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chore: Add large scale many-messages test (#959)

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This commit is contained in:
Matthew Zhou
2025-02-11 10:11:41 -08:00
committed by GitHub
parent be0aa0d7d2
commit 96bdb8df1c
7 changed files with 229 additions and 61 deletions
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12
letta/services/agent_manager.py
View File

@@ -477,39 +477,39 @@ class AgentManager:
)
message = self.message_manager.create_message(message, actor=actor)
message_ids = [message.id] + agent_state.message_ids[1:] # swap index 0 (system)
return self.set_in_context_messages(agent_id=agent_id, message_ids=message_ids, actor=actor)
return self._set_in_context_messages(agent_id=agent_id, message_ids=message_ids, actor=actor)
else:
return agent_state
@enforce_types
def set_in_context_messages(self, agent_id: str, message_ids: List[str], actor: PydanticUser) -> PydanticAgentState:
def _set_in_context_messages(self, agent_id: str, message_ids: List[str], actor: PydanticUser) -> PydanticAgentState:
return self.update_agent(agent_id=agent_id, agent_update=UpdateAgent(message_ids=message_ids), actor=actor)
@enforce_types
def trim_older_in_context_messages(self, num: int, agent_id: str, actor: PydanticUser) -> PydanticAgentState:
message_ids = self.get_agent_by_id(agent_id=agent_id, actor=actor).message_ids
new_messages = [message_ids[0]] + message_ids[num:] # 0 is system message
return self.set_in_context_messages(agent_id=agent_id, message_ids=new_messages, actor=actor)
return self._set_in_context_messages(agent_id=agent_id, message_ids=new_messages, actor=actor)
@enforce_types
def trim_all_in_context_messages_except_system(self, agent_id: str, actor: PydanticUser) -> PydanticAgentState:
message_ids = self.get_agent_by_id(agent_id=agent_id, actor=actor).message_ids
new_messages = [message_ids[0]] # 0 is system message
return self.set_in_context_messages(agent_id=agent_id, message_ids=new_messages, actor=actor)
return self._set_in_context_messages(agent_id=agent_id, message_ids=new_messages, actor=actor)
@enforce_types
def prepend_to_in_context_messages(self, messages: List[PydanticMessage], agent_id: str, actor: PydanticUser) -> PydanticAgentState:
message_ids = self.get_agent_by_id(agent_id=agent_id, actor=actor).message_ids
new_messages = self.message_manager.create_many_messages(messages, actor=actor)
message_ids = [message_ids[0]] + [m.id for m in new_messages] + message_ids[1:]
return self.set_in_context_messages(agent_id=agent_id, message_ids=message_ids, actor=actor)
return self._set_in_context_messages(agent_id=agent_id, message_ids=message_ids, actor=actor)
@enforce_types
def append_to_in_context_messages(self, messages: List[PydanticMessage], agent_id: str, actor: PydanticUser) -> PydanticAgentState:
messages = self.message_manager.create_many_messages(messages, actor=actor)
message_ids = self.get_agent_by_id(agent_id=agent_id, actor=actor).message_ids or []
message_ids += [m.id for m in messages]
return self.set_in_context_messages(agent_id=agent_id, message_ids=message_ids, actor=actor)
return self._set_in_context_messages(agent_id=agent_id, message_ids=message_ids, actor=actor)
@enforce_types
def reset_messages(self, agent_id: str, actor: PydanticUser, add_default_initial_messages: bool = False) -> PydanticAgentState:

