Log10 vs WhyLabs
Overview
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CLI (Node.js)
Manual
Detailed Comparison
It is an AI-powered LLMOps platform that enables developers to build continuously improving LLM-powered applications and ship them into production. | It is the leading observability platform trusted by high-performing teams to help maintain the quality and performance of ML models, LLMs, and data pipelines. |
Manage LLM data;
Continuously monitor the health of your LLM apps;
Optimize your LLM app via a rich debugger;
Easy programmatic integration | Detect, prevent, and mitigate risk in your AI applications;
Seamless integration with your existing pipelines and tools;
Model and data health;
LLM security |
Statistics | |
GitHub Stars 97 | GitHub Stars - |
GitHub Forks 13 | GitHub Forks - |
Stacks 0 | Stacks 1 |
Followers 0 | Followers 4 |
Votes 0 | Votes 0 |
Integrations | |
What are some alternatives to Log10, WhyLabs?
LangSmith
It is a platform for building production-grade LLM applications. It lets you debug, test, evaluate, and monitor chains and intelligent agents built on any LLM framework and seamlessly integrates with LangChain, the go-to open source framework for building with LLMs.
Rhesis AI
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Vivgrid — Build, Evaluate & Deploy AI Agents with Confidence
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SentinelQA
CI failures are painful to debug. SentinelQA gives you run summaries, flaky test detection, regression analysis, visual diffs and AI-generated action items.
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Arize AI
It is an AI observability and LLM evaluation platform designed to help ML and LLM engineers and data scientists surface model issues quicker, resolve their root cause, and ultimately, improve model performance.
Portkey
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promptfoo
It is a tool for testing and evaluating LLM output quality. With this tool, you can systematically test prompts, models, and RAGs with predefined test cases. It can be utilized as a CLI, a library, or integrated into CI/CD pipelines.
Relari
It helps AI teams rigorously test, validate, and improve GenAI applications throughout the entire development lifecycle.
Agentops
It is the toolkit for evaluating and developing robust and reliable AI agents. Build compliant virtual employees with observability, evals, and replay analytics. No more black boxes and prompt guessing.
