Merge 3b3a2d0ceb into 91f1b352b4

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

@@ -174,6 +174,18 @@ providers:
             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

src/llama_stack/distributions/starter/starter.py

@@ -127,7 +127,10 @@ 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