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PandaProbe captures the full execution flow of your LLM application 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 the least invasive (wrappers) to the most flexible (manual APIs).

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Layer 1 — Wrappers (zero-code LLM tracing)

Wrap an LLM provider client to automatically trace every API call. The wrapper returns the same client type as the underlying SDK—no refactors beyond the wrap call.
  • wrap_openai(client) — Chat Completions API and Responses API
  • wrap_gemini(client) — generate_content and generate_content_stream
  • wrap_anthropic(client) — messages.create and messages.stream

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Layer 2 — Integrations (automatic agent framework tracing)

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, Google ADK, Claude Agent SDK, CrewAI, and OpenAI Agents SDK.

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Layer 3 — Manual instrumentation (full control)

Define exactly what gets traced, how spans are named, and what metadata you attach.
  • @pandaprobe.trace and @pandaprobe.span decorators
  • pandaprobe.start_trace() and t.span() context managers

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When to use each layer

  • Use Wrappers when you want LLM call visibility with minimal code changes—especially for direct provider usage without a heavy agent framework.
  • Use Integrations 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.

Wrappers

Zero-code LLM tracing

Integrations

Agent framework tracing

Manual

Decorators and context managers