60
poetry.lock generated
View File

@@ -1,4 +1,4 @@
# This file is automatically @generated by Poetry 1.8.5 and should not be changed by hand.
# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
[[package]]
name = "aiohappyeyeballs"
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{file = "Brotli-1.1.0-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:4f3607b129417e111e30637af1b56f24f7a49e64763253bbc275c75fa887d4b2"},
{file = "Brotli-1.1.0-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:6c6e0c425f22c1c719c42670d561ad682f7bfeeef918edea971a79ac5252437f"},
{file = "Brotli-1.1.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:494994f807ba0b92092a163a0a283961369a65f6cbe01e8891132b7a320e61eb"},
{file = "Brotli-1.1.0-cp39-cp39-win32.whl", hash = "sha256:f0d8a7a6b5983c2496e364b969f0e526647a06b075d034f3297dc66f3b360c64"},
{file = "Brotli-1.1.0-cp39-cp39-win_amd64.whl", hash = "sha256:cdad5b9014d83ca68c25d2e9444e28e967ef16e80f6b436918c700c117a85467"},
{file = "Brotli-1.1.0.tar.gz", hash = "sha256:81de08ac11bcb85841e440c13611c00b67d3bf82698314928d0b676362546724"},
@@ -1184,6 +1142,20 @@ files = [
[package.extras]
tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipython", "littleutils", "pytest", "rich"]
[[package]]
name = "faker"
version = "36.1.0"
description = "Faker is a Python package that generates fake data for you."
optional = false
python-versions = ">=3.9"
files = [
{file = "Faker-36.1.0-py3-none-any.whl", hash = "sha256:aa0b93487d3adf7cd89953d172e3df896cb7b35d8a5222c0da873edbe2f7adf5"},
{file = "faker-36.1.0.tar.gz", hash = "sha256:f40510350aecfe006f45cb3f8879b35e861367cf347f51a7f2ca2c0571fdcc0b"},
]
[package.dependencies]
tzdata = "*"
[[package]]
name = "fastapi"
version = "0.115.7"
@@ -6448,4 +6420,4 @@ tests = ["wikipedia"]
[metadata]
lock-version = "2.0"
python-versions = "<3.14,>=3.10"
content-hash = "2216d6724691913e968e42f1761452f241e8f5341951c744e6811293c1e8e73d"
content-hash = "e2101628603fc9585b5f082e974d9d503de7a50117ce89a518f28c783c5fe650"

1
pyproject.toml
View File

@@ -81,6 +81,7 @@ e2b-code-interpreter = {version = "^1.0.3", optional = true}
anthropic = "^0.43.0"
letta_client = "^0.1.23"
openai = "^1.60.0"
faker = "^36.1.0"
[tool.poetry.extras]

8
tests/configs/llm_model_configs/claude-3-5-sonnet.json Normal file
View File

@@ -0,0 +1,8 @@
{
"model": "claude-3-5-sonnet-20241022",
"model_endpoint_type": "anthropic",
"model_endpoint": "https://api.anthropic.com/v1",
"model_wrapper": null,
"context_window": 200000,
"put_inner_thoughts_in_kwargs": true
}

9
tests/configs/llm_model_configs/claude-3-sonnet-20240229.json
View File

@@ -1,9 +0,0 @@
{
"context_window": 200000,
"model": "claude-3-5-sonnet-20241022",
"model_endpoint_type": "anthropic",
"model_endpoint": "https://api.anthropic.com/v1",
"context_window": 200000,
"model_wrapper": null,
"put_inner_thoughts_in_kwargs": true
}

