Update templates

docs/source/distributions/remote_hosted_distro/nvidia.md

@@ -8,11 +8,11 @@ The `llamastack/distribution-nvidia` distribution consists of the following prov
 | datasetio | `remote::huggingface`, `inline::localfs` |
 | eval | `inline::meta-reference` |
 | inference | `remote::nvidia` |
-| memory | `inline::faiss` |
 | safety | `inline::llama-guard` |
 | scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
 | telemetry | `inline::meta-reference` |
 | tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime`, `remote::model-context-protocol` |
+| vector_io | `inline::faiss` |
 
 
 ### Environment Variables

docs/source/distributions/self_hosted_distro/bedrock.md

@@ -15,11 +15,11 @@ The `llamastack/distribution-bedrock` distribution consists of the following pro
 | datasetio | `remote::huggingface`, `inline::localfs` |
 | eval | `inline::meta-reference` |
 | inference | `remote::bedrock` |
-| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 | safety | `remote::bedrock` |
 | scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
 | telemetry | `inline::meta-reference` |
 | tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime`, `remote::model-context-protocol` |
+| vector_io | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 
 
 

docs/source/distributions/self_hosted_distro/cerebras.md

@@ -8,11 +8,11 @@ The `llamastack/distribution-cerebras` distribution consists of the following pr
 | datasetio | `remote::huggingface`, `inline::localfs` |
 | eval | `inline::meta-reference` |
 | inference | `remote::cerebras` |
-| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 | safety | `inline::llama-guard` |
 | scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
 | telemetry | `inline::meta-reference` |
 | tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime` |
+| vector_io | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 
 
 ### Environment Variables

docs/source/distributions/self_hosted_distro/fireworks.md

@@ -18,11 +18,11 @@ The `llamastack/distribution-fireworks` distribution consists of the following p
 | datasetio | `remote::huggingface`, `inline::localfs` |
 | eval | `inline::meta-reference` |
 | inference | `remote::fireworks` |
-| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 | safety | `inline::llama-guard` |
 | scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
 | telemetry | `inline::meta-reference` |
 | tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime`, `remote::model-context-protocol` |
+| vector_io | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 
 
 ### Environment Variables

docs/source/distributions/self_hosted_distro/meta-reference-gpu.md

@@ -18,11 +18,11 @@ The `llamastack/distribution-meta-reference-gpu` distribution consists of the fo
 | datasetio | `remote::huggingface`, `inline::localfs` |
 | eval | `inline::meta-reference` |
 | inference | `inline::meta-reference` |
-| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 | safety | `inline::llama-guard` |
 | scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
 | telemetry | `inline::meta-reference` |
 | tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime`, `remote::model-context-protocol` |
+| vector_io | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 
 
 Note that you need access to nvidia GPUs to run this distribution. This distribution is not compatible with CPU-only machines or machines with AMD GPUs.

docs/source/distributions/self_hosted_distro/meta-reference-quantized-gpu.md

@@ -18,11 +18,11 @@ The `llamastack/distribution-meta-reference-quantized-gpu` distribution consists
 | datasetio | `remote::huggingface`, `inline::localfs` |
 | eval | `inline::meta-reference` |
 | inference | `inline::meta-reference-quantized` |
-| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 | safety | `inline::llama-guard` |
 | scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
 | telemetry | `inline::meta-reference` |
 | tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime`, `remote::model-context-protocol` |
+| vector_io | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 
 
 The only difference vs. the `meta-reference-gpu` distribution is that it has support for more efficient inference -- with fp8, int4 quantization, etc.

docs/source/distributions/self_hosted_distro/ollama.md

@@ -18,11 +18,11 @@ The `llamastack/distribution-ollama` distribution consists of the following prov
 | datasetio | `remote::huggingface`, `inline::localfs` |
 | eval | `inline::meta-reference` |
 | inference | `remote::ollama` |
-| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 | safety | `inline::llama-guard` |
 | scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
 | telemetry | `inline::meta-reference` |
 | tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime` |
+| vector_io | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 
 
 You should use this distribution if you have a regular desktop machine without very powerful GPUs. Of course, if you have powerful GPUs, you can still continue using this distribution since Ollama supports GPU acceleration.### Environment Variables

docs/source/distributions/self_hosted_distro/remote-vllm.md

@@ -17,11 +17,11 @@ The `llamastack/distribution-remote-vllm` distribution consists of the following
 | datasetio | `remote::huggingface`, `inline::localfs` |
 | eval | `inline::meta-reference` |
 | inference | `remote::vllm` |
-| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 | safety | `inline::llama-guard` |
 | scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
 | telemetry | `inline::meta-reference` |
 | tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime`, `remote::model-context-protocol` |
+| vector_io | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 
 
 You can use this distribution if you have GPUs and want to run an independent vLLM server container for running inference.

docs/source/distributions/self_hosted_distro/tgi.md

@@ -19,11 +19,11 @@ The `llamastack/distribution-tgi` distribution consists of the following provide
 | datasetio | `remote::huggingface`, `inline::localfs` |
 | eval | `inline::meta-reference` |
 | inference | `remote::tgi` |
-| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 | safety | `inline::llama-guard` |
 | scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
 | telemetry | `inline::meta-reference` |
 | tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime`, `remote::model-context-protocol` |
+| vector_io | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 
 
 You can use this distribution if you have GPUs and want to run an independent TGI server container for running inference.

docs/source/distributions/self_hosted_distro/together.md

@@ -18,11 +18,11 @@ The `llamastack/distribution-together` distribution consists of the following pr
 | datasetio | `remote::huggingface`, `inline::localfs` |
 | eval | `inline::meta-reference` |
 | inference | `remote::together` |
-| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 | safety | `inline::llama-guard` |
 | scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
 | telemetry | `inline::meta-reference` |
 | tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime`, `remote::model-context-protocol` |
+| vector_io | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 
 
 ### Environment Variables

llama_stack/apis/agents/agents.py

@@ -88,7 +88,7 @@ class MemoryRetrievalStep(StepCommon):
     step_type: Literal[StepType.memory_retrieval.value] = (
         StepType.memory_retrieval.value
     )
-    memory_bank_ids: List[str]
+    vector_db_ids: str
     inserted_context: InterleavedContent
 
