trulens and llm-trace
Maintenance
17/25
Adoption
10/25
Maturity
25/25
Community
19/25
Maintenance
10/25
Adoption
4/25
Maturity
20/25
Community
0/25
Stars: 3,160
Forks: 251
Downloads: —
Commits (30d): 9
Language: Python
License: MIT
Stars: 1
Forks: —
Downloads: 26
Commits (30d): 0
Language: TypeScript
License: MIT
No risk flags
No Dependents
About trulens
truera/trulens
Evaluation and Tracking for LLM Experiments and AI Agents
This tool helps AI engineers and developers systematically evaluate and track their Large Language Model (LLM) application experiments. It takes your LLM application's prompts, models, retrievers, and knowledge sources as input, and provides detailed feedback and performance insights to help you identify failure modes. The output enables you to understand and improve your application's behavior and performance.
LLM application development
AI agent evaluation
prompt engineering
retrieval-augmented generation
machine learning operations
About llm-trace
moondef/llm-trace
Structured execution traces for LLM debugging – lets AI coding tools see runtime behavior instead of guessing
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