mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-06 09:07:10 +08:00
Add stable ci (#3460)
* add stable ci * fix * update * fix * rename tests dir;fix stable ci bug * add timeout limit * update
This commit is contained in:
YUNSHEN XIE
487
tests/ce/deploy/deploy.py
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487
tests/ce/deploy/deploy.py
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@@ -0,0 +1,487 @@
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import ast
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import json
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import os
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import re
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import signal
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import socket
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import subprocess
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import sys
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import time
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import traceback
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import requests
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import yaml
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from flask import Flask, Response, jsonify, request
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app = Flask(__name__)
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def get_base_port():
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"""获取base port"""
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nv_visible_devices = os.environ.get("CUDA_VISIBLE_DEVICES", "")
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if not nv_visible_devices or nv_visible_devices.lower() == "all":
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return 8000
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# 提取第一个数字
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match = re.search(r"\d+", nv_visible_devices)
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if match:
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return int(match.group(0)) * 100 + 8000
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return 8000
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def is_port_in_use(port):
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"""检查端口是否被占用"""
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with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
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return s.connect_ex(("localhost", port)) == 0
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def get_available_port(env_key: str, default_start: int):
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"""从环境变量读取端口，如果未设置或已被占用，则从default_start开始寻找空闲端口"""
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port_str = os.environ.get(env_key)
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if port_str and port_str.isdigit():
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port = int(port_str)
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if not is_port_in_use(port):
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return port
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else:
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print(f"Warning: Port {port} from {env_key} is in use, searching for a free port...")
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# 从 default_start 开始查找空闲端口
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port = default_start
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while is_port_in_use(port):
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port += 1
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return port
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# 默认参数值
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PID_FILE = "pid_port"
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LOG_FILE = "server.log"
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base_port = get_base_port()
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FLASK_PORT = get_available_port("FLASK_PORT", base_port + 1)
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FD_API_PORT = get_available_port("FD_API_PORT", FLASK_PORT + 1)
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FD_ENGINE_QUEUE_PORT = get_available_port("FD_ENGINE_QUEUE_PORT", FD_API_PORT + 1)
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FD_METRICS_PORT = get_available_port("FD_METRICS_PORT", FD_ENGINE_QUEUE_PORT + 1)
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DEFAULT_PARAMS = {
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"--port": FD_API_PORT,
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"--engine-worker-queue-port": FD_ENGINE_QUEUE_PORT,
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"--metrics-port": FD_METRICS_PORT,
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"--enable-logprob": True,
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}
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def build_command(config):
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"""根据配置构建启动命令"""
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# 基础命令
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cmd = [
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"python",
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"-m",
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"fastdeploy.entrypoints.openai.api_server",
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]
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# 添加配置参数
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for key, value in config.items():
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if "--enable" in key:
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if value:
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cmd.append(key)
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else:
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cmd.extend([key, str(value)])
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return cmd
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def merge_configs(base_config, override_config):
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"""合并配置，优先级：override_config > base_config"""
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merged = base_config.copy()
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if override_config:
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for key in override_config:
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merged[key] = override_config[key]
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return merged
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def get_server_pid():
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"""获取服务进程ID PORT"""
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if os.path.exists(PID_FILE):
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with open(PID_FILE, "r") as f:
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data = yaml.safe_load(f)
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return data
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return None
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def is_server_running():
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"""检查服务是否正在运行"""
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pid_port = get_server_pid()
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if pid_port is None:
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return False, {"status": "Server not running..."}
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_, port = pid_port["PID"], pid_port["PORT"]
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health_check_endpoint = f"http://0.0.0.0:{port}/health"
