Run these end-to-end examples to see how you can generate vector embeddings, both within and outside the database.

• Generate Embeddings
  In these examples, you can see how to use the VECTOR_EMBEDDING SQL function or the UTL_TO_EMBEDDING PL/SQL function to generate a vector embedding from input text strings and images.
• Perform Chunking With Embedding
  In these examples, you can see how to explore the VECTOR_CHUNKS SQL function along with chainable utility PL/SQL functions to split large textual extracts and documents into chunks and then represent each chunk as a vector embedding.
• Configure Chunking Parameters
  Oracle AI Vector Search provides many parameters for chunking text data, such as SPLIT [BY], OVERLAP, or NORMALIZE. In these examples, you can see how to configure these parameters to define your own chunking specifications and strategies, so that you can create meaningful chunks.