mirror of
https://github.com/meta-llama/llama-stack.git
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Get agents tests working
This commit is contained in:
Ashwin Bharambe
Ashwin Bharambe
parent
62dd3b376c
commit
66b658dcce
8 changed files with 352 additions and 269 deletions
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@ -7,47 +7,20 @@
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import os
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import pytest
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import pytest_asyncio
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from llama_stack.apis.agents import * # noqa: F403
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from llama_stack.providers.tests.resolver import resolve_impls_for_test
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from llama_stack.providers.datatypes import * # noqa: F403
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from dotenv import load_dotenv
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# How to run this test:
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#
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# 1. Ensure you have a conda environment with the right dependencies installed.
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# This includes `pytest` and `pytest-asyncio`.
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#
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# 2. Copy and modify the provider_config_example.yaml depending on the provider you are testing.
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#
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# 3. Run:
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#
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# ```bash
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# PROVIDER_ID=<your_provider> \
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# MODEL_ID=<your_model> \
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# PROVIDER_CONFIG=provider_config.yaml \
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# pytest -s llama_stack/providers/tests/agents/test_agents.py \
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# --tb=short --disable-warnings
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# ```
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load_dotenv()
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# pytest -v -s llama_stack/providers/tests/agents/test_agents.py
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# -m "meta_reference"
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@pytest_asyncio.fixture(scope="session")
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async def agents_settings():
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impls = await resolve_impls_for_test(
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Api.agents, deps=[Api.inference, Api.memory, Api.safety]
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)
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@pytest.fixture
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def common_params():
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return {
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"impl": impls[Api.agents],
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"memory_impl": impls[Api.memory],
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"common_params": {
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"model": os.environ["MODEL_ID"] or "Llama3.1-8B-Instruct",
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"instructions": "You are a helpful assistant.",
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},
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"instructions": "You are a helpful assistant.",
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}
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@ -83,230 +56,237 @@ def query_attachment_messages():
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]
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@pytest.mark.asyncio
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async def test_create_agent_turn(agents_settings, sample_messages):
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agents_impl = agents_settings["impl"]
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@pytest.mark.parametrize(
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"inference_model", [pytest.param("Llama3.1-8B-Instruct", id="")], indirect=True
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)
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@pytest.mark.parametrize(
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"safety_model", [pytest.param("Llama-Guard-3-8B", id="")], indirect=True
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)
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class TestAgents:
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@pytest.mark.asyncio
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async def test_create_agent_turn(
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self, agents_stack, sample_messages, common_params, inference_model
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):
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agents_impl, _ = agents_stack
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# First, create an agent
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agent_config = AgentConfig(
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model=agents_settings["common_params"]["model"],
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instructions=agents_settings["common_params"]["instructions"],
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enable_session_persistence=True,
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sampling_params=SamplingParams(temperature=0.7, top_p=0.95),
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input_shields=[],
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output_shields=[],
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tools=[],
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max_infer_iters=5,
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)
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create_response = await agents_impl.create_agent(agent_config)
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agent_id = create_response.agent_id
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# Create a session
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session_create_response = await agents_impl.create_agent_session(
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agent_id, "Test Session"
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)
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session_id = session_create_response.session_id
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# Create and execute a turn
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turn_request = dict(
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agent_id=agent_id,
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session_id=session_id,
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messages=sample_messages,
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stream=True,
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)
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turn_response = [
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chunk async for chunk in await agents_impl.create_agent_turn(**turn_request)
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]
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assert len(turn_response) > 0
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assert all(
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isinstance(chunk, AgentTurnResponseStreamChunk) for chunk in turn_response
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)
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# Check for expected event types
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event_types = [chunk.event.payload.event_type for chunk in turn_response]
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assert AgentTurnResponseEventType.turn_start.value in event_types
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assert AgentTurnResponseEventType.step_start.value in event_types
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assert AgentTurnResponseEventType.step_complete.value in event_types
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assert AgentTurnResponseEventType.turn_complete.value in event_types
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# Check the final turn complete event
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final_event = turn_response[-1].event.payload
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assert isinstance(final_event, AgentTurnResponseTurnCompletePayload)