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if os.path.exists(LOG_FILE):
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with open(LOG_FILE, "r") as f:
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msg = f.readlines()
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result = parse_tqdm_progress(msg)
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try:
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response = requests.get(health_check_endpoint, timeout=2)
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return response.status_code == 200, result
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except requests.exceptions.RequestException as e:
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print(f"Failed to check server health: {e}")
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return False, result
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def parse_tqdm_progress(log_lines):
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"""
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解析 tqdm 风格的进度条
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"""
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tqdm_pattern = re.compile(
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r"(?P<prefix>.+?):\s+(?P<percent>\d+)%\|(?P<bar>.+?)\|\s+(?P<step>\d+/\d+)\s+\[(?P<elapsed>\d+:\d+)<(?P<eta>\d+:\d+),\s+(?P<speed>[\d\.]+it/s)\]"
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)
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for line in reversed(log_lines):
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match = tqdm_pattern.search(line)
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if match:
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data = match.groupdict()
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return {
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"status": "服务启动中",
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"progress": {
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"percent": int(data["percent"]),
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"step": data["step"],
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"speed": data["speed"],
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"eta": data["eta"],
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"elapsed": data["elapsed"],
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"bar": data["bar"].strip(),
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},
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"raw_line": line.strip(),
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}
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return {"status": "服务启动中", "progress": {}, "raw_line": log_lines[-1] if log_lines else "server.log为空"}
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def stop_server(signum=None, frame=None):
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"""停止大模型推理服务"""
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pid_port = get_server_pid()
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if pid_port is None:
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if signum:
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sys.exit(0)
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return jsonify({"status": "error", "message": "Service is not running"}), 400
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server_pid, _ = pid_port["PID"], pid_port["PORT"]
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# 清理PID文件
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if os.path.exists(PID_FILE):
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os.remove(PID_FILE)
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if os.path.exists("gemm_profiles.json"):
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os.remove("gemm_profiles.json")
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try:
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# 终止进程组（包括所有子进程）
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os.killpg(os.getpgid(pid_port["PID"]), signal.SIGTERM)
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except Exception as e:
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print(f"Failed to stop server: {e}, {str(traceback.format_exc())}")
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for port in [FD_API_PORT, FD_ENGINE_QUEUE_PORT, FD_METRICS_PORT]:
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try:
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output = subprocess.check_output(f"lsof -i:{port} -t", shell=True).decode().strip()
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for pid in output.splitlines():
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os.kill(int(pid), signal.SIGKILL)
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print(f"Killed process on port {port}, pid={pid}")
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except Exception as e:
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print(f"Failed to kill process on port: {e}, {str(traceback.format_exc())}")
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# 若log目录存在，则重命名为log_timestamp
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if os.path.isdir("./log"):
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os.rename("./log", "./log_{}".format(time.strftime("%Y%m%d%H%M%S")))
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if signum:
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sys.exit(0)
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return jsonify({"status": "success", "message": "Service stopped", "pid": server_pid}), 200
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# 捕获 SIGINT (Ctrl+C) 和 SIGTERM (kill)
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signal.signal(signal.SIGINT, stop_server)
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signal.signal(signal.SIGTERM, stop_server)
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@app.route("/start", methods=["POST"])
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def start_service():
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"""启动大模型推理服务"""
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# 检查服务是否已在运行
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if is_server_running()[0]:
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return Response(
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json.dumps({"status": "error", "message": "服务已启动，无需start"}, ensure_ascii=False),
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status=400,
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content_type="application/json",
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)
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try:
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base_config = DEFAULT_PARAMS
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override_config = request.get_json() or {}
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print("override_config", override_config)
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final_config = merge_configs(base_config, override_config)
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global FD_API_PORT
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global FD_ENGINE_QUEUE_PORT
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global FD_METRICS_PORT
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FD_API_PORT = final_config["--port"]
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FD_ENGINE_QUEUE_PORT = final_config["--engine-worker-queue-port"]
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FD_METRICS_PORT = final_config["--metrics-port"]
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# 构建命令
