e489ad7a21
- **Add SPDX license headers to python source files**
- **Check for SPDX headers using pre-commit**
commit 9d7ef44c3cfb72ca4c32e1c677d99259d10d4745
Author: Russell Bryant <rbryant@redhat.com>
Date: Fri Jan 31 14:18:24 2025 -0500
Add SPDX license headers to python source files
This commit adds SPDX license headers to python source files as
recommended to
the project by the Linux Foundation. These headers provide a concise way
that is
both human and machine readable for communicating license information
for each
source file. It helps avoid any ambiguity about the license of the code
and can
also be easily used by tools to help manage license compliance.
The Linux Foundation runs license scans against the codebase to help
ensure
we are in compliance with the licenses of the code we use, including
dependencies. Having these headers in place helps that tool do its job.
More information can be found on the SPDX site:
- https://spdx.dev/learn/handling-license-info/
Signed-off-by: Russell Bryant <rbryant@redhat.com>
commit 5a1cf1cb3b80759131c73f6a9dddebccac039dea
Author: Russell Bryant <rbryant@redhat.com>
Date: Fri Jan 31 14:36:32 2025 -0500
Check for SPDX headers using pre-commit
Signed-off-by: Russell Bryant <rbryant@redhat.com>
---------
Signed-off-by: Russell Bryant <rbryant@redhat.com>
129 lines
3.7 KiB
Python
129 lines
3.7 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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import openai # use the official client for correctness check
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import pytest
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import pytest_asyncio
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from ...utils import RemoteOpenAIServer
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# any model with a chat template should work here
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MODEL_NAME = "HuggingFaceH4/zephyr-7b-beta"
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@pytest.fixture(scope="module")
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def server():
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args = [
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# use half precision for speed and memory savings in CI environment
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"--dtype",
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"bfloat16",
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"--max-model-len",
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"8192",
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"--enforce-eager",
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# lora config below
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"--max-num-seqs",
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"128",
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"--enable-chunked-prefill",
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"--max-num-batched-tokens",
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"1000",
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# large prompts create a lot of output
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"--disable-log-requests",
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]
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with RemoteOpenAIServer(MODEL_NAME, args) as remote_server:
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yield remote_server
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@pytest_asyncio.fixture
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async def client(server):
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async with server.get_async_client() as async_client:
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yield async_client
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@pytest.mark.asyncio
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async def test_completion_stream_options_and_logprobs_with_long_prompts(
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client: openai.AsyncOpenAI):
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# Test stream with long prompt
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prompt = "What is the capital of France?" * 400
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stream = await client.completions.create(
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model=MODEL_NAME,
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prompt=prompt,
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max_tokens=5,
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temperature=0.0,
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stream=True,
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stream_options={
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"include_usage": True,
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"continuous_usage_stats": True,
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},
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logprobs=5,
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)
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tokens_received = 0
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finished = False
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async for chunk in stream:
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assert chunk.usage.prompt_tokens >= 0
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assert chunk.usage.completion_tokens >= 0
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assert chunk.usage.total_tokens == (chunk.usage.prompt_tokens +
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chunk.usage.completion_tokens)
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if not finished:
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tokens_received += 1
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assert chunk.choices[0].text
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if chunk.choices[0].finish_reason is not None:
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finished = True
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if finished:
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assert chunk.usage.completion_tokens == tokens_received
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@pytest.mark.asyncio
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async def test_chat_completion_stream_options_and_logprobs_with_long_prompts(
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client: openai.AsyncOpenAI):
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# Test stream with long prompt
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messages = [{
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"role": "system",
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"content": "You are a helpful assistant."
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}, {
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"role": "user",
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"content": "What is the capital of France?" * 400
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}]
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stream = await client.chat.completions.create(
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model=MODEL_NAME,
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messages=messages,
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max_tokens=5,
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temperature=0.0,
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stream=True,
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stream_options={
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"include_usage": True,
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"continuous_usage_stats": True,
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},
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logprobs=True,
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top_logprobs=5,
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)
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tokens_received = 0
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empty_chunks_received = 0
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finished = False
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async for chunk in stream:
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assert chunk.usage.prompt_tokens >= 0
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assert chunk.usage.completion_tokens >= 0
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assert chunk.usage.total_tokens == (chunk.usage.prompt_tokens +
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chunk.usage.completion_tokens)
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if not finished:
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if chunk.choices[0].delta.content == "":
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# when there is no tokens generated
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assert chunk.usage.completion_tokens == 0
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assert chunk.choices[0].logprobs is None
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empty_chunks_received += 1
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else:
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tokens_received += 1
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if chunk.choices[0].finish_reason is not None:
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finished = True
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if finished:
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assert chunk.usage.completion_tokens == tokens_received
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assert empty_chunks_received <= 1
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