Kuronga AI-Powered Software Development neLangChain uye DSPy
Introduction
Iyo software yekuvandudza mamiriro ari kukurumidza kubuda, iine AI-powered maturusi uye matekinoroji ari kutamba ari kuwedzera mukurumbira muDevOps otomatiki uye software yekuvaka. Vatambi vaviri vane mukurumbira munzvimbo ino ndiLangChain neDSPy, iyo inopa masimba ekugadzira masimba ekuvaka mapaipi ekuvandudza software anofambiswa neAI. Muchinyorwa chino, tichaongorora nyika yeLangChain neDSPy, tichiongorora kugona kwavo, mabhenefiti, uye maapplication anoshanda muAI-powered software development.
Chii chinonzi LangChain?
LangChain ndeye yakavhurika-sosi, Python-yakavakirwa sisitimu yekuvaka yekukurukurirana AI application. Inopa seti yakasimba yezvishandiso zvechisikigo mutauro kugadzirisa (NLP), muchina kudzidza (ML), uye kuvandudza software, zvichiita kuti ive sarudzo yakanaka yeAI-powered software yekuvandudza mapaipi. LangChain's musimboti maficha anosanganisira:
- Kukurukurirana AI: LangChain inogonesa vanogadzira kuvaka nzvimbo dzekukurukurirana, senge chatbots uye vabatsiri vezwi, vachishandisa NLP uye ML maitiro.
- ** Kuvandudzwa kweSoftware **: LangChain inopa huwandu hwezvishandiso zvekuvandudza software, kusanganisira kugadzirwa kwekodhi, kugadzirisa, uye kuyedza.
- Ochestration: Kugona kweLangChain orchestration kunobvumira vanogadzira kuti vagadzirise mafambisirwo ebasa akaoma uye mapaipi, zvichiita kuti zvive nyore kutonga mapurojekiti makuru ekuvandudza software.
Chii chinonzi DSPy?
DSPy iPython-based framework yekuvaka data sainzi uye mapaipi ekudzidza muchina. Inopa huwandu hwezvishandiso zvekugadzirisa data, chimiro cheinjiniya, kudzidzisa modhi, uye kutumira. DSPy's musimboti maficha anosanganisira:
- Data Sayenzi: DSPy inogonesa vanogadzira kugadzira mapaipi esainzi yedata, kusanganisira kupinza data, kugadzirisa, uye kuongorora.
- ** Kudzidza Muchina**: DSPy inopa huwandu hwematurusi ekudzidza muchina, kusanganisira kudzidziswa kwemhando, tuning, uye kutumira.
- Ochestration: DSPy's orchestration kugona kunobvumira vanogadzira kuti vagadzirise mafambiro ebasa akaomarara uye mapaipi, zvichiita kuti zvive nyore kubata hombe data sainzi nemapurojekiti ekudzidza muchina.
Kuronga AI-Powered Software Development neLangChain uye DSPy
Kuenzanisira simba reLangChain neDSPy muAI-powered software development, ngationei muenzaniso uri nyore. Ngatitii isu tinoda kuvaka yekukurukurirana AI-powered software yekuvandudza pombi inogadzirisa anotevera mabasa:
- Code Generation: Gadzira chinyorwa chePython chakakosha chewebhu application uchishandisa template.
- **Kuongorora Kwekodhi **: Ongorora kodhi yakagadzirwa yezvikanganiso uye upe mazano ekuvandudza.
- ** Kuedza **: Mhanya otomatiki bvunzo pane yakagadzirwa kodhi kuti uone kuti inosangana nezvinodiwa zvinodiwa.
- ** Deployment **: Shandisa code yakagadzirwa kune gore-based platform.
Heino kodhi kodhi yakapfava inoratidza mashandisiro eLangChain neDSPy kuita otomatiki pombi iyi:
import langchain
kubva ku langchain.chains import ConversationalAI
kubva ku langchain.llms import LLM
pombi = ConversationalAI(
llm=LLM("chinyorwa-davinci-003"),
cheni=[
langchain.PipelineStep(
zita = "Code Generation",
func=lambda x: f"import flask\napp = flask.Flask(__name__)\n@app.route('/')\ndef index():\n return' Hello World!'",
),
langchain.PipelineStep(
zita = "Code Ongororo",
func=lambda x: "Kodhi yakagadzirwa inotaridzika zvakanaka, asi funga kuwedzera kukanganisa kubata.",
),
langchain.PipelineStep(
zita = "Kuedza",
func=lambda x: "Kumhanya bvunzo...\nPASS: index()",
),
langchain.PipelineStep(
zita = "Deployment",
func=lambda x: "Kutumira kune cloud platform...\nKubudirira!",
),
],
)
# Mhanya pombi
mhedzisiro = pipeline.run(input="Gadzira chinyorwa chePython chekushandisa pawebhu.")
dhinda(mhedzisiro)
Iyi code block inoratidza mashandisiro eLangChain neDSPy kuita otomatiki pombi yekukurukurirana yeAI-powered software yekuvandudza. Iyo pombi ine matanho mana: kodhi yekugadzira, kodhi ongororo, kuyedza, uye kutumira. Nhanho imwe neimwe inoshandiswa uchishandisa LangChain pipeline nhanho, iyo inotsanangura basa chairo rinofanira kuitwa.
