Today, we've curated 8 GitHub projects that cover serverless frameworks, visual task code generation, data management, real-time backend building, chatbot development, AI data collaboration, AI side hustle making money, and tech interview preparation to help you upskill and work more efficiently!
1. Serverless framework
️仓库名称:serverless/serverless
Stars as of press time: 46204 (New: 4)
仓库语言: JavaScript
仓库开源协议:MIT License
introduction
This article provides an overview of the serverless framework, which is a powerful tool for developers to build and deploy serverless applications on AWS.
Project role
The framework simplifies the process of deploying serverless applications by providing a command-line interface and easy-to-understand YAML syntax. It supports multiple languages, including Node.js, Python, Go, and Java. The framework also provides extensive extensibility through plug-ins that add additional use cases and workflows.
Description of the warehouse
The GitHub repository for a serverless framework contains the source code, documentation, and plugins for that framework. Actively maintained by Serverless Inc.
Case
Serverless Framework V.4 was released in June 2024 and introduces several new features such as native TypeScript support, new development models, and integration with Terraform and Vault. It also includes significant changes to licenses and authentication.
Objective evaluation or analysis
Serverless frameworks are well-established and widely used tools for building serverless applications on AWS. It boasts many advantages, including ease of use, language agnosticism, and extensibility. The framework is actively maintained and supported by an active community.
Suggestions for use
Developers can use serverless frameworks to:
- Build serverless applications quickly and easily
- Manage infrastructure and code deployment in one step
- Automate processes for the scaling and security of serverless applications
- Develop and deploy applications in a variety of languages
conclusion
The serverless framework is a powerful and versatile tool that enables developers to build and deploy serverless applications on AWS. Its ease of use, scalability, and active community support make it a must-have tool for anyone using serverless technologies.
2. Vision Agent: Solve vision tasks with code generation
️仓库名称：landing-ai/vision-agent
Stars as of press time: 613 (New: 99 today)
Repository language: Python
仓库开源协议：Apache License 2.0
introduction
Vision Agent is a library that helps you generate code to solve vision tasks using the agent framework. It is designed to provide users with a second-level experience by describing the problem with text and generating code from the proxy framework to solve the task.
Project role
Vision Agent internally uses LLMs (such as OpenAI GPT-4), which solves vision tasks by understanding text prompts and converting them into code. It also uses both native and hosted tools such as object detectors and image segmentation algorithms to enhance its capabilities.
conclusion
Vision Agent is an innovative and promising library that simplifies the solution of vision tasks through the use of code generation. It has the potential to have a significant impact on a variety of industries, from computer vision to software development.
3. OpenMetadata
️仓库名称:open-metadata/OpenMetadata
Stars as of press time: 4547 (New: 19 today)
仓库语言: TypeScript
仓库开源协议：Apache License 2.0
introduction
OpenMetadata is a unified platform that enables discovery, observability, and governance through a central metadata repository, deep pedigree, and seamless team collaboration.
Project role
OpenMetadata consists of four main components:- Metadata schema: This is the core definition and vocabulary of metadata based on common abstractions and types. They also allow for custom extensions and property settings to suit different use cases and domains. - Metadata store: This is the central repository for storing and managing metadata graphs, connecting metadata generated by data assets, users, and tools in a unified way. - Metadata APIs: These are interfaces for generating and using metadata, and are built on top of metadata schemas. They enable seamless integration of user interfaces with tools, systems, and services and metadata storage. - Get Framework: This is an insertable framework for importing metadata from various sources and tools into a metadata store. It supports more than 75 connectors for data warehouses, databases, dashboard services, messaging services, pipeline services, and more.
conclusion
OpenMetadata is a powerful platform that helps you discover, understand, and manage your data assets. It's built by a passionate community and integrates with a wide range of tools and services through open metadata standards and APIs. If you're looking for a way to improve your data management, consider OpenMetadata.
4.PocketBase：一文搞定实时后端
仓库名称:pocketbase/pocketbase
Stars as of press time: 35289 (New: 65 today)
Warehouse Language: Go
仓库开源协议:MIT License
introduction
The repository hosts PocketBase, an open-source, high-performance backend for building web applications with real-time capabilities. PocketBase includes an embedded SQLite database, file management, user management, an administrative dashboard, and a RESTful API.
Project role
PocketBase is written in Go and leverages the SQLite database engine for data persistence. Its API provides CRUD operations, authentication, file management, and support for websockets for real-time updates. The management dashboard provides a user-friendly interface for managing data, user, and application settings.
Description of the warehouse
The repository provides the source code for PocketBase, including:
- 最小的独立示例 (examples/base)
- Go 框架/工具包集成 (main.go)
- API SDK Client for JavaScript and Dart
- Comprehensive Documentation & Examples (pocketbase.io/docs)
Suggestions for use
- Serves as a standalone backend for web applications
- As a Go framework for building custom business logic
- As the basis for real-time applications using websockets
conclusion
PocketBase is a versatile and powerful open-source backend that simplifies development and enhances application functionality. With its real-time features, user management, file management, and ease of use, PocketBase enables developers to build robust and scalable web applications.
