Siv Agentic AI hauv Kev Ntsuas Kev Ntsuas Automation nrog LangChain thiab DSPy

Introduction

Lub complexity ntawm software systems tau ua qhov kev xeem automation yog ib qho tseem ceeb ntawm kev txhim kho software. Cov txheej txheem kev xeem automation ib txwm cia siab rau cov txheej txheem sau ntawv, uas tuaj yeem ua rau nkig thiab nyuaj rau tswj. Nyob rau hauv xyoo tas los no, qhov tshwm sim ntawm Agentic AI thiab Orchestration Tools tau qhib qhov muaj peev xwm tshiab rau automating complex scenarios. Hauv tsab xov xwm no, peb yuav tshawb txog qhov kev sib tshuam ntawm Agentic AI, Orchestration Tools, thiab Software Engineering los ua kom muaj kev sib tw nyuaj uas siv LangChain thiab DSPy.

Agentic AI yog dab tsi?

Agentic AI hais txog ib hom kev txawj ntse uas tsim los ua haujlwm sawv cev ntawm tus neeg siv lossis lub kaw lus. Agentic AI systems muaj peev xwm txiav txim siab, kawm los ntawm kev paub dhau los, thiab hloov mus rau qhov xwm txheej tshiab. Nyob rau hauv cov ntsiab lus ntawm kev xeem automation, Agentic AI tuaj yeem siv los hloov kho cov xwm txheej nyuaj los ntawm simulating cov neeg siv kev sib cuam tshuam, txiav txim siab raws li cov ntaub ntawv xeem, thiab hloov pauv hloov cov kev sim.

LangChain yog dab tsi?

LangChain yog qhov chaw qhib Orchestration Tool uas tso cai rau cov neeg tsim khoom los tsim cov AI nyuaj siv ntau hom lus, suav nrog Python, Rust, thiab Go. LangChain muab qhov hloov pauv tau yooj yim thiab cov qauv tsim qauv uas ua rau cov neeg tsim khoom sib koom ua ke sib txawv AI Cheebtsam, xws li natural language processing (NLP) thiab computer vision, los tsim kom tau AI systems.

DSPy yog dab tsi?

DSPy yog lub tsev qiv ntawv Python uas muab cov txheej txheem rau kev tsim thiab siv AI systems. DSPy yog tsim los ua hauj lwm seamlessly nrog LangChain thiab muab ntau yam nta, nrog rau cov ntaub ntawv ua, kev kawm tshuab, thiab kev kawm tob.

Ua raws li Agentic AI hauv Kev Txiav Txim Siab Automation

Txhawm rau siv Agentic AI hauv kev txiav txim siab qhov kev xeem automation, peb tuaj yeem siv LangChain thiab DSPy los tsim cov txheej txheem kev sim automation uas simulates cov neeg siv kev sib cuam tshuam, txiav txim siab raws li cov ntaub ntawv xeem, thiab hloov pauv hloov cov kev sim.

Nov yog ib qho piv txwv yooj yim ntawm qhov peb tuaj yeem siv LangChain thiab DSPy los ua qhov kev sim ntsuas qhov xwm txheej: `` python import langchain los ntawm langchain.chains import LLMChain los ntawm langchain.llms import DSPyLLM

test_scenario = { "user_input": "login", "expected_output": "login tiav" }

Txhais cov Agentic AI tus neeg sawv cev

agent = LLMChain( llm = DSPyLLM(), input_type="text", output_type="text" )

Txhais qhov kev xeem automation muaj nuj nqi

def test_automation(test_scenario): # Simulate cov neeg siv kev sib cuam tshuam user_input = test_scenario["user_input"] # Txiav txim siab raws li cov ntaub ntawv xeem kev txiav txim = agent.run(user_input) # Kho kom haum rau kev hloov pauv kev xeem yog kev txiav txim == "login tiav": print("Test pass") lwm tus: print("Test failed")

Khiav qhov kev xeem automation muaj nuj nqi

test_automation (test_scenario)

Hauv qhov piv txwv no, peb txhais cov xwm txheej sim uas suav nrog simulating tus neeg siv kev sib cuam tshuam, txiav txim siab raws li cov ntaub ntawv xeem, thiab hloov pauv hloov cov kev sim. Peb mam li txhais tus neeg sawv cev Agentic AI siv LangChain thiab DSPy, thiab siv nws los ua kom qhov kev sim ua kom zoo.

