Results for “arviz”

15 skills

Build, fit, validate, and compare Bayesian models using PyMC, including hierarchical models, MCMC sampling, variational inference, posterior predictive checks, and model comparison.

schattenspiegel

Use for writing, reviewing, debugging, or testing Python analysis of Bayesian inference results with ArviZ, including 1.x DataTree groups, legacy InferenceData inputs, xarray dimensions and coordinates, conversion, summaries, R-hat/ESS/MCSE diagnostics, posterior predictive checks, PSIS-LOO, Pareto-k, and model comparison. Trigger on chain/draw shape errors, mislabeled groups, flattened samples, missing log likelihood, or misleading diagnostic claims. Do not use to construct or sample PyMC, NumPyro, or Bambi models, for generic plotting, or for deterministic statistics without Bayesian draws.

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Generates deep links to the Arize UI for traces, spans, sessions, datasets, labeling queues, evaluators, and annotation configs.

36.2k · bundle

Downloads, exports, and inspects existing Arize traces and spans to understand what an LLM app is doing or debug runtime issues. Covers exporting traces by ID, spans by ID, sessions by ID, and root-cause investigation using the ax CLI. Use when the user wants to look at existing trace data, see what their LLM app is doing, export traces, download spans, investigate errors, or analyze behavior regressions.

Generates deep links to the Arize UI for traces, spans, sessions, datasets, labeling queues, evaluators, and annotation configs. Produces clickable URLs for sharing Arize resources with team members. Use when the user wants to link to or open a trace, span, session, dataset, evaluator, or annotation config in the Arize UI.

azure-ai-formrecognizer-java

Extract text, tables, key-value pairs, and structured fields from documents, receipts, invoices, and IDs using Azure AI Document Intelligence SDK for Java.

azure-ai-voicelive-ts

Build real-time voice AI applications with bidirectional WebSocket communication using the Azure AI Voice Live SDK for JavaScript/TypeScript.

azure-ai-vision-imageanalysis-java

Analyze images using Azure AI Vision SDK for Java, enabling captioning, OCR, object detection, tagging, and smart cropping.

arize-evaluator

Creates and runs LLM-as-judge evaluators on Arize, including managing tasks, column mappings, and continuous monitoring.

36.2k · bundle

azure-ai-vision-imageanalysis-py

Analyze images using Azure AI Vision SDK: generate captions, tags, detect objects, extract text (OCR), detect people, and suggest smart crops.

arize-annotation

Creates and manages annotation configs and annotation queues on Arize, and applies human annotations to project spans via the Python SDK.

36.2k · bundle

arize-instrumentation

Adds Arize AX tracing to LLM applications using a two-phase agent-assisted flow that analyzes the codebase before implementing instrumentation.

36.2k · bundle

Manage Arize datasets and examples using the ax CLI: create, list, get, export, and append datasets for evaluation and experimentation.

36.2k · bundle

Build, fit, validate, and compare Bayesian models using PyMC's modern API, including hierarchical models, MCMC sampling, variational inference, posterior predictive checks, and model comparison.

30.2k · bundle

schattenspiegel

Use for writing, reviewing, debugging, testing, or diagnosing Python Bayesian models built directly with PyMC, including Model, coords/dims, Data, random variables, potentials, posterior sampling, prior/posterior predictive checks, and InferenceData output. Trigger on model geometry, shape errors, divergences, sampler choice, mutable prediction data, and probabilistic validation. Do not use for Bambi formula models, NumPyro/JAX programs, ArviZ-only analysis of existing draws, deterministic optimization, or general statistics without PyMC code.