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Evaluation, Benchmarks \u0026 Datasets","*Ops for AI","Catalog","Cost Tracking, Observability, and Budgets"],"sub_categories":["大语言对话模型及数据","评测框架","Open Source Frameworks","Documentation \u0026 Testing Assistants","Vector Store Tutorials","Evaluators and Test Harnesses","Rust","LLM Evaluation Tools","Benchmark Reality Check (real-world tool use)","Evaluation","Comparison Guides","LLMOps","Observability \u0026 Reliability Operations","Frameworks \u0026 Tools","Open source"],"readme":"![PyPI - Version](https://img.shields.io/pypi/v/trulens?label=trulens\u0026link=https%3A%2F%2Fpypi.org%2Fproject%2Ftrulens%2F)\n[![Azure Build Status](https://dev.azure.com/truera/trulens/_apis/build/status%2FTruLens%20E2E%20Tests?branchName=main)](https://dev.azure.com/truera/trulens/_build/latest?definitionId=8\u0026branchName=main)\n![GitHub](https://img.shields.io/github/license/truera/trulens)\n![PyPI - Downloads](https://img.shields.io/pypi/dm/trulens-core)\n[![Discourse](https://img.shields.io/discourse/users?server=https://snowflake.discourse.group/)](https://snowflake.discourse.group/c/ai-research-and-development-community/trulens/97)\n[![Docs](https://img.shields.io/badge/docs-trulens.org-blue)](https://www.trulens.org/getting_started/)\n[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/truera/trulens/blob/main/examples/quickstart/langchain_quickstart.ipynb)\n[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/truera/trulens)\n\n# 🦑 Welcome to TruLens!\n\n![TruLens](https://www.trulens.org/assets/images/Neural_Network_Explainability.png)\n\n**Don't just vibe-check your LLM app!** Systematically evaluate and track your\nLLM experiments with TruLens. As you develop your app including prompts, models,\nretrievers, knowledge sources and more, *TruLens* is the tool you need to\nunderstand its performance.\n\nFine-grained, stack-agnostic instrumentation and comprehensive evaluations help\nyou to identify failure modes \u0026 systematically iterate to improve your\napplication.\n\nRead more about the core concepts behind TruLens including [Feedback Functions](https://www.trulens.org/getting_started/core_concepts/feedback_functions/),\n[The RAG Triad](https://www.trulens.org/getting_started/core_concepts/rag_triad/),\nand [Honest, Harmless and Helpful Evals](https://www.trulens.org/getting_started/core_concepts/honest_harmless_helpful_evals/).\n\n## TruLens in the development workflow\n\nBuild your first prototype then connect instrumentation and logging with\nTruLens. Decide what feedbacks you need, and specify them with TruLens to run\nalongside your app. Then iterate and compare versions of your app in an\neasy-to-use user interface 👇\n\n![Architecture\nDiagram](https://www.trulens.org/assets/images/TruLens_Architecture.png)\n\n## Installation and Setup\n\nInstall the trulens pip package from PyPI.\n\n```bash\n    pip install trulens\n```\n\n## Quick Usage\n\nWalk through how to instrument and evaluate a RAG built from scratch with\nTruLens.\n\n[![Open In\nColab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/truera/trulens/blob/main/examples/quickstart/quickstart.ipynb)\n\n### 💡 Contributing \u0026 Community\n\nInterested in contributing? See our [contributing\nguide](https://www.trulens.org/contributing/) for more details.\n\nThe best way to support TruLens is to give us a ⭐ on\n[GitHub](https://www.github.com/truera/trulens) and join our [discourse\ncommunity](https://snowflake.discourse.group/c/ai-research-and-development-community/trulens/97)!\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftruera%2Ftrulens","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftruera%2Ftrulens","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftruera%2Ftrulens/lists"}