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assert isinstance(final_event.turn, Turn)
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assert final_event.turn.session_id == session_id
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assert final_event.turn.input_messages == sample_messages
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assert isinstance(final_event.turn.output_message, CompletionMessage)
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assert len(final_event.turn.output_message.content) > 0
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@pytest.mark.asyncio
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async def test_rag_agent_as_attachments(
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agents_settings, attachment_message, query_attachment_messages
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):
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urls = [
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"memory_optimizations.rst",
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"chat.rst",
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"llama3.rst",
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"datasets.rst",
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"qat_finetune.rst",
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"lora_finetune.rst",
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]
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attachments = [
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Attachment(
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content=f"https://raw.githubusercontent.com/pytorch/torchtune/main/docs/source/tutorials/{url}",
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mime_type="text/plain",
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# First, create an agent
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agent_config = AgentConfig(
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model=inference_model,
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instructions=common_params["instructions"],
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enable_session_persistence=True,
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sampling_params=SamplingParams(temperature=0.7, top_p=0.95),
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input_shields=[],
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output_shields=[],
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tools=[],
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max_infer_iters=5,
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)
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for i, url in enumerate(urls)
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]
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agents_impl = agents_settings["impl"]
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create_response = await agents_impl.create_agent(agent_config)
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agent_id = create_response.agent_id
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agent_config = AgentConfig(
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model=agents_settings["common_params"]["model"],
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instructions=agents_settings["common_params"]["instructions"],
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enable_session_persistence=True,
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sampling_params=SamplingParams(temperature=0.7, top_p=0.95),
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input_shields=[],
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output_shields=[],
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tools=[
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MemoryToolDefinition(
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memory_bank_configs=[],
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query_generator_config={
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"type": "default",
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"sep": " ",
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},
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max_tokens_in_context=4096,
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max_chunks=10,
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),
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],
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max_infer_iters=5,
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)
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# Create a session
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session_create_response = await agents_impl.create_agent_session(
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agent_id, "Test Session"
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)
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session_id = session_create_response.session_id
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create_response = await agents_impl.create_agent(agent_config)
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agent_id = create_response.agent_id
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# Create and execute a turn
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turn_request = dict(
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agent_id=agent_id,
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session_id=session_id,
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messages=sample_messages,
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stream=True,
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)
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# Create a session
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session_create_response = await agents_impl.create_agent_session(
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agent_id, "Test Session"
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)
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session_id = session_create_response.session_id
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turn_response = [
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chunk async for chunk in await agents_impl.create_agent_turn(**turn_request)
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]
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# Create and execute a turn
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turn_request = dict(
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agent_id=agent_id,
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session_id=session_id,
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messages=attachment_message,
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attachments=attachments,
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stream=True,
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)
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assert len(turn_response) > 0
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assert all(
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isinstance(chunk, AgentTurnResponseStreamChunk) for chunk in turn_response
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)
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turn_response = [
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chunk async for chunk in await agents_impl.create_agent_turn(**turn_request)
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]
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check_event_types(turn_response)
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check_turn_complete_event(turn_response, session_id, sample_messages)
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assert len(turn_response) > 0
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@pytest.mark.asyncio
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async def test_rag_agent_as_attachments(
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self,
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agents_stack,
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attachment_message,
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query_attachment_messages,
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inference_model,
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common_params,
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):
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agents_impl, _ = agents_stack
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urls = [
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"memory_optimizations.rst",
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"chat.rst",
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"llama3.rst",
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"datasets.rst",
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"qat_finetune.rst",
