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https://github.com/confident-ai/deepeval
GitHub - confident-ai/deepeval: The LLM Evaluation Framework · GitHub
The LLM Evaluation Framework. Contribute to confident-ai/deepeval development by creating an account on GitHub.
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https://deepeval.com/
DeepEval by Confident AI - The LLM Evaluation Framework
DeepEval is the open-source LLM evaluation framework for testing and benchmarking LLM applications — 50+ plug-and-play metrics for AI agents, RAG, chatbots,...
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https://deepeval.com/docs/metrics-hallucination
Hallucination | DeepEval by Confident AI - The LLM Evaluation Framework
The hallucination metric uses LLM-as-a-judge to determine whether your LLM generates factually correct information by comparing the actual_output to the…
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https://deepeval.com/blog
Blog | DeepEval by Confident AI - The LLM Evaluation Framework
Latest posts, announcements, and deep dives from the DeepEval team.
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https://towardsdatascience.com/production-ready-llm-agents-a-comprehensive-framework-for-offline-evaluation/
Production-Ready LLM Agents: A Comprehensive Framework for Offline Evaluation | Towards Data Science
We’ve become remarkably good at building sophisticated agent systems, but we haven’t developed the same rigor around proving they work.
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https://deepeval.com/docs/metrics-introduction
Introduction to LLM Metrics | DeepEval by Confident AI - The LLM Evaluation Framework
deepeval offers 50+ SOTA, ready-to-use metrics for you to quickly get started with. Essentially, while a test case represents the thing you're trying to…
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https://deepeval.com/guides/guides-ai-agent-evaluation-metrics
AI Agent Evaluation Metrics | DeepEval by Confident AI - The LLM Evaluation Framework
AI agent evaluation metrics are purpose-built measurements that assess how well autonomous LLM systems reason, plan, execute tools, and complete tasks. Unlike…
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https://deepeval.com/guides/guides-ai-agent-evaluation
AI Agent Evaluation | DeepEval by Confident AI - The LLM Evaluation Framework
AI agent evaluation is the process of measuring how well an agent reasons, selects and calls tools, and completes tasks—separately at each layer—so you can…
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