Kev koom ua ke RAG nrog LLMs rau Kev Txhim Kho Software Txhim Kho Kev Ua Haujlwm

Introduction

Lub software tsim kho thaj chaw yog hloov zuj zus mus sai, tau tsav los ntawm kev nce qib hauv kev txawj ntse (AI), kev kawm tshuab (ML), thiab kev ua cov lus ntuj (NLP). Ob lub thev naus laus zis tseem ceeb uas tau hloov pauv txoj hauv kev peb tsim software yog Retrieval-Augmented Generation (RAG) thiab Cov Qauv Lus Loj (LLMs). Hauv tsab xov xwm no, peb yuav tshawb nrhiav kev koom ua ke ntawm RAG nrog LLMs txhawm rau txhim kho software engineering txheej txheem, txhim kho code tsim, thiab txhim kho cov tsim khoom tsim tawm.

Retrieval-Augmented Generation (RAG) yog dab tsi?

RAG yog ib qho txheej txheem uas sib xyaw ua ke ntawm qhov muaj zog ntawm retrieval-based thiab tiam-raws li txoj hauv kev rau NLP. Nws suav nrog kev muab cov ntaub ntawv cuam tshuam los ntawm cov ntaub ntawv loj ntawm cov ntawv nyeem thiab siv nws los txhawb kev tsim cov ntawv tshiab. Txoj hauv kev no tau pom tias muaj txiaj ntsig zoo hauv ntau yam haujlwm NLP, suav nrog kev teb cov lus nug, sau ntawv sau, thiab tsim cov lej.

** Cov Qauv Lus Loj (LLMs) yog dab tsi?**

LLMs yog hom neural network uas tsim los ua thiab tsim cov lus zoo li tib neeg. Lawv feem ntau raug cob qhia ntawm cov ntaub ntawv loj ntawm cov ntawv nyeem thiab tuaj yeem ua tau zoo rau cov haujlwm tshwj xeeb xws li kev txhais lus, sau ntawv sau, thiab tsim cov lej. LLMs tau ua tiav cov txiaj ntsig hauv lub xeev ntawm ntau yam haujlwm NLP thiab tau siv dav hauv cov ntawv thov xws li chatbots, tus pabcuam virtual, thiab cov tshuab txhais lus.

Kev koom ua ke RAG nrog LLMs rau Kev Txhim Kho Software Txhim Kho Kev Ua Haujlwm

Cov cuab yeej Orchestration: LangChain thiab DSPy

Txhawm rau koom nrog RAG nrog LLMs, peb xav tau cov cuab yeej orchestration uas tuaj yeem tswj hwm cov ntaub ntawv ntws thiab tswj kev ua tiav ntawm RAG thiab LLM cov khoom. Ob qhov nrov orchestration cuab yeej siv tau rau lub hom phiaj no yog LangChain thiab DSPy.

LangChain

LangChain yog lub tsev qiv ntawv qhib Python uas muab qhov yooj yim thiab nkag siab API rau kev tsim cov ntawv thov RAG. Nws tso cai rau cov neeg tsim khoom kom yooj yim sib koom ua ke RAG nrog LLMs thiab lwm yam NLP cov khoom los tsim cov haujlwm tsim kho software muaj zog.

DSPy

DSPy yog lwm lub tsev qiv ntawv qhib Python uas muab API qib siab rau kev tsim cov ntawv thov RAG. Nws yog tsim los ua hauj lwm seamlessly nrog LLMs thiab lwm yam NLP Cheebtsam, ua rau nws yog ib tug zoo tagnrho xaiv rau integrating RAG nrog LLMs.

Code Piv txwv: Integrating RAG nrog LLMs siv LangChain

Nov yog ib qho piv txwv yooj yooj yim uas qhia tau hais tias yuav ua li cas koom nrog RAG nrog LLMs siv LangChain: `` python import langchain los ntawm langchain.chains import RAGChain

rag_model = langchain.RAG( index=langchain.Index( name="my_index", document = ["document1", "document2", "document3"], ), retriever=langchain.Retriever( npe="my_retriever", model="my_retriever_model", ), generator=langchain.Generator( name="my_generator", model="my_generator_model", ), )

Txhais tus qauv LLM

llm_model = langchain.LLM( name="my_llm", model="my_llm_model", )

Tsim RAG saw hlau

rag_chain = RAGChain( name="my_rag_chain", model=rag_model, llm = llm_model, )

Siv RAG saw los tsim cov lej

code = rag_chain.generate( input_text = "Sau ib txoj haujlwm uas siv ob tus lej ua cov tswv yim thiab xa lawv cov lej", )

print(code)

Cov qauv code no qhia tau hais tias yuav ua li cas los txhais tus qauv RAG siv LangChain, txhais tus qauv LLM, tsim RAG saw, thiab siv cov saw los tsim cov lej.

** Sab saum toj 5-10 Feem Ntau Siv Cov Lus Qhia/Snippet **

Nov yog cov saum toj kawg nkaus 5-10 feem ntau siv cov lus txib / snippets rau kev koom ua ke RAG nrog LLMs siv LangChain thiab DSPy:

1. `langchain.RAG()`: Tsim RAG qauv piv txwv.
2. `langchain.Index()`: Tsim ib qho piv txwv rau khaws cia thiab khaws cov ntaub ntawv.
3. `langchain.Retriever()`: Tsim ib qho piv txwv retriever rau retrieving cov ntaub ntawv cuam tshuam.
4. `langchain.Generator()`: Tsim lub tshuab hluav taws xob piv txwv rau kev tsim cov ntawv tshiab.
5. `langchain.LLM()`: Tsim ib qho piv txwv LLM.
6. `RAGChain()`: Tsim RAG chain piv txwv.
7. `rag_chain.generate()`: Siv RAG saw los tsim cov lej.
8. `llm_model.generate()`: Siv tus qauv LLM los tsim cov lej.
9. `index.add_document()`: Ntxiv ib daim ntawv rau qhov ntsuas.
10. `retriever.retrieve()`: Rov muab cov ntaub ntawv ntsig txog siv tus retriever.

**Visualization**

Nov yog kev pom ntawm RAG thiab LLM cov khoom siv Chart.js:
``json
{
  "type": "bar",
  "data": {
    "labels": ["RAG", "LLM"],
    "datasets": [
      {
        "label": "Cov khoom",
        "cov ntaub ntawv": [10, 20],
        "backgroundColor": ["#4CAF50", "#FF9800"]
      }
    ]
  },
  "options": {
    "title": {
      "display": tseeb,
      "text": "RAG and LLM Components"
    },
    "scales": {
      "yAxes": [
        {
          "display": tseeb,
          "beginAtZero": tseeb
        }
      ]
    }
  }
}

Qhov kev pom no qhia tau hais tias muaj pes tsawg tus ntawm cov khoom hauv RAG thiab LLM qauv.

Qhov xaus

Kev koom ua ke ntawm RAG nrog LLMs muaj lub peev xwm los hloov pauv txoj hauv kev peb tsim software. Los ntawm kev sib txuas cov kev ua tau zoo ntawm retrieval-based thiab tiam-raws li txoj hauv kev, RAG tuaj yeem pab LLMs los tsim cov lej raug thiab cuam tshuam. Qhov no tuaj yeem ua rau muaj kev txhim kho tseem ceeb hauv kev tsim cov khoom tsim tawm, cov lej zoo, thiab tag nrho cov software txhim kho kev ua haujlwm. Nrog rau cov cuab yeej orchestration xws li LangChain thiab DSPy, cov neeg tsim khoom tuaj yeem yooj yim integrate RAG nrog LLMs thiab lwm yam NLP cov khoom los tsim cov software tsim muaj zog.

Kev koom ua ke RAG nrog LLMs rau Kev Txhim Kho Software Txhim Kho Kev Ua Haujlwm

Txhais tus qauv LLM

Tsim RAG saw hlau

Siv RAG saw los tsim cov lej

Have Questions?