwemakesi ekushandisa ari nyore.
Technical Insight
Pamwoyo payo LangChain inhengo yekugadzira. Zvikamu zvinogovera yakajairwa Runnable interface, saka template yekukurumidza, LLM, uye inobuda parser inogona kuputirwa pamwe chete (yekukurumidza | modhi | parser) mune imwechete inofona. Nezvekudzoreredza-yakawedzera chizvarwa, inobatanidza embedding modhi uye vector zvitoro kuti itore yakakodzera mamiriro. LangGraph modhi vamiririri semuchina wehurumende, uchipa kudzora kwakajeka pamusoro pezvishwe, mapazi, uye maturusi ekufona.
Mastering LangChain
LangChain inzvimbo yakavhurika-sosi (uye kambani) yekuvaka zvikumbiro zvinofambiswa nemhando dzemitauro mikuru. Inopa zvivakwa zvekuvaka zvinogoneka zvekubatanidza LLM mafoni, kubatanidza kune data uye maturusi, uye kuronga akawanda-nhanho vamiririri. LangChain inonzwisiswa zvakanyanya mumamiriro ehurongwa, kuwana muenzaniso, sarudzo dzepuratifomu, uye kudyidzana kwe ecosystem. Kuti uvake kunzwisisa kwakadzama, bata LangChain semuenzaniso wekushandisa, kwete chinhu chimwe chete: tsanangura mhedzisiro inodiwa, kujekesa fungidziro, uye patsanura izvo hurongwa hunogona kuita zvakavimbika kubva kune zvichiri kuda kutonga kwenyanzvi.
Mukuita, zvikwata zvakasimba zvinoshandisa LangChain zvinoongorora nzira yevatengesi, kuvimbika kwemepu yemugwagwa, uye kuvhara-mungozi vasati vaita. Ivo vanonyora zvakajeka maitiro ebudiriro, bvunzo vachipokana ne data rechokwadi uye mafambiro ebasa, uye iterate zvichibva pane zvakacherechedzwa maitiro ekutadza kwete kuhwina-nguva imwe chete yebhenji. Apa ndipo apo kunzwisisa kwe theoretical kunoshanduka kuve kugona kwakasimba pane chigadzirwa, mutemo, uye mashandiro.
Mamepu emigwagwa emutengesi anopesvedzera izvo izvo timu yako inogona kugadzira inotevera. Panguva imwecheteyo, zviziviso zveLaunch zvinogona kupfuura kugadzikana mune chaiyo yekugadzira workflows. Nzira yakatsiga ndeyekubatanidza kukurumidza kuyedza nekutonga: mhanyisa vatyairi vendege, tora humbowo, buritsa matanda esarudzo, uye urambe uchivandudza chengetedzo semaitiro emuenzaniso, zvinotarisirwa nemushandisi, uye zvinodikanwa zvekutonga.
Strategic Impact
Mamepu emigwagwa emutengesi anopesvedzera izvo izvo timu yako inogona kugadzira inotevera.
Mamepu emigwagwa emutengesi anopesvedzera izvo izvo timu yako inogona kugadzira inotevera. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Mamiriro ezvekutengeserana uye sarudzo dzekuendesa dzinokanganisa mutengo wenguva refu uye njodzi.
Mamiriro ezvekutengeserana uye sarudzo dzekuendesa dzinokanganisa mutengo wenguva refu uye njodzi. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Kambani inokurudzira inogadzirisa kusarudzika kwechigadzirwa, mamiriro ekuchengetedza, uye kuvhurika.
Kambani inokurudzira inogadzirisa kusarudzika kwechigadzirwa, mamiriro ekuchengetedza, uye kuvhurika. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Real-World Implementation
Yekutanga inovaka gwaro Q&A bot iyo inotora yakakodzera maPDF ndima kubva muchitoro chevector uye inoapa kuLLM kune mhinduro dzakadzika.
Mugadziri anogadzira cheni inotora chikumbiro chemushandisi, inodaidza mamiriro ekunze API sechokushandisa, obva agadzira mhedzisiro kuita mhinduro ine hushamwari.
Bhizinesi rinoshandisa LangGraph kuvaka mutengi-rutsigiro uyo anofamba nematanho uye kumbomira kuti atenderwe nevanhu asati adzosera mari.
Chikwata chinoshandisa LangSmith kuteedzera nhanho yega yega yeinononoka kugadzira cheni, tsvaga iyo bhodhoro kufona, uye ongorora mhando yekupindura uchipesana nebvunzo seti.
Maitiro Ekuita
LangChain mukuita
Yekutanga inovaka gwaro Q&A bot iyo inotora yakakodzera maPDF ndima kubva muchitoro chevector uye inoapa kuLLM kune mhinduro dzakadzika.
Yekutanga inovaka gwaro Q&A bot iyo inotora yakakodzera maPDF ndima kubva muchitoro chevector uye inoapa kuLLM yemhinduro dzakadzika Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye kukanganisa mutengo nekufamba kwenguva.
LangChain mukuita
Mugadziri anogadzira cheni inotora chikumbiro chemushandisi, inodaidza mamiriro ekunze API sechokushandisa, obva agadzira mhedzisiro kuita mhinduro ine hushamwari.
Mugadziri anogadzira cheni inotora chikumbiro chemushandisi, anodaidza API yemamiriro ekunze sechishandiso, obva agadzira mhedzisiro kuti ave mhinduro ine hushamwari Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
LangChain mukuita
Bhizinesi rinoshandisa LangGraph kuvaka mutengi-rutsigiro uyo anofamba nematanho uye kumbomira kuti atenderwe nevanhu asati adzosera mari.
Bhizinesi rinoshandisa LangGraph kuvaka mutengi-rutsigiro uyo anofamba nematanho uye kumbomira kuti atenderwe nevanhu asati adzosera mari Matimu anowanzo kuwana mibairo iri nani kana achinge atsanangura hunhu kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
LangChain mukuita
Chikwata chinoshandisa LangSmith kuteedzera nhanho yega yega yeinononoka kugadzira cheni, tsvaga iyo bhodhoro kufona, uye ongorora mhando yekupindura uchipesana nebvunzo seti.
Chikwata chinoshandisa LangSmith kutsvaga nhanho imwe neimwe yeketani yekugadzira inononoka, tsvaga kufona kwebhodhoro, uye kuongorora mhando yekupindura uchipesana nebvunzo seti Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Njodzi & Guardrails
Zviziviso zvekutanga zvinogona kupfuura kugadzikana mune chaiyo yekugadzira workflows.
Mitengo yeAPI kana shanduko yepolicy inogona kukanganisa fungidziro husiku.
Kutsamira kune mumwe-mutengesi kunowedzera kukiya-mukati uye mari yekufambisa.
Implementation Roadmap
Ongorora vanopa uchishandisa ako ega mabasa uye dataset.
Ongorora vanopa uchishandisa ako ega mabasa uye dataset. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Wongorora zvakavanzika, chengetedzo, uye mazwi emutemo usati wabatanidzwa.
Wongorora zvakavanzika, chengetedzo, uye mazwi emutemo usati wabatanidzwa. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Chengetedza chirongwa chekudzokera kumashure kune mamodheru kana vatengesi.
Chengetedza chirongwa chekudzokera kumashure kune mamodheru kana vatengesi. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Tarisa zvinyorwa zvekuburitsa kuitira kuti shanduko yemigwagwa isashamise zvikwata.
Tarisa zvinyorwa zvekuburitsa kuitira kuti shanduko yemigwagwa isashamise zvikwata. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.