langchain/tests/unit_tests/agents/test_agent.py
Harrison Chase 3efee27e56 cr
2023-01-03 14:12:43 -08:00

168 lines
5.1 KiB
Python

"""Unit tests for agents."""
from typing import Any, List, Mapping, Optional
from pydantic import BaseModel
from langchain.agents import AgentExecutor, Tool, initialize_agent
from langchain.callbacks.base import CallbackManager
from langchain.llms.base import LLM
from tests.unit_tests.callbacks.fake_callback_handler import FakeCallbackHandler
class FakeListLLM(LLM, BaseModel):
"""Fake LLM for testing that outputs elements of a list."""
responses: List[str]
i: int = -1
def _call(self, prompt: str, stop: Optional[List[str]] = None) -> str:
"""Increment counter, and then return response in that index."""
self.i += 1
print(self.i)
print(self.responses)
return self.responses[self.i]
@property
def _identifying_params(self) -> Mapping[str, Any]:
return {}
@property
def _llm_type(self) -> str:
"""Return type of llm."""
return "fake_list"
def _get_agent(**kwargs: Any) -> AgentExecutor:
"""Get agent for testing."""
bad_action_name = "BadAction"
responses = [
f"I'm turning evil\nAction: {bad_action_name}\nAction Input: misalignment",
"Oh well\nAction: Final Answer\nAction Input: curses foiled again",
]
fake_llm = FakeListLLM(responses=responses)
tools = [
Tool("Search", lambda x: x, "Useful for searching"),
Tool("Lookup", lambda x: x, "Useful for looking up things in a table"),
]
agent = initialize_agent(
tools, fake_llm, agent="zero-shot-react-description", verbose=True, **kwargs
)
return agent
def test_agent_bad_action() -> None:
"""Test react chain when bad action given."""
agent = _get_agent()
output = agent.run("when was langchain made")
assert output == "curses foiled again"
def test_agent_stopped_early() -> None:
"""Test react chain when bad action given."""
agent = _get_agent(max_iterations=0)
output = agent.run("when was langchain made")
assert output == "Agent stopped due to max iterations."
def test_agent_with_callbacks_global() -> None:
"""Test react chain with callbacks by setting verbose globally."""
import langchain
langchain.verbose = True
handler = FakeCallbackHandler()
manager = CallbackManager(handlers=[handler])
tool = "Search"
responses = [
f"FooBarBaz\nAction: {tool}\nAction Input: misalignment",
"Oh well\nAction: Final Answer\nAction Input: curses foiled again",
]
fake_llm = FakeListLLM(responses=responses, callback_manager=manager, verbose=True)
tools = [
Tool("Search", lambda x: x, "Useful for searching"),
]
agent = initialize_agent(
tools,
fake_llm,
agent="zero-shot-react-description",
verbose=True,
callback_manager=manager,
)
output = agent.run("when was langchain made")
assert output == "curses foiled again"
# 1 top level chain run, 2 LLMChain runs, 2 LLM runs, 1 tool run
assert handler.starts == 6
# 1 extra agent end
assert handler.ends == 7
assert handler.errors == 0
def test_agent_with_callbacks_local() -> None:
"""Test react chain with callbacks by setting verbose locally."""
import langchain
langchain.verbose = False
handler = FakeCallbackHandler()
manager = CallbackManager(handlers=[handler])
tool = "Search"
responses = [
f"FooBarBaz\nAction: {tool}\nAction Input: misalignment",
"Oh well\nAction: Final Answer\nAction Input: curses foiled again",
]
fake_llm = FakeListLLM(responses=responses, callback_manager=manager, verbose=True)
tools = [
Tool("Search", lambda x: x, "Useful for searching"),
]
agent = initialize_agent(
tools,
fake_llm,
agent="zero-shot-react-description",
verbose=True,
callback_manager=manager,
)
agent.agent.llm_chain.verbose = True
output = agent.run("when was langchain made")
assert output == "curses foiled again"
# 1 top level chain run, 2 LLMChain runs, 2 LLM runs, 1 tool run
assert handler.starts == 6
# 1 extra agent end
assert handler.ends == 7
assert handler.errors == 0
def test_agent_with_callbacks_not_verbose() -> None:
"""Test react chain with callbacks but not verbose."""
import langchain
langchain.verbose = False
handler = FakeCallbackHandler()
manager = CallbackManager(handlers=[handler])
tool = "Search"
responses = [
f"FooBarBaz\nAction: {tool}\nAction Input: misalignment",
"Oh well\nAction: Final Answer\nAction Input: curses foiled again",
]
fake_llm = FakeListLLM(responses=responses, callback_manager=manager)
tools = [
Tool("Search", lambda x: x, "Useful for searching"),
]
agent = initialize_agent(
tools,
fake_llm,
agent="zero-shot-react-description",
callback_manager=manager,
)
output = agent.run("when was langchain made")
assert output == "curses foiled again"
# 1 top level chain run, 2 LLMChain runs, 2 LLM runs, 1 tool run
assert handler.starts == 0
assert handler.ends == 0
assert handler.errors == 0