Tracing

Track every model call, agent handoff, and tool execution for faster debugging and optimization.

LangDB Gateway provides detailed tracing to monitor, debug, and optimize LLM workflows.

Below is an example of a trace visualization from the dashboard, showcasing a detailed breakdown of the request stages:

In this example trace you’ll find:

• Overview Metrics

  • Cost: Total spend for this request (e.g. $0.034).

  • Tokens: Input (5,774) vs. output (1,395).

  • Duration: Total end-to-end latency (29.52 s).

• Timeline Breakdown A parallel-track timeline showing each step—from moderation and relevance scoring to model inference and final reply.

• Model Invocations** Every call to gpt-4o-mini, gpt-4o, etc., is plotted with precise start times and durations.

• Agent Hand-offs Transitions between your agents (e.g. search → booking → reply) are highlighted with custom labels like transfer_to_reply_agent.

• Tool Integrations External tools (e.g. booking_tool, travel_tool, python_repl_tool) appear inline with their execution times—so you can spot slow or failed runs immediately.

• Guardrails Rules like Min Word Count and Travel Relevance enforce domain-specific constraints and appear in the trace.

With this level of visibility you can quickly pinpoint bottlenecks, understand cost drivers, and ensure your multi-agent pipelines run smoothly.