mirror of
https://github.com/hwchase17/langchain
synced 2024-11-06 03:20:49 +00:00
32 lines
1.3 KiB
Python
32 lines
1.3 KiB
Python
"""Test memory functionality."""
|
|
from langchain.memory.summary_buffer import ConversationSummaryBufferMemory
|
|
from tests.unit_tests.llms.fake_llm import FakeLLM
|
|
|
|
|
|
def test_summary_buffer_memory_no_buffer_yet() -> None:
|
|
"""Test ConversationSummaryBufferMemory when no inputs put in buffer yet."""
|
|
memory = ConversationSummaryBufferMemory(llm=FakeLLM(), memory_key="baz")
|
|
output = memory.load_memory_variables({})
|
|
assert output == {"baz": ""}
|
|
|
|
|
|
def test_summary_buffer_memory_buffer_only() -> None:
|
|
"""Test ConversationSummaryBufferMemory when only buffer."""
|
|
memory = ConversationSummaryBufferMemory(llm=FakeLLM(), memory_key="baz")
|
|
memory.save_context({"input": "bar"}, {"output": "foo"})
|
|
assert memory.buffer == ["Human: bar\nAI: foo"]
|
|
output = memory.load_memory_variables({})
|
|
assert output == {"baz": "Human: bar\nAI: foo"}
|
|
|
|
|
|
def test_summary_buffer_memory_summary() -> None:
|
|
"""Test ConversationSummaryBufferMemory when only buffer."""
|
|
memory = ConversationSummaryBufferMemory(
|
|
llm=FakeLLM(), memory_key="baz", max_token_limit=13
|
|
)
|
|
memory.save_context({"input": "bar"}, {"output": "foo"})
|
|
memory.save_context({"input": "bar1"}, {"output": "foo1"})
|
|
assert memory.buffer == ["Human: bar1\nAI: foo1"]
|
|
output = memory.load_memory_variables({})
|
|
assert output == {"baz": "foo\nHuman: bar1\nAI: foo1"}
|