 

llama_stack/apis/agents/event_logger.py

@@ -208,7 +208,7 @@ class EventLogger:
             ):
                 details = event.payload.step_details
                 inserted_context = interleaved_content_as_str(details.inserted_context)
-                content = f"fetched {len(inserted_context)} bytes from {details.memory_bank_ids}"
+                content = f"fetched {len(inserted_context)} bytes from {details.vector_db_ids}"
 
                 yield (
                     event,

llama_stack/apis/resource.py

@@ -37,5 +37,5 @@ class Resource(BaseModel):
     provider_id: str = Field(description="ID of the provider that owns this resource")
 
     type: ResourceType = Field(
-        description="Type of resource (e.g. 'model', 'shield', 'memory_bank', etc.)"
+        description="Type of resource (e.g. 'model', 'shield', 'vector_db', etc.)"
     )

llama_stack/distribution/store/tests/test_registry.py

@@ -9,7 +9,7 @@ import os
 import pytest
 import pytest_asyncio
 from llama_stack.apis.inference import Model
-from llama_stack.apis.memory_banks import VectorMemoryBank
+from llama_stack.apis.vector_dbs import VectorDB
 
 from llama_stack.distribution.store.registry import (
     CachedDiskDistributionRegistry,
@@ -42,13 +42,12 @@ async def cached_registry(config):
 
 
 @pytest.fixture
-def sample_bank():
+def sample_vector_db():
-    return VectorMemoryBank(
+    return VectorDB(
-        identifier="test_bank",
+        identifier="test_vector_db",
         embedding_model="all-MiniLM-L6-v2",
-        chunk_size_in_tokens=512,
+        embedding_dimension=384,
-        overlap_size_in_tokens=64,
+        provider_resource_id="test_vector_db",
-        provider_resource_id="test_bank",
         provider_id="test-provider",
     )
 
@@ -70,19 +69,17 @@ async def test_registry_initialization(registry):
 
 
 @pytest.mark.asyncio
-async def test_basic_registration(registry, sample_bank, sample_model):
+async def test_basic_registration(registry, sample_vector_db, sample_model):
-    print(f"Registering {sample_bank}")
+    print(f"Registering {sample_vector_db}")
-    await registry.register(sample_bank)
+    await registry.register(sample_vector_db)
     print(f"Registering {sample_model}")
     await registry.register(sample_model)
-    print("Getting bank")
+    print("Getting vector_db")
-    result_bank = await registry.get("memory_bank", "test_bank")
+    result_vector_db = await registry.get("vector_db", "test_vector_db")
-    assert result_bank is not None
+    assert result_vector_db is not None
-    assert result_bank.identifier == sample_bank.identifier
+    assert result_vector_db.identifier == sample_vector_db.identifier
-    assert result_bank.embedding_model == sample_bank.embedding_model
+    assert result_vector_db.embedding_model == sample_vector_db.embedding_model
-    assert result_bank.chunk_size_in_tokens == sample_bank.chunk_size_in_tokens
+    assert result_vector_db.provider_id == sample_vector_db.provider_id
-    assert result_bank.overlap_size_in_tokens == sample_bank.overlap_size_in_tokens
-    assert result_bank.provider_id == sample_bank.provider_id
 
     result_model = await registry.get("model", "test_model")
     assert result_model is not None
@@ -91,24 +88,23 @@ async def test_basic_registration(registry, sample_bank, sample_model):
 
 
 @pytest.mark.asyncio
-async def test_cached_registry_initialization(config, sample_bank, sample_model):
+async def test_cached_registry_initialization(config, sample_vector_db, sample_model):
     # First populate the disk registry
     disk_registry = DiskDistributionRegistry(await kvstore_impl(config))
     await disk_registry.initialize()
-    await disk_registry.register(sample_bank)
+    await disk_registry.register(sample_vector_db)
     await disk_registry.register(sample_model)
 
     # Test cached version loads from disk
     cached_registry = CachedDiskDistributionRegistry(await kvstore_impl(config))
     await cached_registry.initialize()
 
-    result_bank = await cached_registry.get("memory_bank", "test_bank")
+    result_vector_db = await cached_registry.get("vector_db", "test_vector_db")
-    assert result_bank is not None
+    assert result_vector_db is not None
-    assert result_bank.identifier == sample_bank.identifier
+    assert result_vector_db.identifier == sample_vector_db.identifier
-    assert result_bank.embedding_model == sample_bank.embedding_model
+    assert result_vector_db.embedding_model == sample_vector_db.embedding_model
-    assert result_bank.chunk_size_in_tokens == sample_bank.chunk_size_in_tokens
+    assert result_vector_db.embedding_dimension == sample_vector_db.embedding_dimension
-    assert result_bank.overlap_size_in_tokens == sample_bank.overlap_size_in_tokens
+    assert result_vector_db.provider_id == sample_vector_db.provider_id
-    assert result_bank.provider_id == sample_bank.provider_id
 
 
 @pytest.mark.asyncio
@@ -116,29 +112,28 @@ async def test_cached_registry_updates(config):
     cached_registry = CachedDiskDistributionRegistry(await kvstore_impl(config))
     await cached_registry.initialize()
 
-    new_bank = VectorMemoryBank(
+    new_vector_db = VectorDB(
-        identifier="test_bank_2",
+        identifier="test_vector_db_2",
         embedding_model="all-MiniLM-L6-v2",
-        chunk_size_in_tokens=256,
+        embedding_dimension=384,
-        overlap_size_in_tokens=32,
+        provider_resource_id="test_vector_db_2",
-        provider_resource_id="test_bank_2",
         provider_id="baz",
     )
-    await cached_registry.register(new_bank)
+    await cached_registry.register(new_vector_db)
 
     # Verify in cache
-    result_bank = await cached_registry.get("memory_bank", "test_bank_2")
+    result_vector_db = await cached_registry.get("vector_db", "test_vector_db_2")
-    assert result_bank is not None
+    assert result_vector_db is not None
-    assert result_bank.identifier == new_bank.identifier
+    assert result_vector_db.identifier == new_vector_db.identifier
-    assert result_bank.provider_id == new_bank.provider_id
+    assert result_vector_db.provider_id == new_vector_db.provider_id
 
     # Verify persisted to disk
     new_registry = DiskDistributionRegistry(await kvstore_impl(config))
     await new_registry.initialize()
-    result_bank = await new_registry.get("memory_bank", "test_bank_2")
+    result_vector_db = await new_registry.get("vector_db", "test_vector_db_2")
-    assert result_bank is not None
+    assert result_vector_db is not None
-    assert result_bank.identifier == new_bank.identifier
+    assert result_vector_db.identifier == new_vector_db.identifier
-    assert result_bank.provider_id == new_bank.provider_id
+    assert result_vector_db.provider_id == new_vector_db.provider_id
 
 
 @pytest.mark.asyncio
@@ -146,30 +141,28 @@ async def test_duplicate_provider_registration(config):
     cached_registry = CachedDiskDistributionRegistry(await kvstore_impl(config))
     await cached_registry.initialize()
 
-    original_bank = VectorMemoryBank(
+    original_vector_db = VectorDB(
-        identifier="test_bank_2",
+        identifier="test_vector_db_2",
         embedding_model="all-MiniLM-L6-v2",
-        chunk_size_in_tokens=256,
+        embedding_dimension=384,
-        overlap_size_in_tokens=32,
+        provider_resource_id="test_vector_db_2",
-        provider_resource_id="test_bank_2",
         provider_id="baz",
     )
-    await cached_registry.register(original_bank)
+    await cached_registry.register(original_vector_db)
 
