Add Dana agent provider stub

- Add inline::dana agent provider implementation (stub)
- Register provider in agents registry with proper dependencies
- Add Dana provider to starter distribution (build.yaml, run.yaml, starter.py)
- Add unit tests for provider registration and config validation
- Implementation follows meta-reference pattern with NotImplementedError stubs

src/llama_stack/distributions/starter/build.yaml

@@ -35,6 +35,7 @@ distribution_spec:
     - provider_type: inline::code-scanner
     agents:
     - provider_type: inline::meta-reference
+    - provider_type: inline::dana
     post_training:
     - provider_type: inline::torchtune-cpu
     eval:

src/llama_stack/distributions/starter/run.yaml

@@ -1,235 +1,247 @@
 version: 2
 image_name: starter
 apis:
-- agents
-- batches
-- datasetio
-- eval
-- files
-- inference
-- post_training
-- safety
-- scoring
-- tool_runtime
-- vector_io
+  - agents
+  - batches
+  - datasetio
+  - eval
+  - files
+  - inference
+  - post_training
+  - safety
+  - scoring
+  - tool_runtime
+  - vector_io
 providers:
   inference:
-  - provider_id: ${env.CEREBRAS_API_KEY:+cerebras}
-    provider_type: remote::cerebras
-    config:
-      base_url: https://api.cerebras.ai
-      api_key: ${env.CEREBRAS_API_KEY:=}
-  - provider_id: ${env.OLLAMA_URL:+ollama}
-    provider_type: remote::ollama
-    config:
-      url: ${env.OLLAMA_URL:=http://localhost:11434}
-  - provider_id: ${env.VLLM_URL:+vllm}
-    provider_type: remote::vllm
-    config:
-      url: ${env.VLLM_URL:=}
-      max_tokens: ${env.VLLM_MAX_TOKENS:=4096}
-      api_token: ${env.VLLM_API_TOKEN:=fake}
-      tls_verify: ${env.VLLM_TLS_VERIFY:=true}
-  - provider_id: ${env.TGI_URL:+tgi}
-    provider_type: remote::tgi
-    config:
-      url: ${env.TGI_URL:=}
-  - provider_id: fireworks
-    provider_type: remote::fireworks
-    config:
-      url: https://api.fireworks.ai/inference/v1
-      api_key: ${env.FIREWORKS_API_KEY:=}
-  - provider_id: together
-    provider_type: remote::together
-    config:
-      url: https://api.together.xyz/v1
-      api_key: ${env.TOGETHER_API_KEY:=}
-  - provider_id: bedrock
-    provider_type: remote::bedrock
-    config:
-      api_key: ${env.AWS_BEDROCK_API_KEY:=}
-      region_name: ${env.AWS_DEFAULT_REGION:=us-east-2}
-  - provider_id: ${env.NVIDIA_API_KEY:+nvidia}
-    provider_type: remote::nvidia
-    config:
-      url: ${env.NVIDIA_BASE_URL:=https://integrate.api.nvidia.com}
-      api_key: ${env.NVIDIA_API_KEY:=}
-      append_api_version: ${env.NVIDIA_APPEND_API_VERSION:=True}
-  - provider_id: openai
-    provider_type: remote::openai
-    config:
-      api_key: ${env.OPENAI_API_KEY:=}
-      base_url: ${env.OPENAI_BASE_URL:=https://api.openai.com/v1}
-  - provider_id: anthropic
-    provider_type: remote::anthropic
-    config:
-      api_key: ${env.ANTHROPIC_API_KEY:=}
-  - provider_id: gemini
-    provider_type: remote::gemini
-    config:
-      api_key: ${env.GEMINI_API_KEY:=}
-  - provider_id: ${env.VERTEX_AI_PROJECT:+vertexai}
-    provider_type: remote::vertexai
-    config:
-      project: ${env.VERTEX_AI_PROJECT:=}
-      location: ${env.VERTEX_AI_LOCATION:=us-central1}
-  - provider_id: groq
-    provider_type: remote::groq
-    config:
-      url: https://api.groq.com
-      api_key: ${env.GROQ_API_KEY:=}
-  - provider_id: sambanova
-    provider_type: remote::sambanova
-    config:
-      url: https://api.sambanova.ai/v1
-      api_key: ${env.SAMBANOVA_API_KEY:=}
-  - provider_id: ${env.AZURE_API_KEY:+azure}
-    provider_type: remote::azure
-    config:
-      api_key: ${env.AZURE_API_KEY:=}
-      api_base: ${env.AZURE_API_BASE:=}
-      api_version: ${env.AZURE_API_VERSION:=}
-      api_type: ${env.AZURE_API_TYPE:=}
-  - provider_id: sentence-transformers
-    provider_type: inline::sentence-transformers
+    - provider_id: ${env.CEREBRAS_API_KEY:+cerebras}
+      provider_type: remote::cerebras
+      config:
+        base_url: https://api.cerebras.ai
+        api_key: ${env.CEREBRAS_API_KEY:=}
+    - provider_id: ${env.OLLAMA_URL:+ollama}
+      provider_type: remote::ollama
+      config:
