{"categories":[{"label":"Monitoring","url":"https://skillfed.io/packages/category/system-monitoring/3"}],"enrichment":{"capability":"Auto-instruments LiteLLM function calls (completion, embedding, image generation, and Anthropic API methods) to emit OpenTelemetry-compatible traces for observability in tools like Arize Phoenix.","skillfed_tags":["observability","llm-tracing","opentelemetry"],"use_cases":["Debug LLM application behavior by viewing detailed traces of completion calls, embeddings, and image generation in Arize Phoenix or similar collectors.","Monitor production LLM services to track latency, error rates, and API usage across multiple LLM providers via OpenTelemetry exporters.","Correlate LLM calls with application-level traces to understand end-to-end request flow in complex systems.","Audit and log all LLM API interactions for compliance or troubleshooting without modifying existing LiteLLM code.","Analyze Anthropic API call patterns and performance when using LiteLLM's Anthropic wrapper methods."],"what_it_does":"This package wraps LiteLLM's core functions\u2014completion, embedding, image generation, and Anthropic API calls\u2014to automatically emit structured OpenTelemetry spans. It lets you see detailed traces of every LLM API call your application makes, including inputs, outputs, latency, and errors, without modifying your LiteLLM code.\n\nYou install it, instantiate LiteLLMInstrumentor, point it at a TracerProvider connected to an OpenTelemetry collector (like Arize Phoenix), and call instrument(). From that moment on, all instrumented LiteLLM functions emit traces. The package depends on opentelemetry-sdk, opentelemetry-instrumentation, and openinference-instrumentation to handle the tracing plumbing, and uses wrapt to hook into LiteLLM's function calls.","worth_installing":"Yes, if you use LiteLLM and need observability. The package is actively maintained, has no known vulnerabilities, installs cleanly with low friction, and is Apache-licensed. It solves a real problem\u2014seeing what your LLM calls are actually doing\u2014with minimal code changes. Install it alongside an OpenTelemetry collector (Phoenix, AX, or your own) to get immediate tracing."},"id":"openinference-instrumentation-litellm","links":{"html":"https://skillfed.io/packages/openinference-instrumentation-litellm","md":"https://skillfed.io/packages/openinference-instrumentation-litellm.md","pypi":"https://pypi.org/project/openinference-instrumentation-litellm/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-12","license_spdx":"Apache-2.0","license_treatment":"permissive","name":"openinference-instrumentation-litellm","python_support":"supports_current","summary":"OpenInference liteLLM Instrumentation"},"popularity":{"monthly_downloads":468654,"position":6492,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.1.37"}