{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/10"}],"enrichment":{"capability":"TruLens instruments LLM applications to trace execution step-by-step, evaluate outputs with LLM-based judges, and compare versions to identify failures and cost-quality tradeoffs.","skillfed_tags":["llm-observability","agentic-systems","rag-evaluation"],"use_cases":["Trace retrieval latency and token usage in a RAG pipeline to identify cost-quality tradeoffs.","Evaluate agent reasoning chains step-by-step to catch logical inconsistencies and tool-selection errors.","Compare two versions of an LLM application on a fixed dataset using batch evaluation.","Export traces to an OTLP backend to correlate LLM behavior with infrastructure metrics.","Score context relevance and groundedness of RAG outputs using LLM judges.","Capture Model Context Protocol tool calls with structured spans to debug agentic workflows."],"what_it_does":"TruLens is an open-source library for systematically tracing and evaluating LLM-based applications. It uses OpenTelemetry-native instrumentation to capture every function call, LLM generation, retrieval, and tool invocation as structured spans, then scores outputs using LLM judges that explain their reasoning. The core workflow is: decorate your app functions with the @instrument decorator, run queries or batch datasets through your app, collect traces and evaluation scores, then compare versions to identify which performs best on the tradeoff between quality and cost.\n\nThe package bundles five internal components (trulens-core, trulens-dashboard, trulens-feedback, trulens-otel-semconv, trulens_eval) and is designed to integrate with existing observability infrastructure via OTLP backends. It includes evaluators for agentic systems and supports both inline evaluation (as the app runs) and offline batch evaluation over pre-collected datasets. Additional LLM provider packages and app framework integrations are installed separately.","worth_installing":"Yes. TruLens is actively maintained, has low install friction, carries a permissive MIT license, and solves a concrete problem\u2014systematic tracing and evaluation of LLM applications\u2014that most LLM teams face. It is adopted by major organizations and integrates with standard observability infrastructure. Install it if you need to debug agent failures, compare LLM app versions, or measure quality-cost tradeoffs."},"id":"trulens","links":{"html":"https://skillfed.io/packages/trulens","md":"https://skillfed.io/packages/trulens.md","pypi":"https://pypi.org/project/trulens/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-14","license_spdx":null,"license_treatment":"permissive","name":"trulens","python_support":"supports_current","summary":"Library to systematically track and evaluate LLM based applications."},"popularity":{"monthly_downloads":107852,"position":12591,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"2.13.0"}