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1Z0-1127-25 Practice Question: Building LLM Applications with RAG and Vector Search

A company is using OCI Generative AI for a RAG-based code assistant. They index source code repositories into a vector store. Developers report that the assistant often suggests deprecated APIs or outdated code snippets, even though the latest code is in the repository. The index was built a week ago and has not been updated. They plan to set up incremental updates. However, they notice that even after re-indexing the latest commits, the issue persists. What is the most likely oversight?

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

The vector store is not configured to overwrite existing vectors for updated documents.

If the vector store does not overwrite or update vectors for changed documents, old vectors remain, causing retrieval of outdated code. Option B (chunking at function boundaries) may cause missing imports but not specifically deprecation. Option C (embedding model not fine-tuned on code) might affect quality but not freshness. Option D (low top-k) would affect recall, not freshness.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • The vector store is not configured to overwrite existing vectors for updated documents.

    Why this is correct

    Without overwrite, old vectors persist even after re-indexing, causing retrieval of outdated code.

  • The retrieval top-k is set too low, missing some relevant snippets.

    Why it's wrong here

    Top-k affects recall but does not cause retrieval of outdated over current code.

  • The chunking strategy splits code at function boundaries, losing import statements.

    Why it's wrong here

    This affects code completeness but not the freshness of the retrieved snippets.

  • The embedding model is not fine-tuned on code; it was trained on natural language.

    Why it's wrong here

    Model quality affects relevance but not whether outdated code is still present.

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