diff --git a/scripts/integration-tests.sh b/scripts/integration-tests.sh index 0951feb14..8b0002125 100755 --- a/scripts/integration-tests.sh +++ b/scripts/integration-tests.sh @@ -162,6 +162,17 @@ if [[ "$COLLECT_ONLY" == false ]]; then export LLAMA_STACK_TEST_STACK_CONFIG_TYPE="library_client" echo "Setting stack config type: library_client" fi + + # Set MCP host for in-process MCP server tests + # - For library client and server mode: localhost (both on same host) + # - For docker mode: host.docker.internal (container needs to reach host) + if [[ "$STACK_CONFIG" == docker:* ]]; then + export LLAMA_STACK_TEST_MCP_HOST="host.docker.internal" + echo "Setting MCP host: host.docker.internal (docker mode)" + else + export LLAMA_STACK_TEST_MCP_HOST="localhost" + echo "Setting MCP host: localhost (library/server mode)" + fi fi SETUP_ENV=$(PYTHONPATH=$THIS_DIR/.. python "$THIS_DIR/get_setup_env.py" --suite "$TEST_SUITE" --setup "$TEST_SETUP" --format bash) @@ -338,6 +349,7 @@ if [[ "$STACK_CONFIG" == *"docker:"* && "$COLLECT_ONLY" == false ]]; then DOCKER_ENV_VARS="" DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e LLAMA_STACK_TEST_INFERENCE_MODE=$INFERENCE_MODE" DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e LLAMA_STACK_TEST_STACK_CONFIG_TYPE=server" + DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e LLAMA_STACK_TEST_MCP_HOST=${LLAMA_STACK_TEST_MCP_HOST:-host.docker.internal}" # Disabled: https://github.com/llamastack/llama-stack/issues/4089 #DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:${COLLECTOR_PORT}" DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e OTEL_METRIC_EXPORT_INTERVAL=200" @@ -371,8 +383,11 @@ if [[ "$STACK_CONFIG" == *"docker:"* && "$COLLECT_ONLY" == false ]]; then # Use regular port mapping instead NETWORK_MODE="" PORT_MAPPINGS="" + ADD_HOST_FLAG="" if [[ "$(uname)" != "Darwin" ]] && [[ "$(uname)" != *"MINGW"* ]]; then NETWORK_MODE="--network host" + # On Linux with host network, also add host.docker.internal mapping for consistency + ADD_HOST_FLAG="--add-host=host.docker.internal:host-gateway" else # On non-Linux (macOS, Windows), need explicit port mappings for both app and telemetry PORT_MAPPINGS="-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT -p $COLLECTOR_PORT:$COLLECTOR_PORT" @@ -381,6 +396,7 @@ if [[ "$STACK_CONFIG" == *"docker:"* && "$COLLECT_ONLY" == false ]]; then docker run -d $NETWORK_MODE --name "$container_name" \ $PORT_MAPPINGS \ + $ADD_HOST_FLAG \ $DOCKER_ENV_VARS \ "$IMAGE_NAME" \ --port $LLAMA_STACK_PORT diff --git a/tests/common/mcp.py b/tests/common/mcp.py index 644becd2d..085575ec0 100644 --- a/tests/common/mcp.py +++ b/tests/common/mcp.py @@ -244,8 +244,14 @@ def make_mcp_server(required_auth_token: str | None = None, tools: dict[str, Cal timeout = 2 start_time = time.time() - server_url = f"http://localhost:{port}/sse" - logger.debug(f"Waiting for MCP server thread to start on port {port}") + # Determine the appropriate host for the server URL based on test environment + # - For library client and server mode: use localhost (both on same host) + # - For docker mode: use host.docker.internal (container needs to reach host) + import os + + mcp_host = os.environ.get("LLAMA_STACK_TEST_MCP_HOST", "localhost") + server_url = f"http://{mcp_host}:{port}/sse" + logger.debug(f"Waiting for MCP server thread to start on port {port} (accessible via {mcp_host})") while time.time() - start_time < timeout: if server_thread.is_alive(): diff --git a/tests/integration/responses/conftest.py b/tests/integration/responses/conftest.py new file mode 100644 index 000000000..c29575072 --- /dev/null +++ b/tests/integration/responses/conftest.py @@ -0,0 +1,17 @@ +# 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 pytest + +from llama_stack.core.library_client import LlamaStackAsLibraryClient + + +@pytest.fixture +def responses_client(compat_client): + """Provide a client for responses tests, skipping library client mode.""" + if isinstance(compat_client, LlamaStackAsLibraryClient): + pytest.skip("Responses API tests are not supported in library client mode") + return compat_client diff --git a/tests/integration/responses/recordings/0a4aca0cd075369aaf6133ee82d9d940455cb083c0fd1330c666a12d74df6f89.json