[memory refactor][5/n] Migrate all vector_io providers (#835)

See https://github.com/meta-llama/llama-stack/issues/827 for the broader
design.

This PR finishes off all the stragglers and migrates everything to the
new naming.

llama_stack/templates/nvidia/build.yaml

@@ -4,7 +4,7 @@ distribution_spec:
   providers:
     inference:
     - remote::nvidia
-    memory:
+    vector_io:
     - inline::faiss
     safety:
     - inline::llama-guard

llama_stack/templates/nvidia/nvidia.py

@@ -17,7 +17,7 @@ from llama_stack.templates.template import DistributionTemplate, RunConfigSettin
 def get_distribution_template() -> DistributionTemplate:
     providers = {
         "inference": ["remote::nvidia"],
-        "memory": ["inline::faiss"],
+        "vector_io": ["inline::faiss"],
         "safety": ["inline::llama-guard"],
         "agents": ["inline::meta-reference"],
         "telemetry": ["inline::meta-reference"],

llama_stack/templates/nvidia/run.yaml

@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: nvidia
@@ -17,7 +17,7 @@ providers:
     config:
       url: https://integrate.api.nvidia.com
       api_key: ${env.NVIDIA_API_KEY}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -136,7 +136,7 @@ models:
   provider_model_id: meta/llama-3.2-90b-vision-instruct
   model_type: llm
 shields: []
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []