docs: Fix incorrect vector_db_id usage in RAG tutorial (#3444)

# What does this PR do?
This PR fixes a blocking issue in the detailed RAG tutorial where the
code fails with a 400 Bad Request error.

The root cause is that recent versions of Llama-Stack ignore the
client-generated vector_db_id and assign a new server-side ID. The
tutorial was not updated to reflect this, causing the rag_tool.insert
call to fail.

This change updates the code to capture the authoritative ID from the
.identifier attribute of the register() method's response. This ensures
the tutorial code runs successfully and reflects the current API
behavior.

## Test Plan
The fix can be verified by running the Python code snippet from the
detailed tutorial page.

Run the original code (Before this change):

Result: The script fails with a 400 Bad Request error on the
rag_tool.insert step.

Run the updated code (After this change):

Result: The script runs successfully to completion.

Co-authored-by: Adam Young <[email protected]>

Author: adam-d-young

docs/source/getting_started/detailed_tutorial.md

@@ -460,10 +460,12 @@ client = LlamaStackClient(base_url="http://localhost:8321")
 embed_lm = next(m for m in client.models.list() if m.model_type == "embedding")
 embedding_model = embed_lm.identifier
 vector_db_id = f"v{uuid.uuid4().hex}"
-client.vector_dbs.register(
+# The VectorDB API is deprecated; the server now returns its own authoritative ID.
+# We capture the correct ID from the response's .identifier attribute.
+vector_db_id = client.vector_dbs.register(
     vector_db_id=vector_db_id,
     embedding_model=embedding_model,
-)
+).identifier
 
 # Create Documents
 urls = [