+        url: ${env.OLLAMA_URL:=http://localhost:11434}
+    - provider_id: ${env.VLLM_URL:+vllm}
+      provider_type: remote::vllm
+      config:
+        url: ${env.VLLM_URL:=}
+        max_tokens: ${env.VLLM_MAX_TOKENS:=4096}
+        api_token: ${env.VLLM_API_TOKEN:=fake}
+        tls_verify: ${env.VLLM_TLS_VERIFY:=true}
+    - provider_id: ${env.TGI_URL:+tgi}
+      provider_type: remote::tgi
+      config:
+        url: ${env.TGI_URL:=}
+    - provider_id: fireworks
+      provider_type: remote::fireworks
+      config:
+        url: https://api.fireworks.ai/inference/v1
+        api_key: ${env.FIREWORKS_API_KEY:=}
+    - provider_id: together
+      provider_type: remote::together
+      config:
+        url: https://api.together.xyz/v1
+        api_key: ${env.TOGETHER_API_KEY:=}
+    - provider_id: bedrock
+      provider_type: remote::bedrock
+      config:
+        api_key: ${env.AWS_BEDROCK_API_KEY:=}
+        region_name: ${env.AWS_DEFAULT_REGION:=us-east-2}
+    - provider_id: ${env.NVIDIA_API_KEY:+nvidia}
+      provider_type: remote::nvidia
+      config:
+        url: ${env.NVIDIA_BASE_URL:=https://integrate.api.nvidia.com}
+        api_key: ${env.NVIDIA_API_KEY:=}
+        append_api_version: ${env.NVIDIA_APPEND_API_VERSION:=True}
+    - provider_id: openai
+      provider_type: remote::openai
+      config:
+        api_key: ${env.OPENAI_API_KEY:=}
+        base_url: ${env.OPENAI_BASE_URL:=https://api.openai.com/v1}
+    - provider_id: anthropic
+      provider_type: remote::anthropic
+      config:
+        api_key: ${env.ANTHROPIC_API_KEY:=}
+    - provider_id: gemini
+      provider_type: remote::gemini
+      config:
+        api_key: ${env.GEMINI_API_KEY:=}
+    - provider_id: ${env.VERTEX_AI_PROJECT:+vertexai}
+      provider_type: remote::vertexai
+      config:
+        project: ${env.VERTEX_AI_PROJECT:=}
+        location: ${env.VERTEX_AI_LOCATION:=us-central1}
+    - provider_id: groq
+      provider_type: remote::groq
+      config:
+        url: https://api.groq.com
+        api_key: ${env.GROQ_API_KEY:=}
+    - provider_id: sambanova
+      provider_type: remote::sambanova
+      config:
+        url: https://api.sambanova.ai/v1
+        api_key: ${env.SAMBANOVA_API_KEY:=}
+    - provider_id: ${env.AZURE_API_KEY:+azure}
+      provider_type: remote::azure
+      config:
+        api_key: ${env.AZURE_API_KEY:=}
+        api_base: ${env.AZURE_API_BASE:=}
+        api_version: ${env.AZURE_API_VERSION:=}
+        api_type: ${env.AZURE_API_TYPE:=}
+    - provider_id: sentence-transformers
+      provider_type: inline::sentence-transformers
   vector_io:
-  - provider_id: faiss
-    provider_type: inline::faiss
-    config:
-      persistence:
-        namespace: vector_io::faiss
-        backend: kv_default
-  - provider_id: sqlite-vec
-    provider_type: inline::sqlite-vec
-    config:
-      db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter}/sqlite_vec.db
-      persistence:
-        namespace: vector_io::sqlite_vec
-        backend: kv_default
-  - provider_id: ${env.MILVUS_URL:+milvus}
-    provider_type: inline::milvus
-    config:
-      db_path: ${env.MILVUS_DB_PATH:=~/.llama/distributions/starter}/milvus.db
-      persistence:
-        namespace: vector_io::milvus
-        backend: kv_default
-  - provider_id: ${env.CHROMADB_URL:+chromadb}
-    provider_type: remote::chromadb
-    config:
-      url: ${env.CHROMADB_URL:=}
-      persistence:
-        namespace: vector_io::chroma_remote
-        backend: kv_default
-  - provider_id: ${env.PGVECTOR_DB:+pgvector}
-    provider_type: remote::pgvector
-    config:
-      host: ${env.PGVECTOR_HOST:=localhost}
-      port: ${env.PGVECTOR_PORT:=5432}
-      db: ${env.PGVECTOR_DB:=}
-      user: ${env.PGVECTOR_USER:=}
-      password: ${env.PGVECTOR_PASSWORD:=}
-      persistence:
-        namespace: vector_io::pgvector
-        backend: kv_default
-  - provider_id: ${env.QDRANT_URL:+qdrant}
-    provider_type: remote::qdrant
-    config:
-      api_key: ${env.QDRANT_API_KEY:=}
-      persistence:
-        namespace: vector_io::qdrant_remote
-        backend: kv_default
-  - provider_id: ${env.WEAVIATE_CLUSTER_URL:+weaviate}