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"lora_finetune.rst",
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]
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# Create a second turn querying the agent
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turn_request = dict(
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agent_id=agent_id,
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session_id=session_id,
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messages=query_attachment_messages,
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stream=True,
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)
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turn_response = [
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chunk async for chunk in await agents_impl.create_agent_turn(**turn_request)
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]
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assert len(turn_response) > 0
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@pytest.mark.asyncio
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async def test_create_agent_turn_with_brave_search(
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agents_settings, search_query_messages
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):
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agents_impl = agents_settings["impl"]
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if "BRAVE_SEARCH_API_KEY" not in os.environ:
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pytest.skip("BRAVE_SEARCH_API_KEY not set, skipping test")
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# Create an agent with Brave search tool
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agent_config = AgentConfig(
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model=agents_settings["common_params"]["model"],
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instructions=agents_settings["common_params"]["instructions"],
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enable_session_persistence=True,
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sampling_params=SamplingParams(temperature=0.7, top_p=0.95),
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input_shields=[],
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output_shields=[],
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tools=[
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SearchToolDefinition(
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type=AgentTool.brave_search.value,
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api_key=os.environ["BRAVE_SEARCH_API_KEY"],
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engine=SearchEngineType.brave,
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attachments = [
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Attachment(
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content=f"https://raw.githubusercontent.com/pytorch/torchtune/main/docs/source/tutorials/{url}",
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mime_type="text/plain",
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)
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],
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tool_choice=ToolChoice.auto,
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max_infer_iters=5,
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)
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for i, url in enumerate(urls)
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]
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create_response = await agents_impl.create_agent(agent_config)
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agent_id = create_response.agent_id
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agent_config = AgentConfig(
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model=inference_model,
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instructions=common_params["instructions"],
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enable_session_persistence=True,
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sampling_params=SamplingParams(temperature=0.7, top_p=0.95),
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input_shields=[],
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output_shields=[],
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tools=[
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MemoryToolDefinition(
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memory_bank_configs=[],
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query_generator_config={
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"type": "default",
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"sep": " ",
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},
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max_tokens_in_context=4096,
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max_chunks=10,
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),
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],
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max_infer_iters=5,
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)
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# Create a session
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session_create_response = await agents_impl.create_agent_session(
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agent_id, "Test Session with Brave Search"
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)
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session_id = session_create_response.session_id
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create_response = await agents_impl.create_agent(agent_config)
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agent_id = create_response.agent_id
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# Create and execute a turn
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turn_request = dict(
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agent_id=agent_id,
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session_id=session_id,
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messages=search_query_messages,
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stream=True,
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)
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# Create a session
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session_create_response = await agents_impl.create_agent_session(
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agent_id, "Test Session"
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)
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session_id = session_create_response.session_id
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turn_response = [
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chunk async for chunk in await agents_impl.create_agent_turn(**turn_request)
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]
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# Create and execute a turn
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turn_request = dict(
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agent_id=agent_id,
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session_id=session_id,
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messages=attachment_message,
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attachments=attachments,
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stream=True,
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)
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assert len(turn_response) > 0
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assert all(
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isinstance(chunk, AgentTurnResponseStreamChunk) for chunk in turn_response
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)
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turn_response = [
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chunk async for chunk in await agents_impl.create_agent_turn(**turn_request)
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]
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# Check for expected event types
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assert len(turn_response) > 0
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# Create a second turn querying the agent
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turn_request = dict(
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agent_id=agent_id,
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session_id=session_id,
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messages=query_attachment_messages,
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stream=True,
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)
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turn_response = [
