Online Monitoring for LLM Applications in Production

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Online Monitoring for LLM Applications in Production

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Weights & Biases (W&B) Weave provides online monitoring capabilities for LLM applications in production, enabling ML teams to track performance, quality, and cost metrics in real-time. The platform offers framework-agnostic tracing through the @weave-op() decorator and service API endpoints that allow logging from various programming frameworks and languages. Teams can monitor token usage and latency over time, query aggregate costs by model, and track user feedback signals including thumbs up/down ratings for individual calls. W&B Weaves high-level APIs enable direct access to model costs, feedback scores, and other production metrics without needing to retrieve data call-by-call. The platform supports custom cost definitions for any model, with automatic token tracking for many standard LLM vendor libraries. Teams can build custom production dashboards by fetching traces, costs, feedback, and other metrics from Weave and creating aggregate visualizations for cost distribution by model, user feedback summaries, token usage trends, and latency analysis. Data can be exported in CSV, TSV, JSONL, and JSON formats for further analysis. W&B Weaves online monitoring integrates with existing workflows through easy data input via framework-agnostic tracing and service API endpoints, while providing powerful data output options including programmatic access and export capabilities. The platform helps LLM application teams identify quality regressions, track cost efficiency, monitor user satisfaction signals, and make data-driven decisions about model updates and deployments in production environments.

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