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https://github.com/meta-llama/llama-stack.git
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ef0736527d
This is a sweeping change to clean up some gunk around our "Tool" definitions. First, we had two types `Tool` and `ToolDef`. The first of these was a "Resource" type for the registry but we had stopped registering tools inside the Registry long back (and only registered ToolGroups.) The latter was for specifying tools for the Agents API. This PR removes the former and adds an optional `toolgroup_id` field to the latter. Secondly, as pointed out by @bbrowning in https://github.com/llamastack/llama-stack/pull/3003#issuecomment-3245270132, we were doing a lossy conversion from a full JSON schema from the MCP tool specification into our ToolDefinition to send it to the model. There is no necessity to do this -- we ourselves aren't doing any execution at all but merely passing it to the chat completions API which supports this. By doing this (and by doing it poorly), we encountered limitations like not supporting array items, or not resolving $refs, etc. To fix this, we replaced the `parameters` field by `{ input_schema, output_schema }` which can be full blown JSON schemas. Finally, there were some types in our llama-related chat format conversion which needed some cleanup. We are taking this opportunity to clean those up. This PR is a substantial breaking change to the API. However, given our window for introducing breaking changes, this suits us just fine. I will be landing a concurrent `llama-stack-client` change as well since API shapes are changing.
404 lines
15 KiB
Python
404 lines
15 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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"""
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Integration tests for MCP tools with complex JSON Schema support.
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Tests $ref, $defs, and other JSON Schema features through MCP integration.
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"""
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import json
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import pytest
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from llama_stack import LlamaStackAsLibraryClient
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from tests.common.mcp import make_mcp_server
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AUTH_TOKEN = "test-token"
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@pytest.fixture(scope="function")
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def mcp_server_with_complex_schemas():
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"""MCP server with tools that have complex schemas including $ref and $defs."""
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from mcp.server.fastmcp import Context
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async def book_flight(flight: dict, passengers: list[dict], payment: dict, ctx: Context) -> dict:
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"""
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Book a flight with passenger and payment information.
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This tool uses JSON Schema $ref and $defs for type reuse.
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"""
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return {
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"booking_id": "BK12345",
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"flight": flight,
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"passengers": passengers,
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"payment": payment,
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"status": "confirmed",
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}
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async def process_order(order_data: dict, ctx: Context) -> dict:
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"""
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Process an order with nested address information.
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Uses nested objects and $ref.
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"""
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return {"order_id": "ORD789", "status": "processing", "data": order_data}
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async def flexible_contact(contact_info: str, ctx: Context) -> dict:
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"""
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Accept flexible contact (email or phone).
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Uses anyOf schema.
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"""
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if "@" in contact_info:
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return {"type": "email", "value": contact_info}
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else:
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return {"type": "phone", "value": contact_info}
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# Manually attach complex schemas to the functions
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# (FastMCP might not support this by default, so this is test setup)
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# For MCP, we need to set the schema via tool annotations
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# This is test infrastructure to force specific schemas
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tools = {"book_flight": book_flight, "process_order": process_order, "flexible_contact": flexible_contact}
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# Note: In real MCP implementation, we'd configure these schemas properly
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# For testing, we may need to mock or extend the MCP server setup
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with make_mcp_server(required_auth_token=AUTH_TOKEN, tools=tools) as server_info:
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yield server_info
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@pytest.fixture(scope="function")
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def mcp_server_with_output_schemas():
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"""MCP server with tools that have output schemas defined."""
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from mcp.server.fastmcp import Context
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async def get_weather(location: str, ctx: Context) -> dict:
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"""
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Get weather with structured output.
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Has both input and output schemas.
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"""
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return {"temperature": 72.5, "conditions": "Sunny", "humidity": 45, "wind_speed": 10.2}
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async def calculate(x: float, y: float, operation: str, ctx: Context) -> dict:
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"""
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Perform calculation with validated output.
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"""
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operations = {"add": x + y, "subtract": x - y, "multiply": x * y, "divide": x / y if y != 0 else None}
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result = operations.get(operation)
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return {"result": result, "operation": operation}
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tools = {"get_weather": get_weather, "calculate": calculate}
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with make_mcp_server(required_auth_token=AUTH_TOKEN, tools=tools) as server_info:
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yield server_info
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class TestMCPSchemaPreservation:
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"""Test that MCP tool schemas are preserved correctly."""
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def test_mcp_tools_list_with_schemas(self, llama_stack_client, mcp_server_with_complex_schemas):
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"""Test listing MCP tools preserves input_schema."""
