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Local Whisper

作者 ImpKind · GitHub ↗ · v1.5.0
cross-platform ✓ 安全检测通过
3019
总下载
9
收藏
1
当前安装
5
版本数
在 OpenClaw 中安装
/install whisper-mlx-local
功能描述
Free local speech-to-text for Telegram and WhatsApp using MLX Whisper on Apple Silicon. Private, no API costs.
安全使用建议
This skill appears to be what it claims: a local, Apple Silicon-optimized Whisper daemon and CLI. Before installing, consider the following: (1) The package will run a local HTTP daemon on 127.0.0.1:8787 — only allow trusted local callers (OpenClaw is intended), and be cautious about other local apps talking to that port. (2) The daemon accepts a JSON field containing a filesystem path and will open that path for transcription; ensure only trusted processes can instruct the daemon to avoid accidental processing of unintended files. (3) requirements.txt includes OpenAI and Groq client libraries; if you have OPENAI_API_KEY or GROQ_API_KEY set in your environment (or in a loaded .env), the code can use cloud backends — remove those env vars or avoid installing those packages if you require strict local-only operation. (4) Install via pip installs third-party packages from PyPI — review requirements.txt and consider using a virtualenv or isolated account. (5) If you want automatic startup, inspect the LaunchAgent plist before copying it into ~/Library/LaunchAgents. Overall this skill is coherent with its stated purpose, but take the above precautions if your threat model requires strict local-only privacy.
功能分析
Type: OpenClaw Skill Name: whisper-mlx-local Version: 1.5.0 The skill provides local speech-to-text transcription using MLX Whisper, with optional cloud API fallbacks. All observed behaviors, including the use of `launchctl` for daemon persistence (documented in SKILL.md and README.md), local network communication via `curl` to `localhost:8787` (scripts/transcribe.sh), and optional external API calls to OpenAI/Groq (scripts/transcriber.py) for transcription, are clearly aligned with its stated purpose. There is no evidence of data exfiltration to unauthorized endpoints, malicious execution, obfuscation, or prompt injection attempts against the agent.
能力评估
Purpose & Capability
The name/description (local Whisper on Apple Silicon) match the code: the project provides an MLX-backed daemon and CLI to transcribe audio locally. However, requirements.txt and transcriber.py also include optional cloud backends (OpenAI, Groq) and their client libraries; those are optional (used only if the packages are installed and API keys are present) but are not declared in SKILL.md as optional cloud-capable behavior. This is plausible design (local-first with optional fallbacks) but worth noting because the README emphasizes 'private, no API costs'.
Instruction Scope
SKILL.md's runtime instructions are focused on installing deps, running a local daemon, and wiring OpenClaw to call the provided CLI. The daemon accepts either raw audio uploads or JSON containing a local file path and will read that path off disk and transcribe it. Accepting file-system paths is required for the intended integration, but it also means the daemon can be directed (by local callers) to open arbitrary files on disk — a potential surprise if untrusted local processes can talk to the daemon. The daemon binds to 127.0.0.1, reducing remote exposure.
Install Mechanism
Install is manual via 'pip3 install -r requirements.txt' (PyPI). No downloads from untrusted URLs or archives. requirements.txt contains platform-conditional MLX package and optional cloud client libraries; pip installation will pull those packages from PyPI.
Credentials
The skill declares no required environment variables, which is accurate for basic local operation. The code uses dotenv and will consume environment variables if present (e.g., OPENAI_API_KEY, GROQ_API_KEY, CLAWD_WHISPER_* for port/backend/model, CLAWD_WHISPER_URL in the CLI). If API keys are present in the environment, the transcriber may use cloud backends, which conflicts with the 'private, no API costs' messaging unless you ensure no cloud keys are set. This is optional behavior but should be explicitly considered by users who expect strict local-only operation.
Persistence & Privilege
The skill is not always-enabled and does not autonomously modify other skills. It provides optional instructions to install a LaunchAgent plist for auto-start, which is normal for a user-installed local daemon. The daemon runs as a user process bound to 127.0.0.1; it does not request elevated privileges or modify other skill configurations automatically.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install whisper-mlx-local
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /whisper-mlx-local 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.5.0
Added OpenClaw configuration instructions
v1.2.0
Clearer messaging: free voice message transcription
v1.1.0
Rebrand: Clear positioning as free OpenAI Whisper replacement
v1.0.1
Clean release: removed attribution references
v1.0.0
Initial release: Free local speech-to-text for Apple Silicon
元数据
Slug whisper-mlx-local
版本 1.5.0
许可证
累计安装 2
当前安装数 1
历史版本数 5
常见问题

Local Whisper 是什么?

Free local speech-to-text for Telegram and WhatsApp using MLX Whisper on Apple Silicon. Private, no API costs. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 3019 次。

如何安装 Local Whisper?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install whisper-mlx-local」即可一键安装,无需额外配置。

Local Whisper 是免费的吗?

是的,Local Whisper 完全免费(开源免费),可自由下载、安装和使用。

Local Whisper 支持哪些平台?

Local Whisper 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Local Whisper?

由 ImpKind(@impkind)开发并维护,当前版本 v1.5.0。

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