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If you’re using a framework DecimalAI doesn’t have a first-class integration for — but it emits OpenTelemetry spans following the gen_ai.* semantic conventions — the generic OTel exporter will pick them up.

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Install

pip install decimalai
OTel SDK packages are pulled in transitively.

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Use

import decimalai
decimalai.init(api_key="dai_sk_...", otel=True)

# Any framework emitting OTEL spans will be captured
# Maps gen_ai.* semantic conventions automatically

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What gets captured

DecimalAI maps these OTel attributes onto its trace shape:
OTel attributeDecimalAI field
gen_ai.system / gen_ai.request.modelmodel
gen_ai.prompt.0.content (and indexed siblings)input
gen_ai.completion.0.contentoutput
gen_ai.usage.input_tokensinput_tokens
gen_ai.usage.output_tokensoutput_tokens
Span durationlatency_ms
Tool calls, retriever spans, and embeddings are mapped similarly when they follow the convention.

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When to use this vs. a first-class integration

Use the first-class integration if one exists for your framework — it captures more metadata (tool schemas, handoffs, etc.) than OTel conventions can express. Use generic OTel for:
  • Frameworks DecimalAI doesn’t yet support (Haystack, Mirascope, etc.)
  • Bespoke pipelines you’ve already instrumented with OTel
  • Multi-framework apps where you want a unified exporter

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What’s next

Manifests

register_manifest() is mandatory for OTel-only setups — auto-detection only works for first-class integrations.

Tracing guide

What gets captured at each layer of the stack.