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if not isinstance(llama_stack_client, LlamaStackAsLibraryClient):
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pytest.skip("Library client required for local MCP server")
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test_toolgroup_id = "mcp::complex_list"
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uri = mcp_server_with_complex_schemas["server_url"]
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# Clean up any existing registration
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try:
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llama_stack_client.toolgroups.unregister(toolgroup_id=test_toolgroup_id)
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except Exception:
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pass
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# Register MCP toolgroup
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llama_stack_client.toolgroups.register(
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toolgroup_id=test_toolgroup_id,
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provider_id="model-context-protocol",
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mcp_endpoint=dict(uri=uri),
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)
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provider_data = {"mcp_headers": {uri: {"Authorization": f"Bearer {AUTH_TOKEN}"}}}
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auth_headers = {
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"X-LlamaStack-Provider-Data": json.dumps(provider_data),
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}
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# List runtime tools
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response = llama_stack_client.tool_runtime.list_tools(
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tool_group_id=test_toolgroup_id,
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extra_headers=auth_headers,
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)
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tools = response
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assert len(tools) > 0
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# Check each tool has input_schema
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for tool in tools:
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assert hasattr(tool, "input_schema")
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# Schema might be None or a dict depending on tool
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if tool.input_schema is not None:
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assert isinstance(tool.input_schema, dict)
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# Should have basic JSON Schema structure
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if "properties" in tool.input_schema:
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assert "type" in tool.input_schema
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def test_mcp_schema_with_refs_preserved(self, llama_stack_client, mcp_server_with_complex_schemas):
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"""Test that $ref and $defs in MCP schemas are preserved."""
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if not isinstance(llama_stack_client, LlamaStackAsLibraryClient):
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pytest.skip("Library client required for local MCP server")
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test_toolgroup_id = "mcp::complex_refs"
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uri = mcp_server_with_complex_schemas["server_url"]
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# Register
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try:
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llama_stack_client.toolgroups.unregister(toolgroup_id=test_toolgroup_id)
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except Exception:
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pass
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llama_stack_client.toolgroups.register(
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toolgroup_id=test_toolgroup_id,
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provider_id="model-context-protocol",
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mcp_endpoint=dict(uri=uri),
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)
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provider_data = {"mcp_headers": {uri: {"Authorization": f"Bearer {AUTH_TOKEN}"}}}
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auth_headers = {
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"X-LlamaStack-Provider-Data": json.dumps(provider_data),
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}
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# List tools
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response = llama_stack_client.tool_runtime.list_tools(
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tool_group_id=test_toolgroup_id,
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extra_headers=auth_headers,
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)
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# Find book_flight tool (which should have $ref/$defs)
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book_flight_tool = next((t for t in response if t.name == "book_flight"), None)
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if book_flight_tool and book_flight_tool.input_schema:
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# If the MCP server provides $defs, they should be preserved
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# This is the KEY test for the bug fix
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schema = book_flight_tool.input_schema
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# Check if schema has properties (might vary based on MCP implementation)
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if "properties" in schema:
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# Verify schema structure is preserved (exact structure depends on MCP server)
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assert isinstance(schema["properties"], dict)
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# If $defs are present, verify they're preserved
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if "$defs" in schema:
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assert isinstance(schema["$defs"], dict)
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# Each definition should be a dict
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for _def_name, def_schema in schema["$defs"].items():
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assert isinstance(def_schema, dict)
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def test_mcp_output_schema_preserved(self, llama_stack_client, mcp_server_with_output_schemas):
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"""Test that MCP outputSchema is preserved."""
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if not isinstance(llama_stack_client, LlamaStackAsLibraryClient):
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pytest.skip("Library client required for local MCP server")
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test_toolgroup_id = "mcp::with_output"
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uri = mcp_server_with_output_schemas["server_url"]
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try:
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llama_stack_client.toolgroups.unregister(toolgroup_id=test_toolgroup_id)
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except Exception:
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pass
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llama_stack_client.toolgroups.register(
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toolgroup_id=test_toolgroup_id,
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provider_id="model-context-protocol",
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mcp_endpoint=dict(uri=uri),
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)
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provider_data = {"mcp_headers": {uri: {"Authorization": f"Bearer {AUTH_TOKEN}"}}}
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auth_headers = {
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"X-LlamaStack-Provider-Data": json.dumps(provider_data),
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}
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response = llama_stack_client.tool_runtime.list_tools(
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tool_group_id=test_toolgroup_id,
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extra_headers=auth_headers,
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)
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# Find get_weather tool
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weather_tool = next((t for t in response if t.name == "get_weather"), None)
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if weather_tool:
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# Check if output_schema field exists and is preserved
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assert hasattr(weather_tool, "output_schema")
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# If MCP server provides output schema, it should be preserved
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if weather_tool.output_schema is not None:
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assert isinstance(weather_tool.output_schema, dict)
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# Should have JSON Schema structure
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if "properties" in weather_tool.output_schema:
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assert "type" in weather_tool.output_schema
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class TestMCPToolInvocation:
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"""Test invoking MCP tools with complex schemas."""
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def test_invoke_mcp_tool_with_nested_data(self, llama_stack_client, mcp_server_with_complex_schemas):
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"""Test invoking MCP tool that expects nested object structure."""
