opentelemetry-instrumentation-langchain
OpenTelemetry Langchain instrumentation
Decision gist · record as of 2026-08-14
Yes, if you are building Langchain applications and already use or plan to use OpenTelemetry for observability. The package is actively maintained, has no known vulnerabilities, and integrates cleanly with the OpenTelemetry ecosystem. Install it only if you have an OpenTelemetry collector or exporter configured to receive the traces; the instrumentation alone produces no output.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later; requires an OpenTelemetry collector or exporter to be configured separately to actually receive the traces.
- Low install friction with four runtime dependencies all from the OpenTelemetry ecosystem.
- The package is actively maintained with a recent release and no known vulnerabilities.
License · maintenance · safety
Apache-2.0 (permissive) — Licensed under Apache-2.0 (permissive), allowing use in commercial and private projects with minimal restrictions beyond attribution.
last release 2026-08-10 (4 days) · last repo commit 2026-08-10 · 7,377 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 6,562,609 downloads/mo, #1,888 on PyPI
Alternatives
Verify before relying
pip install opentelemetry-instrumentation-langchain
from opentelemetry.instrumentation.langchain import LangchainInstrumentor
LangchainInstrumentor().instrument()- Whether the package supports all Langchain versions or has specific version constraints beyond what the fact sheet shows.
- Performance overhead of instrumentation on large-scale LLM applications.
- Whether TRACELOOP_TRACE_CONTENT environment variable fully disables all sensitive data logging or only the primary content fields.
What it is and what it does
This package integrates Langchain with OpenTelemetry to automatically trace LLM application execution. When enabled, it captures prompts, completions, and embeddings as attributes on OpenTelemetry spans, giving you visibility into how your Langchain-based application is behaving at runtime.
The instrumentation works by hooking into Langchain's execution flow and emitting span data to your configured OpenTelemetry exporter. By default it logs all content for debugging; you can disable this via the TRACELOOP_TRACE_CONTENT environment variable if you need to reduce trace size or protect sensitive user data. The package depends on the core OpenTelemetry API and instrumentation framework, plus semantic convention libraries for AI workloads.
Use it for
- Debug Langchain chains and agents by inspecting prompts and completions in your tracing backend.
- Monitor LLM application performance and latency across distributed systems using OpenTelemetry exporters.
- Audit and log all prompts and model outputs for compliance or quality evaluation.
- Correlate LLM traces with other application traces for end-to-end observability.
- Reduce trace payload size by disabling content logging in production while keeping structural metrics.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building Langchain applications and already use or plan to use OpenTelemetry for observability.
The package is actively maintained, has no known vulnerabilities, and integrates cleanly with the OpenTelemetry ecosystem. Install it only if you have an OpenTelemetry collector or exporter configured to receive the traces; the instrumentation alone produces no output.
Install
opentelemetry-instrumentation-langchain on PyPI
Before you install
Low install friction with four runtime dependencies all from the OpenTelemetry ecosystem. The package is actively maintained with a recent release and no known vulnerabilities.
Requires Python 3.10 or later; requires an OpenTelemetry collector or exporter to be configured separately to actually receive the traces.
License in practice
Licensed under Apache-2.0 (permissive), allowing use in commercial and private projects with minimal restrictions beyond attribution.
Quickstart
pip install opentelemetry-instrumentation-langchain
from opentelemetry.instrumentation.langchain import LangchainInstrumentor
LangchainInstrumentor().instrument()Verify before relying
- Whether the package supports all Langchain versions or has specific version constraints beyond what the fact sheet shows.
- Performance overhead of instrumentation on large-scale LLM applications.
- Whether TRACELOOP_TRACE_CONTENT environment variable fully disables all sensitive data logging or only the primary content fields.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release <4,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 4 packagesopentelemetry-apiopentelemetry-instrumentationopentelemetry-semantic-conventions-aiopentelemetry-semantic-conventions |
| Maintenance | Actively maintained 4 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 6,562,609 / month, #1,888 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: opentelemetry_instrumentation_langchain-0.62.3-py3-none-any.whl
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See also opentelemetry-instrumentation-bedrock · opentelemetry-instrumentation-haystack · opentelemetry-instrumentation-litellm · opentelemetry-instrumentation-ollama · opentelemetry-instrumentation-transformers · promptflow-tracing · langfuse · opentelemetry-instrumentation-llamaindex · opentelemetry-instrumentation-groq · opentelemetry-instrumentation-watsonx