Iji LangChain na StackGen na-ahazi mmepe sọftụwia AI kwadoro maka nyocha ihe mberede akpaaka. | B4N1

Iji LangChain na StackGen na-ahazi mmepe sọftụwia AI kwadoro maka nyocha ihe mberede akpaaka.

6 months ago · b4n1 Read time: 4 min

** Mmepe ngwanrọ AI kwadoro na LangChain na StackGen maka nyocha ihe mberede akpaaka ***

** Okwu mmalite**

Mbili nke ọgụgụ isi Artificial (AI) na akpaaka agbanweela odida mmepe ngwanrọ. Site na mgbagwoju anya nke usoro ngwanrọ ọgbara ọhụrụ, mkpa maka nyocha na mkpebi ihe mere eme nke ọma na nke dị irè aghọwo ihe dị mkpa karịa mgbe ọ bụla. N'isiokwu a, anyị ga-enyocha ike nke iji LangChain na StackGen, ngwá ọrụ egwu egwu abụọ dị ike, iji megharịa nchọpụta ihe merenụ na mkpebi site na iji AI-driven DevOps automation. Anyị ga-enyochakwa n'iji AWS DevOps Agent na Claude Agents, wee nyochaa ohere nke iji akpaaka AI kwadoro dochie otu DevOps.

** Gịnị bụ LangChain?**

LangChain bụ ihe mepere emepe, usoro Python dabere na iwulite ngwa ndị AI kwadoro. Ọ na-enye otu ngwaọrụ na ọba akwụkwọ maka nhazi asụsụ eke (NLP), mmụta igwe (ML), na sayensị data. LangChain na-enye ndị mmepe ohere ịmepụta ụdị AI omenala ma jikọta ha na isi mmalite data dị iche iche, na-eme ka ọ bụrụ nhọrọ dị mma maka ịmepụta pipeline DevOps automation AI.

Gịnị bụ StackGen?

StackGen bụ nwa afọ igwe ojii, ngwa mepere emepe maka iwulite na ijikwa akụrụngwa dịka koodu (IaC). Ọ na-enye syntax nkwupụta maka ịkọwapụta nhazi akụrụngwa ma na-emezi ntinye na njikwa nke akụrụngwa igwe ojii. StackGen na-ejikọta ya na LangChain n'enweghị nsogbu, na-enyere ndị mmepe aka ịmepụta pipeline IaC kwadoro AI nke na-akpaghị aka nyocha na mkpebi ihe merenụ.

** Iji LangChain na StackGen na-arụ ọrụ AI-Driven DevOps Automation**

Iji mejuputa automation DevOps nke AI na LangChain na StackGen, anyị kwesịrị ịgbaso usoro ndị a:

  1. ** Kọwaa ihe nlereanya AI ***: Iji LangChain, anyị na-akọwapụta ụdị AI omenala nke nwere ike nyochaa data merenụ ma chọpụta ihe ndị nwere ike ime.
  2. ** Jikọta na StackGen ***: Anyị na-ejikọta ihe nlereanya AI na StackGen, na-eme ka ọ rụọ ọrụ na ntinye na njikwa nke akụrụngwa igwe ojii.
  3. ** Hazie AWS DevOps Agent ***: Anyị na-ahazi AWS DevOps Agent ịnakọta data merenụ wee ziga ya na ụdị LangChain AI maka nyocha.
  4. ** Mepụta Claude Agent ***: Anyị na-emepụta Claude Agent, ụdị nke AI na-arụ ọrụ akpaaka nke nwere ike dochie ndị otu DevOps.

** Ọmụmaatụ koodu: LangChain AI Model ***

Nke a bụ ọmụmaatụ koodu dị mfe nke na-egosi otu esi emepụta ụdị LangChain AI maka nyocha ihe merenụ: "Python mbubata langchain si langchain.llms bubata LLM

ụdị = LLM aha = "ihe omume_analysis", ụdị = "ederede-davinci-003", max_length=2048, )

Kọwaa data ihe merenụ

Event_data = { "incident_id": "INC-001", "description": "Error 500 na mmepụta ihe nkesa", "timestamp": "2023-02-15 14:30:00", }

Nyochaa data ihe merenụ

nyocha = model.run ( Quick=f"Chọọ ihe merenụ {incident_data['incident_id']} nwere nkọwa {incident_data['nkọwa']}", )

Bipụta nyocha

ebipụta(analysis) `` Koodu a na-akọwapụta ụdị LangChain AI nke na-enyocha data merenụ ma na-enye nchịkọta nke ihe nwere ike ịkpata ya.

