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- **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>
144 lines
7.2 KiB
Python
144 lines
7.2 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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import json
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import subprocess
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import sys
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import tempfile
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from vllm.entrypoints.openai.protocol import BatchRequestOutput
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# ruff: noqa: E501
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INPUT_BATCH = """{"custom_id": "request-1", "method": "POST", "url": "/v1/chat/completions", "body": {"model": "NousResearch/Meta-Llama-3-8B-Instruct", "messages": [{"role": "system", "content": "You are a helpful assistant."},{"role": "user", "content": "Hello world!"}],"max_tokens": 1000}}
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{"custom_id": "request-2", "method": "POST", "url": "/v1/chat/completions", "body": {"model": "NousResearch/Meta-Llama-3-8B-Instruct", "messages": [{"role": "system", "content": "You are an unhelpful assistant."},{"role": "user", "content": "Hello world!"}],"max_tokens": 1000}}
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{"custom_id": "request-3", "method": "POST", "url": "/v1/chat/completions", "body": {"model": "NonExistModel", "messages": [{"role": "system", "content": "You are an unhelpful assistant."},{"role": "user", "content": "Hello world!"}],"max_tokens": 1000}}
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{"custom_id": "request-4", "method": "POST", "url": "/bad_url", "body": {"model": "NousResearch/Meta-Llama-3-8B-Instruct", "messages": [{"role": "system", "content": "You are an unhelpful assistant."},{"role": "user", "content": "Hello world!"}],"max_tokens": 1000}}
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{"custom_id": "request-5", "method": "POST", "url": "/v1/chat/completions", "body": {"stream": "True", "model": "NousResearch/Meta-Llama-3-8B-Instruct", "messages": [{"role": "system", "content": "You are an unhelpful assistant."},{"role": "user", "content": "Hello world!"}],"max_tokens": 1000}}"""
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INVALID_INPUT_BATCH = """{"invalid_field": "request-1", "method": "POST", "url": "/v1/chat/completions", "body": {"model": "NousResearch/Meta-Llama-3-8B-Instruct", "messages": [{"role": "system", "content": "You are a helpful assistant."},{"role": "user", "content": "Hello world!"}],"max_tokens": 1000}}
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{"custom_id": "request-2", "method": "POST", "url": "/v1/chat/completions", "body": {"model": "NousResearch/Meta-Llama-3-8B-Instruct", "messages": [{"role": "system", "content": "You are an unhelpful assistant."},{"role": "user", "content": "Hello world!"}],"max_tokens": 1000}}"""
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INPUT_EMBEDDING_BATCH = """{"custom_id": "request-1", "method": "POST", "url": "/v1/embeddings", "body": {"model": "intfloat/e5-mistral-7b-instruct", "input": "You are a helpful assistant."}}
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{"custom_id": "request-2", "method": "POST", "url": "/v1/embeddings", "body": {"model": "intfloat/e5-mistral-7b-instruct", "input": "You are an unhelpful assistant."}}
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{"custom_id": "request-3", "method": "POST", "url": "/v1/embeddings", "body": {"model": "intfloat/e5-mistral-7b-instruct", "input": "Hello world!"}}
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{"custom_id": "request-4", "method": "POST", "url": "/v1/embeddings", "body": {"model": "NonExistModel", "input": "Hello world!"}}"""
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INPUT_SCORE_BATCH = """{"custom_id": "request-1", "method": "POST", "url": "/v1/score", "body": {"model": "BAAI/bge-reranker-v2-m3", "text_1": "What is the capital of France?", "text_2": ["The capital of Brazil is Brasilia.", "The capital of France is Paris."]}}
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{"custom_id": "request-2", "method": "POST", "url": "/v1/score", "body": {"model": "BAAI/bge-reranker-v2-m3", "text_1": "What is the capital of France?", "text_2": ["The capital of Brazil is Brasilia.", "The capital of France is Paris."]}}"""
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def test_empty_file():
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with tempfile.NamedTemporaryFile(
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"w") as input_file, tempfile.NamedTemporaryFile(
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"r") as output_file:
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input_file.write("")
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input_file.flush()
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proc = subprocess.Popen([
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sys.executable, "-m", "vllm.entrypoints.openai.run_batch", "-i",
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input_file.name, "-o", output_file.name, "--model",
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"intfloat/e5-mistral-7b-instruct"
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], )
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proc.communicate()
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proc.wait()
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assert proc.returncode == 0, f"{proc=}"
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contents = output_file.read()
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assert contents.strip() == ""
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def test_completions():
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with tempfile.NamedTemporaryFile(
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"w") as input_file, tempfile.NamedTemporaryFile(
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"r") as output_file:
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input_file.write(INPUT_BATCH)
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input_file.flush()
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proc = subprocess.Popen([
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sys.executable, "-m", "vllm.entrypoints.openai.run_batch", "-i",
