使用fastchat实现大模型高并发对话_fastchat并发处理能力

手动执行脚本

python3 -m fastchat.serve.controller
CUDA_VISIBLE_DEVICES=0 python3 -m fastchat.serve.model_worker --model-path /home/NLP/LLM/pretrained_model/LanguageModels/ChatGLM2_6B --limit-worker-concurrency 100 --max-gpu-memory "44GiB" --port 31001 --worker http://localhost:31001 --load-8bit
CUDA_VISIBLE_DEVICES=0 python3 -m fastchat.serve.model_worker --model-path /home/NLP/LLM/pretrained_model/LanguageModels/ChatGLM2_6B --limit-worker-concurrency 100 --max-gpu-memory "44GiB" --port 31002 --worker http://localhost:31002 --load-8bit
CUDA_VISIBLE_DEVICES=1 python3 -m fastchat.serve.model_worker --model-path /home/NLP/LLM/pretrained_model/LanguageModels/ChatGLM2_6B --limit-worker-concurrency 100 --max-gpu-memory "44GiB" --port 31003 --worker http://localhost:31003 --load-8bit
CUDA_VISIBLE_DEVICES=1 python3 -m fastchat.serve.model_worker --model-path /home/NLP/LLM/pretrained_model/LanguageModels/ChatGLM2_6B --limit-worker-concurrency 100 --max-gpu-memory "44GiB" --port 31004 --worker http://localhost:31004 --load-8bit
python3 -m fastchat.serve.gradio_web_server --concurrency-count=150
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脚本一键启动

import subprocess
import multiprocessing
import time
import fastchat.serve.gradio_web_server

def execute_command(command):
    # Execute the command
    try:
        subprocess.run(command, shell=True, check=True)
    except subprocess.CalledProcessError as e:
        print(f"Error executing command: {e}")

if __name__ == "__main__":
    scripts = [
        "python3 -m fastchat.serve.controller",
        "CUDA_VISIBLE_DEVICES=0 python3 -m fastchat.serve.model_worker --model-path /home/NLP/LLM/pretrained_model/LanguageModels/ChatGLM2_6B --limit-worker-concurrency 100 --max-gpu-memory 44GiB --port 31001 --worker http://localhost:31001 --load-8bit",
        "CUDA_VISIBLE_DEVICES=0 python3 -m fastchat.serve.model_worker --model-path /home/NLP/LLM/pretrained_model/LanguageModels/ChatGLM2_6B --limit-worker-concurrency 100 --max-gpu-memory 44GiB --port 31002 --worker http://localhost:31002 --load-8bit",
        "CUDA_VISIBLE_DEVICES=1 python3 -m fastchat.serve.model_worker --model-path /home/NLP/LLM/pretrained_model/LanguageModels/ChatGLM2_6B --limit-worker-concurrency 100 --max-gpu-memory 44GiB --port 31003 --worker http://localhost:31003 --load-8bit",
        "CUDA_VISIBLE_DEVICES=1 python3 -m fastchat.serve.model_worker --model-path /home/NLP/LLM/pretrained_model/LanguageModels/ChatGLM2_6B --limit-worker-concurrency 100 --max-gpu-memory 44GiB --port 31004 --worker http://localhost:31004 --load-8bit",
        "python3 -m fastchat.serve.gradio_web_server --concurrency-count=150"
    ]
    processes = []
    start_time = 10
    add_time = 5
    for script in scripts:
        # Create a new process for each command
        p = multiprocessing.Process(target=execute_command, args=(script,))
        processes.append(p)

    for p in processes:
        p.start()
        # Wait for 5 seconds before starting the next process
        time.sleep(start_time)
        start_time += add_time

    for p in processes:
        p.join()
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