Gadzira mumiriri wetsika uchishandisa LangChain

**Kuita Agent Quality Optimization neLangChain uye DSPy yeAI-Powered DevOps Automation **

Introduction

Iko kuwedzera kuomarara kweazvino software masisitimu kwakonzera kudiwa kuri kukura kweanoshanda uye anoshanda DevOps otomatiki. MaAgent-based masisitimu akabuda senzira inovimbisa yekuzadzisa chinangwa ichi, kushandisa hungwaru hwekugadzira (AI) uye kudzidza muchina (ML) kukwirisa mashandiro ehurongwa nekuvandudza mhando. Muchikamu chino, tichaongorora kushandiswa kwehunyanzvi kweagent quality optimization muAgentCore, leveraging LangChain uye DSPy yeAI-powered DevOps otomatiki.

**AgentCore: Hwaro hweAI-Powered DevOps Automation **

AgentCore ndeye yakavhurika-sosi sisitimu yekuvaka AI-powered DevOps otomatiki masisitimu. Inopa modular dhizaini inoita kuti vanogadzira vagadzire vamiririri vetsika kune akasiyana mabasa, akadai sekutarisa, kutumira, uye kuyedzwa. AgentCore akakosha maficha anosanganisira:

** Modular Architecture**: Mavakirwo eAgentCore akagadzirwa kuti ave akanyanya modular, achibvumira vanogadzira kugadzira vamiririri vetsika uye kuvabatanidza zvisina musono nemusimboti framework.
**AI-Powered Sarudzo Kuita **: AgentCore inokwirisa AI uye ML algorithms kuita sarudzo ine ruzivo nezve system performance uye mhando.
Real-Time Monitoring: AgentCore inopa chaiyo-nguva yekutarisisa kugona, inoita kuti vanogadzira vatarise maitiro ehurongwa uye vaone zvingangoitika zvisati zvave matambudziko makuru.

**LangChain: Chimiro chekuvaka Kukurukurirana AI Agents **

LangChain iPython framework yekuvaka hurukuro yeAI vamiririri. Inopa huwandu hwezvishandiso uye maraibhurari ekugadzira tsika vamiririri vanogona kupinda mumutauro wechisikigo hurukuro nevashandisi. LangChain akakosha maficha anosanganisira:

Kukurukurirana AI: LangChain inogonesa vanogadzira kugadzira tsika dzekukurukurirana dzeAI vamiririri vanogona kuita hurukuro dzemutauro wechisikigo nevashandisi.
** Modular Architecture **: Chivakwa cheLangChain chakagadzirirwa kuve chakanyanya modular, chichibvumira vanogadzira kugadzira vamiririri vetsika uye vabatanidze pasina musono nemusimboti framework.
Kubatanidzwa neDSPy: LangChain inopa mubatanidzwa usina musono neDSPy, zvichiita kuti vanogadzira vakwanise kuwedzera hunyanzvi hweDSPy's AI neML muvamiririri vavo veAI.

DSPy: Chimiro cheKuvaka AI neML Models

DSPy iPython framework yekuvaka AI neML modhi. Inopa huwandu hwezvishandiso uye maraibhurari ekugadzira emhando dzemhando dzinogona kushandiswa mumhando dzakasiyana dzekushandisa, kusanganisira DevOps otomatiki. DSPy's akakosha maficha anosanganisira:

** AI neML Modelling **: DSPy inogonesa vanogadzira kugadzira tsika AI neML modhi inogona kushandiswa mumhando dzakasiyana dzekushandisa, kusanganisira DevOps otomatiki.
Kubatanidzwa neLangChain: DSPy inopa mubatanidzwa usina musono neLangChain, zvichiita kuti vanogadzira vakwanise kuwedzera kugona kweLangChain yekukurukurirana kweAI mumhando dzavo dzeAI neML.
Real-Time Predictive Analytics: DSPy inopa chaiyo-nguva yekufungidzira analytics kugona, ichigonesa vanogadzira kuita sarudzo dzine ruzivo nezvemaitiro ehurongwa uye kunaka.

Kuita Agent Quality Optimization neLangChain uye DSPy

Kuti tiite agent quality optimization neLangChain uye DSPy, tinoda kutevera matanho aya:

**Gadzira Custom Agent **: Gadzira mumiririri wetsika uchishandisa LangChain iyo inogona kuita hurukuro yemutauro wechisikigo nevashandisi.
Batanidza DSPy: Batanidza DSPy nemumiririri wetsika kuti uwedzere kugona kweDSPy's AI neML.
Dzidzisa Muenzaniso: Rovedza AI neML modhi uchishandisa DSPy kukwenenzvera kunaka kweajenti.
Nyonza Mumiririri: Tumira mumiririri wetsika nemodhi yakadzidziswa kuti ikwidzise kunaka kwemumiririri.

