Anan ga hangen nesa na wakilin AI ta amfani da Chart.js: Json { "type": "bar", "data": { "labels": ["Input User", "Decision", "Adaptation"], "datasets": [ { "label": "Wakilin AI", "bayanai": [10, 20, 30], "backgroundColor": "rgba(255, 99, 132, 0.2)", "BorderColor": "rgba(255, 99, 132, 1)", "BorderWidth": 1 } ] }, "zaɓi": { "take": { "nuna": gaskiya, "text": "Agent AI Agent" }, "ma'auni": { "yAxes": [ { "zama": { "beginAtZero": gaskiya } } ] } } }
Wannan hangen nesa yana nuna aikin wakilin AI na Agent a cikin simintin hulɗar masu amfani, yanke shawara dangane da bayanan gwaji, da daidaitawa ga canza yanayin gwaji.
**Kammalawa**
A cikin wannan labarin, mun binciko haɗin gwiwar Agentic AI, Kayan aikin Orchestration, da Injiniya na Software don sarrafa hadaddun yanayin gwaji ta amfani da LangChain da DSPy. Mun aiwatar da misali mai sauƙi na AI Agentic a cikin ƙirar gwajin ƙididdigewa kuma mun samar da kewayon umarni / snippets don LangChain da DSPy. Mun kuma hango aikin wakilin AI na Agent ta amfani da Chart.js. Ta hanyar amfani da AI da Kayayyakin Orchestration, masu haɓakawa za su iya gina ingantattun tsarin sarrafa kansa na gwaji waɗanda ke kwaikwaya mu'amalar mai amfani, yanke shawara dangane da bayanan gwaji, da daidaitawa ga canza yanayin gwaji.