Results for “pingora”

Train, evaluate, export, prune, and run inference for PointPillars 3D object detection models from LiDAR point clouds using NVIDIA TAO.

Creates executable Polars dataframe contracts using Pandera's Polars backend for runtime validation of schemas, columns, and checks.

Build production RAG pipelines and persistent agent memory using Pinecone as the vector database backend.

Import object detection models from HuggingFace or NVIDIA NGC into a DeepStream pipeline with automated ONNX download, TensorRT engine build, custom parser, multi-stream benchmark, and PDF report generation.

Manages vector embeddings with Pinecone for semantic search, recommendation, and RAG pipelines.

Analyzes and documents Figma's marketing design system, including color tokens, typography hierarchy, spacing, and component patterns.

Optimizes Pine Script for performance, user experience, and visual appeal on TradingView. Use when improving script speed, reducing load time, enhancing UI, organizing inputs, improving colors and visuals, or making scripts more user-friendly. Triggers on "optimize", "improve", "faster", "better UX", "clean up", or enhancement requests.

Assess Active Directory security posture using PingCastle, BloodHound, and Purple Knight to identify misconfigurations, privilege escalation paths, and attack vectors.

Guides choice among spironolactone, eplerenone, and esaxerenone for primary aldosteronism based on comparative efficacy, safety, and patient-specific factors. Triggers include when initiating MRA therapy and asking 'Which MRA should I prescribe?' or considering switching agents due to adverse effects, cost, or need for potassium supplementation.

Dense, machine-readable API reference for PyFixest — high-dimensional fixed-effects OLS/WLS/IV and Poisson (feols, fepois, feglm), clustered/robust standard errors, R-style formula syntax, and post-estimation. Use when writing or debugging Python fixed-effects regressions with the pyfixest package.

Crea y gestiona entornos Python reproducibles con venv, pip, Poetry o Conda, aislando dependencias y configurando variables de entorno para evitar conflictos.

Provides code examples and best practices for using Pinecone, a managed vector database for production RAG, recommendation, and semantic search applications.

PUA Pro extensions: self-evolution notes, compaction state continuity, KPI-style summaries, flavor switching, and feedback tools.

Ingests case studies, past proposals, and boilerplate from library/inbox into structured indexes. Use when the user requests to 'index proposal library', 're-index case studies', 'ingest inbox docs', or 'validate library'.

Searches, downloads, analyzes, and saves research papers using arXiv, Google Scholar, and Zotero.

Run PyTorch training across GPUs with minimal changes.

Foodora-only CLI for checking past orders and active order status (Deliveroo WIP).

Create performance improvement plan templates. TRIGGERS - Use when user needs help with pip-template related tasks.

Solves single- and multi-objective optimization problems with NSGA-II/III, MOEA/D, and other evolutionary algorithms, including constraint handling, Pareto front analysis, and benchmark problems.

容嬷嬷（反派虚构）认知与表达框架（压缩蒸馏）：针刑符号、忠仆反派、童年阴影喜剧化 触发：还珠格格 等。反面教材；禁止暴力模仿

Template do pack (ai-ml/03-rag-pipeline.md). Orienta o agente em integracao de IA/ML, LLM e pipelines de dados alinhado a esse contexto.

Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommendation systems, or semantic search at scale. Best for serverless, managed infrastructure.

Query, analyze, and tune PostgreSQL databases through your AI agent with safe access controls, including index tuning recommendations, query plan analysis, health monitoring, and schema intelligence.

Foodora-only CLI for checking past orders and active order status (Deliveroo WIP).

Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.

明台（谍战虚构）认知与表达框架（压缩蒸馏）：公子成长、技能蒙太奇、信仰落地 触发：伪装者 等。禁止间谍违法教程

Systematic Review Pipeline Orchestrator - Coordinates systematic literature review automation Manages the complete 7-stage PRISMA 2020 pipeline from research question to RAG system Delegates to specialized agents (I1, I2, I3) while enforcing human checkpoints Use when: conducting systematic reviews, building knowledge repositories, PRISMA automation Triggers: systematic review, PRISMA, literature review automation

提供英格玛·伯格曼导演风格的创意建议，涵盖视觉方案、叙事手法和场景设计，适用于剧本创作和影像设计。

Create performance improvement plan templates. TRIGGERS - Use when user needs help with pip-template related tasks.

Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommendation systems, or semantic search at scale. Best for serverless, managed infrastructure.

Foodora-only CLI for checking past orders and active order status (Deliveroo WIP).

Use the Figma MCP server to fetch design context, screenshots, variables, and assets from Figma, and to translate Figma nodes into production code. Trigger when a task involves Figma URLs, node IDs, design-to-code implementation, or Figma MCP setup and troubleshooting.

Screen products for FDA, EPA, USDA, CPSC, FCC, and other government agency requirements using AskRosetta. Use when checking regulatory compliance for US imports.

Train reinforcement learning agents at millions of steps per second using optimized PPO, vectorized environments, and multi-agent support.

Food order (Foodora via ordercli)