Ịhazi AI-Powered DevOps Automation na DSPy na LangChain | B4N1

Ịhazi AI-Powered DevOps Automation na DSPy na LangChain

3 months ago · b4n1 Read time: 5 min

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Okwu mmalite

Odida obodo mmepe ngwanrọ na-agbanwe ngwa ngwa, yana nnabata na-abawanye nke Artificial Intelligence (AI) na mmụta igwe (ML) na akpaaka DevOps. Automation nke AI kwadoro nwere ike inye aka mee ka usoro ọrụ dị mgbagwoju anya dị mgbagwoju anya, melite arụmọrụ, ma belata ohere nke njehie mmadụ. N'isiokwu a, anyị ga-enyocha otu esi etinye DSPy na LangChain iji mejuputa ndị ọrụ AI kwadoro maka nyocha ihe kpatara mgbọrọgwụ na njikarịcha arụmọrụ na pipeline mmepe software.

Gịnị bụ DSPy?

DSPy bụ ọba akwụkwọ Eke Ọgba nke na-enye ndị mmepe ohere iwulite ma bukwaa usoro ọrụ akpaaka nke AI kwadoro. Ọ na-enye usoro ngbanwe na mgbanwe maka ijikọ ụdị AI na ML dị iche iche, na-eme ka ọ bụrụ ezigbo nhọrọ maka akpaaka DevOps.

Kedu ihe bụ LangChain?

LangChain bụ ọba akwụkwọ Python na-enyere ndị mmepe aka iwulite na ibuga ndị nnọchi anya AI mkparịta ụka. Ọ na-enye API dị mfe ma nwee nghọta maka ịmepụta ndị ọrụ nwere ike ịghọta na zaghachi na ntinye asụsụ eke.

Na-emejuputa ndị nnọchi anya AI maka nyocha ihe kpatara mgbọrọgwụ

Nyocha ihe kpatara mgbọrọgwụ bụ akụkụ dị oke mkpa nke DevOps automation, ebe ọ na-enyere aka ịchọpụta ihe kpatara nsogbu ma gbochie ha ime n'ọdịnihu. Iji mejuputa nyocha ihe kpatara mgbọrọgwụ AI-kwadoro, anyị nwere ike iji DSPy mepụta usoro ọrụ na-ejikọta na LangChain.

Nke a bụ nkọwapụta ọkwa dị elu nke usoro ọrụ:

  1. ** Nchịkọta data ***: Anakọta data dị mkpa sitere na isi mmalite dị iche iche, dị ka ndekọ, metrics, na faịlụ nhazi.
  2. ** Nhazi data ***: Hazie data anakọtara iji kwado ya maka nyocha.
  3. ** Ọzụzụ Nlereanya ***: Zụlite ụdị ML na data emeberela iji chọpụta ụkpụrụ na mmekọrịta.
  4. ** Ihe Nlereanya Nlereanya ***: Tinye ihe nlereanya a zụrụ azụ na ọrụ DSPy.
  5. ** Njikọ Agent ***: Jikọta usoro ọrụ DSPy na onye nnọchi anya LangChain iji mee ka mmekọrịta asụsụ eke.

Usoro Ihe Nlereanya: Mgbọrọgwụ Analysis Workflow

"Python mbubata dspy ka dsp onye nnọchi anya mbubata langchain

Kọwaa usoro ọrụ DSPy

usoro ọrụ = dsp. Usoro ọrụ ( aha = "mgbọrọgwụ_cause_analysis", ọrụ =[ dsp.Task("data_nchịkọta", "Cnakọta data sitere na ndekọ na metrics"), dsp.Task ("data_preprocessing", "Nhazi data maka nyocha"), dsp.Task("model_training", "Zụlite ụdị ML na data emechara"), dsp.Task ("model_deployment", "Tinye ụdị a zụrụ azụ na DSPy workflow"), ], )

Kọwaa onye nnọchi anya LangChain

onye nnọchi anya = onye nnọchi anya ( aha = "mgbọrọgwụ_cause_agent", ụdị = "distilbert-base-uncased", Quick = "Gịnị bụ isi ihe kpatara nsogbu ahụ?", )

Jikọta usoro ọrụ DSPy na onye nnọchi anya LangChain

workflow.add_agent (onye nnọchi anya)

Mepụta usoro ọrụ

workflow.run() ``

Na-emejuputa ndị nnọchi anya AI maka nkwalite arụmọrụ

Nkwalite arụmọrụ bụ akụkụ ọzọ dị oke mkpa nke akpaaka DevOps, ebe ọ na-enyere aka melite ọsọ na nrụpụta nke pipeline mmepe ngwanrọ. Iji mejuputa njikarịcha arụmọrụ AI kwadoro, anyị nwere ike iji DSPy mepụta usoro ọrụ nke jikọtara ya na LangChain.

