Verify the vector database

Verify that you created a vector database of your documentation.

Procedure

  1. Run the following command: 
    ls -lR output
    The tool generates an image archive (.tar), which contains the vector database files and metadata. The following shows the structure of the output directory: 
    output
├── rag-content-output-latest.tar
└── vector_db 
    ├── faiss_store.db 
    └── llama-stack.yaml
    In the example above:
    • rag-content-output-latest.taris the generated image archive.
    • faiss_store.dbis the vector database file.
    • llama-stack.yamlis the Llama Stack configuration file.
  2. Verify that you get the expected results by querying the generated vector database using the following command: 
    podman run --rm \ 
    -u 0 \ 
    -v "$(pwd)/output/vector_db:/vector_db:Z" \
registry.redhat.io/lightspeed-core/rag-tool-rhel9:v0.5-latest 
\python scripts/query_rag.py \ 
   -p /vector_db \ 
   -x index \ -m embeddings_model \ 
   -k 5 \ 
   -q "Prerequisites for installation"
    In the example above:
    • -k tells the AI tool to find the five most relevant matches from your documentation.
    • -q is your prompt; change the string according to your requirements.

    The command displays the top five query results, along with the scores. Verify that the results are expected.