UpTrain
Open-source LLM evaluation and refinement
Overview
UpTrain is an open-source toolkit designed to help developers evaluate and enhance their LLM applications. It offers a wide range of pre-built evaluation metrics to test for aspects like factual accuracy, relevance, and tone. Beyond just evaluation, UpTrain provides tools to refine applications by identifying failure cases and suggesting improvements. It can be integrated into CI/CD pipelines to automate testing and ensure the ongoing quality of LLM-powered features.
✨ Key Features
- Open-Source Evaluation Framework
- 50+ Pre-built Evaluation Metrics
- Factual Accuracy & Hallucination Checks
- Response Quality & Relevance Scoring
- Code Generation & Agent Evaluation
- Automated Data Refinement
- CI/CD Integration
🎯 Key Differentiators
- Extensive library of pre-built, domain-specific evaluation metrics
- Focus on both evaluation and refinement of LLM applications
- Completely open-source and easy to integrate
- Tools for evaluating complex agents and code generation
Unique Value: UpTrain provides an open-source, comprehensive, and easy-to-use framework for evaluating and refining LLM applications, enabling developers to build more accurate and reliable AI systems.
🎯 Use Cases (5)
✅ Best For
- Scoring the contextual relevance of retrieved documents in a RAG pipeline
- Checking for factual accuracy in a text summarization model
- Automated testing of an AI agent's tool usage
💡 Check With Vendor
Verify these considerations match your specific requirements:
- Real-time production monitoring and observability
- ML experiment tracking for model training
🏆 Alternatives
While some tools focus on a specific niche like RAG evaluation, UpTrain offers a broader set of metrics for various use cases. Its focus on refinement, not just evaluation, also sets it apart from pure testing frameworks.
💻 Platforms
✅ Offline Mode Available
🔌 Integrations
🛟 Support Options
- ✓ Email Support
- ✓ Dedicated Support (Enterprise tier)
💰 Pricing
Free tier: The open-source framework is entirely free.
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