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test / openai_server /test_openai_server.py
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import time
import pytest
import os
# to avoid copy-paste, only other external reference besides main() (for local_server=True)
from tests.utils import wrap_test_forked
def launch_openai_server():
from openai_server.server import run
run()
def test_openai_server():
# for manual separate OpenAI server on existing h2oGPT, run:
# Shell 1: CUDA_VISIBLE_DEVICES=0 python generate.py --verbose=True --score_model=None --pre_load_embedding_model=False --gradio_offline_level=2 --base_model=openchat/openchat-3.5-1210 --inference_server=vllm:ip:port --max_seq_len=4096 --save_dir=duder1 --verbose --openai_server=True --concurrency_count=64 --openai_server=False
# Shell 2: pytest -s -v openai_server/test_openai_server.py::test_openai_server # once client done, hit CTRL-C, should pass
# Shell 3: pytest -s -v openai_server/test_openai_server.py::test_openai_client_test2 # should pass
launch_openai_server()
# repeat0 = 100 # e.g. to test concurrency
repeat0 = 1
@pytest.mark.parametrize("stream_output", [False, True])
@pytest.mark.parametrize("chat", [False, True])
@pytest.mark.parametrize("local_server", [False])
@wrap_test_forked
def test_openai_client_test2(stream_output, chat, local_server):
prompt = "Who are you?"
api_key = 'EMPTY'
enforce_h2ogpt_api_key = False
repeat = 1
run_openai_client(stream_output, chat, local_server, prompt, api_key, enforce_h2ogpt_api_key, repeat)
@pytest.mark.parametrize("stream_output", [False, True])
@pytest.mark.parametrize("chat", [False, True])
@pytest.mark.parametrize("local_server", [True])
@pytest.mark.parametrize("prompt", ["Who are you?", "Tell a very long kid's story about birds."])
@pytest.mark.parametrize("api_key", [None, "EMPTY", os.environ.get('H2OGPT_H2OGPT_KEY', 'EMPTY')])
@pytest.mark.parametrize("enforce_h2ogpt_api_key", [False, True])
@pytest.mark.parametrize("repeat", list(range(0, repeat0)))
@wrap_test_forked
def test_openai_client(stream_output, chat, local_server, prompt, api_key, enforce_h2ogpt_api_key, repeat):
run_openai_client(stream_output, chat, local_server, prompt, api_key, enforce_h2ogpt_api_key, repeat)
def run_openai_client(stream_output, chat, local_server, prompt, api_key, enforce_h2ogpt_api_key, repeat):
base_model = 'openchat/openchat-3.5-1210'
if local_server:
from src.gen import main
main(base_model=base_model, chat=False,
stream_output=stream_output, gradio=True,
num_beams=1, block_gradio_exit=False,
add_disk_models_to_ui=False,
enable_tts=False,
enable_stt=False,
enforce_h2ogpt_api_key=enforce_h2ogpt_api_key,
# or use file with h2ogpt_api_keys=h2ogpt_api_keys.json
h2ogpt_api_keys=[api_key] if api_key else None,
)
time.sleep(10)
else:
# RUN something
# e.g. CUDA_VISIBLE_DEVICES=0 python generate.py --verbose=True --score_model=None --gradio_offline_level=2 --base_model=openchat/openchat-3.5-1210 --inference_server=vllm:IP:port --max_seq_len=4096 --save_dir=duder1 --verbose --openai_server=True --concurency_count=64
pass
# api_key = "EMPTY" # if gradio/openai server not keyed. Can't pass '' itself, leads to httpcore.LocalProtocolError: Illegal header value b'Bearer '
# Setting H2OGPT_H2OGPT_KEY does not key h2oGPT, just passes along key to gradio inference server, so empty key is valid test regardless of the H2OGPT_H2OGPT_KEY value
# api_key = os.environ.get('H2OGPT_H2OGPT_KEY', 'EMPTY') # if keyed and have this in env with same key
print('api_key: %s' % api_key)
# below should be consistent with server prefix, host, and port
base_url = 'http://localhost:5000/v1'
verbose = True
system_prompt = "You are a helpful assistant."
chat_conversation = []
add_chat_history_to_context = True
client_kwargs = dict(model=base_model,
max_tokens=200,
stream=stream_output)
from openai import OpenAI, AsyncOpenAI
client_args = dict(base_url=base_url, api_key=api_key)
openai_client = OpenAI(**client_args)
async_client = AsyncOpenAI(**client_args)
try:
test_chat(chat, openai_client, async_client, system_prompt, chat_conversation, add_chat_history_to_context,
prompt, client_kwargs, stream_output, verbose)
except AssertionError:
if enforce_h2ogpt_api_key and api_key is None:
print("Expected to fail since no key but enforcing.")
else:
raise
# MODELS
model_info = openai_client.models.retrieve(base_model)
assert model_info.base_model == base_model
model_list = openai_client.models.list()
assert model_list.data[0] == base_model
def test_chat(chat, openai_client, async_client, system_prompt, chat_conversation, add_chat_history_to_context,
prompt, client_kwargs, stream_output, verbose):
# COMPLETION
if chat:
client = openai_client.chat.completions
async_client = async_client.chat.completions
messages0 = []
if system_prompt:
messages0.append({"role": "system", "content": system_prompt})
if chat_conversation and add_chat_history_to_context:
for message1 in chat_conversation:
if len(message1) == 2:
messages0.append(
{'role': 'user', 'content': message1[0] if message1[0] is not None else ''})
messages0.append(
{'role': 'assistant', 'content': message1[1] if message1[1] is not None else ''})
messages0.append({'role': 'user', 'content': prompt if prompt is not None else ''})
client_kwargs.update(dict(messages=messages0))
else:
client = openai_client.completions
async_client = async_client.completions
client_kwargs.update(dict(prompt=prompt))
responses = client.create(**client_kwargs)
if not stream_output:
if chat:
text = responses.choices[0].message.content
else:
text = responses.choices[0].text
print(text)
else:
collected_events = []
text = ''
for event in responses:
collected_events.append(event) # save the event response
if chat:
delta = event.choices[0].delta.content
else:
delta = event.choices[0].text # extract the text
text += delta # append the text
if verbose:
print('delta: %s' % delta)
print(text)
if "Who" in prompt:
assert 'OpenAI' in text or 'chatbot' in text
else:
assert 'birds' in text
if __name__ == '__main__':
launch_openai_server()