「on-device」の検索結果

Semantic + keyword search and connection-discovery across the user's own Apple Notes via the apple-notes MCP server. Use when the user wants to find, recall, or synthesize something from their notes, or surface non-obvious bridges/related notes. macOS, on-device.

日本語の概要は準備中です。原文の説明を表示しています。

Local and self-hosted text-to-speech with Kokoro, the ~82M-parameter open-weight (Apache 2.0) model by hexgrad. Use when synthesizing speech offline, on-device, in the browser, or on your own server without per-character API cost — for high-volume narration, audiobooks, privacy-constrained pipelines, and prototyping. Covers running Kokoro via the Python `kokoro` package, ONNX / kokoro-js in the browser, and the OpenAI-compatible Kokoro-FastAPI wrapper; picking voices and language codes; blending voices; chunking long text; controlling pronunciation via misaki/espeak-ng; and judging when Kokoro is the right tool versus when its lack of voice cloning, narrow emotional range, and weaker non-English quality mean you should reach for a hosted or larger model instead. Not for voice cloning, expressive/emotional character performance, or high-fidelity multilingual work — say so and route elsewhere.

日本語の概要は準備中です。原文の説明を表示しています。

Playbook for capturing SOCKS5/VPN-tunnel traffic on Android devices and emulators with mitmproxy, tcpdump, or PCAPdroid. Use when debugging on-device network traffic or correlating Kotlin/Rust logs.

日本語の概要は準備中です。原文の説明を表示しています。

Analyzes Android apps to identify key user workflows for AppFunctions such as creating a note, playing media, or sending an automated or AI agent triggered message, voice commands, or system shortcuts, without needing to open the app UI. Generates Kotlin code to expose these workflows to the Android system, allowing agents to discover and execute them on-device. Also refines KDoc documentation to ensure AI agents correctly understand and use the provided functionality.

日本語の概要は準備中です。原文の説明を表示しています。

Semantic + keyword search and connection-discovery across the user's own Apple Notes via the apple-notes MCP server. Use when the user wants to find, recall, or synthesize something from their notes, or surface non-obvious bridges/related notes. macOS, on-device.

日本語の概要は準備中です。原文の説明を表示しています。

Transcribe speech to text using the Speech framework. Use when implementing live microphone transcription with AVAudioEngine, recognizing pre-recorded audio files, configuring on-device vs server-based recognition, handling authorization flows, or adopting the new SpeechAnalyzer API (iOS 26+) for modern async/await speech-to-text.

日本語の概要は準備中です。原文の説明を表示しています。

Collect and analyze on-device performance metrics and crash diagnostics using MetricKit. Use when setting up MXMetricManager, handling MXMetricPayload or MXDiagnosticPayload, processing crash/hang/disk-write diagnostics via MXCallStackTree, adding custom signpost metrics, or uploading telemetry to an analytics backend.

日本語の概要は準備中です。原文の説明を表示しています。

Integrate and optimize Core ML models in iOS apps for on-device machine learning inference. Covers model loading (.mlmodelc, .mlpackage), predictions with auto-generated classes and MLFeatureProvider, compute unit configuration (CPU, GPU, Neural Engine), MLTensor, VNCoreMLRequest, MLComputePlan, multi-model pipelines, and deployment strategies. Use when loading Core ML models, making predictions, configuring compute units, or profiling model performance.

日本語の概要は準備中です。原文の説明を表示しています。

Semantic + keyword search and connection-discovery across the user's own Apple Notes via the apple-notes MCP server. Use when the user wants to find, recall, or synthesize something from their notes, or surface non-obvious bridges/related notes. macOS, on-device.

日本語の概要は準備中です。原文の説明を表示しています。

Apple FoundationModelsフレームワークによるオンデバイスLLM — テキスト生成、@Generableによるガイド生成、ツール呼び出し、iOS 26+でのスナップショットストリーミング。