Nke a bụ nkọwapụta ọkwa dị elu nke usoro ọrụ:

  1. ** Nchịkọta data ***: Anakọta data dị mkpa sitere na isi mmalite dị iche iche, dị ka ndekọ, metrics, na faịlụ nhazi.
  2. ** Nhazi data ***: Hazie data anakọtara iji kwado ya maka nyocha.
  3. ** Ọzụzụ Nlereanya ***: Zụlite ụdị ML na data emeberela iji chọpụta ụkpụrụ na mmekọrịta.
  4. ** Ihe Nlereanya Nlereanya ***: Tinye ihe nlereanya a zụrụ azụ na ọrụ DSPy.
  5. ** Njikọ Agent ***: Jikọta usoro ọrụ DSPy na onye nnọchi anya LangChain iji mee ka mmekọrịta asụsụ eke.

Ọmụmaatụ koodu: Nrụpụta arụmọrụ arụmọrụ

"Python mbubata dspy ka dsp onye nnọchi anya mbubata langchain

Kọwaa usoro ọrụ DSPy

usoro ọrụ = dsp. Usoro ọrụ ( aha = "efficiency_optimization", ọrụ =[ dsp.Task("data_nchịkọta", "Cnakọta data sitere na ndekọ na metrics"), dsp.Task ("data_preprocessing", "Nhazi data maka nyocha"), dsp.Task("model_training", "Zụlite ụdị ML na data emechara"), dsp.Task ("model_deployment", "Tinye ụdị a zụrụ azụ na DSPy workflow"), ], )

Kọwaa onye nnọchi anya LangChain

onye nnọchi anya = onye nnọchi anya ( aha = "efficiency_agent", ụdị = "distilbert-base-uncased", Quick="Kedu ka m ga-esi welie pipeline maka ịrụ ọrụ ka mma?", )

Jikọta usoro ọrụ DSPy na onye nnọchi anya LangChain

workflow.add_agent (onye nnọchi anya)

Mepụta usoro ọrụ

workflow.run() ``

Top 5-10 Iwu/Snippets kacha eji

Nke a bụ ụfọdụ iwu na snippets ndị a na-ejikarị maka DSPy na LangChain:

DSPy

  1. `dsp.Workflow (aha = "my_workflow", ọrụ = [...])": Mepụta usoro DSPy ọhụrụ.
  2. dsp.Task (aha = "my_task", nkọwa = "My ọrụ") : Mepụta a ọhụrụ ọrụ na a DSPy workflow.
  3. `workflow.add_agent(agent): Tinye onye nnọchi anya LangChain na usoro ọrụ DSPy.
  4. `workflow.run()': Gbaa usoro ọrụ DSPy.
  5. `dsp.get_task_output(task):': Nweta mmepụta nke ọrụ na a DSPy workflow.

LangChain

  1. `Agent (aha = "my_agent", model = "distilbert-base-uncased", ozugbo = "My ozugbo")': Mepụta onye nnọchi anya LangChain ọhụrụ.
  2. `agent.respond(prompt="My Quick")': Nweta nzaghachi n'aka onye nnọchi anya LangChain.
  3. `agent.add_context(context="My context")': Tinye ihe gbara ya gburugburu na onye nnọchi anya LangChain.
  4. `agent.remove_context(context="My context")': Wepu ihe gbara ya gburugburu na onye nnọchi anya LangChain.
  5. agent.get_model(): Nweta ụdị ML n'okpuru nke onye nnọchite LangChain.

Nlere anya

Nke a bụ nleba anya nke usoro DSPy na LangChain na-eji Chart.js:

Json { "ụdị": "ogwe", "data": { "labels": ["Nnyocha ihe kpatara mgbọrọgwụ", "Njicha arụmọrụ"], "datasets": [ { "label": "Ọrụ ọrụ DSPy", "data": [10, 20], "backgroundColor": ["#4CAF50", "#FF9800"] }, { "label": "LangChain Agent", "data": [5, 15], "backgroundColor": ["#2196F3", "#009688"] } ] }, "Nhọrọ": { " aha": { "ngosi": eziokwu, "ederede": "DSPy na LangChain Workflow" }, "ọnụego": { "yAxes": [ { "akara aka": { "beginAtZero": eziokwu } } ] } } } ``

Ọhụụ a na-egosi ọnụọgụ ọrụ na usoro ọrụ DSPy ọ bụla yana ọnụọgụ nzaghachi sitere na onye nnọchi anya LangChain ọ bụla.

Mmechi

N'isiokwu a, anyị nyochara otu esi etinye DSPy na LangChain iji mejuputa ndị ọrụ AI na-akwado maka nyocha ihe kpatara mgbọrọgwụ na njikarịcha arụmọrụ na pipeline mmepe software. Anyị nyere ihe atụ koodu na nhụta anya iji gosi echiche ndị ahụ, anyị gosipụtara ụfọdụ iwu na snippets ndị a na-ejikarị eme ihe maka DSPy na LangChain. Site n'ịgbaso ntuziaka a, ndị mmepe nwere ike ịmepụta usoro ọrụ akpaaka nke AI kwadoro site na iji DSPy na LangChain.

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