196
tests/manual_test_many_messages.py Normal file
View File

@@ -0,0 +1,196 @@
import datetime
import json
import math
import os
import random
import uuid
import pytest
from faker import Faker
from tqdm import tqdm
from letta import create_client
from letta.orm import Base
from letta.schemas.embedding_config import EmbeddingConfig
from letta.schemas.llm_config import LLMConfig
from letta.schemas.message import Message
from letta.services.agent_manager import AgentManager
from letta.services.message_manager import MessageManager
from tests.integration_test_summarizer import LLM_CONFIG_DIR
@pytest.fixture(autouse=True)
def truncate_database():
from letta.server.server import db_context
with db_context() as session:
for table in reversed(Base.metadata.sorted_tables): # Reverse to avoid FK issues
session.execute(table.delete()) # Truncate table
session.commit()
@pytest.fixture(scope="function")
def client():
filename = os.path.join(LLM_CONFIG_DIR, "claude-3-5-sonnet.json")
config_data = json.load(open(filename, "r"))
llm_config = LLMConfig(**config_data)
client = create_client()
client.set_default_llm_config(llm_config)
client.set_default_embedding_config(EmbeddingConfig.default_config(provider="openai"))
yield client
def generate_tool_call_id():
"""Generates a unique tool call ID."""
return "toolu_" + uuid.uuid4().hex[:24]
def generate_timestamps(base_time):
"""Creates a sequence of timestamps for user, assistant, and tool messages."""
user_time = base_time
send_time = user_time + datetime.timedelta(seconds=random.randint(2, 5))
tool_time = send_time + datetime.timedelta(seconds=random.randint(1, 3))
next_group_time = tool_time + datetime.timedelta(seconds=random.randint(5, 10))
return user_time, send_time, tool_time, next_group_time
def get_conversation_pair():
fake = Faker()
return f"Where does {fake.name()} live?", f"{fake.address()}"
def create_user_message(agent_id, organization_id, message_text, timestamp):
"""Creates a user message dictionary."""
return {
"role": "user",
"content": [
{
"type": "text",
"text": json.dumps(
{"type": "user_message", "message": message_text, "time": timestamp.strftime("%Y-%m-%d %I:%M:%S %p PST-0800")}, indent=2
),
}
],
"organization_id": organization_id,
"agent_id": agent_id,
"model": None,
"name": None,
"tool_calls": None,
"tool_call_id": None,
}
def create_send_message(agent_id, organization_id, assistant_text, tool_call_id, timestamp):
"""Creates an assistant message dictionary."""
return {
"role": "assistant",
"content": [{"type": "text", "text": f"Assistant reply generated at {timestamp.strftime('%Y-%m-%d %I:%M:%S %p PST-0800')}."}],
"organization_id": organization_id,
"agent_id": agent_id,
"model": "claude-3-5-haiku-20241022",
"name": None,
"tool_calls": [
{
"id": tool_call_id,
"function": {
"name": "send_message",
"arguments": json.dumps(
{"message": assistant_text, "time": timestamp.strftime("%Y-%m-%d %I:%M:%S %p PST-0800")}, indent=2
),
},
"type": "function",
}
],
"tool_call_id": None,
}
def create_tool_message(agent_id, organization_id, tool_call_id, timestamp):
"""Creates a tool response message dictionary."""
return {
"role": "tool",
"content": [
{
"type": "text",
"text": json.dumps(
{"status": "OK", "message": "None", "time": timestamp.strftime("%Y-%m-%d %I:%M:%S %p PST-0800")}, indent=2
),
}
],
"organization_id": organization_id,
"agent_id": agent_id,
"model": "claude-3-5-haiku-20241022",
"name": "send_message",
"tool_calls": None,
"tool_call_id": tool_call_id,
}
@pytest.mark.parametrize("num_messages", [1000])
def test_many_messages_performance(client, num_messages):
"""Main test function to generate messages and insert them into the database."""
message_manager = MessageManager()
agent_manager = AgentManager()
actor = client.user
start_time = datetime.datetime.now()
last_event_time = start_time # Track last event time
def log_event(event):
nonlocal last_event_time
now = datetime.datetime.now()
total_elapsed = (now - start_time).total_seconds()
step_elapsed = (now - last_event_time).total_seconds()
print(f"[+{total_elapsed:.3f}s | Δ{step_elapsed:.3f}s] {event}")
last_event_time = now # Update last event time
log_event(f"Starting test with {num_messages} messages")
agent_state = client.create_agent(name="manager")
log_event(f"Created agent with ID {agent_state.id}")
message_group_size = 3
num_groups = math.ceil((num_messages - 4) / message_group_size)
base_time = datetime.datetime(2025, 2, 10, 16, 3, 22)
current_time = base_time
organization_id = "org-00000000-0000-4000-8000-000000000000"
all_messages = []
for _ in tqdm(range(num_groups)):
user_text, assistant_text = get_conversation_pair()
tool_call_id = generate_tool_call_id()
user_time, send_time, tool_time, current_time = generate_timestamps(current_time)
new_messages = [
Message(**create_user_message(agent_state.id, organization_id, user_text, user_time)),
Message(**create_send_message(agent_state.id, organization_id, assistant_text, tool_call_id, send_time)),
Message(**create_tool_message(agent_state.id, organization_id, tool_call_id, tool_time)),
]
all_messages.extend(new_messages)
log_event(f"Finished generating {len(all_messages)} messages")
message_manager.create_many_messages(all_messages, actor=actor)
log_event("Inserted messages into the database")
agent_manager._set_in_context_messages(
agent_id=agent_state.id, message_ids=agent_state.message_ids + [m.id for m in all_messages], actor=client.user
)
log_event("Updated agent context with messages")
messages = message_manager.list_messages_for_agent(agent_id=agent_state.id, actor=client.user, limit=1000000000)
log_event(f"Retrieved {len(messages)} messages from the database")
assert len(messages) >= num_groups * message_group_size
response = client.send_message(
agent_id=agent_state.id,
role="user",
message="What have we been talking about?",
)
log_event("Sent message to agent and received response")
assert response
log_event("Test completed successfully")

4
tests/manual_test_multi_agent_broadcast_large.py
View File

@@ -54,7 +54,8 @@ def roll_dice_tool(client):
yield tool
def test_multi_agent_large(client, roll_dice_tool):
@pytest.mark.parametrize("num_workers", [50])
def test_multi_agent_large(client, roll_dice_tool, num_workers):
manager_tags = ["manager"]
worker_tags = ["helpers"]
@@ -72,7 +73,6 @@ def test_multi_agent_large(client, roll_dice_tool):
# Create 3 worker agents
worker_agents = []
num_workers = 50
for idx in tqdm(range(num_workers)):
worker_agent_state = client.create_agent(
name=f"worker-{idx}", include_multi_agent_tools=False, tags=worker_tags, tool_ids=[roll_dice_tool.id]