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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.
303 lines
10 KiB
Python
303 lines
10 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.safety import Safety
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from llama_stack.apis.tools import ListToolDefsResponse, ToolDef, ToolGroups, 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 = ListToolDefsResponse(
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data=[
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ToolDef(
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name="story_maker",
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toolgroup_id="mcp::my_mcp_server",
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description="Make a story",
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input_schema={
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"type": "object",
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"properties": {
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"story_title": {"type": "string", "description": "Title of the story", "title": "Story Title"},
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"input_words": {
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"type": "array",
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"description": "Input words",
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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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"required": ["story_title"],
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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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# Verify the input schema
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input_schema = second_tool.input_schema
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assert input_schema is not None
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assert input_schema["type"] == "object"
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properties = input_schema["properties"]
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assert len(properties) == 2
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# Verify a string property
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story_title = properties["story_title"]
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assert story_title["type"] == "string"
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assert story_title["description"] == "Title of the story"
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assert story_title["title"] == "Story Title"
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# Verify an array property
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input_words = properties["input_words"]
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assert input_words["type"] == "array"
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assert input_words["description"] == "Input words"
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assert input_words["items"]["type"] == "string"
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assert input_words["title"] == "Input Words"
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assert input_words["default"] == []
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# Verify required fields
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assert input_schema["required"] == ["story_title"]
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