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# What does this PR do? <!-- Provide a short summary of what this PR does and why. Link to relevant issues if applicable. --> Add items and title to ToolParameter/ToolParamDefinition. Adding items will resolve the issue that occurs with Gemini LLM when an MCP tool has array-type properties. <!-- If resolving an issue, uncomment and update the line below --> <!-- Closes #[issue-number] --> ## Test Plan <!-- Describe the tests you ran to verify your changes with result summaries. *Provide clear instructions so the plan can be easily re-executed.* --> Unite test cases will be added. --------- Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Kai Wu <kaiwu@meta.com> Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
310 lines
11 KiB
Python
310 lines
11 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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from datetime import datetime
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from unittest.mock import AsyncMock
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import pytest
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from llama_stack.apis.agents import (
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Agent,
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AgentConfig,
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AgentCreateResponse,
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)
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from llama_stack.apis.common.responses import PaginatedResponse
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from llama_stack.apis.inference import Inference
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from llama_stack.apis.resource import ResourceType
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from llama_stack.apis.safety import Safety
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from llama_stack.apis.tools import ListToolsResponse, Tool, ToolGroups, ToolParameter, ToolRuntime
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from llama_stack.apis.vector_io import VectorIO
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from llama_stack.providers.inline.agents.meta_reference.agent_instance import ChatAgent
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from llama_stack.providers.inline.agents.meta_reference.agents import MetaReferenceAgentsImpl
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from llama_stack.providers.inline.agents.meta_reference.config import MetaReferenceAgentsImplConfig
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from llama_stack.providers.inline.agents.meta_reference.persistence import AgentInfo
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@pytest.fixture
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def mock_apis():
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return {
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"inference_api": AsyncMock(spec=Inference),
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"vector_io_api": AsyncMock(spec=VectorIO),
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"safety_api": AsyncMock(spec=Safety),
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"tool_runtime_api": AsyncMock(spec=ToolRuntime),
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"tool_groups_api": AsyncMock(spec=ToolGroups),
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}
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@pytest.fixture
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def config(tmp_path):
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return MetaReferenceAgentsImplConfig(
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persistence_store={
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"type": "sqlite",
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"db_path": str(tmp_path / "test.db"),
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},
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responses_store={
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"type": "sqlite",
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"db_path": str(tmp_path / "test.db"),
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},
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)
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@pytest.fixture
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async def agents_impl(config, mock_apis):
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impl = MetaReferenceAgentsImpl(
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config,
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mock_apis["inference_api"],
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mock_apis["vector_io_api"],
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mock_apis["safety_api"],
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mock_apis["tool_runtime_api"],
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mock_apis["tool_groups_api"],
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{},
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)
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await impl.initialize()
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yield impl
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await impl.shutdown()
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@pytest.fixture
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def sample_agent_config():
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return AgentConfig(
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sampling_params={
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"strategy": {"type": "greedy"},
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"max_tokens": 0,
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"repetition_penalty": 1.0,
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},
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input_shields=["string"],
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output_shields=["string"],
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toolgroups=["mcp::my_mcp_server"],
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client_tools=[
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{
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"name": "client_tool",
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"description": "Client Tool",
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"parameters": [
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{
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"name": "string",
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"parameter_type": "string",
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"description": "string",
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"required": True,
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"default": None,
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}
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],
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"metadata": {
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"property1": None,
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"property2": None,
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},
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}
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],
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tool_choice="auto",
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tool_prompt_format="json",
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tool_config={
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"tool_choice": "auto",
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"tool_prompt_format": "json",
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"system_message_behavior": "append",
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},
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max_infer_iters=10,
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model="string",
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instructions="string",
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enable_session_persistence=False,
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response_format={
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"type": "json_schema",
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"json_schema": {
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"property1": None,
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"property2": None,
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},
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},
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)
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async def test_create_agent(agents_impl, sample_agent_config):
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response = await agents_impl.create_agent(sample_agent_config)
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assert isinstance(response, AgentCreateResponse)
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assert response.agent_id is not None
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stored_agent = await agents_impl.persistence_store.get(f"agent:{response.agent_id}")
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assert stored_agent is not None
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agent_info = AgentInfo.model_validate_json(stored_agent)
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assert agent_info.model == sample_agent_config.model
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assert agent_info.created_at is not None
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assert isinstance(agent_info.created_at, datetime)
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async def test_get_agent(agents_impl, sample_agent_config):
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create_response = await agents_impl.create_agent(sample_agent_config)
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agent_id = create_response.agent_id
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agent = await agents_impl.get_agent(agent_id)
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assert isinstance(agent, Agent)
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assert agent.agent_id == agent_id
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assert agent.agent_config.model == sample_agent_config.model
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assert agent.created_at is not None
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assert isinstance(agent.created_at, datetime)
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async def test_list_agents(agents_impl, sample_agent_config):
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agent1_response = await agents_impl.create_agent(sample_agent_config)
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agent2_response = await agents_impl.create_agent(sample_agent_config)
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response = await agents_impl.list_agents()
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assert isinstance(response, PaginatedResponse)
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assert len(response.data) == 2
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agent_ids = {agent["agent_id"] for agent in response.data}
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assert agent1_response.agent_id in agent_ids
