Results for “lightning-platform”

Build accessible modal dialogs in LWC using the LightningModal base class, covering open(), close(), sizes, and accessibility.

Builds a custom LWC lookup component with typeahead search via Apex SOSL/SOQL, debounce, keyboard navigation, and pill UI for cases where standard pickers fall short.

Implements sibling communication between Lightning Web Components using Lightning Message Service (LMS) or the legacy pubsub utility, covering message channel definition, publish/subscribe patterns, and scope selection.

Guides using the lightning-record-picker base component for single-record selection in LWC, covering display-info, matching-info, graph-QL filters, and accessibility.

Guides secure design and review of Lightning Web Components, covering DOM safety, Apex data exposure, and Lightning Web Security.

Enforce quality, security, and accessibility standards for Salesforce Lightning Web Components, Aura components, and Visualforce pages.

Guides Lightning Web Component developers in setting up lightning-datatable with stable row identity, typed columns, row actions, inline edit, and bounded infinite loading.

High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use when you want clean training loops with built-in best practices.

Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard, MLflow), and distributed training (DDP, FSDP, DeepSpeed) for scalable neural network training.

Optimizes Lightning Web Components for slow initial load, heavy rerenders, large-list rendering, payload reduction, and lazy instantiation choices such as lwc:if, tabs, or dynamic components.

Comprehensive Cloudflare platform skill covering Workers, Pages, storage (KV, D1, R2), AI (Workers AI, Vectorize, Agents SDK), networking (Tunnel, Spectrum), security (WAF, DDoS), and infrastructure-as-code (Terraform, Pulumi). Use for any Cloudflare development task.

Builds memory-safe, performant Lightning Web Components with correct lifecycle hook usage, covering build, review, and troubleshooting workflows.

Trace, evaluate, and monitor LLM applications with an open-source observability platform.

Open-source AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, or monitoring production AI systems with real-time insights.

4-stage funnel that screens all 500+ Hyperliquid perps down to the top trading opportunities. Scores setups 0-400 across smart money, market structure, technicals, and funding. BTC macro filter, hourly trend gate (counter-trend = hard skip), cross-scan momentum tracking. Near-zero LLM tokens — all computation in Python. Use when scanning for new trading opportunities on Hyperliquid, evaluating setups, or checking market conditions.

Organizes PyTorch code with a Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks, and minimal boilerplate. Scales from laptop to supercomputer with the same code.

Routes to 82 Lightning Web Components skill packages covering reactivity, wire adapters, component communication, accessibility, performance, security, and Jest testing. Finds and opens the exact skill package for LWC-related requests.

High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use when you want clean training loops with built-in best practices.

Deploy applications and infrastructure to Cloudflare using Workers, Pages, and related platform services.

Creates a new Jetson target-platform profile YAML by selecting a reference devkit and optional custom carrier, then updates the active target pointer.

Switch the active Jetson target-platform pointer to an existing profile YAML. Use before customize/build/flash to change target; not for authoring profiles — use jetson-init-target instead.

Transforms business requirements, use case descriptions, or meeting transcripts into a technical Power Platform solution architecture, including component selection and Mermaid.js diagrams.

Fine-tune open models or Gemini models using Agent Platform infrastructure, from environment setup through data preparation, job configuration, monitoring, and deployment.

Open-source AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, or monitoring production AI systems with real-time insights.

Spark by Lightspark: statechain-derived L2 with FROST threshold signatures, leaf architecture, Lightning compatibility. Beta launched April 2025; managed by Spark Operators (SOs). USE WHEN: integrating with Spark, evaluating Spark vs Ark vs Lightning, designing leaf-based UTXO trees.

Automate lead generation, web scraping, and social media data extraction workflows through PhantomBuster's cloud platform via Composio.

Render long lists (1k+ rows) efficiently in Salesforce LWC using lightning-datatable infinite loading or an IntersectionObserver sentinel, with keyset pagination and accessibility guidance.

Guides designing or reviewing Lightning Web Components for keyboard access, semantic labeling, and focus management, prioritizing base components over custom ARIA.

Self-hosted observability platform for LLM applications, providing tracing, evaluation, datasets, experiments, and real-time monitoring to debug and improve AI systems.

Theme Salesforce Lightning base components and custom LWCs using SLDS Styling Hooks, covering global and component hooks, shadow DOM considerations, Experience Cloud theming, and SLDS 2 migration.

Build cross-platform Flutter apps with proven patterns for widgets, state management (Riverpod/Bloc), GoRouter navigation, performance optimization, and testing.

Implements and trains LLMs using Lightning AI's LitGPT with 20+ pretrained architectures (Llama, Gemma, Phi, Qwen, Mistral). Use when need clean model implementations, educational understanding of architectures, or production fine-tuning with LoRA/QLoRA. Single-file implementations, no abstraction layers.

Terraform infrastructure-as-code agent skill and plugin for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. Covers module design patterns, state management strategies, provider configuration, security hardening, policy-as-code with Sentinel/OPA, and CI/CD plan/apply workflows. Use when: user wants to design Terraform modules, manage state backends, review Terraform security, implement multi-region deployments, or follow IaC best practices.

Builds fast, standard-compliant web components with Lit, reactive properties, and Shadow DOM. Use for framework-agnostic UI.

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production. Use when: langfuse, llm observability, llm tracing, prompt management, llm evaluation.