Packages
A keyboard-driven, vim-like web browser built on Python and Qt that prioritizes keyboard navigation over mouse interaction.
QuTiP simulates the dynamics of closed and open quantum systems using numerical backends (NumPy, SciPy) and supports Hamiltonians and collapse operators with arbitrary time-dependence.
Decodes and disassembles WebAssembly binary modules into readable instruction format according to the MVP specification, with a command-line tool for inspecting module structure.
However, do not rely on it for production systems requiring ongoing maintenance or support for newer WASM specifications—test thoroughly against your target WASM…
Qwen-Agent is a framework for building LLM applications with tool usage, planning, memory, and instruction-following capabilities, including pre-built assistants for browsing, code execution, and custom workflows.
However, verify the actual license terms (metadata shows unclear treatment despite Apache 2.0 headers), confirm Python version support for your environment, and…
Qwen3-ASR provides speech recognition and language identification for 52 languages and dialects, plus forced-alignment for timestamping speech in 11 languages, with both streaming and offline inference modes.
Provides helper functions to preprocess and integrate images, videos, and audio with Qwen multimodal language models for use in transformers pipelines.
Qwen-TTS generates speech from text using Qwen3-TTS models, supporting voice cloning, voice design, and instruction-based voice control across 10 languages with streaming and non-streaming output.
However, the package is very recent (first release 2026-01-22) with aging maintenance status, so expect potential API changes and monitor for updates.
Provides helper functions to process images and videos for use with Qwen-VL vision-language models, handling multiple input formats including local files, URLs, base64-encoded data, and PIL images.
Qwix is a JAX quantization library that applies Quantization-Aware Training (QAT) and Post-Training Quantization (PTQ) to neural network models, supporting deployment on XLA devices (CPU/GPU/TPU) and LiteRT targets.