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PandaProbe captures the full execution flow of your LLM as traces composed of spans. Each trace represents a single request or operation; spans represent individual steps within that trace. Together they give you a structured, queryable record of what ran, in what order, and with what inputs and outputs.
Traces and spans are persisted and indexed for search, filtering, and evaluation. Instrumentation is opt-in per deploy via environment configuration; when tracing is disabled, the SDK avoids network I/O and mutation.
Instrumentation is organized into three layers, ordered from zero-code drop-ins to fully manual control.

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Layer 1 — LLM Providers (zero-code wrappers)

Wrap an LLM client to automatically trace every API call. The wrapper returns the same client type as the underlying SDK—no refactors beyond the wrap call.

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Layer 2 — Agent Frameworks (automatic agent integrations)

Hook into an agent framework to trace the full lifecycle: LLM calls, tool invocations, sub-agent handoffs, guardrails, and related steps—without instrumenting each call yourself. Supported stacks include LangGraph, LangChain, DeepAgents, Google ADK, Claude Agent SDK, CrewAI, OpenAI Agents SDK, and Vercel AI SDK. Availability varies by language; see the integration matrix.

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Layer 3 — Manual instrumentation (full control)

Define exactly what gets traced, how spans are named, and what metadata you attach.
  • Python: @pandaprobe.trace, @pandaprobe.span, pandaprobe.start_trace(), and t.span()
  • TypeScript: @trace, @span, withTrace(), withSpan(), and startTrace()

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When to use each layer

  • Use LLM Providers when you want LLM call visibility with minimal code changes—especially for direct provider usage without a heavy agent framework.
  • Use Agent Frameworks when you run on a supported agent framework and want end-to-end traces (LLM + tools + orchestration) with consistent semantics.
  • Use Manual instrumentation when you need custom span names, kinds, metadata, or you are building your own agent runtime and wrappers do not fit.

LLM Providers

Zero-code LLM tracing

Agent Frameworks

Agent framework tracing

Manual

Decorators and context managers