-    duplicate_bank = VectorMemoryBank(
+    duplicate_vector_db = VectorDB(
-        identifier="test_bank_2",
+        identifier="test_vector_db_2",
         embedding_model="different-model",
-        chunk_size_in_tokens=128,
+        embedding_dimension=384,
-        overlap_size_in_tokens=16,
+        provider_resource_id="test_vector_db_2",
-        provider_resource_id="test_bank_2",
         provider_id="baz",  # Same provider_id
     )
-    await cached_registry.register(duplicate_bank)
+    await cached_registry.register(duplicate_vector_db)
 
-    result = await cached_registry.get("memory_bank", "test_bank_2")
+    result = await cached_registry.get("vector_db", "test_vector_db_2")
     assert result is not None
     assert (
-        result.embedding_model == original_bank.embedding_model
+        result.embedding_model == original_vector_db.embedding_model
     )  # Original values preserved
 
 
@@ -179,36 +172,35 @@ async def test_get_all_objects(config):
     await cached_registry.initialize()
 
     # Create multiple test banks
-    test_banks = [
+    test_vector_dbs = [
-        VectorMemoryBank(
+        VectorDB(
-            identifier=f"test_bank_{i}",
+            identifier=f"test_vector_db_{i}",
             embedding_model="all-MiniLM-L6-v2",
-            chunk_size_in_tokens=256,
+            embedding_dimension=384,
-            overlap_size_in_tokens=32,
+            provider_resource_id=f"test_vector_db_{i}",
-            provider_resource_id=f"test_bank_{i}",
             provider_id=f"provider_{i}",
         )
         for i in range(3)
     ]
 
-    # Register all banks
+    # Register all vector_dbs
-    for bank in test_banks:
+    for vector_db in test_vector_dbs:
-        await cached_registry.register(bank)
+        await cached_registry.register(vector_db)
 
     # Test get_all retrieval
     all_results = await cached_registry.get_all()
     assert len(all_results) == 3
 
-    # Verify each bank was stored correctly
+    # Verify each vector_db was stored correctly
-    for original_bank in test_banks:
+    for original_vector_db in test_vector_dbs:
-        matching_banks = [
+        matching_vector_dbs = [
-            b for b in all_results if b.identifier == original_bank.identifier
+            v for v in all_results if v.identifier == original_vector_db.identifier
         ]
-        assert len(matching_banks) == 1
+        assert len(matching_vector_dbs) == 1
-        stored_bank = matching_banks[0]
+        stored_vector_db = matching_vector_dbs[0]
-        assert stored_bank.embedding_model == original_bank.embedding_model
+        assert stored_vector_db.embedding_model == original_vector_db.embedding_model
-        assert stored_bank.provider_id == original_bank.provider_id
+        assert stored_vector_db.provider_id == original_vector_db.provider_id
-        assert stored_bank.chunk_size_in_tokens == original_bank.chunk_size_in_tokens
         assert (
-            stored_bank.overlap_size_in_tokens == original_bank.overlap_size_in_tokens
+            stored_vector_db.embedding_dimension
+            == original_vector_db.embedding_dimension
         )

llama_stack/distribution/ui/page/distribution/memory_banks.py

@@ -1,23 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the terms described in the LICENSE file in
-# the root directory of this source tree.
-
-import streamlit as st
-from modules.api import llama_stack_api
-
-
-def memory_banks():
-    st.header("Memory Banks")
-    memory_banks_info = {
-        m.identifier: m.to_dict() for m in llama_stack_api.client.memory_banks.list()
-    }
-
-    if len(memory_banks_info) > 0:
-        selected_memory_bank = st.selectbox(
-            "Select a memory bank", list(memory_banks_info.keys())
-        )
-        st.json(memory_banks_info[selected_memory_bank])
-    else:
-        st.info("No memory banks found")

llama_stack/distribution/ui/page/distribution/resources.py

@@ -6,10 +6,10 @@
 
 from page.distribution.datasets import datasets
 from page.distribution.eval_tasks import eval_tasks
-from page.distribution.memory_banks import memory_banks
 from page.distribution.models import models
 from page.distribution.scoring_functions import scoring_functions
 from page.distribution.shields import shields
+from page.distribution.vector_dbs import vector_dbs
 
 from streamlit_option_menu import option_menu
 
@@ -17,7 +17,7 @@ from streamlit_option_menu import option_menu
 def resources_page():
     options = [
         "Models",
-        "Memory Banks",
+        "Vector Databases",
         "Shields",
         "Scoring Functions",
         "Datasets",
@@ -37,8 +37,8 @@ def resources_page():
     )
     if selected_resource == "Eval Tasks":
         eval_tasks()
-    elif selected_resource == "Memory Banks":
+    elif selected_resource == "Vector Databases":
-        memory_banks()
+        vector_dbs()
     elif selected_resource == "Datasets":
         datasets()
     elif selected_resource == "Models":

llama_stack/distribution/ui/page/distribution/vector_dbs.py

@@ -0,0 +1,23 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+import streamlit as st
+from modules.api import llama_stack_api
+
+
+def vector_dbs():
+    st.header("Vector Databases")
+    vector_dbs_info = {
+        v.identifier: v.to_dict() for v in llama_stack_api.client.vector_dbs.list()
+    }
+
+    if len(vector_dbs_info) > 0:
+        selected_vector_db = st.selectbox(
+            "Select a vector database", list(vector_dbs_info.keys())
+        )
+        st.json(vector_dbs_info[selected_vector_db])
+    else:
+        st.info("No vector databases found")

llama_stack/distribution/ui/page/playground/rag.py

@@ -29,12 +29,12 @@ def rag_chat_page():
         if uploaded_files:
             st.success(f"Successfully uploaded {len(uploaded_files)} files")
             # Add memory bank name input field
-            memory_bank_name = st.text_input(
+            vector_db_name = st.text_input(
-                "Memory Bank Name",
+                "Vector Database Name",
-                value="rag_bank",
+                value="rag_vector_db",
-                help="Enter a unique identifier for this memory bank",
+                help="Enter a unique identifier for this vector database",
             )
-            if st.button("Create Memory Bank"):
+            if st.button("Create Vector Database"):
                 documents = [
                     Document(
                         document_id=uploaded_file.name,
@@ -44,37 +44,33 @@ def rag_chat_page():
                 ]
 
                 providers = llama_stack_api.client.providers.list()
-                memory_provider = None
+                vector_io_provider = None
 
                 for x in providers:
-                    if x.api == "memory":
+                    if x.api == "vector_io":
-                        memory_provider = x.provider_id
+                        vector_io_provider = x.provider_id
 
