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https://github.com/meta-llama/llama-stack.git
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skip code interp
This commit is contained in:
Xi Yan
parent
37b6da37ba
commit
876693e710
1 changed files with 57 additions and 34 deletions
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@ -8,15 +8,13 @@ from typing import Any, Dict
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from uuid import uuid4
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import pytest
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from llama_stack_client import Agent, AgentEventLogger, Document
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from llama_stack_client.types.shared_params.agent_config import AgentConfig, ToolConfig
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from llama_stack.apis.agents.agents import (
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AgentConfig as Server__AgentConfig,
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)
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from llama_stack.apis.agents.agents import (
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ToolChoice,
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)
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from llama_stack_client import Agent, AgentEventLogger, Document
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from llama_stack_client.types.shared_params.agent_config import AgentConfig, ToolConfig
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def get_boiling_point(liquid_name: str, celcius: bool = True) -> int:
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@ -36,7 +34,9 @@ def get_boiling_point(liquid_name: str, celcius: bool = True) -> int:
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return -1
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def get_boiling_point_with_metadata(liquid_name: str, celcius: bool = True) -> Dict[str, Any]:
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def get_boiling_point_with_metadata(
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liquid_name: str, celcius: bool = True
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) -> Dict[str, Any]:
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"""
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Returns the boiling point of a liquid in Celcius or Fahrenheit
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@ -56,7 +56,10 @@ def get_boiling_point_with_metadata(liquid_name: str, celcius: bool = True) -> D
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@pytest.fixture(scope="session")
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def agent_config(llama_stack_client_with_mocked_inference, text_model_id):
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available_shields = [shield.identifier for shield in llama_stack_client_with_mocked_inference.shields.list()]
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available_shields = [
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shield.identifier
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for shield in llama_stack_client_with_mocked_inference.shields.list()
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]
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available_shields = available_shields[:1]
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agent_config = dict(
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model=text_model_id,
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@ -109,7 +112,9 @@ def test_agent_simple(llama_stack_client_with_mocked_inference, agent_config):
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session_id=session_id,
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)
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logs = [str(log) for log in AgentEventLogger().log(bomb_response) if log is not None]
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logs = [
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str(log) for log in AgentEventLogger().log(bomb_response) if log is not None
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]
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logs_str = "".join(logs)
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assert "I can't" in logs_str
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@ -170,7 +175,9 @@ def test_tool_config(llama_stack_client_with_mocked_inference, agent_config):
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Server__AgentConfig(**agent_config)
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def test_builtin_tool_web_search(llama_stack_client_with_mocked_inference, agent_config):
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def test_builtin_tool_web_search(
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llama_stack_client_with_mocked_inference, agent_config
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):
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agent_config = {
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**agent_config,
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"instructions": "You are a helpful assistant that can use web search to answer questions.",
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@ -201,7 +208,9 @@ def test_builtin_tool_web_search(llama_stack_client_with_mocked_inference, agent
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assert found_tool_execution
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def test_builtin_tool_code_execution(llama_stack_client_with_mocked_inference, agent_config):
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def test_builtin_tool_code_execution(
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llama_stack_client_with_mocked_inference, agent_config
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):
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agent_config = {
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**agent_config,
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"tools": [
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@ -230,7 +239,9 @@ def test_builtin_tool_code_execution(llama_stack_client_with_mocked_inference, a
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# This test must be run in an environment where `bwrap` is available. If you are running against a
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# server, this means the _server_ must have `bwrap` available. If you are using library client, then
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# you must have `bwrap` available in test's environment.
