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Daily GitHub Project Recommendation: Public APIs - Your API Treasure Trove, Unlocking Endless Possibilities!

Still racking your brain searching for suitable free APIs? Today, I’m bringing you a GitHub gem – public-apis/public-apis. It’s not just a repository; it’s a meticulously maintained collection of free APIs by the global developer community, designed to help you easily find various service interfaces and accelerate your development process.

Project Highlights

With its astonishing scale and breadth, public-apis/public-apis has become an undisputed star in the developer community. Boasting over 368k stars and 38k forks, this project is undoubtedly the go-to place for finding free APIs.

  • Massive Resources, Everything You Need: From animal facts, anime data, financial market information to weather forecasts, geocoding services, and even machine learning models, this project covers almost every field you can imagine. Whether you want to add a random cat picture feature to your app or need real-time stock data, you’ll find inspiration and solutions here.
  • Community-Driven, Continuously Updated: This list is manually maintained and curated by community members like you and me, ensuring the quality and timeliness of its content. This means you’ll always find the latest and most reliable APIs without worrying about outdated data.
  • Boost Development Efficiency: Say goodbye to tedious API search processes! This project brings together various free APIs in one place, meticulously categorized, allowing you to quickly locate the features you need and dedicate more effort to developing core business logic.

Use Cases

This “API treasure trove” is suitable for various scenarios:

  • Rapid Prototyping: Quickly integrate features for your next hackathon project or MVP.
  • Learning and Exploration: Understand how different types of APIs work and how to integrate them into your own projects.
  • Enhance Existing Applications: Add novel, interesting, or practical functionalities to your website or mobile app.

How to Get Started / Links

Curious to explore? Simply visit the project’s GitHub page, where you can browse API lists under various categories through a clear directory index. Each API comes with a brief description and a link.

GitHub Repository Link: public-apis/public-apis

Call to Action

Don’t hesitate! Click the link now and explore this vast world of free APIs. If you discover new, high-quality APIs, you’re also welcome to contribute to the community and make this treasure trove even richer. Share it with your developer friends and unlock endless possibilities together!

Daily GitHub Project Recommendation: Anthropic Official Release, Interactive Tutorial to Master Prompt Engineering!

In the era of AI, how to communicate effectively with Large Language Models (LLMs) to make them understand and precisely execute our instructions has become a core skill. Today, we’re featuring a treasure trove project created by the renowned AI company Anthropic – anthropics/prompt-eng-interactive-tutorial. With over 20k stars and 2k forks, this tutorial has quickly become a star resource in the field of Prompt Engineering due to its exceptional quality and immense practicality!

Project Highlights: Your Practical Guide to Prompt Engineering

This interactive tutorial aims to provide you with a comprehensive, step-by-step learning path for Prompt Engineering, specifically tailored for Anthropic’s Claude model, though its core principles are equally applicable to other major LLMs.

  • Official Authority, Systematic Instruction: Developed firsthand by the Anthropic team, ensuring the content’s professionalism and foresight. The tutorial starts with the basic structure of a prompt and gradually delves into advanced techniques, covering the entire process from “what it is” to “how to do it.”
  • Interactive Learning Experience: The tutorial is presented in Jupyter Notebook format, with each lesson featuring an “Example Playground” area where you can modify prompts in real-time, observe Claude’s response changes, and deepen your understanding through hands-on practice. Additionally, detailed answer keys are provided for easy verification and learning.
  • Comprehensive Coverage, Addressing Pain Points: The tutorial is rigorously structured, divided into nine chapters across beginner, intermediate, and advanced levels. It covers basics like “clear instructions” and “assigning roles,” progresses to “separating data from instructions,” “chain of thought (Precognition),” “avoiding hallucinations,” and even “building complex industrial-grade prompts” (e.g., for chatbots, legal, finance, programming), helping you solve common problems and challenges when interacting with LLMs.
  • Wide Applications, Enhanced Efficiency: Through learning, you will better understand the strengths and limitations of LLMs, master the 80/20 rule for optimizing prompts, and build efficient, precise prompts from scratch, thereby significantly boosting your collaboration efficiency with AI.

