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Exam details
An LLM application combines a language model with product logic, data, tools, prompts, and user experience to solve a specific workflow.
RAG retrieves relevant external documents and adds them to model context so answers can use fresh or private knowledge.
Grounding ties model output to provided sources, records, or tool results, reducing hallucinations and making answers easier to verify.
Prompt injection is an attack where untrusted content tries to override instructions, reveal secrets, or force unintended actions.
Tool calling lets an LLM request structured actions such as database queries, web searches, calculations, or file edits instead of only producing text.