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if not isinstance(llama_stack_client, LlamaStackAsLibraryClient):
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pytest.skip("Library client required for local MCP server")
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test_toolgroup_id = "mcp::complex_invoke_nested"
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uri = mcp_server_with_complex_schemas["server_url"]
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try:
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llama_stack_client.toolgroups.unregister(toolgroup_id=test_toolgroup_id)
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except Exception:
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pass
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llama_stack_client.toolgroups.register(
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toolgroup_id=test_toolgroup_id,
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provider_id="model-context-protocol",
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mcp_endpoint=dict(uri=uri),
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)
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provider_data = {"mcp_headers": {uri: {"Authorization": f"Bearer {AUTH_TOKEN}"}}}
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auth_headers = {
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"X-LlamaStack-Provider-Data": json.dumps(provider_data),
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}
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# List tools to populate the tool index
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llama_stack_client.tool_runtime.list_tools(
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tool_group_id=test_toolgroup_id,
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extra_headers=auth_headers,
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)
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# Invoke tool with complex nested data
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result = llama_stack_client.tool_runtime.invoke_tool(
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tool_name="process_order",
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kwargs={
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"order_data": {
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"items": [{"name": "Widget", "quantity": 2}, {"name": "Gadget", "quantity": 1}],
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"shipping": {"address": {"street": "123 Main St", "city": "San Francisco", "zipcode": "94102"}},
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}
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},
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extra_headers=auth_headers,
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)
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# Should succeed without schema validation errors
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assert result.content is not None
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assert result.error_message is None
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def test_invoke_with_flexible_schema(self, llama_stack_client, mcp_server_with_complex_schemas):
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"""Test invoking tool with anyOf schema (flexible input)."""
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if not isinstance(llama_stack_client, LlamaStackAsLibraryClient):
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pytest.skip("Library client required for local MCP server")
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test_toolgroup_id = "mcp::complex_invoke_flexible"
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uri = mcp_server_with_complex_schemas["server_url"]
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try:
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llama_stack_client.toolgroups.unregister(toolgroup_id=test_toolgroup_id)
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except Exception:
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pass
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llama_stack_client.toolgroups.register(
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toolgroup_id=test_toolgroup_id,
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provider_id="model-context-protocol",
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mcp_endpoint=dict(uri=uri),
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)
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provider_data = {"mcp_headers": {uri: {"Authorization": f"Bearer {AUTH_TOKEN}"}}}
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auth_headers = {
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"X-LlamaStack-Provider-Data": json.dumps(provider_data),
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}
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# List tools to populate the tool index
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llama_stack_client.tool_runtime.list_tools(
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tool_group_id=test_toolgroup_id,
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extra_headers=auth_headers,
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)
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# Test with email format
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result_email = llama_stack_client.tool_runtime.invoke_tool(
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tool_name="flexible_contact",
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kwargs={"contact_info": "user@example.com"},
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extra_headers=auth_headers,
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)
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assert result_email.error_message is None
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# Test with phone format
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result_phone = llama_stack_client.tool_runtime.invoke_tool(
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tool_name="flexible_contact",
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kwargs={"contact_info": "+15551234567"},
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extra_headers=auth_headers,
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)
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assert result_phone.error_message is None
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class TestAgentWithMCPTools:
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"""Test agents using MCP tools with complex schemas."""
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@pytest.mark.skip(reason="we need tool call recording for this test since session_id is injected")
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def test_agent_with_complex_mcp_tool(self, llama_stack_client, text_model_id, mcp_server_with_complex_schemas):
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"""Test agent can use MCP tools with $ref/$defs schemas."""
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if not isinstance(llama_stack_client, LlamaStackAsLibraryClient):
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pytest.skip("Library client required for local MCP server")
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from llama_stack_client import Agent
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test_toolgroup_id = "mcp::complex_agent"
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uri = mcp_server_with_complex_schemas["server_url"]
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try:
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llama_stack_client.toolgroups.unregister(toolgroup_id=test_toolgroup_id)
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except Exception:
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pass
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llama_stack_client.toolgroups.register(
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toolgroup_id=test_toolgroup_id,
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provider_id="model-context-protocol",
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mcp_endpoint=dict(uri=uri),
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)
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provider_data = {"mcp_headers": {uri: {"Authorization": f"Bearer {AUTH_TOKEN}"}}}
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auth_headers = {
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"X-LlamaStack-Provider-Data": json.dumps(provider_data),
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}
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# Create agent with MCP tools
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agent = Agent(
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client=llama_stack_client,
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model=text_model_id,
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instructions="You are a helpful assistant that can process orders and book flights.",
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tools=[test_toolgroup_id],
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extra_headers=auth_headers,
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)
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session_id = agent.create_session("test-session-complex")
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# Ask agent to use a tool with complex schema
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response = agent.create_turn(
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session_id=session_id,
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messages=[
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{"role": "user", "content": "Process an order with 2 widgets going to 123 Main St, San Francisco"}
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],
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stream=False,
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extra_headers=auth_headers,
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)
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steps = response.steps
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# Verify agent was able to call the tool
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# (The LLM should have been able to understand the schema and formulate a valid call)
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tool_execution_steps = [s for s in steps if s.step_type == "tool_execution"]
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# Agent might or might not call the tool depending on the model
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# But if it does, there should be no errors
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for step in tool_execution_steps:
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if step.tool_responses:
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for tool_response in step.tool_responses:
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assert tool_response.content is not None
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