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def test_code_interpreter_for_attachments(llama_stack_client_with_mocked_inference, agent_config):
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def test_code_interpreter_for_attachments(
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llama_stack_client_with_mocked_inference, agent_config
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):
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agent_config = {
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**agent_config,
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"tools": [
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@ -292,7 +303,9 @@ def test_custom_tool(llama_stack_client_with_mocked_inference, agent_config):
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assert "get_boiling_point" in logs_str
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def test_custom_tool_infinite_loop(llama_stack_client_with_mocked_inference, agent_config):
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def test_custom_tool_infinite_loop(
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llama_stack_client_with_mocked_inference, agent_config
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):
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client_tool = get_boiling_point
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agent_config = {
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**agent_config,
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@ -315,7 +328,9 @@ def test_custom_tool_infinite_loop(llama_stack_client_with_mocked_inference, age
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stream=False,
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)
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num_tool_calls = sum([1 if step.step_type == "tool_execution" else 0 for step in response.steps])
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num_tool_calls = sum(
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[1 if step.step_type == "tool_execution" else 0 for step in response.steps]
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)
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assert num_tool_calls <= 5
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@ -327,18 +342,25 @@ def test_tool_choice_required(llama_stack_client_with_mocked_inference, agent_co
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def test_tool_choice_none(llama_stack_client_with_mocked_inference, agent_config):
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tool_execution_steps = run_agent_with_tool_choice(llama_stack_client_with_mocked_inference, agent_config, "none")
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tool_execution_steps = run_agent_with_tool_choice(
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llama_stack_client_with_mocked_inference, agent_config, "none"
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)
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assert len(tool_execution_steps) == 0
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def test_tool_choice_get_boiling_point(llama_stack_client_with_mocked_inference, agent_config):
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def test_tool_choice_get_boiling_point(
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llama_stack_client_with_mocked_inference, agent_config
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):
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if "llama" not in agent_config["model"].lower():
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pytest.xfail("NotImplemented for non-llama models")
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tool_execution_steps = run_agent_with_tool_choice(
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llama_stack_client_with_mocked_inference, agent_config, "get_boiling_point"
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)
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assert len(tool_execution_steps) >= 1 and tool_execution_steps[0].tool_calls[0].tool_name == "get_boiling_point"
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assert (
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len(tool_execution_steps) >= 1
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and tool_execution_steps[0].tool_calls[0].tool_name == "get_boiling_point"
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)
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def run_agent_with_tool_choice(client, agent_config, tool_choice):
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@ -368,8 +390,12 @@ def run_agent_with_tool_choice(client, agent_config, tool_choice):
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return [step for step in response.steps if step.step_type == "tool_execution"]
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@pytest.mark.parametrize("rag_tool_name", ["builtin::rag/knowledge_search", "builtin::rag"])
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def test_rag_agent(llama_stack_client_with_mocked_inference, agent_config, rag_tool_name):
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@pytest.mark.parametrize(
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"rag_tool_name", ["builtin::rag/knowledge_search", "builtin::rag"]
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)
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def test_rag_agent(
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llama_stack_client_with_mocked_inference, agent_config, rag_tool_name
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):
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urls = ["chat.rst", "llama3.rst", "memory_optimizations.rst", "lora_finetune.rst"]
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documents = [
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Document(
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@ -418,17 +444,22 @@ def test_rag_agent(llama_stack_client_with_mocked_inference, agent_config, rag_t
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stream=False,
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)
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# rag is called
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tool_execution_step = next(step for step in response.steps if step.step_type == "tool_execution")
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tool_execution_step = next(
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step for step in response.steps if step.step_type == "tool_execution"
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)
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assert tool_execution_step.tool_calls[0].tool_name == "knowledge_search"
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# document ids are present in metadata
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assert all(
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doc_id.startswith("num-") for doc_id in tool_execution_step.tool_responses[0].metadata["document_ids"]
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doc_id.startswith("num-")
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for doc_id in tool_execution_step.tool_responses[0].metadata["document_ids"]
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)
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if expected_kw:
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assert expected_kw in response.output_message.content.lower()
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def test_rag_agent_with_attachments(llama_stack_client_with_mocked_inference, agent_config):
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def test_rag_agent_with_attachments(
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llama_stack_client_with_mocked_inference, agent_config
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):
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urls = ["chat.rst", "llama3.rst", "memory_optimizations.rst", "lora_finetune.rst"]
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documents = [
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Document(
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@ -520,19 +551,7 @@ def test_rag_and_code_agent(llama_stack_client_with_mocked_inference, agent_conf
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],
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}
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agent = Agent(llama_stack_client_with_mocked_inference, **agent_config)
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inflation_doc = Document(
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document_id="test_csv",
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content="https://raw.githubusercontent.com/meta-llama/llama-stack-apps/main/examples/resources/inflation.csv",
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mime_type="text/csv",
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metadata={},
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)
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user_prompts = [
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(
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"Here is a csv file, can you describe it?",
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[inflation_doc],
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"code_interpreter",
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"",
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),
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(
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"when was Perplexity the company founded?",
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[],
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@ -555,7 +574,9 @@ def test_rag_and_code_agent(llama_stack_client_with_mocked_inference, agent_conf
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documents=docs,
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stream=False,
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)
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tool_execution_step = next(step for step in response.steps if step.step_type == "tool_execution")
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tool_execution_step = next(
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step for step in response.steps if step.step_type == "tool_execution"
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)
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assert tool_execution_step.tool_calls[0].tool_name == tool_name
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if expected_kw:
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assert expected_kw in response.output_message.content.lower()
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@ -565,7 +586,9 @@ def test_rag_and_code_agent(llama_stack_client_with_mocked_inference, agent_conf
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"client_tools",
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[(get_boiling_point, False), (get_boiling_point_with_metadata, True)],
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)
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def test_create_turn_response(llama_stack_client_with_mocked_inference, agent_config, client_tools):
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def test_create_turn_response(
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llama_stack_client_with_mocked_inference, agent_config, client_tools
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):
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client_tool, expects_metadata = client_tools
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agent_config = {
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**agent_config,
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