-                llama_stack_api.client.memory_banks.register(
+                llama_stack_api.client.vector_dbs.register(
-                    memory_bank_id=memory_bank_name,  # Use the user-provided name
+                    vector_db_id=vector_db_name,  # Use the user-provided name
-                    params={
+                    embedding_dimension=384,
-                        "memory_bank_type": "vector",
+                    embedding_model="all-MiniLM-L6-v2",
-                        "embedding_model": "all-MiniLM-L6-v2",
+                    provider_id=vector_io_provider,
-                        "chunk_size_in_tokens": 512,
-                        "overlap_size_in_tokens": 64,
-                    },
-                    provider_id=memory_provider,
                 )
 
-                # insert documents using the custom bank name
+                # insert documents using the custom vector db name
-                llama_stack_api.client.memory.insert(
+                llama_stack_api.client.tool_runtime.rag_tool.insert(
-                    bank_id=memory_bank_name,  # Use the user-provided name
+                    vector_db_id=vector_db_name,  # Use the user-provided name
                     documents=documents,
                 )
-                st.success("Memory bank created successfully!")
+                st.success("Vector database created successfully!")
 
         st.subheader("Configure Agent")
         # select memory banks
-        memory_banks = llama_stack_api.client.memory_banks.list()
+        vector_dbs = llama_stack_api.client.vector_dbs.list()
-        memory_banks = [bank.identifier for bank in memory_banks]
+        vector_dbs = [vector_db.identifier for vector_db in vector_dbs]
-        selected_memory_banks = st.multiselect(
+        selected_vector_dbs = st.multiselect(
-            "Select Memory Banks",
+            "Select Vector Databases",
-            memory_banks,
+            vector_dbs,
         )
 
         available_models = llama_stack_api.client.models.list()
@@ -141,14 +137,14 @@ def rag_chat_page():
             dict(
                 name="builtin::memory",
                 args={
-                    "memory_bank_ids": [bank_id for bank_id in selected_memory_banks],
+                    "vector_db_ids": [
+                        vector_db_id for vector_db_id in selected_vector_dbs
+                    ],
                 },
             )
         ],
         tool_choice="auto",
         tool_prompt_format="json",
-        input_shields=[],
-        output_shields=[],
         enable_session_persistence=False,
     )
 

llama_stack/providers/inline/vector_io/chroma/__init__.py

@@ -14,8 +14,10 @@ from .config import ChromaInlineImplConfig
 async def get_provider_impl(
     config: ChromaInlineImplConfig, deps: Dict[Api, ProviderSpec]
 ):
-    from llama_stack.providers.remote.memory.chroma.chroma import ChromaMemoryAdapter
+    from llama_stack.providers.remote.vector_io.chroma.chroma import (
+        ChromaVectorIOAdapter,
+    )
 
-    impl = ChromaMemoryAdapter(config, deps[Api.inference])
+    impl = ChromaVectorIOAdapter(config, deps[Api.inference])
     await impl.initialize()
     return impl

llama_stack/providers/remote/vector_io/chroma/__init__.py

@@ -14,8 +14,8 @@ from .config import ChromaRemoteImplConfig
 async def get_adapter_impl(
     config: ChromaRemoteImplConfig, deps: Dict[Api, ProviderSpec]
 ):
-    from .chroma import ChromaMemoryAdapter
+    from .chroma import ChromaVectorIOAdapter
 
-    impl = ChromaMemoryAdapter(config, deps[Api.inference])
+    impl = ChromaVectorIOAdapter(config, deps[Api.inference])
     await impl.initialize()
     return impl

llama_stack/providers/remote/vector_io/chroma/chroma.py

@@ -86,13 +86,13 @@ class ChromaIndex(EmbeddingIndex):
         await maybe_await(self.client.delete_collection(self.collection.name))
 
 
-class ChromaMemoryAdapter(VectorIO, VectorDBsProtocolPrivate):
+class ChromaVectorIOAdapter(VectorIO, VectorDBsProtocolPrivate):
     def __init__(
         self,
         config: Union[ChromaRemoteImplConfig, ChromaInlineImplConfig],
         inference_api: Api.inference,
     ) -> None:
-        log.info(f"Initializing ChromaMemoryAdapter with url: {config}")
+        log.info(f"Initializing ChromaVectorIOAdapter with url: {config}")
         self.config = config
         self.inference_api = inference_api
 

llama_stack/templates/bedrock/bedrock.py

@@ -10,7 +10,7 @@ from llama_models.sku_list import all_registered_models
 
 from llama_stack.apis.models import ModelInput
 from llama_stack.distribution.datatypes import Provider, ToolGroupInput
-from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
+from llama_stack.providers.inline.vector_io.faiss.config import FaissImplConfig
 from llama_stack.providers.remote.inference.bedrock.bedrock import MODEL_ALIASES
 from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
 
@@ -18,7 +18,7 @@ from llama_stack.templates.template import DistributionTemplate, RunConfigSettin
 def get_distribution_template() -> DistributionTemplate:
     providers = {
         "inference": ["remote::bedrock"],
-        "memory": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
+        "vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
         "safety": ["remote::bedrock"],
         "agents": ["inline::meta-reference"],
         "telemetry": ["inline::meta-reference"],
@@ -34,7 +34,7 @@ def get_distribution_template() -> DistributionTemplate:
         ],
     }
     name = "bedrock"
-    memory_provider = Provider(
+    vector_io_provider = Provider(
         provider_id="faiss",
         provider_type="inline::faiss",
         config=FaissImplConfig.sample_run_config(f"distributions/{name}"),
@@ -78,7 +78,7 @@ def get_distribution_template() -> DistributionTemplate:
         run_configs={
             "run.yaml": RunConfigSettings(
                 provider_overrides={
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=default_models,
                 default_tool_groups=default_tool_groups,

llama_stack/templates/bedrock/build.yaml

@@ -4,7 +4,7 @@ distribution_spec:
   providers:
     inference:
     - remote::bedrock
-    memory:
+    vector_io:
     - inline::faiss
     - remote::chromadb
     - remote::pgvector

llama_stack/templates/bedrock/run.yaml

@@ -5,17 +5,17 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: bedrock
     provider_type: remote::bedrock
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -104,7 +104,7 @@ models:
   provider_model_id: meta.llama3-1-405b-instruct-v1:0
   model_type: llm
 shields: []
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []

llama_stack/templates/cerebras/build.yaml

@@ -6,7 +6,7 @@ distribution_spec:
     - remote::cerebras
     safety:
     - inline::llama-guard
-    memory:
+    vector_io:
     - inline::faiss
     - remote::chromadb
     - remote::pgvector

