Learn and create, pioneering the AI era.
The article outlines three practical approaches to get the most out of DeepSeek—using it as a conversational assistant, integrating its API to power AI tools such as the Chrome immersive‑translation plugin, and leveraging it for AI‑assisted programming—while comparing the V3 and R1 models and offering concrete configuration steps.
This guide shows how to obtain free DeepSeek API access through GitHub Models and SiliconFlow, detailing the required API base URL, key, and model name, how to register, create keys, verify usage with a web chat tool, and compare model choices and platform limits.
The article conducts a practical, step‑by‑step evaluation of Cursor, Windsurf, and GitHub Copilot’s multi‑file editing capabilities using a simple web‑chat bot, revealing that Cursor completes all required UI, storage, and application changes in a single interaction, while the others need two rounds, with Copilot showing notable improvement on a retest.
This article walks through a step‑by‑step demonstration of how a Python beginner can use GitHub Copilot to build a command‑line tool that renders QR codes as text, illustrating interface familiarization, handling errors, iterative prompting, and final code refinement.
This article surveys the leading AI‑powered code editors—including GitHub Copilot, Cursor, CodeGeeX and others—detailing their pricing, core features such as code completion, inline and sidebar chat, project‑wide editing, and step‑by‑step setup instructions for developers of any skill level.
This article demonstrates how browser‑based AI web‑creation platforms like Bolt and v0 can generate complete front‑end code from natural‑language prompts or design images, optimize prompts, preview results, and publish a site with a single click, while also showing how to download the code for further development.
The article surveys the surge of AI programming tools in 2024, illustrating how even non‑programmers can build full applications with AI assistants, compares ChatGPT’s code‑generation workflow with its Code Interpreter feature, and outlines each approach’s strengths and limitations.
This article explains how to configure key OpenAI chat completion parameters—such as temperature, top_p, streaming, response format, and tool selection—and walks through the structure of the API's JSON response, highlighting fields like id, model, choices, finish_reason, and usage for better control and cost estimation.
This article explains how to automate batch document processing with LLM APIs by mastering the messages parameter, defining system, user, and assistant roles, and iteratively polishing system prompts through scripts or OpenAI's GPTs editor and Playground interfaces.
With a growing array of overseas and domestic LLM APIs in 2024, this guide explains how to pick the right model—starting with a top‑tier option like GPT‑4o for feasibility testing, then moving to cost‑effective or Chinese alternatives, while weighing price, inference speed, context window, API compatibility, and rate limits.
