Oracle AI Vector Search supports both in-database embedding generation and external embedding providers , making A the correct answer. The supplied question source identifies the same combination.

For in-database processing, Oracle AI Database includes an ONNX runtime. Compatible ONNX embedding models can be imported as database objects and invoked directly through SQL using functions such as VECTOR_EMBEDDING . This allows vectorization to occur without moving source data outside the database.

Oracle also supports REST-based embedding generation. DBMS_VECTOR.UTL_TO_EMBEDDING and related APIs can call external or local providers. Officially documented providers include OCI Generative AI, Cohere, OpenAI, Google AI, Hugging Face, Vertex AI, Mistral, Ollama, and Private AI, depending on the operation and configuration.

Manual Python export/import workflows are technically possible in custom architectures, but they are not the supported approaches being tested. Option C is explicitly false because Oracle supports in-database ONNX inference.

Therefore, A correctly captures Oracle's native and external embedding-generation strategies.

Study Guide reference/topic: Agentic AI for Oracle AI Database — ONNX Runtime, VECTOR_EMBEDDING, DBMS_VECTOR, REST embedding providers, and AI Vector Search.

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