Files
letta-server/tests/integration_test_chat_completions.py
Kian Jones 25d54dd896 chore: enable F821, F401, W293 (#9503)
* auto fixes

* auto fix pt2 and transitive deps and undefined var checking locals()

* manual fixes (ignored or letta-code fixed)

* fix circular import
2026-02-24 10:55:08 -08:00

195 lines
6.3 KiB
Python

import os
import threading
import uuid
import pytest
from dotenv import load_dotenv
from letta_client import Letta
from openai import AsyncOpenAI
from openai.types.chat.chat_completion_chunk import ChatCompletionChunk
from letta.schemas.embedding_config import EmbeddingConfig
from letta.schemas.enums import AgentType, MessageStreamStatus
from letta.schemas.llm_config import LLMConfig
from letta.schemas.openai.chat_completion_request import ChatCompletionRequest, UserMessage as OpenAIUserMessage
from letta.schemas.usage import LettaUsageStatistics
from tests.utils import wait_for_server
# --- Server Management --- #
def _run_server():
"""Starts the Letta server in a background thread."""
load_dotenv()
from letta.server.rest_api.app import start_server
start_server(debug=True)
@pytest.fixture(scope="session")
def server_url():
"""Ensures a server is running and returns its base URL."""
url = os.getenv("LETTA_SERVER_URL", "http://localhost:8283")
if not os.getenv("LETTA_SERVER_URL"):
thread = threading.Thread(target=_run_server, daemon=True)
thread.start()
wait_for_server(url) # Allow server startup time
return url
# --- Client Setup --- #
@pytest.fixture(scope="session")
def client(server_url):
"""Creates a REST client for testing."""
client = Letta(base_url=server_url)
yield client
@pytest.fixture(scope="function")
def roll_dice_tool(client):
def roll_dice():
"""
Rolls a 6 sided die.
Returns:
str: The roll result.
"""
return "Rolled a 10!"
tool = client.tools.upsert_from_function(func=roll_dice)
# Yield the created tool
yield tool
@pytest.fixture(scope="function")
def weather_tool(client):
def get_weather(location: str) -> str:
"""
Fetches the current weather for a given location.
Args:
location (str): The location to get the weather for.
Returns:
str: A formatted string describing the weather in the given location.
Raises:
RuntimeError: If the request to fetch weather data fails.
"""
import requests
url = f"https://wttr.in/{location}?format=%C+%t"
response = requests.get(url)
if response.status_code == 200:
weather_data = response.text
return f"The weather in {location} is {weather_data}."
else:
raise RuntimeError(f"Failed to get weather data, status code: {response.status_code}")
tool = client.tools.upsert_from_function(func=get_weather)
# Yield the created tool
yield tool
@pytest.fixture(scope="function")
def agent(client, roll_dice_tool, weather_tool):
"""Creates an agent and ensures cleanup after tests."""
agent_state = client.agents.create(
agent_type=AgentType.letta_v1_agent,
name=f"test_compl_{str(uuid.uuid4())[5:]}",
tool_ids=[roll_dice_tool.id, weather_tool.id],
include_base_tools=True,
memory_blocks=[
{"label": "human", "value": "(I know nothing about the human)"},
{"label": "persona", "value": "Friendly agent"},
],
llm_config=LLMConfig.default_config(model_name="gpt-4o-mini"),
embedding_config=EmbeddingConfig.default_config(provider="openai"),
)
yield agent_state
# --- Helper Functions --- #
def _get_chat_request(message, stream=True):
"""Returns a chat completion request with streaming enabled."""
return ChatCompletionRequest(
model="gpt-4o-mini",
messages=[OpenAIUserMessage(content=message)],
stream=stream,
)
def _assert_valid_chunk(chunk, idx, chunks):
"""Validates the structure of each streaming chunk."""
if isinstance(chunk, ChatCompletionChunk):
assert chunk.choices, "Each ChatCompletionChunk should have at least one choice."
elif isinstance(chunk, LettaUsageStatistics):
assert chunk.completion_tokens > 0, "Completion tokens must be > 0."
assert chunk.prompt_tokens > 0, "Prompt tokens must be > 0."
assert chunk.total_tokens > 0, "Total tokens must be > 0."
assert chunk.step_count == 1, "Step count must be 1."
elif isinstance(chunk, MessageStreamStatus):
assert chunk == MessageStreamStatus.done, "Stream should end with 'done' status."
assert idx == len(chunks) - 1, "The last chunk must be 'done'."
else:
pytest.fail(f"Unexpected chunk type: {chunk}")
# --- Test Cases --- #
@pytest.mark.asyncio
@pytest.mark.parametrize("message", ["Tell me a short joke"])
async def test_chat_completions_streaming_openai_client(disable_e2b_api_key, client, agent, roll_dice_tool, message):
"""Tests Letta's OpenAI-compatible chat completions streaming endpoint."""
async_client = AsyncOpenAI(base_url="http://localhost:8283/v1", max_retries=0)
stream = await async_client.chat.completions.create(
model=agent.id, # agent ID goes in model field
messages=[{"role": "user", "content": message}],
stream=True,
)
received_chunks = 0
stop_chunk_count = 0
last_chunk = None
content_parts = []
try:
async for chunk in stream:
assert isinstance(chunk, ChatCompletionChunk), f"Unexpected chunk type: {type(chunk)}"
assert chunk.choices, "Each ChatCompletionChunk should have at least one choice."
last_chunk = chunk
if chunk.choices[0].finish_reason == "stop":
stop_chunk_count += 1
assert stop_chunk_count == 1, f"Multiple stop chunks detected: {chunk.model_dump_json(indent=4)}"
continue
if chunk.choices[0].delta.content:
content_parts.append(chunk.choices[0].delta.content)
received_chunks += 1
except Exception as e:
pytest.fail(f"Streaming failed with exception: {e}")
print("\n=== Stream Summary ===")
print(f"Received chunks: {received_chunks}")
print(f"Full response: {''.join(content_parts)}")
print(f"Stop chunk count: {stop_chunk_count}")
assert received_chunks > 0, "No valid streaming chunks were received."
assert stop_chunk_count == 1, "Expected exactly one stop chunk."
assert last_chunk is not None, "No last chunk received."
assert last_chunk.choices[0].finish_reason == "stop", "Last chunk should have finish_reason='stop'"