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cmd = build_command(final_config)
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except Exception as e:
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error_msg = f"Failed to start service: {e}, {str(traceback.format_exc())}"
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print(error_msg)
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return Response(
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json.dumps({"status": "error", "message": error_msg}, ensure_ascii=False),
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status=500,
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content_type="application/json",
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)
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print("cmd", cmd)
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try:
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# 设置环境变量并启动进程
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env = os.environ.copy()
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with open(LOG_FILE, "w") as log:
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process = subprocess.Popen(cmd, stdout=log, stderr=log, env=env, start_new_session=True)
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# 保存进程ID,port到yaml文件
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with open(PID_FILE, "w") as f:
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yaml.dump({"PID": process.pid, "PORT": final_config["--port"]}, f)
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json_data = {
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"status": "success",
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"message": "服务启动命令已执行",
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"pid": process.pid,
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"config": final_config,
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"log_file": LOG_FILE,
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"cmd": cmd,
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"port_info": {
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"api_port": FD_API_PORT,
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"queue_port": FD_ENGINE_QUEUE_PORT,
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"metrics_port": FD_METRICS_PORT,
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},
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}
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return Response(json.dumps(json_data, ensure_ascii=False), status=200, content_type="application/json")
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except Exception as e:
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error_msg = f"Failed to start service: {e}, {str(traceback.format_exc())}"
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print(error_msg)
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return Response(
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json.dumps({"status": "error", "message": error_msg}, ensure_ascii=False),
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status=500,
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content_type="application/json",
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)
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@app.route("/switch", methods=["POST"])
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def switch_service():
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"""切换模型服务"""
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# kill掉已有服务
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stop_server()
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time.sleep(2)
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try:
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base_config = DEFAULT_PARAMS
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override_config = request.get_json() or {}
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final_config = merge_configs(base_config, override_config)
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global FD_API_PORT
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global FD_ENGINE_QUEUE_PORT
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global FD_METRICS_PORT
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FD_API_PORT = final_config["--port"]
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FD_ENGINE_QUEUE_PORT = final_config["--engine-worker-queue-port"]
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FD_METRICS_PORT = final_config["--metrics-port"]
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# 构建命令
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cmd = build_command(final_config)
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except Exception as e:
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error_msg = f"Failed to switch service: {e}, {str(traceback.format_exc())}"
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print(error_msg)
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return Response(
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json.dumps({"status": "error", "message": error_msg}, ensure_ascii=False),
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status=500,
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content_type="application/json",
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)
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print("cmd", cmd)
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try:
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# 设置环境变量并启动进程
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env = os.environ.copy()
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with open(LOG_FILE, "w") as log:
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process = subprocess.Popen(cmd, stdout=log, stderr=log, env=env, start_new_session=True)
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# 保存进程ID,port到yaml文件
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with open(PID_FILE, "w") as f:
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yaml.dump({"PID": process.pid, "PORT": final_config["--port"]}, f)
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json_data = {
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"status": "success",
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"message": "服务启动命令已执行",
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"pid": process.pid,
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"config": final_config,
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"log_file": LOG_FILE,
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"cmd": cmd,
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"port_info": {
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"api_port": FD_API_PORT,
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"queue_port": FD_ENGINE_QUEUE_PORT,
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"metrics_port": FD_METRICS_PORT,
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},
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}
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return Response(json.dumps(json_data, ensure_ascii=False), status=200, content_type="application/json")
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except Exception as e:
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error_msg = f"Failed to switch service: {e}, {str(traceback.format_exc())}"
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print(error_msg)
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return Response(
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json.dumps({"status": "error", "message": error_msg}, ensure_ascii=False),
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status=500,