** 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 LangChain thiab DSPy:

1. `langchain.LLMChain(llm=DSPyLLM())`: Tsim ib tus neeg sawv cev AI siv LangChain thiab DSPy.
2. `DSPyLLM()`: Pib ua ib qho piv txwv ntawm DSPy LLM (Large Language Model).
3. `LLMChain(input_type="text", output_type="text")`: Tsim ib tus neeg sawv cev Agentic AI nrog cov ntawv sau thiab tso tawm hom.
4. `agent.run(user_input)`: Khiav Agentic AI tus neeg saib xyuas nrog cov neeg siv tswv yim.
5. `test_scenario = {"user_input": "login", "expected_output": "login successful"}`: Txhais qhov kev sim nrog cov neeg siv cov tswv yim thiab cov txiaj ntsig xav tau.
6. `langchain.chains.LLMChain(llm=DSPyLLM())`: Tsim ib tus neeg sawv cev AI siv LangChain thiab DSPy.
7. `DSPyLLM().predict(user_input)`: kwv yees cov zis ntawm DSPy LLM nrog cov neeg siv tswv yim.
8. `LLMChain(input_type="text", output_type="text").run(user_input)`: Khiav tus Agentic AI tus neeg saib xyuas nrog cov ntawv sau thiab cov ntawv tso tawm.
9. `test_automation(test_scenario)`: Khiav qhov kev xeem automation muaj nuj nqi nrog rau qhov kev xeem scenario.
10. `langchain.chains.LLMChain(llm=DSPyLLM()).run(user_input)`: Khiav tus Agentic AI tus neeg saib xyuas nrog cov neeg siv tswv yim.

**Visualization**

Nov yog qhov pom ntawm Agentic AI tus neeg sawv cev siv Chart.js:
``json
{
  "type": "bar",
  "data": {
    "labels": ["User Input", "Kev txiav txim siab", "Adaptation"],
    "datasets": [
      {
        "label": "Agent AI Agent",
        "cov ntaub ntawv": [10, 20, 30],
        "backgroundColor": "rgba(255, 99, 132, 0.2)",
        "borderColor": "rgba(255, 99, 132, 1)",
        "BorderWidth": 1
      }
    ]
  },
  "options": {
    "title": {
      "display": tseeb,
      "text": "Agent AI Agent"
    },
    "scales": {
      "yAxes": [
        {
          "ticks": {
            "beginAtZero": tseeb
          }
        }
      ]
    }
  }
}

Qhov kev pom no qhia tau hais tias Agentic AI tus neeg saib xyuas kev ua tau zoo hauv kev simulating cov neeg siv kev sib cuam tshuam, txiav txim siab raws li cov ntaub ntawv xeem, thiab hloov kho rau cov kev hloov pauv.

Qhov xaus

Hauv tsab xov xwm no, peb tau tshawb nrhiav qhov kev sib tshuam ntawm Agentic AI, Cov Cuab Yeej Orchestration, thiab Software Engineering los ua kom cov xwm txheej nyuaj uas siv LangChain thiab DSPy. Peb tau ua ib qho piv txwv yooj yim ntawm Agentic AI hauv kev txiav txim siab kev sim automation thiab muab ntau yam ntawm cov lus txib / cov ntsiab lus rau LangChain thiab DSPy. Peb kuj pom qhov Agentic AI tus neeg saib xyuas kev ua tau zoo siv Chart.js. Los ntawm leveraging Agentic AI thiab Orchestration Tools, developers muaj peev xwm tsim sophisticated xeem automation moj khaum uas simulate cov neeg siv kev sib cuam tshuam, txiav txim siab raws li cov ntaub ntawv xeem, thiab hloov mus rau kev hloov pauv tej yam kev mob.