** Iwu 5-10 Kachasị Eji mee ihe

Nke a bụ iwu/snippets 5-10 kacha eji eme ihe maka LangChain na StackGen:

  1. `langchain llm': Ndepụta LLM dị (Ụdị Asụsụ buru ibu)
  2. langchain model: Akọwapụta a omenala AI nlereanya
  3. 'stackgen init': Na-ebute ọrụ StackGen ọhụrụ
  4. 'stackgen deploy': Na-ebuga nhazi akụrụngwa na igwe ojii
  5. `aws devops agent ịnakọta': Na-anakọta data merenụ wee ziga ya na ụdị LangChain AI.
  6. `langchain analyzer': Nyochaa data merenụ site na iji ụdị LangChain AI
  7. 'stackgen update': na-emelite nhazi akụrụngwa ma na-ebuga mgbanwe na igwe ojii
  8. `langchain n'ịwa': Na-ewepụta nchịkọta nyocha
  9. 'stackgen delete': na-ehichapụ nhazi akụrụngwa na akụrụngwa
  10. 'langchain ụgbọ oloko': Ọ na-azụ ụdị LangChain AI na data ọhụrụ

** Nlere anya: AI-Sriven DevOps Automation Pipeline**

Nke a bụ nleba anya nke pipeline akpaaka DevOps na-ebugharị site na iji Chart.js: chaatị { "ụdị": "dag", "data": { "ọnụ": [ { "id": "incident_data", "label": "Data ihe mberede", "x": 0, "y": 0 }, { "id": "langchain_model", "label": "Model LangChain AI", "x": 2, "y": 0 }, { "id": "stackgen_infra", "label": "Infrastructure StackGen", "x": 4, "y": 0 }, { "id": "aws_devops_agent", "label": "AWS DevOps Agent", "x": 6, "y": 0 }, { "id": "claudia_agent", "label": "Claude Agent", "x": 8, "y": 0 } ], "ọnụ": [ { "isi iyi": "incident_data", "target": "langchain_model", "label": "Nyochaa" }, { "isi iyi": "langchain_model", "target": "stackgen_infra", "label": "Bugharịa" }, { "isi iyi": "stackgen_infra", "target": "aws_devops_agent", "label": "Na-anakọta" }, { "source": "aws_devops_agent", "target": "claudia_agent", "label": "Kpebie" } ] } } Ọhụụ a na-egosi mgbaba data merenụ site na pipeline akpaaka DevOps na-anya AI, site na nyocha ruo na mkpebi.

Mkpebi

N'edemede a, anyị nyochara ikike nke iji LangChain na StackGen mebere nyocha na mkpebi ihe mere site na iji ngwa DevOps nke AI na-anya. Anyị nyochara ojiji nke AWS DevOps Agent na Claude Agents, wee tụlere ohere nke iji akpaaka AI kwadoro dochie otu DevOps. Site n'iji ngwá ọrụ na teknụzụ ndị a eme ihe, òtù dị iche iche nwere ike imeziwanye oge nzaghachi ihe omume, belata oge nkwụsị, ma welie ntụkwasị obi n'ozuzu ya.

** Ọrụ n'ọdịnihu ***

Ọrụ n'ọdịnihu na mpaghara a gụnyere:

  • Mepụta ụdị AI dị elu maka nyocha na mkpebi ihe merenụ
  • Ijikọ LangChain na StackGen na ngwaọrụ na nyiwe DevOps ndị ọzọ
  • Na-enyocha iji ndị ọrụ akpaaka AI na-akwado, dị ka Claude Agents
  • Na-eme nyocha ọzọ na arụmọrụ nke AI-chụpụrụ DevOps automation na ọnọdụ ụwa n'ezie.

Site n'ịga n'ihu na-emepe emepe na melite AI-driven DevOps automation, anyị nwere ike ịmepụta nke ọma, dị irè na usoro mmepe ngwanrọ nke na-erite uru ma òtù na ndị ọrụ njedebe.

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