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content_type="application/json",
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)
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@app.route("/status", methods=["GET", "POST"])
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def service_status():
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"""检查服务状态"""
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health, msg = is_server_running()
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if not health:
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return Response(json.dumps(msg, ensure_ascii=False), status=500, content_type="application/json")
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# 检查端口是否监听
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ports_status = {
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"api_port": FD_API_PORT if is_port_in_use(FD_API_PORT) else None,
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"queue_port": FD_ENGINE_QUEUE_PORT if is_port_in_use(FD_ENGINE_QUEUE_PORT) else None,
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"metrics_port": FD_METRICS_PORT if is_port_in_use(FD_METRICS_PORT) else None,
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}
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msg["status"] = "服务启动完成"
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msg["ports_status"] = ports_status
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return Response(json.dumps(msg, ensure_ascii=False), status=200, content_type="application/json")
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@app.route("/stop", methods=["POST"])
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def stop_service():
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"""停止大模型推理服务"""
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res, status_code = stop_server()
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return res, status_code
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@app.route("/config", methods=["GET"])
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def get_config():
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"""获取当前server配置"""
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health, msg = is_server_running()
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if not health:
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return Response(json.dumps(msg, ensure_ascii=False), status=500, content_type="application/json")
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|
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if not os.path.exists("log/api_server.log"):
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return Response(
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json.dumps({"message": "api_server.log不存在"}, ensure_ascii=False),
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status=500,
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content_type="application/json",
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)
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try:
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# 筛选出包含"args:"的行
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with open("log/api_server.log", "r") as f:
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lines = [line for line in f.readlines() if "args:" in line]
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last_line = lines[-1] if lines else ""
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# 使用正则表达式提取JSON格式的配置
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match = re.search(r"args\s*[:：]\s*(.*)", last_line)
|
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if not match:
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return Response(
|
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json.dumps({"message": "api_server.log中没有args信息，请检查log"}, ensure_ascii=False),
|
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status=500,
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content_type="application/json",
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)
|
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# 尝试解析JSON
|
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config_json = match.group(1).strip()
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config_data = ast.literal_eval(config_json)
|
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print("config_data", config_data, type(config_data))
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return Response(
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json.dumps({"server_config": config_data}, ensure_ascii=False), status=200, content_type="application/json"
|
||||
)
|
||||
|
||||
except Exception as e:
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error_msg = f"{e}, {str(traceback.format_exc())}"
|
||||
print(error_msg)
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return Response(
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json.dumps({"message": "api_server.log解析失败，请检查log", "error": error_msg}, ensure_ascii=False),
|
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status=500,
|
||||
content_type="application/json",
|
||||
)
|
||||
|
||||
|
||||
@app.route("/wait_for_infer", methods=["POST"])
|
||||
def wait_for_infer():
|
||||
timeout = int(request.args.get("timeout", 120)) # 可选超时时间，默认120秒
|
||||
interval = 2
|
||||
response_interval = 10
|
||||
start_time = time.time()
|
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next_response_time = start_time
|
||||
|
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def generate():
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nonlocal next_response_time
|
||||
while True:
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health, msg = is_server_running()
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now = time.time()
|
||||
|
||||
elapsed = time.time() - start_time
|
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|
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if health:
|
||||
ports_status = {
|
||||
"api_port": FD_API_PORT if is_port_in_use(FD_API_PORT) else None,
|
||||
"queue_port": FD_ENGINE_QUEUE_PORT if is_port_in_use(FD_ENGINE_QUEUE_PORT) else None,
|
||||
"metrics_port": FD_METRICS_PORT if is_port_in_use(FD_METRICS_PORT) else None,
|
||||
}
|
||||
msg["status"] = "服务启动完成"
|
||||
msg["ports_status"] = ports_status
|
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yield json.dumps(msg, ensure_ascii=False) + "\n"
|
||||
break
|
||||
|
||||
if elapsed >= timeout:
|
||||
|
||||
def tail_file(path, lines=50):
|
||||
try:
|
||||
with open(path, "r", encoding="utf-8", errors="ignore") as f:
|
||||
return "".join(f.readlines()[-lines:])
|
||||
except Exception as e:
|
||||
return f"[无法读取 {path}]: {e}, {str(traceback.format_exc())}\n"
|
||||
|
||||
result = f"服务启动超时，耗时：[{timeout}s]\n\n"
|
||||
result += "==== server.log tail 50 ====\n"
|
||||
result += tail_file("server.log")
|
||||
result += "\n==== log/workerlog.0 tail 50 ====\n"
|
||||
result += tail_file("log/workerlog.0")
|
||||
|
||||
yield result
|
||||
break
|
||||
|
||||
if now >= next_response_time:
|
||||
msg["status"] = f"服务启动中，耗时：[{int(elapsed)}s]"
|
||||
yield json.dumps(msg, ensure_ascii=False) + "\n"
|
||||
next_response_time += response_interval
|
||||
|
||||
time.sleep(interval)
|
||||
|
||||
return Response(generate(), status=200, content_type="text/plain")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
print(f"FLASK_PORT: {FLASK_PORT}")
|
||||
print(f"FD_API_PORT: {FD_API_PORT}")
|
||||
print(f"FD_ENGINE_QUEUE_PORT: {FD_ENGINE_QUEUE_PORT}")
|
||||
print(f"FD_METRICS_PORT: {FD_METRICS_PORT}")
|
||||
app.run(host="0.0.0.0", port=FLASK_PORT, debug=False)
|
||||
Reference in New Issue
Block a user