“streaming”的搜索结果

Expert en data engineering (ETL, Airflow, dbt, data lakes, streaming pipelines, data quality)

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Data Engineer IA — Expert en pipelines de données (ETL, data lakes, dbt, Airflow, streaming). Construit des pipelines fiables, scalables et auditable.

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Expert en Apache Kafka (producers, consumers, streams, connectors, schema registry)

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Expert en performance des agents IA (optimisation latence, streaming, caching, traitement par lots)

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Build real-time streaming applications with Azure Event Hubs SDK for Java. Use when implementing event streaming, high-throughput data ingestion, or building event-driven architectures.

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Use when you need to write or review programmatic JDBC with Spring — including JdbcClient (Spring Framework 7+) as the default API, JdbcTemplate only where batch/streaming APIs require JdbcOperations, NamedParameterJdbcTemplate for legacy named-param code, parameterized SQL, RowMapper mapping to records, batch operations, transactions, safe handling of generated keys, DataAccessException handling, read-only transactions, streaming large result sets, and @JdbcTest slice testing. This should trigger for requests such as Review Java code for Spring JDBC (JdbcTemplate, JdbcClient, NamedParameterJdbcTemplate); Apply best practices for Spring JDBC data access in Java code; Detect and fix SQL injection risks in JDBC code; Improve transaction boundaries or exception handling for JDBC operations. Part of cursor-rules-java project

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Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named — don't Read the file).

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Build real-time streaming applications with Azure Event Hubs SDK for Java. Use when implementing event streaming, high-throughput data ingestion, or building event-driven architectures.

中文简介正在准备中。当前显示原文说明。

Build real-time streaming applications with Azure Event Hubs SDK for Java. Use when implementing event streaming, high-throughput data ingestion, or building event-driven architectures.

中文简介正在准备中。当前显示原文说明。

Expert data engineer for ETL/ELT pipelines, streaming, data warehousing. Activate on: data pipeline, ETL, ELT, data warehouse, Spark, Kafka, Airflow, dbt, data modeling, star schema, streaming data, batch processing, data quality. NOT for: API design (use api-architect), ML training (use ML skills), dashboards (use design skills).

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Architecture-level decisions for putting a CDN in front of a web app's static assets, API responses, and file/media delivery: provider selection (hyperscaler vs. specialist $/GB), signed-URL / tokenized access for gating private content at the edge, cache invalidation strategy (versioned URLs vs. purge APIs), origin shield / tiered caching for high-miss-rate content, and CDN-layer geo-restriction. Use when deciding which CDN to put in front of a new or growing service, when private/paywalled files need edge delivery without an origin round-trip per request, or when purge/invalidation behavior is being designed rather than debugged. NOT for HTTP cache-control header syntax, Vary, stale-while-revalidate, or surrogate-key purge mechanics (see `cdn-cache-control-headers`); NOT for Cloudflare-specific product configuration once Cloudflare is already chosen (see `cloudflare`); NOT for video-specific transcoding, adaptive bitrate ladders, or streaming-protocol packaging (see `managed-video-streaming-pipeline`).

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Spark, pandas, polars, DuckDB optimization for batch data processing. Activate on: batch processing, Spark optimization, polars, DuckDB, pandas performance, data frame, shuffle, partition, memory optimization. NOT for: streaming pipelines (use streaming-pipeline-architect), warehouse queries (use data-warehouse-optimizer).

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Apache Airflow DAGs, operators, SLA monitoring, and workflow orchestration. Activate on: Airflow, DAG, operator, sensor, scheduler, task dependency, SLA, backfill, XCom. NOT for: dbt transformations (use dbt-analytics-engineer), streaming pipelines (use streaming-pipeline-architect).

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Build real-time streaming applications with Azure Event Hubs SDK for Java. Use when implementing event streaming, high-throughput data ingestion, or building event-driven architectures.

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Process multimedia files with FFmpeg (video/audio encoding, conversion, streaming, filtering, hardware acceleration), ImageMagick (image manipulation, format conversion, batch processing, effects, composition), and RMBG (AI-powered background removal). Use when converting media formats, encoding videos with specific codecs (H.264, H.265, VP9), resizing/cropping images, removing backgrounds from images, extracting audio from video, applying filters and effects, optimizing file sizes, creating streaming manifests (HLS/DASH), generating thumbnails, batch processing images, creating composite images, or implementing media processing pipelines. Supports 100+ formats, hardware acceleration (NVENC, QSV), and complex filtergraphs.

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Build with OpenAI's stateless APIs - Chat Completions (GPT-5, GPT-4o), Embeddings, Images (DALL-E 3), Audio (Whisper + TTS), and Moderation. Includes Node.js SDK and fetch-based approaches for Cloudflare Workers. Use when: implementing chat completions with GPT-5/GPT-4o, streaming responses with SSE, using function calling/tools, creating structured outputs with JSON schemas, generating embeddings for RAG (text-embedding-3-small/large), generating images with DALL-E 3, editing images with GPT-Image-1, transcribing audio with Whisper, synthesizing speech with TTS (11 voices), moderating content (11 safety categories), or troubleshooting rate limits (429), invalid API keys (401), function calling failures, streaming parse errors, embeddings dimension mismatches, or token limit exceeded.

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Implements React Server Components (RSC) patterns with Next.js App Router including data fetching, streaming, selective hydration, and server/client composition. Use when users request "server components", "RSC", "Next.js app router", "server-side rendering", or "streaming".

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在OpenClaw的QA Lab中验证Telegram草稿与最终消息的送达顺序，通过QA Channel和实际Telegram插件运行同一场景。

• 检查Telegram草稿与最终消息的送达
• 通过QA Channel验证消息流程
• 通过实际Telegram插件运行验证

通过日志和复现操作排查OpenClaw的模型通信、工具执行及响应流问题，并检查已保存的对话和附件，为修复原因与再次验证收集证据。

• 排查本地测试与真实服务的行为差异
• 确认模型实际可见的工具
• 调查响应流的延迟或中断

将视频和音频导入VideoDB，按语音或画面搜索场景并制作片段，还可添加字幕和音轨、调整画面比例、设置直播事件通知，以及记录和总结桌面操作。

• 按语音或画面查找并截取场景
• 添加字幕、背景音乐或配音
• 调整视频分辨率和画面比例

分别衡量实时界面与数据推送的延迟、数据新鲜度和待处理任务，梳理事件发生到屏幕显示的完整路径，逐段改进，并在运行环境中验证结果。

• 调查实时界面的延迟
• 检查推送数据的新鲜度
• 减少队列积压

使用Apple的FoundationModels为iOS 26及以上版本的应用添加端侧语言模型功能，支持文本生成、摘要、数据提取、自定义处理调用和生成过程中的界面更新。

• 离线生成文本和摘要
• 从自然语言中提取表单字段
• 让AI调用应用自定义处理

检查已发布网址的页面与API响应、静态文件、持续连接及性能变化。支持单次检查、指定时段监控，以及测试环境与生产环境对比，并报告与基准值的差异。

• 部署后检查生产与测试环境
• 合并代码或更新依赖后验证修复
• 持续监控刚发布的网站

从文本中提取所需信息，整理为固定字段，并用Pydantic验证类型和值。涵盖结构化大语言模型输出、验证失败后的重试，以及逐步接收生成中的结果。

• 从文本中提取联系方式或企业信息
• 将文章归入预设类别
• 统一评论分析的字段