** Iji LangChain na DSPy na-eme Agentic AI na Automation Deterministic Test ***

** Okwu mmalite**

Mgbagwoju anya nke sistemu ngwanrọ emeela akpaaka nnwale ka ọ bụrụ akụkụ dị mkpa nke mmepe ngwanrọ. Usoro akpaaka ọdịnaala na-adabere na usoro ederede, nke nwere ike ịkagbu ma sie ike idowe. N'ime afọ ndị na-adịbeghị anya, mpụta nke Agentic AI na Orchestration Tools emeghela ohere ọhụrụ maka ịmegharị ọnọdụ ule dị mgbagwoju anya. N'isiokwu a, anyị ga-enyocha njikọ nke AI Agentic AI, Ngwá Ọrụ Orchestration, na Software Engineering iji megharịa ihe ngosi ule mgbagwoju anya site na iji LangChain na DSPy.

Gịnị bụ AI?

AI Agentic na-ezo aka n'ụdị ọgụgụ isi arụpụtara emebere iji mee ihe n'aha onye ọrụ ma ọ bụ sistemụ. Usoro AI nke AI nwere ike ime mkpebi, mụta ihe site na ahụmahụ, na ime mgbanwe n'ọnọdụ ọhụrụ. N'ihe gbasara akpaaka nnwale, Agentic AI nwere ike iji megharịa ọnọdụ nnwale dị mgbagwoju anya site na ịmekọrịta mmekọrịta ndị ọrụ, ịme mkpebi dabere na data nnwale, na ime mgbanwe na ọnọdụ nnwale.

** Gịnị bụ LangChain?**

LangChain bụ ngwá ọrụ Orchestration mepere emepe nke na-enye ndị mmepe ohere iwu usoro AI siri ike site na iji asụsụ mmemme dị iche iche, gụnyere Python, Rust, na Go. LangChain na-enye ihe owuwu na-agbanwe agbanwe na modular nke na-enyere ndị mmepe aka ijikọ akụkụ AI dị iche iche, dị ka nhazi asụsụ eke (NLP) na ọhụụ kọmputa, iji wuo usoro AI ọkaibe.

Gịnị bụ DSPy?

DSPy bụ ọba akwụkwọ Eke Ọgba nke na-enye otu ngwaọrụ maka iwulite na ibuga sistemụ AI. Emebere DSPy ka ya na LangChain na-arụ ọrụ n'enweghị nsogbu ma na-enye ọtụtụ atụmatụ, gụnyere nhazi data, mmụta igwe, na mmụta miri emi.

** Na-eme Agenttic AI na Automation Deterministic Test ***

Iji mejuputa Agentic AI na deterministic test automation, anyị nwere ike iji LangChain na DSPy iji wuo usoro nyocha akpaaka nke na-eme ka mmekọrịta ndị ọrụ na-emekọrịta ihe, na-eme mkpebi dabere na data ule, na-agbanwe agbanwe na ọnọdụ ule.

Nke a bụ ihe atụ dị mfe nke otu anyị nwere ike isi jiri LangChain na DSPy megharịa ọnọdụ nnwale: "Python mbubata langchain si langchain.chains bubata LLMChain si langchain.llms bubata DSPyLLM

test_scenario = { "user_input": "login", "expected_output": "nbanye nke ọma" }

Kọwaa onye nnọchi anya AI Agent

onye nnọchi anya = LLMChain ( llm=DSPyLLM(), input_type = "ederede", mmepụta_type = "ederede" )

Kọwaa ọrụ akpaaka nnwale

def test_automation(test_scenario): # Mekọrịta mmekọrịta onye ọrụ user_input = test_scenario["user_input"] # Mee mkpebi dabere na data nnwale mkpebi = agent.run(user_input) # Kwado na mgbanwe ọnọdụ ule ọ bụrụ na mkpebi == "nbanye aga nke ọma": ebipụta("Nnwale gafere") ọzọ: ebipụta("Nnwale dara")

Gbaa ọrụ akpaaka nnwale

test_automation(ule_nyocha) `` N'ihe atụ a, anyị na-akọwapụta ọnọdụ nlele nke gụnyere ịmekọrịta mmekọrịta onye ọrụ, ịme mkpebi dabere na data ule, na ime mgbanwe na ọnọdụ ule na-agbanwe. Anyị na-akọwapụta onye nnọchi anya AI Agent site na iji LangChain na DSPy, wee jiri ya megharịa ọnọdụ nnwale ahụ.

