forked from Archives/langchain
9e74df2404
Fix issue#1645: Parse either whitespace or newline after 'Action Input:' in llm_output in mrkl agent. Unittests added accordingly. Co-authored-by: ₿ingnan.ΞTH <brillliantz@outlook.com>
122 lines
4.1 KiB
Python
122 lines
4.1 KiB
Python
"""Test MRKL functionality."""
|
|
|
|
import pytest
|
|
|
|
from langchain.agents.mrkl.base import ZeroShotAgent, get_action_and_input
|
|
from langchain.agents.mrkl.prompt import FORMAT_INSTRUCTIONS, PREFIX, SUFFIX
|
|
from langchain.agents.tools import Tool
|
|
from langchain.prompts import PromptTemplate
|
|
from tests.unit_tests.llms.fake_llm import FakeLLM
|
|
|
|
|
|
def test_get_action_and_input() -> None:
|
|
"""Test getting an action from text."""
|
|
llm_output = (
|
|
"Thought: I need to search for NBA\n" "Action: Search\n" "Action Input: NBA"
|
|
)
|
|
action, action_input = get_action_and_input(llm_output)
|
|
assert action == "Search"
|
|
assert action_input == "NBA"
|
|
|
|
|
|
def test_get_action_and_input_whitespace() -> None:
|
|
"""Test getting an action from text."""
|
|
llm_output = "Thought: I need to search for NBA\nAction: Search \nAction Input: NBA"
|
|
action, action_input = get_action_and_input(llm_output)
|
|
assert action == "Search"
|
|
assert action_input == "NBA"
|
|
|
|
|
|
def test_get_action_and_input_newline() -> None:
|
|
"""Test getting an action from text where Action Input is a code snippet."""
|
|
llm_output = (
|
|
"Now I need to write a unittest for the function.\n\n"
|
|
"Action: Python\nAction Input:\n```\nimport unittest\n\nunittest.main()\n```"
|
|
)
|
|
action, action_input = get_action_and_input(llm_output)
|
|
assert action == "Python"
|
|
assert action_input == "```\nimport unittest\n\nunittest.main()\n```"
|
|
|
|
|
|
def test_get_final_answer() -> None:
|
|
"""Test getting final answer."""
|
|
llm_output = (
|
|
"Thought: I need to search for NBA\n"
|
|
"Action: Search\n"
|
|
"Action Input: NBA\n"
|
|
"Observation: founded in 1994\n"
|
|
"Thought: I can now answer the question\n"
|
|
"Final Answer: 1994"
|
|
)
|
|
action, action_input = get_action_and_input(llm_output)
|
|
assert action == "Final Answer"
|
|
assert action_input == "1994"
|
|
|
|
|
|
def test_get_final_answer_new_line() -> None:
|
|
"""Test getting final answer."""
|
|
llm_output = (
|
|
"Thought: I need to search for NBA\n"
|
|
"Action: Search\n"
|
|
"Action Input: NBA\n"
|
|
"Observation: founded in 1994\n"
|
|
"Thought: I can now answer the question\n"
|
|
"Final Answer:\n1994"
|
|
)
|
|
action, action_input = get_action_and_input(llm_output)
|
|
assert action == "Final Answer"
|
|
assert action_input == "1994"
|
|
|
|
|
|
def test_get_final_answer_multiline() -> None:
|
|
"""Test getting final answer that is multiline."""
|
|
llm_output = (
|
|
"Thought: I need to search for NBA\n"
|
|
"Action: Search\n"
|
|
"Action Input: NBA\n"
|
|
"Observation: founded in 1994 and 1993\n"
|
|
"Thought: I can now answer the question\n"
|
|
"Final Answer: 1994\n1993"
|
|
)
|
|
action, action_input = get_action_and_input(llm_output)
|
|
assert action == "Final Answer"
|
|
assert action_input == "1994\n1993"
|
|
|
|
|
|
def test_bad_action_input_line() -> None:
|
|
"""Test handling when no action input found."""
|
|
llm_output = "Thought: I need to search for NBA\n" "Action: Search\n" "Thought: NBA"
|
|
with pytest.raises(ValueError):
|
|
get_action_and_input(llm_output)
|
|
|
|
|
|
def test_bad_action_line() -> None:
|
|
"""Test handling when no action input found."""
|
|
llm_output = (
|
|
"Thought: I need to search for NBA\n" "Thought: Search\n" "Action Input: NBA"
|
|
)
|
|
with pytest.raises(ValueError):
|
|
get_action_and_input(llm_output)
|
|
|
|
|
|
def test_from_chains() -> None:
|
|
"""Test initializing from chains."""
|
|
chain_configs = [
|
|
Tool(name="foo", func=lambda x: "foo", description="foobar1"),
|
|
Tool(name="bar", func=lambda x: "bar", description="foobar2"),
|
|
]
|
|
agent = ZeroShotAgent.from_llm_and_tools(FakeLLM(), chain_configs)
|
|
expected_tools_prompt = "foo: foobar1\nbar: foobar2"
|
|
expected_tool_names = "foo, bar"
|
|
expected_template = "\n\n".join(
|
|
[
|
|
PREFIX,
|
|
expected_tools_prompt,
|
|
FORMAT_INSTRUCTIONS.format(tool_names=expected_tool_names),
|
|
SUFFIX,
|
|
]
|
|
)
|
|
prompt = agent.llm_chain.prompt
|
|
assert isinstance(prompt, PromptTemplate)
|
|
assert prompt.template == expected_template
|