{"categories":[{"label":"Monitoring","url":"https://skillfed.io/packages/category/system-monitoring/2"}],"enrichment":{"capability":"Phoenix Client provides a Python interface to the Phoenix observability platform's REST API, enabling programmatic management of datasets, experiments, traces, prompts, and feedback for LLM applications.","skillfed_tags":["llm-observability","experiment-tracking","api-client"],"use_cases":["Create and version prompt templates with variable substitution, then retrieve and format them for use with LLM APIs.","Build evaluation datasets from pandas DataFrames or CSV files and manage them centrally for reproducible experiment runs.","Query and filter application traces by time range, status, or custom criteria to debug LLM behavior in production.","Run LLM evaluations as pytest tests and automatically record results as Phoenix experiments for tracking.","Collect human feedback and automated evaluation scores on LLM outputs and associate them with specific traces."],"what_it_does":"Phoenix Client is a Python SDK for interacting with the Arize Phoenix observability platform via REST API. It abstracts away HTTP details and provides resource-oriented methods for managing LLM application data: creating and versioning prompts with template variables, building evaluation datasets from DataFrames or dictionaries, querying and filtering traces, recording experiment results, and collecting human feedback and automated evaluations.\n\nThe package is designed for teams running LLM applications who need to track behavior, debug issues, and run structured evaluations programmatically. It supports both synchronous and asynchronous clients, discovers configuration from environment variables or a `.env.phoenix` dotenv file, and integrates with pytest for running LLM evaluations as ordinary test cases. Its runtime dependencies (httpx, OpenTelemetry SDK and exporters, openinference conventions, tqdm, typing-extensions) are all lightweight and widely used.","worth_installing":"Yes. The package is actively maintained, has no known vulnerabilities, uses a permissive license, and offers low install friction. Install it if you are already running a Phoenix instance and need programmatic access to its API from Python; it is purpose-built for that workflow. If you do not have a Phoenix server running or do not need API-level control over datasets and experiments, it will not be useful."},"id":"arize-phoenix-client","links":{"html":"https://skillfed.io/packages/arize-phoenix-client","md":"https://skillfed.io/packages/arize-phoenix-client.md","pypi":"https://pypi.org/project/arize-phoenix-client/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-11","license_spdx":null,"license_treatment":"permissive","name":"arize-phoenix-client","python_support":"supports_current","summary":"LLM Observability"},"popularity":{"monthly_downloads":1120895,"position":4338,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"3.1.0"}