llama_stack/templates/cerebras/cerebras.py

@@ -13,7 +13,7 @@ from llama_stack.distribution.datatypes import ModelInput, Provider, ToolGroupIn
 from llama_stack.providers.inline.inference.sentence_transformers import (
     SentenceTransformersInferenceConfig,
 )
-from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
+from llama_stack.providers.inline.vector_io.faiss.config import FaissImplConfig
 from llama_stack.providers.remote.inference.cerebras import CerebrasImplConfig
 from llama_stack.providers.remote.inference.cerebras.cerebras import model_aliases
 from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
@@ -23,7 +23,7 @@ def get_distribution_template() -> DistributionTemplate:
     providers = {
         "inference": ["remote::cerebras"],
         "safety": ["inline::llama-guard"],
-        "memory": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
+        "vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
         "agents": ["inline::meta-reference"],
         "eval": ["inline::meta-reference"],
         "datasetio": ["remote::huggingface", "inline::localfs"],
@@ -68,7 +68,7 @@ def get_distribution_template() -> DistributionTemplate:
             "embedding_dimension": 384,
         },
     )
-    memory_provider = Provider(
+    vector_io_provider = Provider(
         provider_id="faiss",
         provider_type="inline::faiss",
         config=FaissImplConfig.sample_run_config(f"distributions/{name}"),
@@ -100,7 +100,7 @@ def get_distribution_template() -> DistributionTemplate:
             "run.yaml": RunConfigSettings(
                 provider_overrides={
                     "inference": [inference_provider, embedding_provider],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=default_models + [embedding_model],
                 default_shields=[],

llama_stack/templates/cerebras/run.yaml

@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: cerebras
@@ -24,7 +24,7 @@ providers:
   - provider_id: llama-guard
     provider_type: inline::llama-guard
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -106,7 +106,7 @@ models:
   provider_id: sentence-transformers
   model_type: embedding
 shields: []
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []

llama_stack/templates/experimental-post-training/run.yaml

@@ -60,7 +60,7 @@ providers:
   - provider_id: llama-guard
     provider_type: inline::llama-guard
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -82,7 +82,7 @@ metadata_store:
   db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/meta-reference-gpu}/registry.db
 models: []
 shields: []
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []

llama_stack/templates/fireworks/build.yaml

@@ -4,7 +4,7 @@ distribution_spec:
   providers:
     inference:
     - remote::fireworks
-    memory:
+    vector_io:
     - inline::faiss
     - remote::chromadb
     - remote::pgvector

llama_stack/templates/fireworks/fireworks.py

@@ -18,7 +18,7 @@ from llama_stack.distribution.datatypes import (
 from llama_stack.providers.inline.inference.sentence_transformers import (
     SentenceTransformersInferenceConfig,
 )
-from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
+from llama_stack.providers.inline.vector_io.faiss.config import FaissImplConfig
 from llama_stack.providers.remote.inference.fireworks import FireworksImplConfig
 from llama_stack.providers.remote.inference.fireworks.fireworks import MODEL_ALIASES
 from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
@@ -27,7 +27,7 @@ from llama_stack.templates.template import DistributionTemplate, RunConfigSettin
 def get_distribution_template() -> DistributionTemplate:
     providers = {
         "inference": ["remote::fireworks"],
-        "memory": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
+        "vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
         "safety": ["inline::llama-guard"],
         "agents": ["inline::meta-reference"],
         "telemetry": ["inline::meta-reference"],
@@ -55,7 +55,7 @@ def get_distribution_template() -> DistributionTemplate:
         provider_type="inline::sentence-transformers",
         config=SentenceTransformersInferenceConfig.sample_run_config(),
     )
-    memory_provider = Provider(
+    vector_io_provider = Provider(
         provider_id="faiss",
         provider_type="inline::faiss",
         config=FaissImplConfig.sample_run_config(f"distributions/{name}"),
@@ -107,7 +107,7 @@ def get_distribution_template() -> DistributionTemplate:
             "run.yaml": RunConfigSettings(
                 provider_overrides={
                     "inference": [inference_provider, embedding_provider],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=default_models + [embedding_model],
                 default_shields=[ShieldInput(shield_id="meta-llama/Llama-Guard-3-8B")],
@@ -119,7 +119,7 @@ def get_distribution_template() -> DistributionTemplate:
                         inference_provider,
                         embedding_provider,
                     ],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                     "safety": [
                         Provider(
                             provider_id="llama-guard",

llama_stack/templates/fireworks/run-with-safety.yaml

@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: fireworks
@@ -20,7 +20,7 @@ providers:
   - provider_id: sentence-transformers
     provider_type: inline::sentence-transformers
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -161,7 +161,7 @@ shields:
   provider_id: llama-guard-vision
 - shield_id: CodeScanner
   provider_id: code-scanner
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []

llama_stack/templates/fireworks/run.yaml

@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: fireworks
@@ -20,7 +20,7 @@ providers:
   - provider_id: sentence-transformers
     provider_type: inline::sentence-transformers
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -150,7 +150,7 @@ models:
   model_type: embedding
 shields:
 - shield_id: meta-llama/Llama-Guard-3-8B
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []

llama_stack/templates/hf-endpoint/build.yaml

@@ -4,7 +4,7 @@ distribution_spec:
   providers:
     inference:
     - remote::hf::endpoint
-    memory:
+    vector_io:
     - inline::faiss
     - remote::chromadb
     - remote::pgvector

llama_stack/templates/hf-endpoint/hf_endpoint.py

@@ -14,7 +14,7 @@ from llama_stack.distribution.datatypes import (
 from llama_stack.providers.inline.inference.sentence_transformers import (
     SentenceTransformersInferenceConfig,
 )
-from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
+from llama_stack.providers.inline.vector_io.faiss.config import FaissImplConfig
 from llama_stack.providers.remote.inference.tgi import InferenceEndpointImplConfig
 from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
 
@@ -22,7 +22,7 @@ from llama_stack.templates.template import DistributionTemplate, RunConfigSettin
 def get_distribution_template() -> DistributionTemplate:
     providers = {
         "inference": ["remote::hf::endpoint"],
-        "memory": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
+        "vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
         "safety": ["inline::llama-guard"],
         "agents": ["inline::meta-reference"],
         "telemetry": ["inline::meta-reference"],
@@ -48,7 +48,7 @@ def get_distribution_template() -> DistributionTemplate:
         provider_type="inline::sentence-transformers",
         config=SentenceTransformersInferenceConfig.sample_run_config(),
     )
-    memory_provider = Provider(
+    vector_io_provider = Provider(
         provider_id="faiss",
         provider_type="inline::faiss",
         config=FaissImplConfig.sample_run_config(f"distributions/{name}"),
@@ -97,7 +97,7 @@ def get_distribution_template() -> DistributionTemplate:
             "run.yaml": RunConfigSettings(
                 provider_overrides={
                     "inference": [inference_provider, embedding_provider],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=[inference_model, embedding_model],
                 default_tool_groups=default_tool_groups,
@@ -115,7 +115,7 @@ def get_distribution_template() -> DistributionTemplate:
                             ),
                         ),
                     ],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=[
                     inference_model,

