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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. confident ai llm evaluation github deepeval framework https://deepeval.com/docs/metrics-dag DAG (Deep Acyclic Graph) | DeepEval by Confident AI - The LLM Evaluation Framework The deep acyclic graph (DAG) metric in deepeval is currently the most versatile custom metric for you to easily build deterministic decision trees for… 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,... confident ai llm evaluation deepeval framework https://deepeval.com/guides/guides-using-custom-llms Using Custom LLMs for Evaluation | DeepEval by Confident AI - The LLM Evaluation Framework All of deepeval's metrics uses LLMs for evaluation, and is currently defaulted to OpenAI's GPT models. However, for users that don't wish to use OpenAI's GPT… custom llms for evaluation https://deepeval.com/guides/guides-multi-turn-evaluation-metrics Multi-Turn Evaluation Metrics | DeepEval by Confident AI - The LLM Evaluation Framework Multi-turn evaluation metrics are purpose-built measurements that assess how well LLM systems perform across extended conversations. Unlike single-turn metrics… evaluation metrics confident ai multi turn deepeval https://deepeval.com/docs/conversation-simulator-model-callback Model Callback | DeepEval by Confident AI - The LLM Evaluation Framework The model_callback is the bridge between the simulator and your LLM application. It receives the simulated user input and returns your chatbot's assistant turn. confident ai llm evaluation model callback deepeval