hf_text-generation-inference/integration-tests/models/test_completion_prompts.py

115 lines
3.3 KiB
Python

import pytest
import requests
import json
from aiohttp import ClientSession
from text_generation.types import (
Completion,
)
@pytest.fixture(scope="module")
def flash_llama_completion_handle(launcher):
with launcher(
"TinyLlama/TinyLlama-1.1B-Chat-v1.0",
) as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_llama_completion(flash_llama_completion_handle):
await flash_llama_completion_handle.health(300)
return flash_llama_completion_handle.client
# NOTE: since `v1/completions` is a deprecated inferface/endpoint we do not provide a convience
# method for it. Instead, we use the `requests` library to make the HTTP request directly.
@pytest.mark.release
def test_flash_llama_completion_single_prompt(
flash_llama_completion, response_snapshot
):
response = requests.post(
f"{flash_llama_completion.base_url}/v1/completions",
json={
"model": "tgi",
"prompt": "Say this is a test",
"max_tokens": 5,
"seed": 0,
},
headers=flash_llama_completion.headers,
stream=False,
)
response = response.json()
assert len(response["choices"]) == 1
assert response == response_snapshot
@pytest.mark.release
def test_flash_llama_completion_many_prompts(flash_llama_completion, response_snapshot):
response = requests.post(
f"{flash_llama_completion.base_url}/v1/completions",
json={
"model": "tgi",
"prompt": ["Say", "this", "is", "a"],
"max_tokens": 10,
"seed": 0,
},
headers=flash_llama_completion.headers,
stream=False,
)
response = response.json()
assert len(response["choices"]) == 4
all_indexes = [choice["index"] for choice in response["choices"]]
all_indexes.sort()
assert all_indexes == [0, 1, 2, 3]
assert response == response_snapshot
@pytest.mark.release
async def test_flash_llama_completion_many_prompts_stream(
flash_llama_completion, response_snapshot
):
request = {
"model": "tgi",
"prompt": [
"What color is the sky?",
"Is water wet?",
"What is the capital of France?",
"def mai",
],
"max_tokens": 10,
"seed": 0,
"stream": True,
}
url = f"{flash_llama_completion.base_url}/v1/completions"
chunks = []
async with ClientSession(headers=flash_llama_completion.headers) as session:
async with session.post(url, json=request) as response:
# iterate over the stream
async for chunk in response.content.iter_any():
# remove "data:"
chunk = chunk.decode().split("\n\n")
# remove "data:" if present
chunk = [c.replace("data:", "") for c in chunk]
# remove empty strings
chunk = [c for c in chunk if c]
# remove completion marking chunk
chunk = [c for c in chunk if c != " [DONE]"]
# parse json
chunk = [json.loads(c) for c in chunk]
for c in chunk:
chunks.append(Completion(**c))
assert "choices" in c
assert 0 <= c["choices"][0]["index"] <= 4
assert response.status == 200
assert chunks == response_snapshot