标签：#Python

GitHub热门项目 | MOSS‑TTS Family is an open‑source speech and sound generation model family from MOSI.AI and the OpenMOSS team. It is designed for high‑fidelity, high‑expressiveness, and complex real‑world scenarios, covering stable long‑form speech, multi‑speaker dialogue, voice/character design, environmental sound effects, and real‑time streaming TTS. | Stars: 2,051 | 53 stars today | 语言: Python

GitHub热门项目 | 🚀🤖 Crawl4AI: Open-source LLM Friendly Web Crawler & Scraper. Don't be shy, join here: https://discord.gg/jP8KfhDhyN | Stars: 66,704 | 210 stars today | 语言: Python

GitHub热门项目 | Python tool for converting files and office documents to Markdown. | Stars: 126,876 | 1,263 stars today | 语言: Python

A while ago I tried to build a local coding assistant. I downloaded Qwen3, fired it up on my MacBook with 16GB of RAM, and within a day realized the output quality was nowhere close to Claude or GPT-5. The model could fit . It just couldn't compete . So I changed the question. If I can't make the model smarter on my hardware, can I make what I feed it smarter? Where the tokens actually go I started watching where my Claude / Cursor / Copilot sessions actually spent their tokens. The surprise: most of it wasn't reasoning. It was lookup . Every fresh chat about my company's database re-discovered the same things: What does status = 3 mean? (cancelled) How does orders join to users ? ( orders.user_id → users.id ) What's that cryptic JobStatus enum? (a dozen integer codes nobody remembers) The model figured it out, the session ended, and tomorrow it figured it out again . Same tokens, same latency, every single time. The expensive part of working with an AI wasn't the thinking — it was re-teaching it things it had already learned yesterday. There's a lot of attention right now on trimming AI output tokens (talk like a caveman, strip the pleasantries, etc.). But in my workflow the bigger leak was on the input side: paying full token cost every session to re-establish context that never changed. "Memory" isn't a feature, it's an architecture question AI clients are starting to bolt on "memory" features. But they're proprietary, opaque, and locked to one tool. Claude's memory doesn't help Cursor. Cursor's doesn't help Copilot. You can't inspect it, you can't share it with a teammate, and you can't diff it. What I actually wanted was an explicit, inspectable, shareable context layer that any AI client could read deterministically — same answer every time, same file my team could hand off. I picked the highest re-learn cost in my world to start with: SQL databases. Enter amnesic amnesic is an open-source MCP server that gives any AI client persistent semantic memory of your

GitHub热门项目 | "CLI-Anything: Making ALL Software Agent-Native" -- CLI-Hub: https://clianything.cc/ | Stars: 40,887 | 2,602 stars this week | 语言: Python

GitHub热门项目 | SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformer | Stars: 7,767 | 629 stars this week | 语言: Python

GitHub热门项目 | Fully autonomous & self-evolving research from idea to paper. Chat an Idea. Get a Paper. 🦞 | Stars: 12,859 | 451 stars this week | 语言: Python

GitHub热门项目 | "ViMax: Agentic Video Generation (Director, Screenwriter, Producer, and Video Generator All-in-One)" | Stars: 7,822 | 1,940 stars this week | 语言: Python

GitHub热门项目 | Academic Research Skills for Claude Code: research → write → review → revise → finalize | Stars: 22,783 | 7,385 stars this week | 语言: Python

GitHub热门项目 | Learn it. Build it. Ship it for others. | Stars: 22,616 | 12,787 stars this week | 语言: Python

GitHub热门项目 | Training library for Megatron-based models with bidirectional Hugging Face conversion capability | Stars: 670 | 7 stars today | 语言: Python

GitHub热门项目 | Build and run agents you can see, understand and trust. | Stars: 25,763 | 86 stars today | 语言: Python

GitHub热门项目 | A high-throughput and memory-efficient inference and serving engine for LLMs | Stars: 81,187 | 121 stars today | 语言: Python

GitHub热门项目 | Open source voice AI platform. Self-hosted alternative to Vapi and Retell. On Prem, BYOK across Speech to Speech or LLM/STT/TTS, with a visual workflow builder, MCP native and telephony support. | Stars: 3,426 | 197 stars today | 语言: Python

GitHub热门项目 | Machine Learning Systems | Stars: 24,459 | 141 stars today | 语言: Python

GitHub热门项目 | 754 structured cybersecurity skills for AI agents · Mapped to 5 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND & NIST AI RMF · agentskills.io standard · Works with Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI & 20+ platforms · 26 security domains · Apache 2.0 | Stars: 10,997 | 886 stars today | 语言: Python

GitHub热门项目 | Kronos: A Foundation Model for the Language of Financial Markets | Stars: 26,898 | 401 stars today | 语言: Python

GitHub热门项目 | Fully automatic censorship removal for language models | Stars: 22,036 | 211 stars today | 语言: Python

GitHub热门项目 | Open source repository of plugins primarily intended for knowledge workers to use in Claude Cowork | Stars: 17,306 | 695 stars today | 语言: Python

GitHub热门项目 | 利用AI大模型，一键生成高清短视频 Generate short videos with one click using AI LLM. | Stars: 62,262 | 1,742 stars today | 语言: Python