-    provider_type: remote::weaviate
-    config:
-      weaviate_api_key: null
-      weaviate_cluster_url: ${env.WEAVIATE_CLUSTER_URL:=localhost:8080}
-      persistence:
-        namespace: vector_io::weaviate
-        backend: kv_default
-  files:
-  - provider_id: meta-reference-files
-    provider_type: inline::localfs
-    config:
-      storage_dir: ${env.FILES_STORAGE_DIR:=~/.llama/distributions/starter/files}
-      metadata_store:
-        table_name: files_metadata
-        backend: sql_default
-  safety:
-  - provider_id: llama-guard
-    provider_type: inline::llama-guard
-    config:
-      excluded_categories: []
-  - provider_id: code-scanner
-    provider_type: inline::code-scanner
-  agents:
-  - provider_id: meta-reference
-    provider_type: inline::meta-reference
-    config:
-      persistence:
-        agent_state:
-          namespace: agents
+    - provider_id: faiss
+      provider_type: inline::faiss
+      config:
+        persistence:
+          namespace: vector_io::faiss
           backend: kv_default
-        responses:
-          table_name: responses
+    - provider_id: sqlite-vec
+      provider_type: inline::sqlite-vec
+      config:
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter}/sqlite_vec.db
+        persistence:
+          namespace: vector_io::sqlite_vec
+          backend: kv_default
+    - provider_id: ${env.MILVUS_URL:+milvus}
+      provider_type: inline::milvus
+      config:
+        db_path: ${env.MILVUS_DB_PATH:=~/.llama/distributions/starter}/milvus.db
+        persistence:
+          namespace: vector_io::milvus
+          backend: kv_default
+    - provider_id: ${env.CHROMADB_URL:+chromadb}
+      provider_type: remote::chromadb
+      config:
+        url: ${env.CHROMADB_URL:=}
+        persistence:
+          namespace: vector_io::chroma_remote
+          backend: kv_default
+    - provider_id: ${env.PGVECTOR_DB:+pgvector}
+      provider_type: remote::pgvector
+      config:
+        host: ${env.PGVECTOR_HOST:=localhost}
+        port: ${env.PGVECTOR_PORT:=5432}
+        db: ${env.PGVECTOR_DB:=}
+        user: ${env.PGVECTOR_USER:=}
+        password: ${env.PGVECTOR_PASSWORD:=}
+        persistence:
+          namespace: vector_io::pgvector
+          backend: kv_default
+    - provider_id: ${env.QDRANT_URL:+qdrant}
+      provider_type: remote::qdrant
+      config:
+        api_key: ${env.QDRANT_API_KEY:=}
+        persistence:
+          namespace: vector_io::qdrant_remote
+          backend: kv_default
+    - provider_id: ${env.WEAVIATE_CLUSTER_URL:+weaviate}
+      provider_type: remote::weaviate
+      config:
+        weaviate_api_key: null
+        weaviate_cluster_url: ${env.WEAVIATE_CLUSTER_URL:=localhost:8080}
+        persistence:
+          namespace: vector_io::weaviate
+          backend: kv_default
+  files:
+    - provider_id: meta-reference-files
+      provider_type: inline::localfs
+      config:
+        storage_dir: ${env.FILES_STORAGE_DIR:=~/.llama/distributions/starter/files}
+        metadata_store:
+          table_name: files_metadata
           backend: sql_default
-          max_write_queue_size: 10000
-          num_writers: 4
+  safety:
+    - provider_id: llama-guard
+      provider_type: inline::llama-guard
+      config:
+        excluded_categories: []
+    - provider_id: code-scanner
+      provider_type: inline::code-scanner
+  agents:
+    - provider_id: meta-reference
+      provider_type: inline::meta-reference
+      config:
+        persistence:
+          agent_state:
+            namespace: agents
+            backend: kv_default
+          responses:
+            table_name: responses
+            backend: sql_default
+            max_write_queue_size: 10000
+            num_writers: 4
+    - provider_id: dana
+      provider_type: inline::dana
+      config:
+        persistence:
+          agent_state:
+            namespace: agents
+            backend: kv_default
+          responses:
+            table_name: responses
+            backend: sql_default
+            max_write_queue_size: 10000
+            num_writers: 4
   post_training:
-  - provider_id: torchtune-cpu