llama_stack/templates/hf-endpoint/run-with-safety.yaml

@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: hf-endpoint
@@ -25,7 +25,7 @@ providers:
     config:
       endpoint_name: ${env.SAFETY_INFERENCE_ENDPOINT_NAME}
       api_token: ${env.HF_API_TOKEN}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -113,7 +113,7 @@ models:
   model_type: embedding
 shields:
 - shield_id: ${env.SAFETY_MODEL}
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []

llama_stack/templates/hf-endpoint/run.yaml

@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: hf-endpoint
@@ -20,7 +20,7 @@ providers:
   - provider_id: sentence-transformers
     provider_type: inline::sentence-transformers
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -103,7 +103,7 @@ models:
   provider_id: sentence-transformers
   model_type: embedding
 shields: []
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []

llama_stack/templates/hf-serverless/build.yaml

@@ -4,7 +4,7 @@ distribution_spec:
   providers:
     inference:
     - remote::hf::serverless
-    memory:
+    vector_io:
     - inline::faiss
     - remote::chromadb
     - remote::pgvector

llama_stack/templates/hf-serverless/hf_serverless.py

@@ -14,7 +14,7 @@ from llama_stack.distribution.datatypes import (
 from llama_stack.providers.inline.inference.sentence_transformers import (
     SentenceTransformersInferenceConfig,
 )
-from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
+from llama_stack.providers.inline.vector_io.faiss.config import FaissImplConfig
 from llama_stack.providers.remote.inference.tgi import InferenceAPIImplConfig
 from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
 
@@ -22,7 +22,7 @@ from llama_stack.templates.template import DistributionTemplate, RunConfigSettin
 def get_distribution_template() -> DistributionTemplate:
     providers = {
         "inference": ["remote::hf::serverless"],
-        "memory": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
+        "vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
         "safety": ["inline::llama-guard"],
         "agents": ["inline::meta-reference"],
         "telemetry": ["inline::meta-reference"],
@@ -49,7 +49,7 @@ def get_distribution_template() -> DistributionTemplate:
         provider_type="inline::sentence-transformers",
         config=SentenceTransformersInferenceConfig.sample_run_config(),
     )
-    memory_provider = Provider(
+    vector_io_provider = Provider(
         provider_id="faiss",
         provider_type="inline::faiss",
         config=FaissImplConfig.sample_run_config(f"distributions/{name}"),
@@ -98,7 +98,7 @@ def get_distribution_template() -> DistributionTemplate:
             "run.yaml": RunConfigSettings(
                 provider_overrides={
                     "inference": [inference_provider, embedding_provider],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=[inference_model, embedding_model],
                 default_tool_groups=default_tool_groups,
@@ -116,7 +116,7 @@ def get_distribution_template() -> DistributionTemplate:
                             ),
                         ),
                     ],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=[
                     inference_model,

llama_stack/templates/hf-serverless/run-with-safety.yaml

@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: hf-serverless
@@ -25,7 +25,7 @@ providers:
     config:
       huggingface_repo: ${env.SAFETY_MODEL}
       api_token: ${env.HF_API_TOKEN}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -113,7 +113,7 @@ models:
   model_type: embedding
 shields:
 - shield_id: ${env.SAFETY_MODEL}
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []

llama_stack/templates/hf-serverless/run.yaml

@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: hf-serverless
@@ -20,7 +20,7 @@ providers:
   - provider_id: sentence-transformers
     provider_type: inline::sentence-transformers
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -103,7 +103,7 @@ models:
   provider_id: sentence-transformers
   model_type: embedding
 shields: []
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []

llama_stack/templates/meta-reference-gpu/build.yaml

@@ -4,7 +4,7 @@ distribution_spec:
   providers:
     inference:
     - inline::meta-reference
-    memory:
+    vector_io:
     - inline::faiss
     - remote::chromadb
     - remote::pgvector

llama_stack/templates/meta-reference-gpu/meta_reference.py

@@ -19,14 +19,14 @@ from llama_stack.providers.inline.inference.meta_reference import (
 from llama_stack.providers.inline.inference.sentence_transformers import (
     SentenceTransformersInferenceConfig,
 )
-from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
+from llama_stack.providers.inline.vector_io.faiss.config import FaissImplConfig
 from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
 
 
 def get_distribution_template() -> DistributionTemplate:
     providers = {
         "inference": ["inline::meta-reference"],
-        "memory": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
+        "vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
         "safety": ["inline::llama-guard"],
         "agents": ["inline::meta-reference"],
         "telemetry": ["inline::meta-reference"],
@@ -55,7 +55,7 @@ def get_distribution_template() -> DistributionTemplate:
         provider_type="inline::sentence-transformers",
         config=SentenceTransformersInferenceConfig.sample_run_config(),
     )
-    memory_provider = Provider(
+    vector_io_provider = Provider(
         provider_id="faiss",
         provider_type="inline::faiss",
         config=FaissImplConfig.sample_run_config(f"distributions/{name}"),
@@ -103,7 +103,7 @@ def get_distribution_template() -> DistributionTemplate:
             "run.yaml": RunConfigSettings(
                 provider_overrides={
                     "inference": [inference_provider, embedding_provider],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=[inference_model, embedding_model],
                 default_tool_groups=default_tool_groups,
@@ -122,7 +122,7 @@ def get_distribution_template() -> DistributionTemplate:
                             ),
                         ),
                     ],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=[
                     inference_model,

llama_stack/templates/meta-reference-gpu/run-with-safety.yaml

@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: meta-reference-inference
@@ -27,7 +27,7 @@ providers:
       model: ${env.SAFETY_MODEL}
       max_seq_len: 4096
       checkpoint_dir: ${env.SAFETY_CHECKPOINT_DIR:null}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -115,7 +115,7 @@ models:
   model_type: embedding
 shields:
 - shield_id: ${env.SAFETY_MODEL}
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []

llama_stack/templates/meta-reference-gpu/run.yaml

@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: meta-reference-inference
@@ -21,7 +21,7 @@ providers:
   - provider_id: sentence-transformers
     provider_type: inline::sentence-transformers
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -104,7 +104,7 @@ models:
   provider_id: sentence-transformers
   model_type: embedding
 shields: []
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []

llama_stack/templates/meta-reference-quantized-gpu/build.yaml

@@ -4,7 +4,7 @@ distribution_spec:
   providers:
     inference:
     - inline::meta-reference-quantized
-    memory:
+    vector_io:
     - inline::faiss
     - remote::chromadb
     - remote::pgvector

llama_stack/templates/meta-reference-quantized-gpu/meta_reference.py

@@ -14,14 +14,14 @@ from llama_stack.providers.inline.inference.meta_reference import (
 from llama_stack.providers.inline.inference.sentence_transformers import (
     SentenceTransformersInferenceConfig,
 )
-from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
+from llama_stack.providers.inline.vector_io.faiss.config import FaissImplConfig
 from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
 
