1Z0-1127-25 OCI Generative AI Service Practice Question
A developer needs to generate embeddings for a set of search queries to be used in a semantic search system. Which input type should they specify when calling the Embedding API?
⚠ Common exam trap
Many candidates confuse 'search_query' with 'search_document' or assume a generic input type like 'clustering' or 'classification' is valid, not realizing that the Embedding API explicitly distinguishes between query and document embeddings for optimal semantic search performance.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
search_query
The Embedding API in OCI Generative AI requires specifying the input type as 'search_query' when generating embeddings for search queries in a semantic search system. This input type optimizes the embedding model to produce vectors that are specifically tuned for query-side representation, ensuring better alignment with document embeddings during similarity search.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
clustering
Why it's wrong here
This is for clustering tasks.
- ✗
search_document
Why it's wrong here
This is for longer documents to be indexed.
- ✗
classification
Why it's wrong here
This is for classification tasks.
- ✓
search_query
Why this is correct
This is optimized for short queries in search.
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