"""Test MRKL functionality.""" from typing import Tuple import pytest from langchain.agents.mrkl.base import ZeroShotAgent from langchain.agents.mrkl.output_parser import MRKLOutputParser from langchain.agents.mrkl.prompt import FORMAT_INSTRUCTIONS, PREFIX, SUFFIX from langchain.agents.tools import Tool from langchain.prompts import PromptTemplate from langchain.schema import AgentAction, OutputParserException from tests.unit_tests.llms.fake_llm import FakeLLM def get_action_and_input(text: str) -> Tuple[str, str]: output = MRKLOutputParser().parse(text) if isinstance(output, AgentAction): return output.tool, str(output.tool_input) else: return "Final Answer", output.return_values["output"] 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_action_and_input_newline_after_keyword() -> None: """Test getting an action and action input from the text when there is a new line before the action (after the keywords "Action:" and "Action Input:") """ llm_output = """ I can use the `ls` command to list the contents of the directory \ and `grep` to search for the specific file. Action: Terminal Action Input: ls -l ~/.bashrc.d/ """ action, action_input = get_action_and_input(llm_output) assert action == "Terminal" assert action_input == "ls -l ~/.bashrc.d/\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(OutputParserException) as e_info: get_action_and_input(llm_output) assert e_info.value.observation is not None def test_bad_action_line() -> None: """Test handling when no action found.""" llm_output = ( "Thought: I need to search for NBA\n" "Thought: Search\n" "Action Input: NBA" ) with pytest.raises(OutputParserException) as e_info: get_action_and_input(llm_output) assert e_info.value.observation is not None 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