 
 def get_distribution_template() -> DistributionTemplate:
     providers = {
         "inference": ["inline::meta-reference-quantized"],
-        "memory": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
+        "vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
         "safety": ["inline::llama-guard"],
         "agents": ["inline::meta-reference"],
         "telemetry": ["inline::meta-reference"],
@@ -64,7 +64,7 @@ def get_distribution_template() -> DistributionTemplate:
         provider_type="inline::sentence-transformers",
         config=SentenceTransformersInferenceConfig.sample_run_config(),
     )
-    memory_provider = Provider(
+    vector_io_provider = Provider(
         provider_id="faiss",
         provider_type="inline::faiss",
         config=FaissImplConfig.sample_run_config(f"distributions/{name}"),
@@ -93,7 +93,7 @@ def get_distribution_template() -> DistributionTemplate:
             "run.yaml": RunConfigSettings(
                 provider_overrides={
                     "inference": [inference_provider, embedding_provider],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=[inference_model, embedding_model],
                 default_tool_groups=default_tool_groups,

llama_stack/templates/meta-reference-quantized-gpu/run.yaml

@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: meta-reference-inference
@@ -23,7 +23,7 @@ providers:
   - provider_id: sentence-transformers
     provider_type: inline::sentence-transformers
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -106,7 +106,7 @@ models:
   provider_id: sentence-transformers
   model_type: embedding
 shields: []
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []

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: []

llama_stack/templates/ollama/build.yaml

@@ -4,7 +4,7 @@ distribution_spec:
   providers:
     inference:
     - remote::ollama
-    memory:
+    vector_io:
     - inline::faiss
     - remote::chromadb
     - remote::pgvector

llama_stack/templates/ollama/ollama.py

@@ -16,7 +16,7 @@ from llama_stack.distribution.datatypes import (
 from llama_stack.providers.inline.inference.sentence_transformers import (
     SentenceTransformersInferenceConfig,
 )
-from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
+from llama_stack.providers.inline.vector_io.faiss.config import FaissImplConfig
 from llama_stack.providers.remote.inference.ollama import OllamaImplConfig
 from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
 
@@ -24,7 +24,7 @@ from llama_stack.templates.template import DistributionTemplate, RunConfigSettin
 def get_distribution_template() -> DistributionTemplate:
     providers = {
         "inference": ["remote::ollama"],
-        "memory": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
+        "vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
         "safety": ["inline::llama-guard"],
         "agents": ["inline::meta-reference"],
         "telemetry": ["inline::meta-reference"],
@@ -49,7 +49,7 @@ def get_distribution_template() -> DistributionTemplate:
         provider_type="inline::sentence-transformers",
         config=SentenceTransformersInferenceConfig.sample_run_config(),
     )
-    memory_provider = Provider(
+    vector_io_provider = Provider(
         provider_id="faiss",
         provider_type="inline::faiss",
         config=FaissImplConfig.sample_run_config(f"distributions/{name}"),
@@ -98,7 +98,7 @@ def get_distribution_template() -> DistributionTemplate:
             "run.yaml": RunConfigSettings(
                 provider_overrides={
                     "inference": [inference_provider, embedding_provider],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=[inference_model, embedding_model],
                 default_tool_groups=default_tool_groups,
@@ -109,7 +109,7 @@ def get_distribution_template() -> DistributionTemplate:
                         inference_provider,
                         embedding_provider,
                     ],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                     "safety": [
                         Provider(
                             provider_id="llama-guard",

llama_stack/templates/ollama/run-with-safety.yaml

@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: ollama
@@ -19,7 +19,7 @@ providers:
   - provider_id: sentence-transformers
     provider_type: inline::sentence-transformers
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -110,7 +110,7 @@ shields:
   provider_id: llama-guard
 - shield_id: CodeScanner
   provider_id: code-scanner
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []

llama_stack/templates/ollama/run.yaml

@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: ollama
@@ -19,7 +19,7 @@ providers:
   - provider_id: sentence-transformers
     provider_type: inline::sentence-transformers
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -99,7 +99,7 @@ models:
   provider_id: sentence-transformers
   model_type: embedding
 shields: []
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []

llama_stack/templates/remote-vllm/build.yaml

@@ -4,7 +4,7 @@ distribution_spec:
   providers:
     inference:
     - remote::vllm
-    memory:
+    vector_io:
     - inline::faiss
     - remote::chromadb
     - remote::pgvector

llama_stack/templates/remote-vllm/run-with-safety.yaml

@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: vllm-inference
@@ -27,7 +27,7 @@ providers:
   - provider_id: sentence-transformers
     provider_type: inline::sentence-transformers
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -115,7 +115,7 @@ models:
   model_type: embedding
 shields:
 - shield_id: ${env.SAFETY_MODEL}
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []

llama_stack/templates/remote-vllm/run.yaml

@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: vllm-inference
@@ -21,7 +21,7 @@ providers:
   - provider_id: sentence-transformers
     provider_type: inline::sentence-transformers
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -104,7 +104,7 @@ models:
   provider_id: sentence-transformers
   model_type: embedding
 shields: []
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []

llama_stack/templates/remote-vllm/vllm.py

@@ -16,7 +16,7 @@ from llama_stack.distribution.datatypes import (
 from llama_stack.providers.inline.inference.sentence_transformers import (
     SentenceTransformersInferenceConfig,
 )
-from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
+from llama_stack.providers.inline.vector_io.faiss.config import FaissImplConfig
 from llama_stack.providers.remote.inference.vllm import VLLMInferenceAdapterConfig
 from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
 
@@ -24,7 +24,7 @@ from llama_stack.templates.template import DistributionTemplate, RunConfigSettin
 def get_distribution_template() -> DistributionTemplate:
     providers = {
         "inference": ["remote::vllm"],
-        "memory": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
+        "vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
         "safety": ["inline::llama-guard"],
         "agents": ["inline::meta-reference"],
         "eval": ["inline::meta-reference"],
@@ -52,7 +52,7 @@ def get_distribution_template() -> DistributionTemplate:
         provider_type="inline::sentence-transformers",
         config=SentenceTransformersInferenceConfig.sample_run_config(),
     )
-    memory_provider = Provider(
+    vector_io_provider = Provider(
         provider_id="faiss",
         provider_type="inline::faiss",
         config=FaissImplConfig.sample_run_config(f"distributions/{name}"),
@@ -100,7 +100,7 @@ def get_distribution_template() -> DistributionTemplate:
             "run.yaml": RunConfigSettings(
                 provider_overrides={
                     "inference": [inference_provider, embedding_provider],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=[inference_model, embedding_model],
                 default_tool_groups=default_tool_groups,
@@ -118,7 +118,7 @@ def get_distribution_template() -> DistributionTemplate:
                         ),
                         embedding_provider,
                     ],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=[
                     inference_model,

llama_stack/templates/tgi/build.yaml

@@ -4,7 +4,7 @@ distribution_spec:
   providers:
     inference:
     - remote::tgi
-    memory:
+    vector_io:
     - inline::faiss
     - remote::chromadb
     - remote::pgvector

