ai-observability

Observability for LLM chat and agent systems - tracing model calls, tool calls and agent steps as spans, token, cost, latency and error metrics, logging prompts and completions with redaction, correlation ids across agent runs and conversations, quality feedback signals, sampling, dashboards and alerts, replaying runs from traces, and retention and privacy. Load when instrumenting LLM calls or agent loops, debugging a bad answer or runaway run, tracking cost, or deciding what to log and keep.