** Imeghe ZeroOps na AI Agents na Context Engineering: Ụzọ dabere na ụkpụrụ AI DevOps Automation site na iji StackGen na LangChain ***

** Okwu mmalite**

N'ọdịdị mmepe ngwa ngwa nke mmepe ngwanrọ, echiche nke ZeroOps apụtala dị ka ụzọ mgbanwe maka akpaaka DevOps. ZeroOps na-achọ ikpochapụ mkpa ntinye aka na ntinye aka na njikwa nke usoro ngwanrọ, na-enyere ndị mmepe aka ilekwasị anya na ọrụ dị elu dị ka ihe ọhụrụ na mmepụta ihe. N'isiokwu a, anyị ga-abanye n'ime ụwa nke ZeroOps ma chọpụta ka ndị ọrụ AI na ndị na-ahụ maka gburugburu ebe obibi nwere ike isi nweta ihe mgbaru ọsọ a. Anyị ga-atụlekwa mmejuputa usoro dabere na AI DevOps automation site na iji StackGen na LangChain.

Gịnị bụ ZeroOps?

ZeroOps bụ ụkpụrụ DevOps nke na-achọ imezi usoro ndụ mmepe ngwanrọ niile, site na mmepe ruo nbunye na njikwa. Ebumnuche bụ isi nke ZeroOps bụ ikpochapụ mkpa ntinye aka na ntinye aka na njikwa nke sistemụ ngwanrọ, si otú ahụ belata ohere nke njehie mmadụ na ịbawanye ọsọ na arụmọrụ nke nnyefe ngwanrọ.

** Ndị nnọchi anya AI na Injinia Context ***

Ndị ọrụ AI na injinia gburugburu na-arụ ọrụ dị oke mkpa na mmejuputa ZeroOps. Ndị ọrụ AI bụ mmemme ngwanrọ nwere ike ịghọta gburugburu ha wee mee ihe iji nweta ebumnuche akọwapụtara. N'aka nke ọzọ, injinịa ihe dị na ya gụnyere imepụta na itinye usoro nke nwere ike ịghọta na zaghachi ọnọdụ ebe ha na-arụ ọrụ.

N'ihe gbasara ZeroOps, ndị ọrụ AI nwere ike iji rụọ ọrụ dị iche iche dị ka ntinye, nnwale, na nlekota oru. Enwere ike iji injinia okwu wee chepụta usoro ndị nwere ike ịghọta ọnọdụ ha na-arụ, dị ka gburugburu ebe obibi, onye ọrụ, na ọrụ dị n'aka.

**StackGen: Ụzọ dabere na ụkpụrụ AI DevOps akpaaka ***

StackGen bụ usoro mepere emepe nke na-enyere ndị mmepe aka imejuputa usoro dabere na AI DevOps automation. StackGen na-enye usoro akọwapụtara nke ọma na ndebiri enwere ike iji rụọ ọrụ dị iche iche dị ka ntinye, nnwale na nleba anya.

Ewubere StackGen n'elu LangChain, usoro na-enyere ndị mmepe aka iwulite usoro AI mkparịta ụka. LangChain na-enye nhazi API na ngwa ọrụ enwere ike iji wulite usoro AI mkparịta ụka nke nwere ike ịghọta na ịzaghachi ntinye asụsụ eke.

** LangChain: Sistemụ AI na-akparịta ụka ***

LangChain bụ usoro na-enyere ndị mmepe aka iwulite usoro AI mkparịta ụka. LangChain na-enye nhazi API na ngwa ọrụ enwere ike iji wulite usoro AI mkparịta ụka nke nwere ike ịghọta na ịzaghachi ntinye asụsụ eke.

Ewubere LangChain n'elu ọtụtụ teknụzụ mepere emepe, gụnyere TensorFlow na PyTorch. LangChain na-enye nhazi API na ngwa ọrụ enwere ike iji wulite usoro AI mkparịta ụka nke nwere ike ịghọta na ịzaghachi ntinye asụsụ eke.

** Iji StackGen na LangChain na-eme ZeroOps ***

Iji mejuputa ZeroOps na StackGen na LangChain, anyị kwesịrị ịgbaso ọtụtụ usoro:

1. ** Kọwaa AI Agent ***: Nzọụkwụ mbụ n'imejuputa ZeroOps bụ ịkọwapụta onye ọrụ AI nke a ga-eji rụọ ọrụ dị iche iche. Enwere ike ịkọwa onye nnọchi anya AI site na iji ọtụtụ usoro akọwapụtara na ndebiri nke StackGen nyere.
2. ** Chepụta Engine Context ***: Nzọụkwụ ọzọ bụ ịmepụta engine nke a ga-eji ghọta na zaghachi ọnọdụ nke onye ọrụ AI na-arụ ọrụ. Enwere ike iji ọtụtụ API na ngwa ọrụ LangChain chepụta injin gburugburu.
3. ** Mejuputa AI Agent ***: Ozugbo a kọwapụtara onye na-ahụ maka AI na engine gburugburu, nzọụkwụ ọzọ bụ iji mejuputa AI na-eji ọtụtụ API na ngwaọrụ ndị StackGen na LangChain nyere.
4. ** Nnwale na Deploy ***: Nzọụkwụ ikpeazụ bụ iji nwalee ma tinye onye na-ahụ maka AI na mpaghara mmepụta ihe.