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chunk async for chunk in await agents_impl.create_agent_turn(**turn_request)
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]
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assert len(turn_response) > 0
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@pytest.mark.asyncio
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async def test_create_agent_turn_with_brave_search(
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self, agents_stack, search_query_messages, common_params, inference_model
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):
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agents_impl, _ = agents_stack
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if "BRAVE_SEARCH_API_KEY" not in os.environ:
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pytest.skip("BRAVE_SEARCH_API_KEY not set, skipping test")
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# Create an agent with Brave search tool
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agent_config = AgentConfig(
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model=inference_model,
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instructions=common_params["instructions"],
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enable_session_persistence=True,
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sampling_params=SamplingParams(temperature=0.7, top_p=0.95),
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input_shields=[],
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output_shields=[],
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tools=[
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SearchToolDefinition(
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type=AgentTool.brave_search.value,
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api_key=os.environ["BRAVE_SEARCH_API_KEY"],
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engine=SearchEngineType.brave,
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)
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],
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tool_choice=ToolChoice.auto,
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max_infer_iters=5,
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)
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create_response = await agents_impl.create_agent(agent_config)
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agent_id = create_response.agent_id
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# Create a session
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session_create_response = await agents_impl.create_agent_session(
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agent_id, "Test Session with Brave Search"
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)
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session_id = session_create_response.session_id
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# Create and execute a turn
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turn_request = dict(
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agent_id=agent_id,
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session_id=session_id,
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messages=search_query_messages,
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stream=True,
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)
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turn_response = [
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chunk async for chunk in await agents_impl.create_agent_turn(**turn_request)
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]
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assert len(turn_response) > 0
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assert all(
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isinstance(chunk, AgentTurnResponseStreamChunk) for chunk in turn_response
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)
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# Check for expected event types
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check_event_types(turn_response)
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# Check for tool execution events
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tool_execution_events = [
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chunk
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for chunk in turn_response
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if isinstance(chunk.event.payload, AgentTurnResponseStepCompletePayload)
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and chunk.event.payload.step_details.step_type
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== StepType.tool_execution.value
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]
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assert len(tool_execution_events) > 0, "No tool execution events found"
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# Check the tool execution details
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tool_execution = tool_execution_events[0].event.payload.step_details
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assert isinstance(tool_execution, ToolExecutionStep)
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assert len(tool_execution.tool_calls) > 0
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assert tool_execution.tool_calls[0].tool_name == BuiltinTool.brave_search
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assert len(tool_execution.tool_responses) > 0
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# Check the final turn complete event
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check_turn_complete_event(turn_response, session_id, search_query_messages)
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def check_event_types(turn_response):
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event_types = [chunk.event.payload.event_type for chunk in turn_response]
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assert AgentTurnResponseEventType.turn_start.value in event_types
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assert AgentTurnResponseEventType.step_start.value in event_types
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assert AgentTurnResponseEventType.step_complete.value in event_types
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assert AgentTurnResponseEventType.turn_complete.value in event_types
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# Check for tool execution events
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tool_execution_events = [
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chunk
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for chunk in turn_response
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if isinstance(chunk.event.payload, AgentTurnResponseStepCompletePayload)
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and chunk.event.payload.step_details.step_type == StepType.tool_execution.value
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]
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assert len(tool_execution_events) > 0, "No tool execution events found"
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# Check the tool execution details
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tool_execution = tool_execution_events[0].event.payload.step_details
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assert isinstance(tool_execution, ToolExecutionStep)
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assert len(tool_execution.tool_calls) > 0
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assert tool_execution.tool_calls[0].tool_name == BuiltinTool.brave_search
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assert len(tool_execution.tool_responses) > 0
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# Check the final turn complete event
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def check_turn_complete_event(turn_response, session_id, input_messages):
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final_event = turn_response[-1].event.payload
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assert isinstance(final_event, AgentTurnResponseTurnCompletePayload)
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assert isinstance(final_event.turn, Turn)
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assert final_event.turn.session_id == session_id
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assert final_event.turn.input_messages == search_query_messages
|
||||
assert final_event.turn.input_messages == input_messages
|
||||
assert isinstance(final_event.turn.output_message, CompletionMessage)
|
||||
assert len(final_event.turn.output_message.content) > 0
|
||||
|
|
|
|||
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