Merge branch 'embeddings' of https://github.com/hardikjshah/llama-stack into embeddings

tests/integration/inference/test_openai_completion.py

@@ -268,9 +268,9 @@ def test_openai_chat_completion_streaming_with_n(compat_client, client_with_mode
         False,
     ],
 )
-def test_inference_store(openai_client, client_with_models, text_model_id, stream):
+def test_inference_store(compat_client, client_with_models, text_model_id, stream):
     skip_if_model_doesnt_support_openai_chat_completion(client_with_models, text_model_id)
-    client = openai_client
+    client = compat_client
     # make a chat completion
     message = "Hello, world!"
     response = client.chat.completions.create(
@@ -301,9 +301,14 @@ def test_inference_store(openai_client, client_with_models, text_model_id, strea
 
     retrieved_response = client.chat.completions.retrieve(response_id)
     assert retrieved_response.id == response_id
-    assert retrieved_response.input_messages[0]["content"] == message, retrieved_response
     assert retrieved_response.choices[0].message.content == content, retrieved_response
 
+    input_content = (
+        getattr(retrieved_response.input_messages[0], "content", None)
+        or retrieved_response.input_messages[0]["content"]
+    )
+    assert input_content == message, retrieved_response
+
 
 @pytest.mark.parametrize(
     "stream",
@@ -312,9 +317,9 @@ def test_inference_store(openai_client, client_with_models, text_model_id, strea
         False,
     ],
 )
-def test_inference_store_tool_calls(openai_client, client_with_models, text_model_id, stream):
+def test_inference_store_tool_calls(compat_client, client_with_models, text_model_id, stream):
     skip_if_model_doesnt_support_openai_chat_completion(client_with_models, text_model_id)
-    client = openai_client
+    client = compat_client
     # make a chat completion
     message = "What's the weather in Tokyo? Use the get_weather function to get the weather."
     response = client.chat.completions.create(
@@ -361,7 +366,11 @@ def test_inference_store_tool_calls(openai_client, client_with_models, text_mode
 
     retrieved_response = client.chat.completions.retrieve(response_id)
     assert retrieved_response.id == response_id
-    assert retrieved_response.input_messages[0]["content"] == message
+    input_content = (
+        getattr(retrieved_response.input_messages[0], "content", None)
+        or retrieved_response.input_messages[0]["content"]
+    )
+    assert input_content == message, retrieved_response
     tool_calls = retrieved_response.choices[0].message.tool_calls
     # sometimes model doesn't ouptut tool calls, but we still want to test that the tool was called
     if tool_calls:

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

@@ -628,3 +628,69 @@ async def test_responses_store_list_input_items_logic():
     result = await responses_store.list_response_input_items("resp_123", limit=0, order=Order.asc)
     assert result.object == "list"
     assert len(result.data) == 0  # Should return no items
+
+
+@pytest.mark.asyncio
+async def test_store_response_uses_rehydrated_input_with_previous_response(
+    openai_responses_impl, mock_responses_store, mock_inference_api
+):
+    """Test that _store_response uses the full re-hydrated input (including previous responses)
+    rather than just the original input when previous_response_id is provided."""
+
+    # Setup - Create a previous response that should be included in the stored input
+    previous_response = OpenAIResponseObjectWithInput(
+        id="resp-previous-123",
+        object="response",
+        created_at=1234567890,
+        model="meta-llama/Llama-3.1-8B-Instruct",
+        status="completed",
+        input=[
+            OpenAIResponseMessage(
+                id="msg-prev-user", role="user", content=[OpenAIResponseInputMessageContentText(text="What is 2+2?")]
+            )
+        ],
+        output=[
+            OpenAIResponseMessage(
+                id="msg-prev-assistant",
+                role="assistant",
+                content=[OpenAIResponseOutputMessageContentOutputText(text="2+2 equals 4.")],
+            )
+        ],
+    )
+
+    mock_responses_store.get_response_object.return_value = previous_response
+
+    current_input = "Now what is 3+3?"
+    model = "meta-llama/Llama-3.1-8B-Instruct"
+    mock_chat_completion = load_chat_completion_fixture("simple_chat_completion.yaml")
+    mock_inference_api.openai_chat_completion.return_value = mock_chat_completion
+
+    # Execute - Create response with previous_response_id
+    result = await openai_responses_impl.create_openai_response(
+        input=current_input,
+        model=model,
+        previous_response_id="resp-previous-123",
+        store=True,
+    )
+
+    store_call_args = mock_responses_store.store_response_object.call_args
+    stored_input = store_call_args.kwargs["input"]
+
+    # Verify that the stored input contains the full re-hydrated conversation:
+    # 1. Previous user message
+    # 2. Previous assistant response
+    # 3. Current user message
+    assert len(stored_input) == 3
+
+    assert stored_input[0].role == "user"
+    assert stored_input[0].content[0].text == "What is 2+2?"
+
+    assert stored_input[1].role == "assistant"
+    assert stored_input[1].content[0].text == "2+2 equals 4."
+
+    assert stored_input[2].role == "user"
+    assert stored_input[2].content == "Now what is 3+3?"
+
+    # Verify the response itself is correct
+    assert result.model == model
+    assert result.status == "completed"

tests/unit/utils/test_sqlstore.py

@@ -9,7 +9,7 @@ from tempfile import TemporaryDirectory
 import pytest
 
 from llama_stack.providers.utils.sqlstore.api import ColumnType
-from llama_stack.providers.utils.sqlstore.sqlite.sqlite import SqliteSqlStoreImpl
+from llama_stack.providers.utils.sqlstore.sqlalchemy_sqlstore import SqlAlchemySqlStoreImpl
 from llama_stack.providers.utils.sqlstore.sqlstore import SqliteSqlStoreConfig
 
 
@@ -17,7 +17,7 @@ from llama_stack.providers.utils.sqlstore.sqlstore import SqliteSqlStoreConfig
 async def test_sqlite_sqlstore():
     with TemporaryDirectory() as tmp_dir:
         db_name = "test.db"
-        sqlstore = SqliteSqlStoreImpl(
+        sqlstore = SqlAlchemySqlStoreImpl(
             SqliteSqlStoreConfig(
                 db_path=tmp_dir + "/" + db_name,
             )