原文:Docker
如果你在单个生产节点上用过Docker,然后发现单个节点的资源不够用,那么你会怎么做呢?我也遇到过这种情况! 关于在生产环境中使用Docker Swarm,我会为你提供一些建议,也许能够帮到你。这些都是我一年来积累的一些经验。
另外,如果你对Docker Swam不熟悉的话,可以参考我之前的博客My experience with Docker Swarm - when you may need it?(http://suo.im/1m7qW8)
1. 阅读官方文档
<artifacts_info> | |
The assistant can create and reference artifacts during conversations. Artifacts are for substantial, self-contained content that users might modify or reuse, displayed in a separate UI window for clarity. | |
# Good artifacts are... | |
- Substantial content (>15 lines) | |
- Content that the user is likely to modify, iterate on, or take ownership of | |
- Self-contained, complex content that can be understood on its own, without context from the conversation | |
- Content intended for eventual use outside the conversation (e.g., reports, emails, presentations) | |
- Content likely to be referenced or reused multiple times |
version: '2' | |
services: | |
nextchat: | |
image: yidadaa/chatgpt-next-web | |
ports: | |
- "3000" | |
nginx: | |
image: nginx:alpine | |
ports: |
import asyncio | |
import logging | |
import webbrowser | |
from urllib.parse import quote | |
import httpx | |
from uuid import uuid4 | |
from connectai.lark.websocket import WS_LARK_PROXY_SERVER, WS_LARK_PROXY_PROTOCOL |
#!/usr/bin/python3 | |
import sys | |
import asyncio | |
import greenlet | |
class AsyncIoGreenlet(greenlet.greenlet): | |
def __init__(self, driver, fn): | |
greenlet.greenlet.__init__(self, fn, driver) | |
self.driver = driver |
原文:Docker
如果你在单个生产节点上用过Docker,然后发现单个节点的资源不够用,那么你会怎么做呢?我也遇到过这种情况! 关于在生产环境中使用Docker Swarm,我会为你提供一些建议,也许能够帮到你。这些都是我一年来积累的一些经验。
另外,如果你对Docker Swam不熟悉的话,可以参考我之前的博客My experience with Docker Swarm - when you may need it?(http://suo.im/1m7qW8)
1. 阅读官方文档
/** | |
* 1. 创建websocket连接,后端会生成对应的channel<user_id, task_id>,前端是一个固定的url | |
* 2. 监听创建成功事件 | |
* 2.1 如果创建成功就将任务<source_url, title, author>通过创建好的websocket发送到服务端 | |
* 2.2 如果创建失败,直接reject | |
* 3. 监听接收消息事件 | |
* 3.1 如果收到转换成功的url,代表后端的整个转换任务成功,将url resove出去 | |
* 3.2 收到其他任务进度消息,可以忽略 | |
*/ | |
export const submitTask = ( |
FROM nginx:alpine AS builder | |
# nginx:alpine contains NGINX_VERSION environment variable, like so: | |
# ENV NGINX_VERSION 1.15.0 | |
# Our NCHAN version | |
ENV NCHAN_VERSION 1.1.15 | |
# Download sources | |
RUN wget "http://nginx.org/download/nginx-${NGINX_VERSION}.tar.gz" -O nginx.tar.gz && \ |
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local count = 0 | |
local sum = 0 | |
local min = 0 | |
local max = 0 | |
local cursor = "0" | |
local result = nil | |
local data = nil | |
repeat | |
result = redis.call("zscan", KEYS[1], cursor, "count", 100) |
#!/usr/bin/env python | |
# http://www.rabbitmq.com/tutorials/tutorial-two-python.html | |
from connect import connection, pika | |
channel = connection.channel() | |
channel.exchange_declare(exchange='dlx') | |
result = channel.queue_declare(queue='dl') | |
queue_name = result.method.queue |