First Move (11~18) - Code, Learn, Build
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First Move (11~18) - Code, Learn, Build

Structured, level-based technology learning paths from foundational exploration to industry mastery.

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  • Python Programming (Active)
  • Computer Science Core
  • Web Development
  • AI & Machine Learning

Platform Architecture

  • Level-Based Progression
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  • Curated Official Resources

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← Generative AI & LLM Agents|Level 3: Autonomous Multi-Agent Systems & Evaluation

6. LLM Evaluation (RAGAS / G-Eval) & Safety Guardrails

Lesson 6 of 6
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LLM Evaluation (RAGAS / G-Eval) & Safety Guardrails

Measure Faithfulness, Context Precision, Answer Relevance, and enforce input/output security guardrails against prompt injections.

LLM Evaluation Metrics & Guardrails

### RAG Triad Evaluation Metrics - **Faithfulness**: Measures whether answer facts are strictly grounded in retrieved context (detects hallucinations). - **Answer Relevance**: Measures how directly the generated answer addresses user query goals. - **Context Precision**: Measures the signal-to-noise ratio of retrieved vector passages.
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