Why LLM Observability Matters
Non-determinism: Same inputs can yield different outputs, causing inconsistent user experiences.
Debugging: Tracing how an output was generated helps identify root causes.
Monitoring Trends: Track changes in latency, cost, and accuracy over time
Anomaly Detection: Spot and act on unusual behaviors (e.g., cost spikes, low relevance).
Continuous Improvement: Evaluate responses using built-in metrics and improve prompts or model selection. FutureAGI.com
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Top 5 LLM Observability Tools for 2025
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