feat: Add responses and safety impl extra_body

tests/unit/providers/agents/meta_reference/test_openai_responses.py

@@ -91,6 +91,12 @@ def mock_conversations_api():
     return mock_api
 
 
+@pytest.fixture
+def mock_safety_api():
+    safety_api = AsyncMock()
+    return safety_api
+
+
 @pytest.fixture
 def openai_responses_impl(
     mock_inference_api,
@@ -98,6 +104,7 @@ def openai_responses_impl(
     mock_tool_runtime_api,
     mock_responses_store,
     mock_vector_io_api,
+    mock_safety_api,
     mock_conversations_api,
 ):
     return OpenAIResponsesImpl(
@@ -106,6 +113,7 @@ def openai_responses_impl(
         tool_runtime_api=mock_tool_runtime_api,
         responses_store=mock_responses_store,
         vector_io_api=mock_vector_io_api,
+        safety_api=mock_safety_api,
         conversations_api=mock_conversations_api,
     )
 

tests/unit/providers/agents/meta_reference/test_responses_safety_utils.py

@@ -0,0 +1,160 @@
+# 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 unittest.mock import AsyncMock, MagicMock
+
+import pytest
+
+from llama_stack.apis.agents.agents import ResponseShieldSpec
+from llama_stack.providers.inline.agents.meta_reference.responses.openai_responses import (
+    OpenAIResponsesImpl,
+)
+from llama_stack.providers.inline.agents.meta_reference.responses.utils import (
+    extract_shield_ids,
+    extract_text_content,
+)
+
+
+@pytest.fixture
+def mock_apis():
+    """Create mock APIs for testing."""
+    return {
+        "inference_api": AsyncMock(),
+        "tool_groups_api": AsyncMock(),
+        "tool_runtime_api": AsyncMock(),
+        "responses_store": AsyncMock(),
+        "vector_io_api": AsyncMock(),
+        "conversations_api": AsyncMock(),
+        "safety_api": AsyncMock(),
+    }
+
+
+@pytest.fixture
+def responses_impl(mock_apis):
+    """Create OpenAIResponsesImpl instance with mocked dependencies."""
+    return OpenAIResponsesImpl(**mock_apis)
+
+
+def test_extract_shield_ids_from_strings(responses_impl):
+    """Test extraction from simple string shield IDs."""
+    shields = ["llama-guard", "content-filter", "nsfw-detector"]
+    result = extract_shield_ids(shields)
+    assert result == ["llama-guard", "content-filter", "nsfw-detector"]
+
+
+def test_extract_shield_ids_from_objects(responses_impl):
+    """Test extraction from ResponseShieldSpec objects."""
+    shields = [
+        ResponseShieldSpec(type="llama-guard"),
+        ResponseShieldSpec(type="content-filter"),
+    ]
+    result = extract_shield_ids(shields)
+    assert result == ["llama-guard", "content-filter"]
+
+
+def test_extract_shield_ids_mixed_formats(responses_impl):
+    """Test extraction from mixed string and object formats."""
+    shields = [
+        "llama-guard",
+        ResponseShieldSpec(type="content-filter"),
+        "nsfw-detector",
+    ]
+    result = extract_shield_ids(shields)
+    assert result == ["llama-guard", "content-filter", "nsfw-detector"]
+
+
+def test_extract_shield_ids_none_input(responses_impl):
+    """Test extraction with None input."""
+    result = extract_shield_ids(None)
+    assert result == []
+
+
+def test_extract_shield_ids_empty_list(responses_impl):
+    """Test extraction with empty list."""
+    result = extract_shield_ids([])
+    assert result == []
+
+
+def test_extract_shield_ids_unknown_format(responses_impl):
+    """Test extraction with unknown shield format raises ValueError."""
+    # Create an object that's neither string nor ResponseShieldSpec
+    unknown_object = {"invalid": "format"}  # Plain dict, not ResponseShieldSpec
+    shields = ["valid-shield", unknown_object, "another-shield"]
+    with pytest.raises(ValueError, match="Unknown shield format.*expected str or ResponseShieldSpec"):
+        extract_shield_ids(shields)
+
+
+def test_extract_text_content_string(responses_impl):
+    """Test extraction from simple string content."""
+    content = "Hello world"
+    result = extract_text_content(content)
+    assert result == "Hello world"
+
+
+def test_extract_text_content_list_with_text(responses_impl):
+    """Test extraction from list content with text parts."""
+    content = [
+        MagicMock(text="Hello "),
+        MagicMock(text="world"),
+    ]
+    result = extract_text_content(content)
+    assert result == "Hello  world"
+
+
+def test_extract_text_content_list_with_refusal(responses_impl):
+    """Test extraction skips refusal parts."""
+    # Create text parts
+    text_part1 = MagicMock()
+    text_part1.text = "Hello"
+
+    text_part2 = MagicMock()
+    text_part2.text = "world"
+
+    # Create refusal part (no text attribute)
+    refusal_part = MagicMock()
+    refusal_part.type = "refusal"
+    refusal_part.refusal = "Blocked"
+    del refusal_part.text  # Remove text attribute
+
+    content = [text_part1, refusal_part, text_part2]
+    result = extract_text_content(content)
+    assert result == "Hello world"
+
+
+def test_extract_text_content_empty_list(responses_impl):
+    """Test extraction from empty list returns None."""
+    content = []
+    result = extract_text_content(content)
+    assert result is None
+
+
+def test_extract_text_content_no_text_parts(responses_impl):
+    """Test extraction with no text parts returns None."""
+    # Create image part (no text attribute)
+    image_part = MagicMock()
+    image_part.type = "image"
+    image_part.image_url = "http://example.com"
+
+    # Create refusal part (no text attribute)
+    refusal_part = MagicMock()
+    refusal_part.type = "refusal"
+    refusal_part.refusal = "Blocked"
+
+    # Explicitly remove text attributes to simulate non-text parts
+    if hasattr(image_part, "text"):
+        delattr(image_part, "text")
+    if hasattr(refusal_part, "text"):
+        delattr(refusal_part, "text")
+
+    content = [image_part, refusal_part]
+    result = extract_text_content(content)
+    assert result is None
+
+
+def test_extract_text_content_none_input(responses_impl):
+    """Test extraction with None input returns None."""
+    result = extract_text_content(None)
+    assert result is None

