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🔥 JiyaBatra / CODEVIBE- - CodeVibe is an interactive learning platform designed to hel

GitHub热门项目 | CodeVibe is an interactive learning platform designed to help beginners understand programming through simple lessons and hands-on practice. It includes structured course sections, coding examples, and a built-in HTML compiler that lets users write and test code directly in the browser, making learning web development practical, engaging. | Stars: 28 | 2 stars today | 语言: JavaScript

2026-05-31 原文 →
AI 资讯

Run Aider on Ollama, Bedrock, or Any LLM Provider — One Gateway, Every Model

Aider is the best terminal AI coding tool I've used. But by default it sends every diff through your OpenAI or Anthropic key, which gets expensive fast on real refactors — a single 100-file repo map can torch a few dollars before Aider even reads your prompt. This post shows how to run Aider against any LLM provider — Ollama for free local runs, OpenRouter for mixed-provider routing, AWS Bedrock for the enterprise plate — through a single OpenAI-compatible endpoint. I'll use Lynkr , the self-hosted gateway I maintain, but the pattern works with any OpenAI-compatible proxy. Full disclosure: I build Lynkr. I'll point out where it loses to LiteLLM and OpenRouter further down so you can make an honest call. The setup in three commands # 1. Start the gateway npx lynkr@latest # 2. Point Aider at it export OPENAI_API_BASE = http://localhost:8081/v1 export OPENAI_API_KEY = any-value # 3. Run Aider with any model name Lynkr knows about aider --model openai/gpt-4o That's it. Aider speaks the OpenAI Chat Completions protocol; Lynkr speaks it back and quietly translates the call to whichever upstream provider you've configured (Ollama, Bedrock, Anthropic, Azure, OpenRouter, Databricks, llama.cpp, LM Studio, ...). Aider has no idea it's talking to a router. Why bother? The cost math Aider's own leaderboard shows GPT-4o and Claude 3.5 Sonnet at the top — but you don't need a $3-per-million-tokens model to rename a variable. You need it for the architecture decisions. Lynkr's tier routing splits the work: Aider call type Routes to Cost Repo map summarization qwen2.5-coder:7b (Ollama, local) $0 File edits, single-function diffs gemini-flash-1.5 (OpenRouter) ~$0.075/M Architecture / multi-file refactors claude-3.5-sonnet (Anthropic) $3/M On a typical 4-hour Aider session, 80–90% of the calls are repo-map and small-diff calls. Routing those to local + cheap models while keeping Claude Sonnet for the hard reasoning has cut my own Aider spend by roughly 70%. Your mileage will vary base

2026-05-30 原文 →
AI 资讯

BAIXAR VÍDEO DO YOUTUBE

Criei um gerenciador de downloads desktop em Python e quero feedback da comunidade! O PyFlowDownloader é um app desktop feito com Python + PySide6 que usa yt-dlp para baixar vídeos e áudios de forma assíncrona do youtube. Algumas coisas que ele já faz: Fila de downloads com progresso em tempo real Cancelamento de downloads ativos ou pendentes Suporte a MP4 e MP3, de 144p até 1080p Histórico com exportação para CSV Interface desktop com tema visual via QSS Build para Windows via PyInstaller + pipeline de release no GitHub Actions Está na versão v0.3.0 e ainda tem muito espaço pra crescer. Repositório: https://github.com/Vinny00101/PyFlowDownloader Se você puder **testar e deixar sua opinião nos comentários, ficaria muito grato! Quer saber: O que achou da experiência de uso? Algum bug que encontrou? O que você adicionaria ou melhoraria no projeto? Todo feedback é bem-vindo!

2026-05-30 原文 →