'streaming' 검색 결과

Build charts with TradingView's lightweight-charts, including candlesticks, lines, live updates, scales, and annotations. Guidance checks installed types and v5 APIs to support chart integration, framework lifecycle handling, and troubleshooting of common data and display issues.

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• Build candlestick charts with a separate volume pane
• Add live updates and historical data
• Fix v4-to-v5 API migration issues

Start, inspect, and stop a CARLA UE 5.8 server. Choose an editor-based server, packaged build, or full editor; configure headless operation and ports; and enable native ROS 2 integration when the build supports it.

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• Start a UE 5.8 server for a CARLA client
• Configure camera image publishing through ROS 2
• Investigate missing maps or connection failures

Inspect a vehicle or another object in a running CARLA simulation. Read position, speed, and acceleration from the same simulation frame, check vehicle controls and steering angle, or stream the object's state over time.

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• Checking the ego vehicle's speed and heading
• Streaming acceleration data for ten seconds
• Inspecting a specific vehicle's controls

Build workflows that extract structured data from LLM responses, check field types and values with Pydantic, and retry failed extractions. Includes examples for nested data, classification, and receiving results as they are generated.

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• Extracting contact and company details from text
• Classifying articles into predefined categories
• Checking review analysis against validation rules

Implement Mamba, a model architecture that processes sequences through an internal state with computation scaling linearly with input length. Covers pretrained text generation, Mamba-1 and Mamba-2 configuration, speed comparisons with Transformers, and GPU memory troubleshooting.

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• Explore models for long sequences or streaming applications
• Generate text with pretrained Mamba models
• Compare Mamba-1 and Mamba-2 configurations

Build data processing pipelines for machine learning, from preprocessing to batch predictions. Uses Ray Data to handle datasets larger than memory, distribute work across CPUs and GPUs, and feed data into training frameworks.

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• Preprocessing datasets larger than memory
• Running batch predictions across multiple GPUs
• Preparing image and tabular data for training

Guides you through setting up RWKV, generating text, processing long documents in chunks, and fine-tuning models. Explains how to carry context between steps and compare memory use with Transformer models.

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• Build streaming text generation
• Process long documents in chunks
• Plan RWKV fine-tuning

Build Next.js 14+ applications with App Router, server-rendered components, and form actions. Produces routes, page layouts, data fetching, loading and error states, and SEO metadata, while supporting performance optimization and deployment preparation.

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• Building pages and layouts with App Router
• Implementing form submissions with Server Actions
• Adding loading states, error handling, and SEO metadata

Run builds, tests, and other long commands in the background while continuing other work. Explains how to read new log output, check completion, send input, and stop processes using the available platform controls.

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• Running long builds or tests in the background
• Monitoring development servers and streaming logs
• Taking over an automatically backgrounded command

Plan and review new Omnigent harness integrations, the adapters connecting agent runtimes to the platform. Compare SDK and subprocess approaches with native interface wrappers, using capability matrices and checklists for implementation and testing.

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• Plan a new agent runtime integration
• Compare SDK and native integration requirements
• Review approval, streaming, and session support

Connect stock data to an application using Finnhub Stock API. The skill covers current quotes, company profiles, historical prices, and market news, with server-side request handling to protect API keys and manage cached responses.

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• Display current stock prices on a dashboard
• Retrieve historical prices and trading volumes
• Show company profiles alongside stock quotes

Guides development of apps for viewing USD, a 3D scene format. Selects browser streaming or local implementation references, covering rendering, camera controls, selection, interface layout, and validation while keeping users’ scene files unchanged.

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• Build a browser viewer for USD scenes
• Develop a local workstation viewer
• Add camera controls and object selection

Build AI agents on Cloudflare Workers with the Agents SDK. Implement persistent state, real-time chat, scheduled tasks, multi-step background workflows, and MCP servers, using current Cloudflare documentation to guide implementation.

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• Build agents that retain and synchronize state
• Create real-time chat with resumable streaming
• Implement scheduled tasks and multi-step workflows

Write and review Cloudflare Workers code using current official guidance. Check configuration, asynchronous tasks, large response handling, secrets, and service connections, with findings supported by documentation, code locations, or validation results.

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• Writing a new Cloudflare Worker
• Reviewing Workers code before production use
• Checking wrangler.jsonc and service bindings

Design live monitoring dashboards with clear priorities, linked charts, and predictable update behavior. Covers mobile interactions, connection failures, and rendering performance so users can scan current conditions, spot anomalies, and explore details as data changes.

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• Design an operations dashboard using a WebSocket feed
• Improve charts receiving frequent data updates
• Plan linked chart selections and filters

Launch the real iPolloWork app on Daytona or locally and run scripted end-to-end tests through its debugging connection. Collect machine-checkable assertions, validated screenshots, and reports as evidence of the tested behavior.

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• Run scripted end-to-end tests on Daytona
• Collect screenshots and reports for a pull request
• Run tests locally when Daytona is unavailable

Document and validate Daytona interface workflows with labeled screenshots in a browsable HTML page. Add short videos when motion matters, check that evidence shows the claimed behavior, and share it for pull request review.

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• Prepare visual evidence for a pull request
• Verify each step of an interface workflow
• Show streaming text or animations with video

Integrate Pyth Network price feeds into Solana applications. Fetch or stream market prices, use them in on-chain programs, and check data freshness and uncertainty. Examples also cover moving averages that smooth short-term price changes.

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• Fetch prices for multiple assets
• Display continuously updated prices
• Use market prices in Solana programs

Build Solana applications using Helius for transaction submission, token and NFT queries, and wallet analysis. It also guides live data streams and webhooks, which notify applications when selected blockchain events occur.

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• Build a live wallet activity dashboard
• Query tokens and NFTs held by an address
• Notify an application about transfers or swaps

Build Solana apps with Phantom wallet connection, message and transaction signing, token-based access, NFT minting, and crypto payments. Add DFlow token swaps and live price or order-book displays, showing current buy and sell orders.

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• Add Phantom wallet login to an app
• Build pages restricted to token holders
• Implement token swaps with DFlow

Build chat bots for multiple platforms using shared TypeScript logic with Chat SDK. The skill guides message handling, interactive cards, webhook connections, streamed AI replies, and adapters that connect platforms or store conversation state.

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• Build a bot for Slack and Teams
• Respond to mentions and direct messages
• Add approval buttons to message cards

Analyze Excel files with 10,000 or more rows using reading methods suited to their size. Convert data to Parquet, a column-based storage format, reduce memory use, and prepare summaries, charts, or filtered exports.

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• Summarizing regional sales from 100,000 rows
• Exporting high-value transactions from a million-row log
• Speeding up repeated analysis with Parquet

Build interactive React cards and forms from JSON commands sent by an AI agent. Using @ant-design/x-card and A2UI, a protocol for describing interfaces, this skill covers data binding, user actions, custom components, and progressive rendering.

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• Display interactive cards inside AI chat responses
• Build forms driven by agent commands
• Render an interface progressively as commands arrive

Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows

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