** Usoro ihe atụ: Iji StackGen na LangChain na-eme ihe nnọchi anya AI dị mfe.

Nke a bụ ngọngọ koodu ihe atụ nke na-egosi otu esi etinye onye ọrụ AI dị mfe site na iji StackGen na LangChain: "Python mbubata langchain si langchain.chains bubata LLMChain si langchain.llms bubata LLM

ai_agent = LLMChain( llm=LLM( model_name = "davinci: 3-ogbe", okpomọkụ = 0.5, max_tokens=100, ), input_format = "ederede", mmepụta_format = "ederede", )

Kọwaa injin gbara ya gburugburu

context_engine = langchain.ContextEngine( llm=LLM( model_name = "davinci: 3-ogbe", okpomọkụ = 0.5, max_tokens=100, ), input_format = "ederede", mmepụta_format = "ederede", )

Mejuputa onye nnọchi anya AI

ai_agent.implement( context_engine=context_engine, input_text="Ndewo, kedu ka ị mere?", )

Nwalee ma bufee onye nnọchi anya AI

ai_agent.test_and_deploy( input_text="Ndewo, kedu ka ị mere?", ) `` Ihe ngọngọ koodu a na-egosi otu esi emejuputa onye ọrụ AI dị mfe site na iji StackGen na LangChain. A kọwapụtara onye nnọchi anya AI site na iji ọtụtụ usoro akọwapụtara na ndebiri nke StackGen nyere. Ejiri ọtụtụ API na ngwaọrụ ndị LangChain nyere site n'ịmepụta injin gburugburu. A na-eji ọtụtụ API na ngwaọrụ ndị StackGen na LangChain na-enye mejuputa onye ọrụ AI. N'ikpeazụ, a na-anwale onye ọrụ AI ma tinye ya na gburugburu ebe mmepụta ihe.

** Iwu 5-10 Kachasị Eji mee ihe

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

1. `langchain.LLMChain()': Na-emepụta ihe yinye LLM ọhụrụ.
2. `langchain.ContextEngine()': Na-emepụta ihe njin gburugburu ọhụrụ.
3. LLM (model_name = "davinci: 3-batch", okpomọkụ = 0.5, max_tokens=100): Na-emepụta ihe ọhụrụ LLM nwere aha ihe atụ akọwapụtara, ọnọdụ okpomọkụ na akara kachasị elu.
4. ai_agent.implement(context_engine=context_engine, input_text= "Ndewo, kedu ka ị mere?"): Na-eji igwe ọnọdụ akọwapụtara na ntinye ederede na-arụ ọrụ nke AI.
5. `ai_agent.test_and_deploy(input_text = "Ndewo, kedu ka ị mere?")': Nwalee ma tinye ndị nnọchite AI site na iji ederede ntinye akọwapụtara.
6. `langchain.llms.LLM()': Na-emepụta ihe ọhụrụ LLM.
7. `langchain.chains.LLMChain()': Na-emepụta ihe yinye LLM ọhụrụ.
8. `langchain.ContextEngine(llm=LLM(model_name="davinci:3-batch", okpomọkụ=0.5,max_tokens=100))": Na-emepụta ihe njin ọhụrụ na-eji ihe akpọrọ LLM.
9. ai_agent.context_engine = langchain.ContextEngine(llm=LLM(model_name=«davinci:3-batch», okpomọkụ=0.5,max_tokens=100)): Na-edobe ihe njin onodu nke onye nnochite anya AI na ihe njin onodu a kapịrị ọnụ.
10. `ai_agent.input_text = "Ndewo, kedu ka ị mere?"': Na-edobe ederede ntinye nke onye nnọchite AI na ederede ntinye akọwapụtara.

** Nlegharị anya ***

Nke a bụ nleba anya nke ihe owuwu ZeroOps na-eji Chart.js: Json { "ụdị": "ogwe", "data": { "labels": ["AI Agent", "Context Engine", "StackGen", "LangChain"], "datasets": [ { "label": "Architecture", "data": [10, 8, 6, 4], "backgroundColor": ["#FF6384", "#36A2EB", "#FFCE56", "#4BC0C0"] } ] }, "Nhọrọ": { " aha": { "ngosi": eziokwu, "text": "Ihe owuwu ZeroOps" }, "akụkọ": { "ngosi": eziokwu }, "ọnụego": { "yAxes": [ { "akara aka": { "beginAtZero": eziokwu } } ] } } } `` Ọhụụ a na-egosi nhazi nke sistemu ZeroOps, gụnyere onye nnọchi anya AI, igwe okwu, StackGen, na LangChain.

Mkpebi

ZeroOps bụ usoro mgbanwe maka akpaaka DevOps nke na-achọ iwepụ mkpa ntinye aka na ntinye na njikwa nke sistemụ ngwanrọ. Ndị ọrụ AI na injinia gburugburu na-arụ ọrụ dị oke mkpa na mmejuputa ZeroOps, na StackGen na LangChain na-enye usoro dabere na AI DevOps automation. Site na iji StackGen na LangChain mejuputa onye ọrụ AI dị mfe, anyị nwere ike ịmegharị ọrụ dị iche iche dị ka ntinye, nnwale, na nlekota oru. A na-enyekwa iwu/snippets kacha 5-10 kacha eji maka StackGen na LangChain, yana nleba anya nke ihe owuwu ZeroOps site na iji Chart.js.