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Model Inputs
Tokens Token IDs Embeddings Cosine similarity Context windows System and user messages Prompt delimiters Structured prompts
Generation Controls
Temperature Top-k sampling Top-p sampling Stop sequences Maximum output tokens Deterministic seeds Frequency penalties Streaming tokens
Grounding & Retrieval
Chunking documents Vector search Top-k retrieval Metadata filtering Prompt grounding Citation mapping Context packing Reranking results
Evaluation & Safety
Hallucination checks Prompt injection defense PII redaction Output schema validation Human review queues Golden test sets Latency measurement Token cost accounting
Generative AI / Grounding & Retrieval

Prompt grounding

Learn Prompt grounding in Generative AI with a focused explanation, a topic-specific example, and a mastery check.

12 min read • Intermediate
generative-ai-021.py
python 
context='Policy: refunds allowed within 14 days.'
question='Can I refund after 30 days?'
print(f'Use only this context: {context}\nQuestion: {question}')
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Original Syntaxis Content · Original Syntaxis Content

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Prompt grounding Mastery Check →
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Citation mapping