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feat(tools): use { input_schema, output_schema } for ToolDefinition
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parent
42414a1a1b
commit
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20 changed files with 1989 additions and 386 deletions
478
tests/integration/tool_runtime/test_mcp_json_schema.py
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478
tests/integration/tool_runtime/test_mcp_json_schema.py
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# 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"
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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_runtime_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.data
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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"
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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_runtime_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.data 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_runtime_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.data 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"
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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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# 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"
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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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# 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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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"
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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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)
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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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class TestSchemaValidation:
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"""Test schema validation (future feature)."""
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def test_invalid_input_rejected(self, llama_stack_client, mcp_server_with_complex_schemas):
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"""Test that invalid input is rejected (if validation is implemented)."""
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# This test documents expected behavior once we add input validation
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# For now, it may pass invalid data through
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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"
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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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# Try to invoke with completely wrong data type
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# Once validation is added, this should raise an error
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try:
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llama_stack_client.tool_runtime.invoke_tool(
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tool_name="process_order",
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kwargs={"order_data": "this should be an object not a string"},
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extra_headers=auth_headers,
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)
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# For now, this might succeed (no validation)
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# After adding validation, we'd expect a ValidationError
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except Exception:
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# Expected once validation is implemented
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pass
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class TestOutputValidation:
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"""Test output schema validation (future feature)."""
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def test_output_matches_schema(self, llama_stack_client, mcp_server_with_output_schemas):
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"""Test that tool output is validated against output_schema (if implemented)."""
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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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||||
# Invoke tool
|
||||
result = llama_stack_client.tool_runtime.invoke_tool(
|
||||
tool_name="get_weather",
|
||||
kwargs={"location": "San Francisco"},
|
||||
extra_headers=auth_headers,
|
||||
)
|
||||
|
||||
# Tool should return valid output
|
||||
assert result.error_message is None
|
||||
assert result.content is not None
|
||||
|
||||
# Once output validation is implemented, the system would check
|
||||
# that result.content matches the tool's output_schema
|
Loading…
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Reference in a new issue