b/tests/integration/responses/recordings/0a4aca0cd075369aaf6133ee82d9d940455cb083c0fd1330c666a12d74df6f89.json new file mode 100644 index 000000000..9b432130b --- /dev/null +++ b/tests/integration/responses/recordings/0a4aca0cd075369aaf6133ee82d9d940455cb083c0fd1330c666a12d74df6f89.json @@ -0,0 +1,549 @@ +{ + "test_id": "tests/integration/responses/test_tool_responses.py::test_response_streaming_multi_turn_tool_execution[openai_client-txt=openai/gpt-4o-experiment_analysis_streaming]", + "request": { + "method": "POST", + "url": "https://api.openai.com/v1/v1/chat/completions", + "headers": {}, + "body": { + "model": "gpt-4o", + "messages": [ + { + "role": "user", + "content": "I need a complete analysis: First, get the experiment ID for 'chemical_reaction', then get the results for that experiment, and tell me if the yield was above 80%. Return only one tool call per step. Please stream your analysis process." + }, + { + "role": "assistant", + "content": "", + "tool_calls": [ + { + "index": 0, + "id": "call_Q9Gcxub7UbQsxJWVkiy4FETr", + "type": "function", + "function": { + "name": "get_experiment_id", + "arguments": "{\"experiment_name\":\"chemical_reaction\"}" + } + } + ] + }, + { + "role": "tool", + "tool_call_id": "call_Q9Gcxub7UbQsxJWVkiy4FETr", + "content": [ + { + "type": "text", + "text": "exp_003" + } + ] + } + ], + "stream": true, + "stream_options": { + "include_usage": true + }, + "tools": [ + { + "type": "function", + "function": { + "name": "get_user_id", + "description": "\n Get the user ID for a given username. 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test_response_non_streaming_basic(compat_client, text_model_id, case): - response = compat_client.responses.create( +def test_response_non_streaming_basic(responses_client, text_model_id, case): + response = responses_client.responses.create( model=text_model_id, input=case.input, stream=False, @@ -31,10 +31,10 @@ def test_response_non_streaming_basic(compat_client, text_model_id, case): "Total tokens should equal input + output tokens" ) - retrieved_response = compat_client.responses.retrieve(response_id=response.id) + retrieved_response = responses_client.responses.retrieve(response_id=response.id) assert retrieved_response.output_text == response.output_text - next_response = compat_client.responses.create( + next_response = responses_client.responses.create( model=text_model_id, input="Repeat your previous response in all caps.", previous_response_id=response.id, @@ -44,8 +44,8 @@ def test_response_non_streaming_basic(compat_client, text_model_id, case): @pytest.mark.parametrize("case", basic_test_cases) -def test_response_streaming_basic(compat_client, text_model_id, case): - response = compat_client.responses.create( +def test_response_streaming_basic(responses_client, text_model_id, case): + response = responses_client.responses.create( model=text_model_id, input=case.input, stream=True, @@ -98,15 +98,15 @@ def test_response_streaming_basic(compat_client, text_model_id, case): validator.assert_response_consistency() # Verify stored response matches streamed response - retrieved_response = compat_client.responses.retrieve(response_id=response_id) + retrieved_response = responses_client.responses.retrieve(response_id=response_id) final_event = events[-1] assert retrieved_response.output_text == final_event.response.output_text @pytest.mark.parametrize("case", basic_test_cases) -def test_response_streaming_incremental_content(compat_client, text_model_id, case): +def test_response_streaming_incremental_content(responses_client, text_model_id, case): """Test that streaming actually delivers content incrementally, not just at the end.""" - response = compat_client.responses.create( + response = responses_client.responses.create( model=text_model_id, input=case.input, stream=True, @@ -170,10 +170,10 @@ def test_response_streaming_incremental_content(compat_client, text_model_id, ca @pytest.mark.parametrize("case", multi_turn_test_cases) -def test_response_non_streaming_multi_turn(compat_client, text_model_id, case): +def test_response_non_streaming_multi_turn(responses_client, text_model_id, case): previous_response_id = None for turn_input, turn_expected in case.turns: - response = compat_client.responses.create( + response = responses_client.responses.create( model=text_model_id, input=turn_input, previous_response_id=previous_response_id, @@ -184,8 +184,8 @@ def test_response_non_streaming_multi_turn(compat_client, text_model_id, case): @pytest.mark.parametrize("case", image_test_cases) -def test_response_non_streaming_image(compat_client, text_model_id, case): - response = compat_client.responses.create( +def test_response_non_streaming_image(responses_client, text_model_id, case): + response = responses_client.responses.create( model=text_model_id, input=case.input, stream=False, @@ -195,10 +195,10 @@ def test_response_non_streaming_image(compat_client, text_model_id, case): @pytest.mark.parametrize("case", multi_turn_image_test_cases) -def test_response_non_streaming_multi_turn_image(compat_client, text_model_id, case): +def test_response_non_streaming_multi_turn_image(responses_client, text_model_id, case): previous_response_id = None for turn_input, turn_expected in case.turns: - response = compat_client.responses.create( + response = responses_client.responses.create( model=text_model_id, input=turn_input, previous_response_id=previous_response_id, diff --git a/tests/integration/responses/test_conversation_responses.py b/tests/integration/responses/test_conversation_responses.py index babb77793..bbd861e0d 100644 --- a/tests/integration/responses/test_conversation_responses.py +++ b/tests/integration/responses/test_conversation_responses.py @@ -131,18 +131,18 @@ class TestConversationResponses: assert len(response.output_text.strip()) > 0 # this is not ready yet - # def test_conversation_compat_client(self, compat_client, text_model_id): + # def test_conversation_compat_client(self, responses_client, text_model_id): # """Test conversation parameter works with compatibility client.""" - # if not hasattr(compat_client, "conversations"): - # pytest.skip("compat_client does not support conversations API") + # if not hasattr(responses_client, "conversations"): + # pytest.skip("responses_client does not support conversations API") # - # conversation = compat_client.conversations.create() - # response = compat_client.responses.create( + # conversation = responses_client.conversations.create() + # response = responses_client.responses.create( # model=text_model_id, input="Tell me a joke", conversation=conversation.id # ) # # assert response is not None # assert len(response.output_text.strip()) > 0 # - # conversation_items = compat_client.conversations.items.list(conversation.id) + # conversation_items = responses_client.conversations.items.list(conversation.id) # assert len(conversation_items.data) >= 2 diff --git a/tests/integration/responses/test_file_search.py b/tests/integration/responses/test_file_search.py index dde5fd7f6..b2a634fb0 100644 --- a/tests/integration/responses/test_file_search.py +++ b/tests/integration/responses/test_file_search.py @@ -9,8 +9,6 @@ import time import pytest -from llama_stack.core.library_client import LlamaStackAsLibraryClient - from .helpers import new_vector_store, upload_file @@ -28,12 +26,9 @@ from .helpers import new_vector_store, upload_file }, ], ) -def test_response_text_format(compat_client, text_model_id, text_format): - if isinstance(compat_client, LlamaStackAsLibraryClient): - pytest.skip("Responses API text format is not yet supported in library client.") - +def test_response_text_format(responses_client, text_model_id, text_format): stream = False - response = compat_client.responses.create( + response = responses_client.responses.create( model=text_model_id, input="What is the capital of France?", stream=stream, @@ -47,13 +42,10 @@ def test_response_text_format(compat_client, text_model_id, text_format): @pytest.fixture -def vector_store_with_filtered_files(compat_client, embedding_model_id, embedding_dimension, tmp_path_factory): +def vector_store_with_filtered_files(responses_client, embedding_model_id, embedding_dimension, tmp_path_factory): # """Create a vector store with multiple files that have different attributes for filtering tests.""" - if isinstance(compat_client, LlamaStackAsLibraryClient): - pytest.skip("upload_file() is not yet supported in library client somehow?") - vector_store = new_vector_store( - compat_client, "test_vector_store_with_filters", embedding_model_id, embedding_dimension + responses_client, "test_vector_store_with_filters", embedding_model_id, embedding_dimension ) tmp_path = tmp_path_factory.mktemp("filter_test_files") @@ -104,11 +96,11 @@ def vector_store_with_filtered_files(compat_client, embedding_model_id, embeddin file_path.write_text(file_data["content"]) # Upload file - file_response = upload_file(compat_client, file_data["name"], str(file_path)) + file_response = upload_file(responses_client, file_data["name"], str(file_path)) file_ids.append(file_response.id) # Attach file to vector store with attributes - file_attach_response = compat_client.vector_stores.files.create( + file_attach_response = responses_client.vector_stores.files.create( vector_store_id=vector_store.id, file_id=file_response.id, attributes=file_data["attributes"], @@ -117,7 +109,7 @@ def vector_store_with_filtered_files(compat_client, embedding_model_id, embeddin # Wait for attachment while file_attach_response.status == "in_progress": time.sleep(0.1) - file_attach_response = compat_client.vector_stores.files.retrieve( + file_attach_response = responses_client.vector_stores.files.retrieve( vector_store_id=vector_store.id, file_id=file_response.id, ) @@ -127,17 +119,17 @@ def vector_store_with_filtered_files(compat_client, embedding_model_id, embeddin # Cleanup: delete vector store and files try: - compat_client.vector_stores.delete(vector_store_id=vector_store.id) + responses_client.vector_stores.delete(vector_store_id=vector_store.id) for file_id in file_ids: try: - compat_client.files.delete(file_id=file_id) + responses_client.files.delete(file_id=file_id) except Exception: pass # File might already be deleted except Exception: pass # Best effort cleanup -def test_response_file_search_filter_by_region(compat_client, text_model_id, vector_store_with_filtered_files): +def test_response_file_search_filter_by_region(responses_client, text_model_id, vector_store_with_filtered_files): """Test file search with region equality filter.""" tools = [ { @@ -147,7 +139,7 @@ def test_response_file_search_filter_by_region(compat_client, text_model_id, vec } ] - response = compat_client.responses.create( + response = responses_client.responses.create( model=text_model_id, input="What are the updates from the US region?", tools=tools, @@ -168,7 +160,7 @@ def test_response_file_search_filter_by_region(compat_client, text_model_id, vec assert "asia" not in result.text.lower() -def test_response_file_search_filter_by_category(compat_client, text_model_id, vector_store_with_filtered_files): +def test_response_file_search_filter_by_category(responses_client, text_model_id, vector_store_with_filtered_files): """Test file search with category equality filter.""" tools = [ { @@ -178,7 +170,7 @@ def test_response_file_search_filter_by_category(compat_client, text_model_id, v } ] - response = compat_client.responses.create( + response = responses_client.responses.create( model=text_model_id, input="Show me all marketing reports", tools=tools, @@ -198,7 +190,7 @@ def test_response_file_search_filter_by_category(compat_client, text_model_id, v assert "revenue figures" not in result.text.lower() -def test_response_file_search_filter_by_date_range(compat_client, text_model_id, vector_store_with_filtered_files): +def test_response_file_search_filter_by_date_range(responses_client, text_model_id, vector_store_with_filtered_files): """Test file search with date range filter using compound AND.""" tools = [ { @@ -222,7 +214,7 @@ def test_response_file_search_filter_by_date_range(compat_client, text_model_id, } ] - response = compat_client.responses.create( + response = responses_client.responses.create( model=text_model_id, input="What happened in Q1 2023?", tools=tools, @@ -241,7 +233,7 @@ def test_response_file_search_filter_by_date_range(compat_client, text_model_id, assert "q3" not in result.text.lower() -def test_response_file_search_filter_compound_and(compat_client, text_model_id, vector_store_with_filtered_files): +def test_response_file_search_filter_compound_and(responses_client, text_model_id, vector_store_with_filtered_files): """Test file search with compound AND filter (region AND category).""" tools = [ { @@ -257,7 +249,7 @@ def test_response_file_search_filter_compound_and(compat_client, text_model_id, } ] - response = compat_client.responses.create( + response = responses_client.responses.create( model=text_model_id, input="What are the engineering updates from the US?", tools=tools, @@ -277,7 +269,7 @@ def test_response_file_search_filter_compound_and(compat_client, text_model_id, assert "promotional" not in result.text.lower() and "revenue" not in result.text.lower() -def test_response_file_search_filter_compound_or(compat_client, text_model_id, vector_store_with_filtered_files): +def test_response_file_search_filter_compound_or(responses_client, text_model_id, vector_store_with_filtered_files): """Test file search with compound OR filter (marketing OR sales).""" tools = [ { @@ -293,7 +285,7 @@ def test_response_file_search_filter_compound_or(compat_client, text_model_id, v } ] - response = compat_client.responses.create( + response = responses_client.responses.create( model=text_model_id, input="Show me marketing and sales documents", tools=tools, @@ -320,7 +312,7 @@ def test_response_file_search_filter_compound_or(compat_client, text_model_id, v assert categories_found.issubset({"marketing", "sales"}), f"Found unexpected categories: {categories_found}" -def test_response_file_search_streaming_events(compat_client, text_model_id, vector_store_with_filtered_files): +def test_response_file_search_streaming_events(responses_client, text_model_id, vector_store_with_filtered_files): """Test that file search emits proper streaming events (in_progress, searching, completed).""" tools = [ { @@ -329,7 +321,7 @@ def test_response_file_search_streaming_events(compat_client, text_model_id, vec } ] - stream = compat_client.responses.create( + stream = responses_client.responses.create( model=text_model_id, input="What are the marketing updates?", tools=tools, diff --git a/tests/integration/responses/test_tool_responses.py b/tests/integration/responses/test_tool_responses.py index 9bf58c6ff..2c7c7ef34 100644 --- a/tests/integration/responses/test_tool_responses.py +++ b/tests/integration/responses/test_tool_responses.py @@ -9,6 +9,7 @@ import logging # allow-direct-logging import os import httpx +import llama_stack_client import openai import pytest @@ -29,8 +30,8 @@ from .streaming_assertions import StreamingValidator @pytest.mark.parametrize("case", web_search_test_cases) -def test_response_non_streaming_web_search(compat_client, text_model_id, case): - response = compat_client.responses.create( +def test_response_non_streaming_web_search(responses_client, text_model_id, case): + response = responses_client.responses.create( model=text_model_id, input=case.input, tools=case.tools, @@ -48,12 +49,9 @@ def test_response_non_streaming_web_search(compat_client, text_model_id, case): @pytest.mark.parametrize("case", file_search_test_cases) def test_response_non_streaming_file_search( - compat_client, text_model_id, embedding_model_id, embedding_dimension, tmp_path, case + responses_client, text_model_id, embedding_model_id, embedding_dimension, tmp_path, case ): - if isinstance(compat_client, LlamaStackAsLibraryClient): - pytest.skip("Responses API file search is not yet supported in library client.") - - vector_store = new_vector_store(compat_client, "test_vector_store", embedding_model_id, embedding_dimension) + vector_store = new_vector_store(responses_client, "test_vector_store", embedding_model_id, embedding_dimension) if case.file_content: file_name = "test_response_non_streaming_file_search.txt" @@ -65,16 +63,16 @@ def test_response_non_streaming_file_search( else: raise ValueError("No file content or path provided for case") - file_response = upload_file(compat_client, file_name, file_path) + file_response = upload_file(responses_client, file_name, file_path) # Attach our file to the vector store - compat_client.vector_stores.files.create( + responses_client.vector_stores.files.create( vector_store_id=vector_store.id, file_id=file_response.id, ) # Wait for the file to be attached - wait_for_file_attachment(compat_client, vector_store.id, file_response.id) + wait_for_file_attachment(responses_client, vector_store.id, file_response.id) # Update our tools with the right vector store id tools = case.tools @@ -83,7 +81,7 @@ def test_response_non_streaming_file_search( tool["vector_store_ids"] = [vector_store.id] # Create the response request, which should query our vector store - response = compat_client.responses.create( + response = responses_client.responses.create( model=text_model_id, input=case.input, tools=tools, @@ -105,15 +103,12 @@ def test_response_non_streaming_file_search( def test_response_non_streaming_file_search_empty_vector_store( - compat_client, text_model_id, embedding_model_id, embedding_dimension + responses_client, text_model_id, embedding_model_id, embedding_dimension ): - if isinstance(compat_client, LlamaStackAsLibraryClient): - pytest.skip("Responses API file search is not yet supported in library client.") - - vector_store = new_vector_store(compat_client, "test_vector_store", embedding_model_id, embedding_dimension) + vector_store = new_vector_store(responses_client, "test_vector_store", embedding_model_id, embedding_dimension) # Create the response request, which should query our vector store - response = compat_client.responses.create( + response = responses_client.responses.create( model=text_model_id, input="How many experts does the Llama 4 Maverick model have?", tools=[{"type": "file_search", "vector_store_ids": [vector_store.id]}], @@ -133,13 +128,10 @@ def test_response_non_streaming_file_search_empty_vector_store( def test_response_sequential_file_search( - compat_client, text_model_id, embedding_model_id, embedding_dimension, tmp_path + responses_client, text_model_id, embedding_model_id, embedding_dimension, tmp_path ): """Test file search with sequential responses using previous_response_id.""" - if isinstance(compat_client, LlamaStackAsLibraryClient): - pytest.skip("Responses API file search is not yet supported in library client.") - - vector_store = new_vector_store(compat_client, "test_vector_store", embedding_model_id, embedding_dimension) + vector_store = new_vector_store(responses_client, "test_vector_store", embedding_model_id, embedding_dimension) # Create a test file with content file_content = "The Llama 4 Maverick model has 128 experts in its mixture of experts architecture." @@ -147,21 +139,21 @@ def test_response_sequential_file_search( file_path = tmp_path / file_name file_path.write_text(file_content) - file_response = upload_file(compat_client, file_name, file_path) + file_response = upload_file(responses_client, file_name, file_path) # Attach the file to the vector store - compat_client.vector_stores.files.create( + responses_client.vector_stores.files.create( vector_store_id=vector_store.id, file_id=file_response.id, ) # Wait for the file to be attached - wait_for_file_attachment(compat_client, vector_store.id, file_response.id) + wait_for_file_attachment(responses_client, vector_store.id, file_response.id) tools = [{"type": "file_search", "vector_store_ids": [vector_store.id]}] # First response request with file search - response = compat_client.responses.create( + response = responses_client.responses.create( model=text_model_id, input="How many experts does the Llama 4 Maverick model have?", tools=tools, @@ -178,7 +170,7 @@ def test_response_sequential_file_search( assert "128" in response.output_text or "experts" in response.output_text.lower() # Second response request using previous_response_id - response2 = compat_client.responses.create( + response2 = responses_client.responses.create( model=text_model_id, input="Can you tell me more about the architecture?", tools=tools, @@ -199,14 +191,11 @@ def test_response_sequential_file_search( @pytest.mark.parametrize("case", mcp_tool_test_cases) -def test_response_non_streaming_mcp_tool(compat_client, text_model_id, case, caplog): - if not isinstance(compat_client, LlamaStackAsLibraryClient): - pytest.skip("in-process MCP server is only supported in library client") - +def test_response_non_streaming_mcp_tool(responses_client, text_model_id, case, caplog): with make_mcp_server() as mcp_server_info: tools = setup_mcp_tools(case.tools, mcp_server_info) - response = compat_client.responses.create( + response = responses_client.responses.create( model=text_model_id, input=case.input, tools=tools, @@ -243,15 +232,15 @@ def