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input_file.name, "-o", output_file.name, "--model",
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"NousResearch/Meta-Llama-3-8B-Instruct"
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], )
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proc.communicate()
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proc.wait()
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assert proc.returncode == 0, f"{proc=}"
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contents = output_file.read()
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for line in contents.strip().split("\n"):
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# Ensure that the output format conforms to the openai api.
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# Validation should throw if the schema is wrong.
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BatchRequestOutput.model_validate_json(line)
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def test_completions_invalid_input():
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"""
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Ensure that we fail when the input doesn't conform to the openai api.
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"""
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with tempfile.NamedTemporaryFile(
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"w") as input_file, tempfile.NamedTemporaryFile(
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"r") as output_file:
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input_file.write(INVALID_INPUT_BATCH)
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input_file.flush()
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proc = subprocess.Popen([
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sys.executable, "-m", "vllm.entrypoints.openai.run_batch", "-i",
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input_file.name, "-o", output_file.name, "--model",
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"NousResearch/Meta-Llama-3-8B-Instruct"
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], )
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proc.communicate()
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proc.wait()
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assert proc.returncode != 0, f"{proc=}"
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def test_embeddings():
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with tempfile.NamedTemporaryFile(
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"w") as input_file, tempfile.NamedTemporaryFile(
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"r") as output_file:
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input_file.write(INPUT_EMBEDDING_BATCH)
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input_file.flush()
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proc = subprocess.Popen([
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sys.executable, "-m", "vllm.entrypoints.openai.run_batch", "-i",
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input_file.name, "-o", output_file.name, "--model",
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"intfloat/e5-mistral-7b-instruct"
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], )
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proc.communicate()
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proc.wait()
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assert proc.returncode == 0, f"{proc=}"
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contents = output_file.read()
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for line in contents.strip().split("\n"):
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# Ensure that the output format conforms to the openai api.
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# Validation should throw if the schema is wrong.
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BatchRequestOutput.model_validate_json(line)
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def test_score():
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with tempfile.NamedTemporaryFile(
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"w") as input_file, tempfile.NamedTemporaryFile(
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"r") as output_file:
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input_file.write(INPUT_SCORE_BATCH)
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input_file.flush()
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proc = subprocess.Popen([
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sys.executable,
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"-m",
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"vllm.entrypoints.openai.run_batch",
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"-i",
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input_file.name,
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"-o",
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output_file.name,
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"--model",
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"BAAI/bge-reranker-v2-m3",
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], )
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proc.communicate()
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proc.wait()
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assert proc.returncode == 0, f"{proc=}"
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contents = output_file.read()
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for line in contents.strip().split("\n"):
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# Ensure that the output format conforms to the openai api.
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# Validation should throw if the schema is wrong.
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BatchRequestOutput.model_validate_json(line)
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# Ensure that there is no error in the response.
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line_dict = json.loads(line)
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assert isinstance(line_dict, dict)
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assert line_dict["error"] is None
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