Technical Details and Use Cases

This project primarily uses Jupyter Notebooks as its medium, combining code and text to provide an immersive learning experience. Although the tutorial focuses on the Claude model, the Prompt Engineering principles it explains, such as structured instructions, context management, and guiding thought processes, are universal rules for interacting with all Large Language Models. Therefore, whether you are an AI developer, data scientist, product manager, or anyone looking to improve their communication skills with LLMs, this tutorial will be an invaluable learning resource. If you prefer a more user-friendly experience, the project also thoughtfully provides a Google Sheets-based version.

How to Get Started / Links

Ready to embark on the path to mastering Prompt Engineering? You can find the complete tutorial content in the GitHub repository. We recommend starting with the 01_Basic Prompt Structure chapter and following the course’s chapter order to maximize your learning effectiveness.

Call to Action

Prompt Engineering is an indispensable skill in the future AI world. Don’t miss this high-quality, interactive learning opportunity provided by the official team! If you find this project helpful, please give it a Star and share it with more friends who need to improve their AI interaction skills!

Daily GitHub Project Recommendation: Daytona - Unleash AI Code Potential, Security and Elasticity in Parallel!

Today, we focus on a project that is becoming increasingly important in the context of the AI era – Daytona. If you’re building AI applications and need to run AI-generated code securely and efficiently, then daytonaio/daytona is definitely a choice you shouldn’t miss. With its outstanding performance and security, this project is rapidly becoming a new favorite in the developer community, having already accumulated over 23,000 stars!

Daytona provides a secure and elastic infrastructure specifically designed for running AI-generated code. In today’s pervasive AI models, ensuring that executing AI-generated code doesn’t pose risks to the system while maintaining high efficiency and scalability is a challenge for many developers. Daytona was created precisely to address this pain point.

Project Highlights

  • Ultimate Secure Isolation: Daytona’s core strength lies in its “separated and isolated runtime” environment. It allows you to execute AI-generated code in a completely isolated sandbox, ensuring zero risk to your infrastructure even if the AI code behaves anomalously. This is crucial for handling potentially untrusted, dynamically generated code.
  • Lightning-Fast Speed: In terms of performance, Daytona excels, promising sandbox creation speeds of under 90 milliseconds, from code to execution in one swift motion. This means your AI workflows can run with astounding efficiency, without lengthy waits for environment initialization.
  • Powerful Programmability: Through files, Git, LSP (Language Server Protocol), and execution APIs, Daytona offers comprehensive programmatic control capabilities. Whether managing files within the sandbox, performing code edits, or directly executing code, it provides extremely high flexibility.
  • Infinite Persistence and Compatibility: Your sandboxes can maintain their state indefinitely, solving the pain point of ephemeral environments. Concurrently, it supports OCI/Docker compatibility, meaning you can use any OCI/Docker image to create sandboxes, significantly reducing integration costs.

Technical Details and Use Cases

Daytona is primarily developed in TypeScript and provides SDKs for both Python and TypeScript, making it convenient for developers with different technology stacks. It is particularly well-suited for the following scenarios:

  • AI Agent Development: Securely execute code or instructions generated by AI models to achieve automated tasks.
  • Code Sandbox Services: Provide online programming environments or code execution services for users, ensuring security.
  • Large Language Model (LLM) Applications: When LLMs generate executable code, Daytona can provide a secure execution and verification environment.

How to Get Started

Want to experience Daytona’s powerful features? It’s very simple:

  1. Visit https://app.daytona.io to create an account.
  2. Generate your API key.
  3. Easily create your first secure sandbox using the Python or TypeScript SDK, following the documentation’s guidance!

Quick Start Link: https://www.daytona.io/docs

Call to Action

Daytona, as an open-source project, is rapidly evolving. If you’re interested in secure code execution, AI infrastructure, or distributed systems, feel free to explore its code and contribute your insights. Whether submitting bug reports, suggesting new features, or directly participating in code development, your contributions will help Daytona become even better!

GitHub Repository Link: https://github.com/daytonaio/daytona

Don’t hesitate any longer, head over to Daytona’s GitHub page now and give this project with unlimited potential your Star!