test_response_non_streaming_mcp_tool(compat_client, text_model_id, case, cap exc_type = ( AuthenticationRequiredError - if isinstance(compat_client, LlamaStackAsLibraryClient) - else (httpx.HTTPStatusError, openai.AuthenticationError) + if isinstance(responses_client, LlamaStackAsLibraryClient) + else (httpx.HTTPStatusError, openai.AuthenticationError, llama_stack_client.AuthenticationError) ) # Suppress expected auth error logs only for the failing auth attempt with caplog.at_level( logging.CRITICAL, logger="llama_stack.providers.inline.agents.meta_reference.responses.streaming" ): with pytest.raises(exc_type): - compat_client.responses.create( + responses_client.responses.create( model=text_model_id, input=case.input, tools=tools, @@ -262,7 +251,7 @@ def test_response_non_streaming_mcp_tool(compat_client, text_model_id, case, cap if tool["type"] == "mcp": tool["headers"] = {"Authorization": "Bearer test-token"} - response = compat_client.responses.create( + response = responses_client.responses.create( model=text_model_id, input=case.input, tools=tools, @@ -272,14 +261,11 @@ def test_response_non_streaming_mcp_tool(compat_client, text_model_id, case, cap @pytest.mark.parametrize("case", mcp_tool_test_cases) -def test_response_sequential_mcp_tool(compat_client, text_model_id, case): - if not isinstance(compat_client, LlamaStackAsLibraryClient): - pytest.skip("in-process MCP server is only supported in library client") - +def test_response_sequential_mcp_tool(responses_client, text_model_id, case): with make_mcp_server() as mcp_server_info: tools = setup_mcp_tools(case.tools, mcp_server_info) - response = compat_client.responses.create( + response = responses_client.responses.create( model=text_model_id, input=case.input, tools=tools, @@ -311,7 +297,7 @@ def test_response_sequential_mcp_tool(compat_client, text_model_id, case): text_content = message.content[0].text assert "boiling point" in text_content.lower() - response2 = compat_client.responses.create( + response2 = responses_client.responses.create( model=text_model_id, input=case.input, tools=tools, stream=False, previous_response_id=response.id ) @@ -323,16 +309,13 @@ def test_response_sequential_mcp_tool(compat_client, text_model_id, case): @pytest.mark.parametrize("case", mcp_tool_test_cases) @pytest.mark.parametrize("approve", [True, False]) -def test_response_mcp_tool_approval(compat_client, text_model_id, case, approve): - if not isinstance(compat_client, LlamaStackAsLibraryClient): - pytest.skip("in-process MCP server is only supported in library client") - +def test_response_mcp_tool_approval(responses_client, text_model_id, case, approve): with make_mcp_server() as mcp_server_info: tools = setup_mcp_tools(case.tools, mcp_server_info) for tool in tools: tool["require_approval"] = "always" - response = compat_client.responses.create( + response = responses_client.responses.create( model=text_model_id, input=case.input, tools=tools, @@ -352,13 +335,13 @@ def test_response_mcp_tool_approval(compat_client, text_model_id, case, approve) approval_request = response.output[1] assert approval_request.type == "mcp_approval_request" assert approval_request.name == "get_boiling_point" - assert json.loads(approval_request.arguments) == { - "liquid_name": "myawesomeliquid", - "celsius": True, - } + args = json.loads(approval_request.arguments) + assert args["liquid_name"] == "myawesomeliquid" + # celsius has a default value of True, so it may be omitted or explicitly set + assert args.get("celsius", True) is True # send approval response - response = compat_client.responses.create( + response = responses_client.responses.create( previous_response_id=response.id, model=text_model_id, input=[{"type": "mcp_approval_response", "approval_request_id": approval_request.id, "approve": approve}], @@ -398,8 +381,8 @@ def test_response_mcp_tool_approval(compat_client, text_model_id, case, approve) @pytest.mark.parametrize("case", custom_tool_test_cases) -def test_response_non_streaming_custom_tool(compat_client, text_model_id, case): - response = compat_client.responses.create( +def test_response_non_streaming_custom_tool(responses_client, text_model_id, case): + response = responses_client.responses.create( model=text_model_id, input=case.input, tools=case.tools, @@ -412,8 +395,8 @@ def test_response_non_streaming_custom_tool(compat_client, text_model_id, case): @pytest.mark.parametrize("case", custom_tool_test_cases) -def test_response_function_call_ordering_1(compat_client, text_model_id, case): - response = compat_client.responses.create( +def test_response_function_call_ordering_1(responses_client, text_model_id, case): + response = responses_client.responses.create( model=text_model_id, input=case.input, tools=case.tools, @@ -437,13 +420,13 @@ def test_response_function_call_ordering_1(compat_client, text_model_id, case): "call_id": response.output[0].call_id, } ) - response = compat_client.responses.create( + response = responses_client.responses.create( model=text_model_id, input=inputs, tools=case.tools, stream=False, previous_response_id=response.id ) assert len(response.output) == 1 -def test_response_function_call_ordering_2(compat_client, text_model_id): +def test_response_function_call_ordering_2(responses_client, text_model_id): tools = [ { "type": "function", @@ -468,7 +451,7 @@ def test_response_function_call_ordering_2(compat_client, text_model_id): "content": "Is the weather better in San Francisco or Los Angeles?", } ] - response = compat_client.responses.create( + response = responses_client.responses.create( model=text_model_id, input=inputs, tools=tools, @@ -489,7 +472,7 @@ def test_response_function_call_ordering_2(compat_client, text_model_id): "call_id": output.call_id, } ) - response = compat_client.responses.create( + response = responses_client.responses.create( model=text_model_id, input=inputs, tools=tools, @@ -500,15 +483,12 @@ def test_response_function_call_ordering_2(compat_client, text_model_id): @pytest.mark.parametrize("case", multi_turn_tool_execution_test_cases) -def test_response_non_streaming_multi_turn_tool_execution(compat_client, text_model_id, case): +def test_response_non_streaming_multi_turn_tool_execution(responses_client, text_model_id, case): """Test multi-turn tool execution where multiple MCP tool calls are performed in sequence.""" - if not isinstance(compat_client, LlamaStackAsLibraryClient): - pytest.skip("in-process MCP server is only supported in library client") - with make_mcp_server(tools=dependency_tools()) as mcp_server_info: tools = setup_mcp_tools(case.tools, mcp_server_info) - response = compat_client.responses.create( + response = responses_client.responses.create( input=case.input, model=text_model_id, tools=tools, @@ -550,15 +530,12 @@ def test_response_non_streaming_multi_turn_tool_execution(compat_client, text_mo @pytest.mark.parametrize("case", multi_turn_tool_execution_streaming_test_cases) -def test_response_streaming_multi_turn_tool_execution(compat_client, text_model_id, case): +def test_response_streaming_multi_turn_tool_execution(responses_client, text_model_id, case): """Test streaming multi-turn tool execution where multiple MCP tool calls are performed in sequence.""" - if not isinstance(compat_client, LlamaStackAsLibraryClient): - pytest.skip("in-process MCP server is only supported in library client") - with make_mcp_server(tools=dependency_tools()) as mcp_server_info: tools = setup_mcp_tools(case.tools, mcp_server_info) - stream = compat_client.responses.create( + stream = responses_client.responses.create( input=case.input, model=text_model_id, tools=tools, diff --git a/tests/integration/tool_runtime/test_mcp.py b/tests/integration/tool_runtime/test_mcp.py index 3a8fde37f..9ce0d1c98 100644 --- a/tests/integration/tool_runtime/test_mcp.py +++ b/tests/integration/tool_runtime/test_mcp.py @@ -10,8 +10,6 @@ import pytest from llama_stack_client.lib.agents.agent import Agent from llama_stack_client.lib.agents.turn_events import StepCompleted, StepProgress, ToolCallIssuedDelta -from llama_stack.core.library_client import LlamaStackAsLibraryClient - AUTH_TOKEN = "test-token" from tests.common.mcp import MCP_TOOLGROUP_ID, make_mcp_server @@ -24,9 +22,6 @@ def mcp_server(): def test_mcp_invocation(llama_stack_client, text_model_id, mcp_server): - if not isinstance(llama_stack_client, LlamaStackAsLibraryClient): - pytest.skip("The local MCP server only reliably reachable from library client.") - test_toolgroup_id = MCP_TOOLGROUP_ID uri = mcp_server["server_url"]