Files
letta-server/tests/test_summarize.py
Matthew Zhou 69730988ce feat: Sandboxing for tool execution (#2040)
Co-authored-by: Caren Thomas <carenthomas@Jeffs-MacBook-Pro-2.local>
Co-authored-by: Caren Thomas <carenthomas@jeffs-mbp-2.lan>
Co-authored-by: Caren Thomas <carenthomas@Jeffs-MBP-2.hsd1.ca.comcast.net>
Co-authored-by: Sarah Wooders <sarahwooders@gmail.com>
2024-11-22 10:34:08 -08:00

130 lines
4.6 KiB
Python

import uuid
from typing import List
from letta import create_client
from letta.client.client import LocalClient
from letta.schemas.embedding_config import EmbeddingConfig
from letta.schemas.llm_config import LLMConfig
from letta.schemas.message import Message
from .utils import wipe_config
# test_agent_id = "test_agent"
test_agent_name = f"test_client_{str(uuid.uuid4())}"
client = None
agent_obj = None
# TODO: these tests should include looping through LLM providers, since behavior may vary across providers
# TODO: these tests should add function calls into the summarized message sequence:W
def create_test_agent():
"""Create a test agent that we can call functions on"""
wipe_config()
global client
client = create_client()
client.set_default_llm_config(LLMConfig.default_config("gpt-4"))
client.set_default_embedding_config(EmbeddingConfig.default_config(provider="openai"))
agent_state = client.create_agent(
name=test_agent_name,
)
global agent_obj
agent_obj = client.server._get_or_load_agent(agent_id=agent_state.id)
def test_summarize_messages_inplace():
"""Test summarization via sending the summarize CLI command or via a direct call to the agent object"""
global client
global agent_obj
if agent_obj is None:
create_test_agent()
assert agent_obj is not None, "Run create_agent test first"
assert client is not None, "Run create_agent test first"
# First send a few messages (5)
response = client.user_message(
agent_id=agent_obj.agent_state.id,
message="Hey, how's it going? What do you think about this whole shindig",
).messages
assert response is not None and len(response) > 0
print(f"test_summarize: response={response}")
response = client.user_message(
agent_id=agent_obj.agent_state.id,
message="Any thoughts on the meaning of life?",
).messages
assert response is not None and len(response) > 0
print(f"test_summarize: response={response}")
response = client.user_message(agent_id=agent_obj.agent_state.id, message="Does the number 42 ring a bell?").messages
assert response is not None and len(response) > 0
print(f"test_summarize: response={response}")
response = client.user_message(
agent_id=agent_obj.agent_state.id,
message="Would you be surprised to learn that you're actually conversing with an AI right now?",
).messages
assert response is not None and len(response) > 0
print(f"test_summarize: response={response}")
agent_obj.summarize_messages_inplace()
print(f"Summarization succeeded: messages[1] = \n{agent_obj.messages[1]}")
# response = client.run_command(agent_id=agent_obj.agent_state.id, command="summarize")
def test_auto_summarize():
"""Test that the summarizer triggers by itself"""
client = create_client()
client.set_default_llm_config(LLMConfig.default_config("gpt-4"))
client.set_default_embedding_config(EmbeddingConfig.default_config(provider="openai"))
small_context_llm_config = LLMConfig.default_config("gpt-4")
# default system prompt + funcs lead to ~2300 tokens, after one message it's at 2523 tokens
SMALL_CONTEXT_WINDOW = 3000
small_context_llm_config.context_window = SMALL_CONTEXT_WINDOW
agent_state = client.create_agent(
name="small_context_agent",
llm_config=small_context_llm_config,
)
try:
def summarize_message_exists(messages: List[Message]) -> bool:
for message in messages:
if message.text and "have been hidden from view due to conversation memory constraints" in message.text:
print(f"Summarize message found after {message_count} messages: \n {message.text}")
return True
return False
MAX_ATTEMPTS = 5
message_count = 0
while True:
# send a message
response = client.user_message(
agent_id=agent_state.id,
message="What is the meaning of life?",
)
message_count += 1
print(f"Message {message_count}: \n\n{response.messages}")
# check if the summarize message is inside the messages
assert isinstance(client, LocalClient), "Test only works with LocalClient"
agent_obj = client.server._get_or_load_agent(agent_id=agent_state.id)
if summarize_message_exists(agent_obj._messages):
break
if message_count > MAX_ATTEMPTS:
raise Exception(f"Summarize message not found after {message_count} messages")
finally:
client.delete_agent(agent_state.id)