Set up the SDK

First export your Respan API key, then pick the instrumentation path that matches your stack.

$
export RESPAN_API_KEY="your-api-key"

Auto-instrumented SDKs

These LLM SDKs can be traced automatically — just install Respan and initialize. No instrumentor imports needed.

$
pip install respan-ai

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from respan import Respan
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Respan()
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# All supported LLM calls are now auto-traced

Agent frameworks (explicit instrumentor)

Agent frameworks require an explicit instrumentor because they capture higher-level spans (agent runs, handoffs, tool calls) beyond raw LLM calls.

$
pip install respan-ai respan-instrumentation-openai-agents openai-agents

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from agents import Agent, Runner
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from respan import Respan
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from respan_instrumentation_openai_agents import OpenAIAgentsInstrumentor
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Respan(instrumentations=[OpenAIAgentsInstrumentor()])
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agent = Agent(name="Assistant", instructions="Reply in one sentence.")
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result = Runner.run_sync(agent, "Explain tracing.")
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print(result.final_output)

Disable auto-instrumentation

By default, Respan auto-instruments all supported providers. You can disable specific ones:

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from respan import Respan
2
3
# Disable specific providers
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Respan(
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    block_instruments={"bedrock", "vertexai"}
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)

In Python, you can also enable only specific providers instead of disabling:

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from respan import Respan
2
3
# Only instrument OpenAI and Anthropic
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Respan(
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    instruments={"openai", "anthropic"}
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)

Add custom instrumentors

Agent frameworks and custom integrations require explicit instrumentors. Pass them via the instrumentations parameter:

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from respan import Respan
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from respan_instrumentation_openai_agents import OpenAIAgentsInstrumentor
3
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Respan(instrumentations=[OpenAIAgentsInstrumentor()])

Next steps

• Customize traces — Use decorators to create nested, hierarchical traces
• Enrich span attributes — Attach metadata, customer identifiers, and other properties
• Manual ingestion — Send spans via OTLP or JSON API