UpTrain AI

UpTrain is an open-source LLMOps (Large Language Model Operations) platform that streamlines the evaluation, experimentation, regression testing, and collaboration processes for developers and teams working with large language models (LLMs). It provides a comprehensive suite of tools to ensure the reliability, efficiency, and accuracy of LLM applications, helping users to eliminate guesswork and scale AI with confidence.

Key features:

- Diverse Evaluations: Offers over 20 predefined metrics including response relevancy, structural integrity, completeness, conciseness, retrieval quality, hallucinations, context utilization, coherence, toxicity, fairness & bias, interestingness, emotion & tone, and guideline adherence. Users can also define custom metrics within the extendable framework.
- Faster and Systematic Experimentation: Enables quantitative scoring for informed decision-making, eliminating the need for guesswork and manual review. Supports prompt versioning for easy rollback of changes.
- Automated Regression Testing: Provides automated testing for each prompt-change, config-change, or code-change across a diverse test set, facilitating prompt versioning and hassle-free rollbacks.
- Root Cause Analysis: Monitors and isolates error cases, finds common patterns among them, and provides root cause analysis to help make improvements faster.
- Enriched Datasets: Helps create diverse test sets for different use cases and enrich existing datasets by capturing different edge cases encountered in production.
- Cost Efficiency and Reliability: Offers high-quality and reliable scoring at a reduced cost, capable of handling datasets ranging from 100 to over a million rows without failures.
- Open-Source Framework: The core evaluation framework is open-source, promoting transparency and community-driven enhancements.
- Data Governance Compliance: Can be self-hosted on various cloud platforms (AWS, GCP, etc.), ensuring compliance with data governance needs.
- Single-Line Integration: Facilitates integration in less than 5 minutes with a single API call, streamlining the setup process for users.

How it works:

1. Users integrate UpTrain with their LLM applications using a single API call.
2. The platform is accessed through a web-based dashboard.
3. Users configure evaluations, run experiments, perform regression testing, and conduct root cause analysis through the dashboard.
4. UpTrain can be hosted on various cloud services to fit into existing infrastructure.

Use of AI:

UpTrain leverages generative artificial intelligence to evaluate and improve LLM applications. It uses AI-powered metrics to assess various aspects of LLM outputs and provide insights for improvement.

Target users:

- Developers building and debugging LLM applications
- Product managers overseeing LLM-based products
- Business leaders ensuring the performance and reliability of LLM applications in production

How to access:

UpTrain is an open-source platform. Users can access its core evaluation framework through the open-source repository. For full platform functionality, users can set up UpTrain on their preferred cloud service.