-    provider_type: inline::torchtune-cpu
-    config:
-      checkpoint_format: meta
+    - provider_id: torchtune-cpu
+      provider_type: inline::torchtune-cpu
+      config:
+        checkpoint_format: meta
   eval:
-  - provider_id: meta-reference
-    provider_type: inline::meta-reference
-    config:
-      kvstore:
-        namespace: eval
-        backend: kv_default
+    - provider_id: meta-reference
+      provider_type: inline::meta-reference
+      config:
+        kvstore:
+          namespace: eval
+          backend: kv_default
   datasetio:
-  - provider_id: huggingface
-    provider_type: remote::huggingface
-    config:
-      kvstore:
-        namespace: datasetio::huggingface
-        backend: kv_default
-  - provider_id: localfs
-    provider_type: inline::localfs
-    config:
-      kvstore:
-        namespace: datasetio::localfs
-        backend: kv_default
+    - provider_id: huggingface
+      provider_type: remote::huggingface
+      config:
+        kvstore:
+          namespace: datasetio::huggingface
+          backend: kv_default
+    - provider_id: localfs
+      provider_type: inline::localfs
+      config:
+        kvstore:
+          namespace: datasetio::localfs
+          backend: kv_default
   scoring:
-  - provider_id: basic
-    provider_type: inline::basic
-  - provider_id: llm-as-judge
-    provider_type: inline::llm-as-judge
-  - provider_id: braintrust
-    provider_type: inline::braintrust
-    config:
-      openai_api_key: ${env.OPENAI_API_KEY:=}
+    - provider_id: basic
+      provider_type: inline::basic
+    - provider_id: llm-as-judge
+      provider_type: inline::llm-as-judge
+    - provider_id: braintrust
+      provider_type: inline::braintrust
+      config:
+        openai_api_key: ${env.OPENAI_API_KEY:=}
   tool_runtime:
-  - provider_id: brave-search
-    provider_type: remote::brave-search
-    config:
-      api_key: ${env.BRAVE_SEARCH_API_KEY:=}
-      max_results: 3
-  - provider_id: tavily-search
-    provider_type: remote::tavily-search
-    config:
-      api_key: ${env.TAVILY_SEARCH_API_KEY:=}
-      max_results: 3
-  - provider_id: rag-runtime
-    provider_type: inline::rag-runtime
-  - provider_id: model-context-protocol
-    provider_type: remote::model-context-protocol
+    - provider_id: brave-search
+      provider_type: remote::brave-search
+      config:
+        api_key: ${env.BRAVE_SEARCH_API_KEY:=}
+        max_results: 3
+    - provider_id: tavily-search
+      provider_type: remote::tavily-search
+      config:
+        api_key: ${env.TAVILY_SEARCH_API_KEY:=}
+        max_results: 3
+    - provider_id: rag-runtime
+      provider_type: inline::rag-runtime
+    - provider_id: model-context-protocol
+      provider_type: remote::model-context-protocol
   batches:
-  - provider_id: reference
-    provider_type: inline::reference
-    config:
-      kvstore:
-        namespace: batches
-        backend: kv_default
+    - provider_id: reference
+      provider_type: inline::reference
+      config:
+        kvstore:
+          namespace: batches
+          backend: kv_default
 storage:
   backends:
     kv_default:
@@ -256,21 +268,21 @@ storage:
 registered_resources:
   models: []
   shields:
-  - shield_id: llama-guard
-    provider_id: ${env.SAFETY_MODEL:+llama-guard}
-    provider_shield_id: ${env.SAFETY_MODEL:=}
-  - shield_id: code-scanner
-    provider_id: ${env.CODE_SCANNER_MODEL:+code-scanner}
-    provider_shield_id: ${env.CODE_SCANNER_MODEL:=}
+    - shield_id: llama-guard
+      provider_id: ${env.SAFETY_MODEL:+llama-guard}
+      provider_shield_id: ${env.SAFETY_MODEL:=}
+    - shield_id: code-scanner
+      provider_id: ${env.CODE_SCANNER_MODEL:+code-scanner}
+      provider_shield_id: ${env.CODE_SCANNER_MODEL:=}
   vector_dbs: []
   datasets: []
   scoring_fns: []
   benchmarks: []
   tool_groups:
-  - toolgroup_id: builtin::websearch
-    provider_id: tavily-search
-  - toolgroup_id: builtin::rag
-    provider_id: rag-runtime
+    - toolgroup_id: builtin::websearch
+      provider_id: tavily-search
+    - toolgroup_id: builtin::rag
+      provider_id: rag-runtime
 server:
   port: 8321
 telemetry:

src/llama_stack/distributions/starter/starter.py

@@ -132,7 +132,10 @@ def get_distribution_template(name: str = "starter") -> DistributionTemplate:
             BuildProvider(provider_type="inline::llama-guard"),
             BuildProvider(provider_type="inline::code-scanner"),
         ],
-        "agents": [BuildProvider(provider_type="inline::meta-reference")],
+        "agents": [
+            BuildProvider(provider_type="inline::meta-reference"),
+            BuildProvider(provider_type="inline::dana"),
+        ],
         "post_training": [BuildProvider(provider_type="inline::torchtune-cpu")],
         "eval": [BuildProvider(provider_type="inline::meta-reference")],
         "datasetio": [

src/llama_stack/providers/inline/agents/dana/__init__.py

@@ -0,0 +1,34 @@
+# 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.
+
+from typing import Any
+
+from llama_stack.core.datatypes import AccessRule, Api
+
+from .config import DanaAgentsImplConfig
+
+
+async def get_provider_impl(
+    config: DanaAgentsImplConfig,
+    deps: dict[Api, Any],
+    policy: list[AccessRule],
+    telemetry_enabled: bool = False,
+):
+    from .agents import DanaAgentsImpl
+
+    impl = DanaAgentsImpl(
+        config,
+        deps[Api.inference],
+        deps[Api.vector_io],
+        deps[Api.safety],
+        deps[Api.tool_runtime],
+        deps[Api.tool_groups],
+        deps[Api.conversations],
+        policy,
+        telemetry_enabled,
+    )
+    await impl.initialize()
+    return impl