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assert agent2_response.agent_id in agent_ids
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@pytest.mark.parametrize("enable_session_persistence", [True, False])
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async def test_create_agent_session_persistence(agents_impl, sample_agent_config, enable_session_persistence):
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# Create an agent with specified persistence setting
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config = sample_agent_config.model_copy()
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config.enable_session_persistence = enable_session_persistence
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response = await agents_impl.create_agent(config)
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agent_id = response.agent_id
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# Create a session
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session_response = await agents_impl.create_agent_session(agent_id, "test_session")
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assert session_response.session_id is not None
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# Verify the session was stored
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session = await agents_impl.get_agents_session(agent_id, session_response.session_id)
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assert session.session_name == "test_session"
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assert session.session_id == session_response.session_id
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assert session.started_at is not None
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assert session.turns == []
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# Delete the session
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await agents_impl.delete_agents_session(agent_id, session_response.session_id)
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# Verify the session was deleted
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with pytest.raises(ValueError):
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await agents_impl.get_agents_session(agent_id, session_response.session_id)
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@pytest.mark.parametrize("enable_session_persistence", [True, False])
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async def test_list_agent_sessions_persistence(agents_impl, sample_agent_config, enable_session_persistence):
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# Create an agent with specified persistence setting
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config = sample_agent_config.model_copy()
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config.enable_session_persistence = enable_session_persistence
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response = await agents_impl.create_agent(config)
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agent_id = response.agent_id
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# Create multiple sessions
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session1 = await agents_impl.create_agent_session(agent_id, "session1")
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session2 = await agents_impl.create_agent_session(agent_id, "session2")
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# List sessions
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sessions = await agents_impl.list_agent_sessions(agent_id)
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assert len(sessions.data) == 2
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session_ids = {s["session_id"] for s in sessions.data}
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assert session1.session_id in session_ids
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assert session2.session_id in session_ids
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# Delete one session
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await agents_impl.delete_agents_session(agent_id, session1.session_id)
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# Verify the session was deleted
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with pytest.raises(ValueError):
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await agents_impl.get_agents_session(agent_id, session1.session_id)
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# List sessions again
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sessions = await agents_impl.list_agent_sessions(agent_id)
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assert len(sessions.data) == 1
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assert session2.session_id in {s["session_id"] for s in sessions.data}
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async def test_delete_agent(agents_impl, sample_agent_config):
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# Create an agent
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response = await agents_impl.create_agent(sample_agent_config)
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agent_id = response.agent_id
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# Delete the agent
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await agents_impl.delete_agent(agent_id)
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# Verify the agent was deleted
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with pytest.raises(ValueError):
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await agents_impl.get_agent(agent_id)
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async def test__initialize_tools(agents_impl, sample_agent_config):
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# Mock tool_groups_api.list_tools()
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agents_impl.tool_groups_api.list_tools.return_value = ListToolsResponse(
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data=[
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Tool(
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identifier="story_maker",
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provider_id="model-context-protocol",
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type=ResourceType.tool,
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toolgroup_id="mcp::my_mcp_server",
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description="Make a story",
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parameters=[
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ToolParameter(
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name="story_title",
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parameter_type="string",
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description="Title of the story",
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required=True,
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title="Story Title",
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),
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ToolParameter(
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name="input_words",
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parameter_type="array",
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description="Input words",
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required=False,
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items={"type": "string"},
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title="Input Words",
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default=[],
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),
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],
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)
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]
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)
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create_response = await agents_impl.create_agent(sample_agent_config)
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agent_id = create_response.agent_id
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# Get an instance of ChatAgent
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chat_agent = await agents_impl._get_agent_impl(agent_id)
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assert chat_agent is not None
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assert isinstance(chat_agent, ChatAgent)
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# Initialize tool definitions
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await chat_agent._initialize_tools()
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assert len(chat_agent.tool_defs) == 2
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# Verify the first tool, which is a client tool
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first_tool = chat_agent.tool_defs[0]
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assert first_tool.tool_name == "client_tool"
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assert first_tool.description == "Client Tool"
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# Verify the second tool, which is an MCP tool that has an array-type property
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second_tool = chat_agent.tool_defs[1]
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assert second_tool.tool_name == "story_maker"
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assert second_tool.description == "Make a story"
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parameters = second_tool.parameters
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assert len(parameters) == 2
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# Verify a string property
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story_title = parameters.get("story_title")
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assert story_title is not None
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assert story_title.param_type == "string"
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assert story_title.description == "Title of the story"
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assert story_title.required
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assert story_title.items is None
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assert story_title.title == "Story Title"
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assert story_title.default is None
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# Verify an array property
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input_words = parameters.get("input_words")
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assert input_words is not None
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assert input_words.param_type == "array"
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assert input_words.description == "Input words"
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assert not input_words.required
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assert input_words.items is not None
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assert len(input_words.items) == 1
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assert input_words.items.get("type") == "string"
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assert input_words.title == "Input Words"
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assert input_words.default == []
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