tests/unit/providers/inline/agents/meta_reference/responses/test_streaming.py

@@ -4,10 +4,44 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
+from unittest.mock import AsyncMock
+
+import pytest
+
+from llama_stack.apis.agents.openai_responses import (
+    OpenAIResponseContentPartRefusal,
+    OpenAIResponseText,
+)
+from llama_stack.apis.inference import UserMessage
+from llama_stack.apis.safety import SafetyViolation, ViolationLevel
 from llama_stack.apis.tools import ToolDef
 from llama_stack.providers.inline.agents.meta_reference.responses.streaming import (
+    StreamingResponseOrchestrator,
     convert_tooldef_to_chat_tool,
 )
+from llama_stack.providers.inline.agents.meta_reference.responses.types import ChatCompletionContext
+
+
+@pytest.fixture
+def mock_safety_api():
+    safety_api = AsyncMock()
+    return safety_api
+
+
+@pytest.fixture
+def mock_inference_api():
+    inference_api = AsyncMock()
+    return inference_api
+
+
+@pytest.fixture
+def mock_context():
+    context = AsyncMock(spec=ChatCompletionContext)
+    # Add required attributes that StreamingResponseOrchestrator expects
+    context.tool_context = AsyncMock()
+    context.tool_context.previous_tools = {}
+    context.messages = []
+    return context
 
 
 def test_convert_tooldef_to_chat_tool_preserves_items_field():
@@ -36,3 +70,89 @@ def test_convert_tooldef_to_chat_tool_preserves_items_field():
     assert tags_param["type"] == "array"
     assert "items" in tags_param, "items field should be preserved for array parameters"
     assert tags_param["items"] == {"type": "string"}
+
+
+async def test_check_input_safety_no_violation(mock_safety_api, mock_inference_api, mock_context):
+    """Test input shield validation with no violations."""
+    messages = [UserMessage(content="Hello world")]
+    shield_ids = ["llama-guard"]
+
+    # Mock successful shield validation (no violation)
+    mock_response = AsyncMock()
+    mock_response.violation = None
+    mock_safety_api.run_shield.return_value = mock_response
+
+    # Create orchestrator with safety components
+    orchestrator = StreamingResponseOrchestrator(
+        inference_api=mock_inference_api,
+        ctx=mock_context,
+        response_id="test_id",
+        created_at=1234567890,
+        text=OpenAIResponseText(),
+        max_infer_iters=5,
+        tool_executor=AsyncMock(),
+        safety_api=mock_safety_api,
+        shield_ids=shield_ids,
+    )
+
+    result = await orchestrator._check_input_safety(messages)
+
+    assert result is None
+    mock_safety_api.run_shield.assert_called_once_with(shield_id="llama-guard", messages=messages, params={})
+
+
+async def test_check_input_safety_with_violation(mock_safety_api, mock_inference_api, mock_context):
+    """Test input shield validation with safety violation."""
+    messages = [UserMessage(content="Harmful content")]
+    shield_ids = ["llama-guard"]
+
+    # Mock shield violation
+    violation = SafetyViolation(
+        violation_level=ViolationLevel.ERROR, user_message="Content violates safety guidelines", metadata={}
+    )
+    mock_response = AsyncMock()
+    mock_response.violation = violation
+    mock_safety_api.run_shield.return_value = mock_response
+
+    # Create orchestrator with safety components
+    orchestrator = StreamingResponseOrchestrator(
+        inference_api=mock_inference_api,
+        ctx=mock_context,
+        response_id="test_id",
+        created_at=1234567890,
+        text=OpenAIResponseText(),
+        max_infer_iters=5,
+        tool_executor=AsyncMock(),
+        safety_api=mock_safety_api,
+        shield_ids=shield_ids,
+    )
+
+    result = await orchestrator._check_input_safety(messages)
+
+    assert isinstance(result, OpenAIResponseContentPartRefusal)
+    assert result.refusal == "Content violates safety guidelines"
+
+
+async def test_check_input_safety_empty_inputs(mock_safety_api, mock_inference_api, mock_context):
+    """Test input shield validation with empty inputs."""
+    # Create orchestrator with safety components
+    orchestrator = StreamingResponseOrchestrator(
+        inference_api=mock_inference_api,
+        ctx=mock_context,
+        response_id="test_id",
+        created_at=1234567890,
+        text=OpenAIResponseText(),
+        max_infer_iters=5,
+        tool_executor=AsyncMock(),
+        safety_api=mock_safety_api,
+        shield_ids=[],
+    )
+
+    # Test empty shield_ids
+    result = await orchestrator._check_input_safety([UserMessage(content="test")])
+    assert result is None
+
+    # Test empty messages
+    orchestrator.shield_ids = ["llama-guard"]
+    result = await orchestrator._check_input_safety([])
+    assert result is None