src/llama_stack/providers/inline/agents/dana/agents.py

@@ -0,0 +1,122 @@
+# 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.
+
+from collections.abc import AsyncIterator
+
+from llama_stack.apis.agents import (
+    Agents,
+    ListOpenAIResponseInputItem,
+    ListOpenAIResponseObject,
+    OpenAIDeleteResponseObject,
+    OpenAIResponseInput,
+    OpenAIResponseInputTool,
+    OpenAIResponseObject,
+    OpenAIResponseObjectStream,
+    Order,
+)
+from llama_stack.apis.agents.agents import ResponseGuardrail
+from llama_stack.apis.agents.openai_responses import OpenAIResponsePrompt, OpenAIResponseText
+from llama_stack.apis.conversations import Conversations
+from llama_stack.apis.inference import Inference
+from llama_stack.apis.safety import Safety
+from llama_stack.apis.tools import ToolGroups, ToolRuntime
+from llama_stack.apis.vector_io import VectorIO
+from llama_stack.core.datatypes import AccessRule
+from llama_stack.log import get_logger
+
+from .config import DanaAgentsImplConfig
+
+logger = get_logger(name=__name__, category="agents::dana")
+
+
+class DanaAgentsImpl(Agents):
+    """Stub implementation of the Agents API using the Dana library."""
+
+    def __init__(
+        self,
+        config: DanaAgentsImplConfig,
+        inference_api: Inference,
+        vector_io_api: VectorIO,
+        safety_api: Safety,
+        tool_runtime_api: ToolRuntime,
+        tool_groups_api: ToolGroups,
+        conversations_api: Conversations,
+        policy: list[AccessRule],
+        telemetry_enabled: bool = False,
+    ):
+        self.config = config
+        self.inference_api = inference_api
+        self.vector_io_api = vector_io_api
+        self.safety_api = safety_api
+        self.tool_runtime_api = tool_runtime_api
+        self.tool_groups_api = tool_groups_api
+        self.conversations_api = conversations_api
+        self.telemetry_enabled = telemetry_enabled
+        self.policy = policy
+
+    async def initialize(self) -> None:
+        """Initialize the Dana agents implementation."""
+        # TODO: Initialize Dana library here
+        logger.info("Dana agents implementation initialized (stub)")
+
+    async def shutdown(self) -> None:
+        """Shutdown the Dana agents implementation."""
+        # TODO: Cleanup Dana library here
+        pass
+
+    # OpenAI responses
+    async def get_openai_response(
+        self,
+        response_id: str,
+    ) -> OpenAIResponseObject:
+        """Get a model response."""
+        raise NotImplementedError("Dana provider is not yet implemented")
+
+    async def create_openai_response(
+        self,
+        input: str | list[OpenAIResponseInput],
+        model: str,
+        prompt: OpenAIResponsePrompt | None = None,
+        instructions: str | None = None,
+        previous_response_id: str | None = None,
+        conversation: str | None = None,
+        store: bool | None = True,
+        stream: bool | None = False,
+        temperature: float | None = None,
+        text: OpenAIResponseText | None = None,
+        tools: list[OpenAIResponseInputTool] | None = None,
+        include: list[str] | None = None,
+        max_infer_iters: int | None = 10,
+        guardrails: list[ResponseGuardrail] | None = None,
+    ) -> OpenAIResponseObject | AsyncIterator[OpenAIResponseObjectStream]:
+        """Create a model response."""
+        raise NotImplementedError("Dana provider is not yet implemented")
+
+    async def list_openai_responses(
+        self,
+        after: str | None = None,
+        limit: int | None = 50,
+        model: str | None = None,
+        order: Order | None = Order.desc,
+    ) -> ListOpenAIResponseObject:
+        """List all responses."""
+        raise NotImplementedError("Dana provider is not yet implemented")
+
+    async def list_openai_response_input_items(
+        self,
+        response_id: str,
+        after: str | None = None,
+        before: str | None = None,
+        include: list[str] | None = None,
+        limit: int | None = 20,
+        order: Order | None = Order.desc,
+    ) -> ListOpenAIResponseInputItem:
+        """List input items."""
+        raise NotImplementedError("Dana provider is not yet implemented")
+
+    async def delete_openai_response(self, response_id: str) -> OpenAIDeleteResponseObject:
+        """Delete a response."""
+        raise NotImplementedError("Dana provider is not yet implemented")

