「legacy」の検索結果

Databricks Model Serving endpoint lifecycle and ops. Use when asked to: CRUD serving endpoints (CLI or MLflow Deployments client); configure traffic routing for A/B / canary deploys and zero-downtime version swaps; retrieve OpenAPI schemas; inspect logs, metrics, or permissions; manage legacy AI Gateway rate limits (not Unity Gateway); discover Foundation Model API endpoints at runtime; integrate endpoints into Databricks Apps; or stream from off-platform clients (Vercel AI SDK v6, standalone Node.js). NOT for: Unity Gateway CRUD and management (databricks-unity-gateway), training, MLflow autologging, UC registration, custom PyFunc/ResponsesAgent authoring (databricks-ml-training); Knowledge Assistants/Supervisor Agents (databricks-agent-bricks); MLflow evaluation (databricks-mlflow-evaluation).

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。

Routes FCOS object-detection repo tasks for inference demos, config/data setup, training/evaluation, ONNX export, and legacy PyTorch internals.

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。

Operate the legacy Frustum PointNets code release for KITTI or SUN RGB-D data preparation, TensorFlow runtime setup, training, inference, and 3D detection evaluation.

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。

Route DLTK 0.2.1 medical-imaging workflows across legacy TensorFlow 1.x data, models, Estimators, and deployment utilities.

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。

Use deepjazz for legacy MIDI jazz generation with music21 preprocessing, abstract grammar tokens, Keras/Theano LSTM training, safe diagnostics, and modernization guidance.

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。

Use this DeepCTR repo skill for CTR/recommender feature columns, Keras models, sequence/session models, multitask models, and legacy TensorFlow Estimator workflows.

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。

Routes Darkflow object-detection, training, and export workflows for the legacy YOLO package.

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。

Route AutoGPT Platform self-hosting, backend, frontend, and legacy Classic agent work to focused operating guidance.

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。

Routes AdelaiDet users through legacy-compatible setup, model config selection, training/evaluation, demos, text spotting, dataset preparation, and export/conversion workflows.

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。

Use the ALAE repository for Adversarial Latent Autoencoder data preparation, CUDA training, checkpoint-backed generation, latent editing, and legacy metrics.

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。

Use Argilla 2.x for human-feedback dataset annotation, Python SDK dataset workflows, server deployment/operations, webhooks, and legacy v1/Rubrix migration.

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。

Auth bypass and ATO hunting - legacy protocol matrix (XMLRPC, SharePoint /_vti_bin/, EWS, Citrix, etc.), JWT manipulation, password reset poisoning, SAML auth bypass, session fixation. Wiki-first, FIND schema output.

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。

Main app Jetpack Compose UI patterns (WooTheme, Fragment hosting, composeView/legacyComposeView helpers, preview annotations, WC components). Use when writing, editing, exploring, debugging, or reviewing Compose UI in the store management app. NOT for POS (WooPos*) code — use the `pos` skill instead.

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。

Master modern Angular state management with Signals, NgRx, and RxJS. Use when setting up global state, managing component stores, choosing between state solutions, or migrating from legacy patterns.

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。

Use when generating REST controllers, DTOs, success response contracts, pagination, HTTP status mapping, or API versioning. For RFC 9457 exception and error response formatting, use problem-details-rfc9457 unless the project explicitly requires a legacy error envelope.

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。

Use when implementing exception mapping or RFC 9457 error responses in Spring Boot 4. Preserve an existing legacy error contract unless migration is requested.

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。

Use when implementing exception mapping or RFC 9457 error responses in Spring Boot 3. Preserve an existing legacy error contract unless migration is requested.

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。

Governs employee health data processing for fitness-for-work assessments, occupational health surveillance, COVID testing legacy programmes, and absence management. Applies Art. 9(2)(b) employment obligations and Art. 9(2)(h) health professional exceptions. Covers data minimisation, occupational health provider relationships, and return-to-work procedures. Keywords: health data, Art. 9, occupational health, fitness-for-work, special category, employment, sickness absence.

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。

Create, maintain, or migrate functional skills; supports creating from a requirement brief and migrating an existing legacy skill directory into a functional skill structure.

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。

Migrate lane for fskill-creator; analyzes a legacy skill directory into behavior map, function split proposal, and source evidence.

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。

Generates automated test oracles to verify correct software behavior. Creates assertion-based oracles (expected values), property-based oracles (invariants), differential oracles (comparing implementations), and metamorphic oracles (input transformations). Use when you need to generate assertions for test cases, identify invariants that should always hold, compare new vs legacy implementations, create metamorphic test relationships, validate function correctness, or improve test coverage with better verification strategies. Supports Python (pytest, unittest, hypothesis) and Java (JUnit, property testing).

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。

Identify and replace deprecated API usage in source code with modern alternatives. Use when: (1) Modernizing legacy codebases, (2) Upgrading framework versions (React, Django, Spring, etc.), (3) Fixing deprecation warnings in build output, (4) Preparing for major version upgrades, (5) Ensuring code uses current best practices. Supports Python, JavaScript/TypeScript, Java, and other major languages with both AST-based detection and pattern matching for accurate identification and automated replacement with validation.

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。

Convert code between programming languages while preserving functionality and semantics. Use when: (1) Translating functions, classes, or modules between languages (Python, JavaScript/TypeScript, Java, Go, Rust, C/C++), (2) Migrating entire projects to a different language, (3) Need idiomatic translation that follows target language conventions, (4) Converting between different paradigms (OOP to functional, etc.), (5) Porting legacy code to modern languages. Provides language-specific patterns, idiomatic translation guides, and project migration strategies.

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。

Create, inspect, convert, apply, replace, verify, troubleshoot, update, publish, or restore reversible CodeDrobe themes for supported Chromium/Electron AI desktop apps, including OpenAI Codex, Tencent WorkBuddy, QoderWork (CN/global), and TRAE SOLO (global/CN). Use when a user asks to turn an attached or local reference image into a Codex, WorkBuddy, QoderWork, or TRAE SOLO skin, reproduce a visual style with native UI, build a multi-app theme, work with .codedrobe-theme packages or theme images, analyze a live CDP DOM snapshot, repair DOM compatibility failures, use a custom port or installation path, capture verification screenshots, search the CodeDrobe store or install a store theme by name, publish or submit a theme to the CodeDrobe store, or migrate a legacy .codex-theme file.

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。