Heino kodhi yekodhi yakapfava inoratidza nzira yekugadzira mumiriri wetsika uchishandisa LangChain uye kubatanidza DSPy:

import langchain
kubva ku langchain import LLMChain
kubva langchain.chains import ConversationalChain
kubva langchain.embeddings import Embeddings
kubva ku langchain.llms import LLM


mumiririri = LLMChain(
    llm=LLM(
        muenzaniso="zvinyorwa-davinci-003",
        tembiricha=0.7,
        max_tokens=100,
        min_tokens=10,
    ),
    input_format="zvinyorwa",
    output_format = "chinyorwa",
)

# Batanidza DSPy
dsp = DSPy(
    muenzaniso = "dspb",
    tembiricha=0.7,
    max_tokens=100,
    min_tokens=10,
)

# Rovedza modhi uchishandisa DSPy
dsp.train(
    mumiririri,
    data=[
        {"input": "Tembiricha yanhasi yakaita sei?", "output": "Tembiricha iripo i25°C."},
        {"input": "Chii chinonzi humidity parizvino?", "output": "Hwando huripo i60%."},
    ],
)

# Tumira mumiriri neiyo yakadzidziswa modhi
agent.deploy(dsp)

Mhedzisiro pakuvandudza kweSoftware uye Architecture

Kuita agent quality optimization neLangChain uye DSPy kune zvakati wandei zvinokanganisa pakuvandudza software uye zvivakwa:

Kuvandudzwa Kwekuita KweSistimu: Kukwirisa kwemhando yeAgent kunoita kuti vanogadzira vagadzire vamiririri vetsika vanogona kukwirisa mashandiro ehurongwa nekuvandudza mhando.
** Yakavandudzwa Chiitiko cheMushandisi **: Kukurukurirana AI vamiririri vanogona kupa vashandisi ruzivo rwakanyanya uye rwunobata munhu.
Kuwedzera Kunyatsogona: Kugonesa kwemumiririri kunoita kuti vagadziri vakwanise kuita mabasa anodzokororwa otomatiki uye vatarise mabasa akaomarara uye ekugadzira.

Pamusoro 5-10 Inonyanya Kushandiswa Mirairo/Zvidimbu

Heano epamusoro 5-10 anonyanya kushandiswa mirairo/zvimedu zveLangChain uye DSPy:

langchain.LLMChain(): Inogadzira mumiririri wetsika achishandisa LangChain.
langchain.Embeddings(): Inogadzira chinhu chekumisikidza kuti chishandiswe muchimiro chetsika.
langchain.LLM(): Inogadzira chimiro chemutauro chekushandisa mumiririri wetsika.
dsp.DSPy(): Inogadzira chinhu cheDSPy chekushandisa mumiririri wetsika.
dsp.train(): Inodzidzisa muenzaniso weAI neML uchishandisa DSPy.
dsp.deploy(): Inotumira mumiririri wetsika nemuenzaniso wakadzidziswa.
langchain.ConversationalChain(): Inogadzira hurukuro yeAI mumiririri uchishandisa LangChain.
langchain.chains.ConversationalChain(): Inogadzira hurukuro yeAI mumiririri uchishandisa LangChain.
langchain.embeddings.Embeddings(): Inogadzira chinhu chekumisikidza kuti chishandiswe muchimiro chetsika.
langchain.llms.LLM(): Inogadzira chimiro chemutauro chekushandisa mumiririri wetsika.

Kuona

Heino ratidziro yakapfava uchishandisa Chart.js inoratidza kukanganiswa kweagent quality optimization pane system performance:

{
    "type": "bha",
    "data": {
        "labels": ["Usati Wagadziridza", "Mushure meKugadzirisa"],
        "datasets": [
            {
                "label": "System Performance",
                "data": [80, 95],
                "backgroundColor": "rgba(255, 99, 132, 0.2)",
                "borderColor": "rgba(255, 99, 132, 1)",
                "borderWidth": 1
            }
        ]
    },
    "sarudzo": {
        "zita": {
            "kuratidza": chokwadi,
            "chinyorwa": "Kuitwa kweSystem Pamberi uye Mushure meKugadziridza"
        },
        "zvikero": {
            "yAxes": [
                {
                    "zvikwekwe": {
                        "beginAtZero": chokwadi
                    }
                }
            ]
        }
    }
}

Ichi chitarisiko chinoratidza kukanganisa kweagent quality optimization pane system performance, ichiratidza kuvandudzwa kwakanyanya mukuita kwesystem mushure mekugadzirisa.

Mhedziso

Kuita optimization yemhando yeagent neLangChain uye DSPy kune zvikomborero zvakati wandei, zvinosanganisira kuvandudza mashandiro ehurongwa, ruzivo rwemushandisi rwakawedzerwa, uye nekuwedzera kugona. Nekusimudzira kugona kweLangChain neDSPy, vanogadzira vanogona kugadzira vamiririri vetsika vanogona kukwidziridza mashandiro ehurongwa nekuvandudza mhando. Iyo kodhi kodhi uye yekuona yakapihwa inoratidza tekinoroji yekumisikidzwa kweagent mhando optimization uye maitiro ayo pakuvandudza software uye kuvaka.

Gadzira mumiriri wetsika uchishandisa LangChain

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