src/llama_stack/providers/inline/agents/dana/config.py

@@ -0,0 +1,38 @@
+# 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.
+
+from typing import Any
+
+from pydantic import BaseModel
+
+from llama_stack.core.storage.datatypes import KVStoreReference, ResponsesStoreReference
+
+
+class AgentPersistenceConfig(BaseModel):
+    """Nested persistence configuration for agents."""
+
+    agent_state: KVStoreReference
+    responses: ResponsesStoreReference
+
+
+class DanaAgentsImplConfig(BaseModel):
+    persistence: AgentPersistenceConfig
+
+    @classmethod
+    def sample_run_config(cls, __distro_dir__: str) -> dict[str, Any]:
+        return {
+            "persistence": {
+                "agent_state": KVStoreReference(
+                    backend="kv_default",
+                    namespace="agents",
+                ).model_dump(exclude_none=True),
+                "responses": ResponsesStoreReference(
+                    backend="sql_default",
+                    table_name="responses",
+                ).model_dump(exclude_none=True),
+            }
+        }
+

src/llama_stack/providers/registry/agents.py

@@ -38,4 +38,23 @@ def available_providers() -> list[ProviderSpec]:
             ],
             description="Meta's reference implementation of an agent system that can use tools, access vector databases, and perform complex reasoning tasks.",
         ),
+        InlineProviderSpec(
+            api=Api.agents,
+            provider_type="inline::dana",
+            pip_packages=[
+                "dana",
+            ]
+            + kvstore_dependencies(),  # TODO make this dynamic based on the kvstore config
+            module="llama_stack.providers.inline.agents.dana",
+            config_class="llama_stack.providers.inline.agents.dana.DanaAgentsImplConfig",
+            api_dependencies=[
+                Api.inference,
+                Api.safety,
+                Api.vector_io,
+                Api.tool_runtime,
+                Api.tool_groups,
+                Api.conversations,
+            ],
+            description="Dana library implementation of an agent system (stub).",
+        ),
     ]

tests/unit/providers/inline/agents/dana/__init__.py

@@ -0,0 +1,6 @@
+# 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.
+

tests/unit/providers/inline/agents/dana/test_dana.py

@@ -0,0 +1,46 @@
+# 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.
+
+"""
+Test suite for the Dana agent provider implementation (stub).
+
+TODO: Add tests when implementation is complete.
+"""
+
+from llama_stack.core.datatypes import Api
+from llama_stack.core.distribution import get_provider_registry
+from llama_stack.providers.inline.agents.dana.agents import DanaAgentsImpl
+from llama_stack.providers.inline.agents.dana.config import DanaAgentsImplConfig
+
+
+def test_dana_provider_in_registry():
+    """Test that the Dana provider is registered and can be found in the registry."""
+    provider_registry = get_provider_registry()
+    agents_providers = provider_registry.get(Api.agents, {})
+
+    # Verify the provider is in the registry
+    assert "inline::dana" in agents_providers, "Dana provider should be registered"
+
+    provider_spec = agents_providers["inline::dana"]
+    assert provider_spec.provider_type == "inline::dana"
+    assert provider_spec.api == Api.agents
+    assert provider_spec.module == "llama_stack.providers.inline.agents.dana"
+    assert provider_spec.config_class == "llama_stack.providers.inline.agents.dana.DanaAgentsImplConfig"
+
+
+def test_dana_provider_config():
+    """Test that the Dana provider config can be instantiated."""
+    config = DanaAgentsImplConfig.sample_run_config(__distro_dir__="test")
+    assert isinstance(config, dict)
+    assert "persistence" in config
+    assert "agent_state" in config["persistence"]
+    assert "responses" in config["persistence"]
+
+
+def test_dana_provider_class_exists():
+    """Test that Dana provider class exists."""
+    assert DanaAgentsImpl is not None
+    # TODO: Add actual tests when the provider is implemented