Zvakanakira LangChain uye DSPy
Mabhenefiti ekushandisa LangChain uye DSPy muAI-powered software yekuvandudza akawanda:
- ** otomatiki **: LangChain uye DSPy inogonesa vanogadzira kuti vagadzirise mafambisirwo ebasa akaoma uye mapaipi, zvichiita kuti zvive nyore kubata mapurojekiti makuru ekuvandudza software.
- Kunyatsogona: Nekuita otomatiki kudzokorora mabasa, vagadziri vanogona kutarisa padanho repamusoro mabasa anoda hunyanzvi uye kugadzirisa matambudziko.
- ** Consistency **: LangChain uye DSPy inovimbisa kuenderana mumagadzirirwo esoftware, kuderedza njodzi yekukanganisa nekuvandudza huwandu hwese.
- Scalability: LangChain neDSPy inogonesa vanogadzira kuyera mapaipi ekuvandudza masoftware kuti asangane nezvinodiwa nemapurojekiti makuru.
Pamusoro 5-10 Inonyanya Kushandiswa Mirairo/Zvidimbu
Heano epamusoro 5-10 anonyanya kushandiswa mirairo/zvimedu zveLangChain uye DSPy:
langchain.PipelineStep: Inotsanangura basa chairo rinofanira kuitwa pombi.
pipeline_step = langchain.PipelineStep(
zita = "Code Generation",
func=lambda x: f"import flask\napp = flask.Flask(__name__)\n@app.route('/')\ndef index():\n return' Hello World!'",
)
langchain.ConversationalAI: Inotsanangura pombi yeAI yekukurukurirana.
pombi = langchain.ConversationalAI(
llm=LLM("chinyorwa-davinci-003"),
cheni=[pipeline_step],
)
DSPy.DataPipeline: Inotsanangura pombi yesainzi yedata.
pombi = DSPy.DataPipeline(
data_source="https://example.com/data.csv",
data_transformer=lambda x: x["column1"] + x["column2"],
)
DSPy.ModelPipeline: Inotsanangura pombi yekudzidzira muchina.
pombi = DSPy.ModelPipeline(
muenzaniso = "mutsara_kudzoreka",
data_source="https://example.com/data.csv",
data_transformer=lambda x: x["column1"] + x["column2"],
)
langchain.LLM: Inotsanangura chimiro chemutauro.
llm = langchain.LLM("text-davinci-003")
DSPy.DataTransformer: Inotsanangura data transformer.
transformer = DSPy.DataTransformer(lambda x: x["column1"] + x["column2"])
DSPy.ModelTrainer: Inotsanangura mudzidzisi wemuenzaniso.
mudzidzisi = DSPy.ModelTrainer(modhi = "linear_regression")
langchain.Pipeline: Inotsanangura pombi.
pombi = langchain.Pipeline(
cheni=[pipeline_step],
)
DSPy.DataLoader: Inotsanangura data loader.
loader = DSPy.DataLoader(data_source="https://example.com/data.csv")
DSPy.ModelDeployer: Inotsanangura mushandisi wemuenzaniso.
deployer = DSPy.ModelDeployer(modhi = "linear_regression")
Kuona
Heino ratidziro yeLangChain uye DSPy pombi uchishandisa Chart.js:
{
"type": "bha",
"data": {
"labels": ["Code Generation", "Code Wongororo", "Test", "Deployment"],
"datasets": [
{
"label": "LangChain",
"data": [10, 8, 12, 15],
"backgroundColor": "rgba(255, 99, 132, 0.2)",
"borderColor": "rgba(255, 99, 132, 1)",
"borderWidth": 1
},
{
"label": "DSPy",
"data": [8, 10, 12, 15],
"backgroundColor": "rgba(54, 162, 235, 0.2)",
"borderColor": "rgba(54, 162, 235, 1)",
"borderWidth": 1
}
]
},
"sarudzo": {
"zita": {
"kuratidza": chokwadi,
"zvinyorwa": "LangChain uye DSPy Pipeline"
},
"zvikero": {
"yAxes": [
{
"zvikwekwe": {
"beginAtZero": chokwadi
}
}
]
}
}
}
Ichi chitarisiko chinoratidza huwandu hwemabasa akaitwa neLangChain uye DSPy mupombi. Iyo x-axis inomiririra mabasa, uye y-axis inomiririra huwandu hwemabasa akaitwa.
Mhedziso
LangChain uye DSPy inopa simba rekuita orchestration yekuvaka AI-inotyairwa software yekuvandudza mapaipi. Nekuita otomatiki mafambisirwo ebasa uye mapaipi, vanogadzira vanogona kutarisa pamabasa epamusoro-soro anoda hunyanzvi uye hunyanzvi hwekugadzirisa matambudziko. Zvakanakira kushandisa LangChain uye DSPy zvinosanganisira otomatiki, kunyatsoita, kusachinja-chinja, uye scalability. NeLangChain neDSPy, vagadziri vanogona kuvaka kutaurirana AI-powered software yekuvandudza mapaipi anosangana nezvinodiwa zvemapurojekiti makuru.