To assess the likelihood of each of your predictions, I'll use the following scale:
1️⃣ Very Unlikely
2️⃣ Unlikely
3️⃣ Possible
4️⃣ Likely
CREATE proc [dbo].[sp_MSforeachtable] | |
@command1 nvarchar(2000), @replacechar nchar(1) = N'?', @command2 nvarchar(2000) = null, | |
@command3 nvarchar(2000) = null, @whereand nvarchar(2000) = null, | |
@precommand nvarchar(2000) = null, @postcommand nvarchar(2000) = null | |
AS | |
declare @mscat nvarchar(12) | |
select @mscat = ltrim(str(convert(int, 0x0002))) | |
if (@precommand is not null) | |
exec(@precommand) |
To assess the likelihood of each of your predictions, I'll use the following scale:
1️⃣ Very Unlikely
2️⃣ Unlikely
3️⃣ Possible
4️⃣ Likely
This project is a Node.js application that emphasizes a simple, object-oriented design using JavaScript classes. It leverages modern JavaScript features and is structured for clarity and maintainability. The application is deployed using AWS Lambda's SAM framework to utilize services like SQS and S3. Common scripts for setup, testing, and deployment are located in the `bin` directory, and testing is conducted with Jest, focusing on public interfaces. | |
## Use Existing Styles | |
- Adhere to the project's existing styles and naming conventions. | |
## Object-Oriented Design | |
- Favor simple, object-oriented approaches using classes. | |
- Each file in the `src` directory should export a single class. | |
- Utilize all JavaScript class features, including: | |
- Static methods |
You are an AI assistant designed to provide detailed, step-by-step responses. Your outputs should follow this structure: | |
1. Begin with a <thinking> section. Everything in this section is invisible to the user. | |
2. Inside the thinking section: | |
a. Briefly analyze the question and outline your approach. | |
b. Present a clear plan of steps to solve the problem. | |
c. Use a "Chain of Thought" reasoning process if necessary, breaking down your thought process into numbered steps. | |
3. Include a <reflection> section for each idea where you: | |
a. Review your reasoning. | |
b. Check for potential errors or oversights. |
import { z } from "zod"; | |
import { zodResponseFormat } from "openai/helpers/zod"; | |
const uiSchema = z | |
.lazy(() => | |
z.object({ | |
type: z | |
.enum(["div", "button", "header", "section", "field", "form"]) | |
.describe("The type of the UI component"), | |
label: z |
# WAIT! Do consider that `wait` may not be needed. This article describes | |
# that reasoning. Please read it and make informed decisions. | |
# https://www.varvet.com/blog/why-wait_until-was-removed-from-capybara/ | |
# Have you ever had to sleep() in Capybara-WebKit to wait for AJAX and/or CSS animations? | |
describe 'Modal' do | |
should 'display login errors' do | |
visit root_path |
# Example of using SQLite VSS with OpenAI's text embedding API | |
# from Ruby. | |
# Note: Install/bundle the sqlite3, sqlite_vss, and ruby-openai gems first | |
# OPENAI_API_KEY must also be set in the environment | |
# Other embeddings can be used, but this is the easiest for a quick demo | |
# More on the topic at | |
# https://observablehq.com/@asg017/introducing-sqlite-vss | |
# https://observablehq.com/@asg017/making-sqlite-extension-gem-installable |
DisconnectWSLambda: | |
Type: AWS::Serverless::Function | |
Properties: | |
Handler: index.handler | |
CodeUri: "/var/task/src/ws/disconnect" | |
Runtime: nodejs16.x | |
Architectures: | |
- x86_64 | |
MemorySize: 1152 | |
DisconnectWSRoute: |