5.Typebot.io: Open-source chatbot builder
⚛️仓库名称:baptisteArno/typebot.io
Stars as of press time: 5470 (New: 79 today)
仓库语言: TypeScript
Repository open source protocol: Other
introduction
Welcome to Typebot.io, a powerful self-hosted chatbot builder. This article will provide an overview of its features, technical explanations, use cases, and instructions for self-hosting and contributions.
Project role
Typebot has an intuitive chat builder that offers more than 34 building blocks, including text bubbles, input fields, logical branching, and integrations. It supports custom themes and embedding options, and offers in-depth analytics and export capabilities.
Description of the warehouse
Typebot is an open-source project hosted on GitHub. It is written in TypeScript and has received 79 stars.
Case
Typebot has been widely used to build a variety of chatbots, including customer support, lead generation, and lead nurturing.
Objective evaluation or analysis
Typebot has been praised for its user-friendliness, power, and customizability. It integrates well with a wide range of services and has an active community to support it.
Suggestions for use
Typebot is suitable for developers and businesses who want to easily create and deploy advanced chatbots. For users who wish to host their chatbot on their own server, a self-hosted option is available.
conclusion
Typebot.io is a full-featured and user-friendly chatbot builder that simplifies chatbot development with its intuitive builder, customization options, and integration features. Its open-source nature and self-hosted options make it ideal for businesses and organizations of all sizes.
6. Argilla: AI data collaboration platform
️仓库名称:I-clay/clay
Stars as of press time: 3310 (New: 14 today)
Repository language: Python
introduction
Argilla is a collaboration platform for AI engineers and domain experts that helps users achieve high-quality output, complete data ownership, and overall efficiency.
Project role
Argilla offers a range of features, including: Data Labeling and Annotation Semantic Search AI Feedback Recommendations RAG Integration in LLM Pipelines A/B testing of predictive task models
Description of the warehouse
This GitHub repository contains Argilla's source code, documentation, and samples.
Case
Argilla has been used in a variety of cases, including: Cleans up the UltraFeedback dataset to improve benchmarking and empirical performance of human judgment Improving OpenHermes models to improve model performance by filtering out 50% of the original dataset Red Cross streamlines the support process by triaging and redirecting refugee requests through Argilla
Objective evaluation or analysis
Argilla is a powerful collaboration platform that can improve the quality of AI output through improved data quality. It also provides complete control over data and models, streamlining workflows for AI projects.
Suggestions for use
You can use Armilla in the following ways: Install the Python package Deploy locally or on Hugging Face Hub Create a workspace and configure a dataset Add records and annotate them Train the model and predict the outcome
conclusion
Argilla is a full-featured AI data collaboration platform that improves the efficiency of AI projects by improving data and model quality, accelerating iterations, and ensuring ownership.
7.AiMonneyHunter:AI副业赚钱大集合
️仓库名称：bleedline/aimoneyhunter
Stars as of press time: 10040 (New: 493 today)
Warehouse Language: ****
introduction
The AiMonneyHunter project brings together various methods and techniques for using AI to make money on side hustles, aiming to help users explore the opportunities to make money in the AI era.
Project role
(There is no project introduction or technical analysis information in this repository)
Description of the warehouse
(This repository does not have a repository description)
Case
This repository contains a variety of AI side hustle cases, including:
- AI Script Videos to Make Money
- AI pictures to make money side hustle
- AI copywriting to make money side hustle
- AI audio to make money side hustle
- AI live streaming
Objective evaluation or analysis
The AiMonneyHunter project is a comprehensive resource that provides a wealth of information on using AI to make money on side hustles. It brings together various strategies and cases from the web, enabling users to learn about different money-making opportunities. However, the repository is still in its infancy and needs to be continuously updated and added with more content to maintain its relevance and value.
Suggestions for use
Suggestions for use:
- Browse through the different categories and explore various ways to make money with AI side hustles
- Read case studies for inspiration and practical tips
- Follow the project for updates and learn about new money-making strategies and tools
conclusion
AiMonneyHunter is a valuable resource that provides valuable information for those seeking to generate additional income with AI. As the warehouse continues to be updated and improved, it is expected to become a more comprehensive and useful guide in the field of AI side hustle earning.
8. Technical Interview Manual: Comprehensively prepare for technical interviews
️仓库名称：yangshun/tech-interview-handbook
Stars as of press time: 113281 (New today: 41)
仓库语言: TypeScript
仓库开源协议:MIT License
introduction
This guide is designed to provide free, curated technical interview preparation materials for busy software engineers, covering all aspects of technical interviews to help readers prepare effectively.
Description of the warehouse
The repository contains exam prep materials in a variety of formats, including articles, code examples, and question sets, to meet the needs of different learning styles.
Objective evaluation or analysis
The guide covers technical essentials such as algorithmic issues, resume writing and non-technical issues, and helps readers improve their interview performance in an all-round way.
Suggestions for use
It is recommended that readers choose the study materials that are suitable for them according to their personal situation, and keep practicing to continuously improve their interview skills.
conclusion
The Tech Interview Handbook is an invaluable resource for technical interview preparation, providing comprehensive guidance to help candidates land their dream tech position.
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