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# syntax=docker/dockerfile:1 | ||
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# From the parent directory (main directory of this repo) run: | ||
# | ||
# docker build --build-arg USERID=$(id -u) -t localhost/openai-bench openai | ||
# | ||
# docker run --rm -it --name openai-bench -e OPENAI_API_KEY='secret' \ | ||
# -v"$PWD":/home/user/llama-inference localhost/openai-bench \ | ||
# --baseurl https://api.openai.com:443/v1 --model gpt-3.5-turbo \ | ||
# --filename gpt-3.5-turbo.bench.csv --note "gpt-3.5-turbo" | ||
# | ||
# The container isn't self contained but designed to be used with the repo. | ||
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# Look for newer tags here https://hub.docker.com/_/python: | ||
FROM docker.io/python:3.12-bookworm | ||
ARG USERID=1000 | ||
COPY requirements.txt /tmp | ||
RUN pip3 install --no-cache-dir -r /tmp/requirements.txt | ||
RUN adduser --disabled-password --gecos '' -u $USERID user | ||
USER user | ||
WORKDIR /home/user/llama-inference/openai/ | ||
ENTRYPOINT ["python3", "bench.py"] | ||
CMD [ \ | ||
"--baseurl", "https://api.openai.com:443/v1", \ | ||
"--model", "gpt-3.5-turbo", \ | ||
"--filename", "/dev/stdout", \ | ||
"--note", "gpt-3.5-turbo" \ | ||
] |
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# OpenAI Chat API compatible benchmark | ||
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Benchmark for servers compatible with the [OpenAI Chat Completions API](https://platform.openai.com/docs/guides/text-generation/chat-completions-api). | ||
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You can follow the instructions in the [Dockerfile](Dockerfile) to build a container to run the benchmark. | ||
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Or alternatively on your own machine: | ||
```sh | ||
cd openai | ||
pip3 -r requirements.txt | ||
export OPENAI_API_KEY='secret' #obtain from https://platform.openai.com/api-keys | ||
python3 client.py #to test a single run | ||
python3 bench.py --help #get usage help | ||
python3 bench.py --baseurl https://api.openai.com:443/v1 --model gpt-3.5-turbo \ | ||
--filename gpt-3.5-turbo.bench.csv --note "gpt-3.5-turbo" | ||
``` |
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from client import chat,args | ||
import sys | ||
sys.path.append('../common/') | ||
from questions import questions | ||
import pandas as pd | ||
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if __name__ == '__main__': | ||
counter = 1 | ||
responses = [] | ||
for q in questions: | ||
response = chat(q) | ||
if counter >= 2: # allow for a warmup | ||
responses.append(response) | ||
counter +=1 | ||
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df = pd.DataFrame(responses) | ||
df.to_csv(args.filename, index=False) |
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from openai import OpenAI | ||
import argparse | ||
import time | ||
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#TODO: should use a parent parser without --filename here. | ||
parser = argparse.ArgumentParser(description='Run LLM inference requests and save to a CSV.') | ||
parser.add_argument('--filename', type=str, default='/dev/stdout', | ||
help='Path to the output CSV file (stdout by default).') | ||
parser.add_argument('--note', type=str, | ||
help='Note to add to the rows of the file (--model by default).') | ||
parser.add_argument('--model', type=str, default='gpt-3.5-turbo', | ||
help='Model to use (gpt-3.5-turbo by default).') | ||
parser.add_argument('--baseurl', type=str, default='https://api.openai.com:443/v1', | ||
help='Endpoint base URL (https://api.openai.com:443/v1 by default).') | ||
args = parser.parse_args() | ||
if ('note' not in args): | ||
args.note = args.model | ||
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client = OpenAI(base_url=args.baseurl) | ||
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def chat(prompt:str): | ||
start = time.perf_counter() | ||
result = client.chat.completions.create( | ||
model=args.model, | ||
max_tokens=200, | ||
messages=[ | ||
{"role": "system", "content": "You are a very verbose and helpful assistant"}, | ||
{"role": "user", "content": prompt} | ||
] | ||
) | ||
request_time = time.perf_counter() - start | ||
return {'tok_count': result.usage.completion_tokens, | ||
'time': request_time, | ||
'question': prompt, | ||
'answer': result.choices[0].message.content, | ||
'note': args.note} | ||
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if __name__ == '__main__': | ||
prompt = "San Francisco is a city in" | ||
result = chat(prompt) | ||
tokPerSec = result['tok_count']/result['time'] | ||
print(f"User: {prompt}\n" | ||
f"Chatbot in {result['time']}s with {result['tok_count']} tokens ({tokPerSec} t/s):\n" | ||
f"{result['answer']}") |
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annotated-types==0.6.0 | ||
anyio==4.3.0 | ||
certifi==2024.2.2 | ||
distro==1.9.0 | ||
h11==0.14.0 | ||
httpcore==1.0.5 | ||
httpx==0.27.0 | ||
idna==3.6 | ||
numpy==1.26.4 | ||
openai==1.16.2 | ||
pandas==2.2.1 | ||
pydantic==2.6.4 | ||
pydantic_core==2.16.3 | ||
python-dateutil==2.9.0.post0 | ||
pytz==2024.1 | ||
setuptools==69.1.1 | ||
six==1.16.0 | ||
sniffio==1.3.1 | ||
tqdm==4.66.2 | ||
typing_extensions==4.11.0 | ||
tzdata==2024.1 | ||
wheel==0.43.0 |