** Iwu 5-10 Kachasị Eji mee ihe

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

1. `langchain.LLMChain(llm=DSPyLLM())': Na-emepụta onye nnọchi anya AI Agent iji LangChain na DSPy.
2. DSPyLLM(): Na-amalite ihe atụ DSPy LLM (Large Language Model).
3. LLMChain (input_type = "ederede", mmepụta_type = "ederede"): Na-emepụta onye nnọchi anya AI na ntinye ederede na ụdị mmepụta.
4. agent.run(user_input): Na-eji ntinye onye ọrụ na-arụ ọrụ AI Agent.
5. test_scenario = {"user_input": "login", "expected_output": "nbanye na-aga nke ọma"}: Na-akọwa ọnọdụ nlele site na ntinye onye ọrụ na mmepụta a tụrụ anya ya.
6. `langchain.chains.LLMChain(llm=DSPyLLM())': Na-emepụta onye nnọchi anya AI site na iji LangChain na DSPy.
7. `DSPyLLM() amụma (user_input):': buru amụma mmepụta nke DSPy LLM na ntinye onye ọrụ.
8. LLMChain (input_type = "ederede", mmepụta_type = "ederede").run(user_input): Na-arụ ọrụ Agent AI na ntinye ederede na ụdị mmepụta.
9. test_automation(test_scenario): Na-eji ọnọdụ ule na-arụ ọrụ akpaaka nnwale.
10. langchain.chains.LLMChain(llm=DSPyLLM()) .gbaa(user_input): Na-eji ntinye onye ọrụ na-arụ ọrụ AI Agent.

** Nlegharị anya ***

Nke a bụ nleba anya nke onye nnọchi anya AI na-eji Chart.js: Json { "ụdị": "ogwe", "data": { "labels": ["Ntinye onye ọrụ", "Mkpebi", "Ndagharị"], "datasets": [ { "label": "Onye nnọchite anya AI", "data": [10, 20, 30], "backgroundColor": "rgba(255, 99, 132, 0.2)", "BorderColor": "rgba(255, 99, 132, 1)", "BorderWiidth": 1 } ] }, "Nhọrọ": { " aha": { "ngosi": eziokwu, "ederede": "Agent AI Agent" }, "ọnụego": { "yAxes": [ { "akara aka": { "beginAtZero": eziokwu } } ] } } } `` Ọhụụ a na-egosi arụmọrụ Agenttic AI na-arụ ọrụ na ịmekọrịta mmekọrịta ndị ọrụ, ime mkpebi dabere na data nnwale, yana ime mgbanwe n'ọnọdụ nnwale.

Mkpebi

N'isiokwu a, anyị nyochara njikọ nke AI Agentic AI, Ngwá Ọrụ Orchestration, na Software Engineering iji megharịa ihe ngosi ule mgbagwoju anya site na iji LangChain na DSPy. Anyị mebere ihe atụ dị mfe nke Agentic AI na akpaaka nnwale deterministic wee nye ọtụtụ iwu / snippets maka LangChain na DSPy. Anyị na-ahụkwa anya na arụmọrụ Agenttic AI na-arụ ọrụ site na iji Chart.js. Site n'iji Agentic AI na Ngwá Ọrụ Orchestration, ndị mmepe nwere ike wulite usoro akpaaka nnwale ọkaibe nke na-eme ka mmekọrịta ndị ọrụ na-emekọrịta ihe, na-eme mkpebi dabere na data nnwale, na ime mgbanwe na ọnọdụ ule na-agbanwe.