llama_stack/templates/tgi/run-with-safety.yaml

@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: tgi-inference
@@ -20,7 +20,7 @@ providers:
     provider_type: remote::tgi
     config:
       url: ${env.TGI_SAFETY_URL}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -103,7 +103,7 @@ models:
   model_type: llm
 shields:
 - shield_id: ${env.SAFETY_MODEL}
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []

llama_stack/templates/tgi/run.yaml

@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: tgi-inference
@@ -19,7 +19,7 @@ providers:
   - provider_id: sentence-transformers
     provider_type: inline::sentence-transformers
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -102,7 +102,7 @@ models:
   provider_id: sentence-transformers
   model_type: embedding
 shields: []
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []

llama_stack/templates/tgi/tgi.py

@@ -16,7 +16,7 @@ from llama_stack.distribution.datatypes import (
 from llama_stack.providers.inline.inference.sentence_transformers import (
     SentenceTransformersInferenceConfig,
 )
-from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
+from llama_stack.providers.inline.vector_io.faiss.config import FaissImplConfig
 from llama_stack.providers.remote.inference.tgi import TGIImplConfig
 from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
 
@@ -24,7 +24,7 @@ from llama_stack.templates.template import DistributionTemplate, RunConfigSettin
 def get_distribution_template() -> DistributionTemplate:
     providers = {
         "inference": ["remote::tgi"],
-        "memory": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
+        "vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
         "safety": ["inline::llama-guard"],
         "agents": ["inline::meta-reference"],
         "telemetry": ["inline::meta-reference"],
@@ -52,7 +52,7 @@ def get_distribution_template() -> DistributionTemplate:
         provider_type="inline::sentence-transformers",
         config=SentenceTransformersInferenceConfig.sample_run_config(),
     )
-    memory_provider = Provider(
+    vector_io_provider = Provider(
         provider_id="faiss",
         provider_type="inline::faiss",
         config=FaissImplConfig.sample_run_config(f"distributions/{name}"),
@@ -101,7 +101,7 @@ def get_distribution_template() -> DistributionTemplate:
             "run.yaml": RunConfigSettings(
                 provider_overrides={
                     "inference": [inference_provider, embedding_provider],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=[inference_model, embedding_model],
                 default_tool_groups=default_tool_groups,
@@ -118,7 +118,7 @@ def get_distribution_template() -> DistributionTemplate:
                             ),
                         ),
                     ],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=[
                     inference_model,

llama_stack/templates/together/run-with-safety.yaml

@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: together
@@ -20,7 +20,7 @@ providers:
   - provider_id: sentence-transformers
     provider_type: inline::sentence-transformers
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -156,7 +156,7 @@ shields:
   provider_id: llama-guard-vision
 - shield_id: CodeScanner
   provider_id: code-scanner
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []

llama_stack/templates/together/run.yaml

@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- vector_io
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: together
@@ -145,6 +145,7 @@ models:
   model_type: embedding
 shields:
 - shield_id: meta-llama/Llama-Guard-3-8B
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []

llama_stack/templates/together/together.py

@@ -18,7 +18,7 @@ from llama_stack.distribution.datatypes import (
 from llama_stack.providers.inline.inference.sentence_transformers import (
     SentenceTransformersInferenceConfig,
 )
-from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
+from llama_stack.providers.inline.vector_io.faiss.config import FaissImplConfig
 from llama_stack.providers.remote.inference.together import TogetherImplConfig
 from llama_stack.providers.remote.inference.together.together import MODEL_ALIASES
 from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
@@ -27,7 +27,7 @@ from llama_stack.templates.template import DistributionTemplate, RunConfigSettin
 def get_distribution_template() -> DistributionTemplate:
     providers = {
         "inference": ["remote::together"],
-        "memory": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
+        "vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
         "safety": ["inline::llama-guard"],
         "agents": ["inline::meta-reference"],
         "telemetry": ["inline::meta-reference"],
@@ -48,7 +48,7 @@ def get_distribution_template() -> DistributionTemplate:
         provider_type="remote::together",
         config=TogetherImplConfig.sample_run_config(),
     )
-    memory_provider = Provider(
+    vector_io_provider = Provider(
         provider_id="faiss",
         provider_type="inline::faiss",
         config=FaissImplConfig.sample_run_config(f"distributions/{name}"),
@@ -105,7 +105,7 @@ def get_distribution_template() -> DistributionTemplate:
             "run.yaml": RunConfigSettings(
                 provider_overrides={
                     "inference": [inference_provider, embedding_provider],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=default_models + [embedding_model],
                 default_tool_groups=default_tool_groups,
@@ -117,7 +117,7 @@ def get_distribution_template() -> DistributionTemplate:
                         inference_provider,
                         embedding_provider,
                     ],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                     "safety": [
                         Provider(
                             provider_id="llama-guard",

llama_stack/templates/vllm-gpu/build.yaml

@@ -4,7 +4,7 @@ distribution_spec:
   providers:
     inference:
     - inline::vllm
-    memory:
+    vector_io:
     - inline::faiss
     - remote::chromadb
     - remote::pgvector

llama_stack/templates/vllm-gpu/run.yaml

@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: vllm
@@ -23,7 +23,7 @@ providers:
   - provider_id: sentence-transformers
     provider_type: inline::sentence-transformers
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -106,7 +106,7 @@ models:
   provider_id: sentence-transformers
   model_type: embedding
 shields: []
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []

llama_stack/templates/vllm-gpu/vllm.py

@@ -10,7 +10,7 @@ from llama_stack.providers.inline.inference.sentence_transformers import (
     SentenceTransformersInferenceConfig,
 )
 from llama_stack.providers.inline.inference.vllm import VLLMConfig
-from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
+from llama_stack.providers.inline.vector_io.faiss.config import FaissImplConfig
 from llama_stack.templates.template import (
     DistributionTemplate,
     RunConfigSettings,
@@ -21,7 +21,7 @@ from llama_stack.templates.template import (
 def get_distribution_template() -> DistributionTemplate:
     providers = {
         "inference": ["inline::vllm"],
-        "memory": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
+        "vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
         "safety": ["inline::llama-guard"],
         "agents": ["inline::meta-reference"],
         "telemetry": ["inline::meta-reference"],
@@ -43,7 +43,7 @@ def get_distribution_template() -> DistributionTemplate:
         provider_type="inline::vllm",
         config=VLLMConfig.sample_run_config(),
     )
-    memory_provider = Provider(
+    vector_io_provider = Provider(
         provider_id="faiss",
         provider_type="inline::faiss",
         config=FaissImplConfig.sample_run_config(f"distributions/{name}"),
@@ -93,7 +93,7 @@ def get_distribution_template() -> DistributionTemplate:
             "run.yaml": RunConfigSettings(
                 provider_overrides={
                     "inference": [inference_provider, embedding_provider],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=[inference_model, embedding_model],
                 default_tool_groups=default_tool_groups,