Open-Source Observability · langchain-ai

langsmith-sdk

LangSmith is a Python and JavaScript SDK for debugging, evaluating, and monitoring language model applications. It provides observability and tracing capabilities that integrate with LLM frameworks like LangChain, allowing teams to track model behavior and performance in production.

Talk to DEV.co Discuss Implementation

Source: GitHub — github.com/langchain-ai/langsmith-sdk

960

GitHub stars

256

Forks

Python

Primary language

MIT

License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

Field	Value
Repository	langchain-ai/langsmith-sdk
Owner	langchain-ai
Primary language	Python
License	MIT — OSI-approved
Stars	960
Forks	256
Open issues	167
Latest release	v0.9.8 (2026-07-06)
Last updated	2026-07-08
Source	https://github.com/langchain-ai/langsmith-sdk

What langsmith-sdk is

Client SDK for the LangSmith platform offering tracing, evaluation, and observability for LLM applications. Supports Python and JavaScript/TypeScript with decorators (@traceable) and wrapper utilities for OpenAI and other LLM clients, sending instrumentation data to the hosted LangSmith platform.

Quickstart

Get the langsmith-sdk source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/langchain-ai/langsmith-sdk.git2cd langsmith-sdk3# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

LLM Application Debugging & Tracing

Instrument calls to language models and track execution flow, inputs, and outputs across your application to diagnose failures and unexpected behavior in production.

Evaluation & Benchmarking Workflows

Collect and evaluate LLM outputs against ground truth or custom metrics to measure performance improvements across model iterations and parameter tuning.

Multi-step Agent Observability

Monitor complex agent workflows with multiple LLM calls, tool invocations, and state transitions to understand bottlenecks and optimize latency.

Implementation considerations

Requires API key provisioning and workspace setup on the LangSmith SaaS platform; authentication must be configured via environment variables (LANGSMITH_API_KEY, LANGSMITH_WORKSPACE_ID).
Integration is minimal for LangChain users (native support) but requires manual wrapping or decorator application for non-LangChain LLM calls (e.g., direct OpenAI SDK usage).
Tracing incurs latency and network overhead; consider sampling or filtering in high-volume production environments to manage costs and performance impact.
SDK supports both Python and JavaScript; teams using multiple languages must maintain separate SDK versions and ensure consistent instrumentation patterns.
Platform dependency means SDK reliability and observability visibility are coupled to LangSmith service availability and uptime.

When to avoid it — and what to weigh

Air-gapped or On-premises Requirement — LangSmith is a SaaS platform; this SDK requires external connectivity to smith.langchain.com. If your environment prohibits cloud telemetry, this is not suitable.
No LLM Application Context — This is a specialized observability SDK for LLM applications. If you are building traditional backends or non-AI services, standard APM tools are more appropriate.
Strict Data Residency or Sovereignty — Tracing data is sent to LangChain's managed platform. Organizations requiring data to remain on-premises or in specific regions should evaluate self-hosted alternatives.
Minimal Observability Needs — If your LLM use case is simple or non-critical, the overhead and cost of integrating LangSmith may exceed the value gained from detailed tracing.

License & commercial use

Licensed under MIT (MIT License), a permissive open-source license permitting commercial and proprietary use with minimal restrictions.

MIT license permits commercial use of the SDK itself. However, LangSmith is a SaaS platform with separate commercial terms; SDK usage requires a paid or trial LangSmith account. Review LangSmith's commercial licensing independently.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

Signal	Assessment
Maintenance	Active
Documentation	Strong
License clarity	Clear
Deployment complexity	Low
DEV.co fit	Good
Assessment confidence	High

Security considerations

SDK transmits LLM conversation data, prompts, and outputs to the LangSmith platform over HTTPS. Review data classification and compliance requirements (PII, HIPAA, GDPR) before enabling tracing. API keys and workspace IDs must be stored securely in environment variables. No encryption-at-rest details provided; requires review of LangSmith platform security documentation.

Alternatives to consider

LangFuse

Open-source and self-hosted LLM observability alternative with similar tracing and evaluation capabilities; suitable if on-premises deployment or data residency is required.

DataDog / New Relic APM

General-purpose application monitoring platforms with LLM-aware instrumentation libraries; broader ecosystem but less specialized for language model workflows.

Custom logging + analytics (e.g., OpenTelemetry + custom backend)

Full control and flexibility; suitable for organizations with strong engineering resources and specific observability requirements not met by managed platforms.

Software development agency

Build on langsmith-sdk with DEV.co software developers

Explore LangSmith SDK documentation, review data residency and compliance requirements, and assess pricing against your observability needs.

Talk to DEV.co

Related open-source tools

Surfaced by semantic similarity across the DEV.co open-source index.

langgraphjs langwatch appsmith

Related on DEV.co

Explore the category and the services that help you build with it.

Open-Source Observability AI Application Development API Development Talk to DEV.co

langsmith-sdk FAQ

Does this SDK require LangChain?

No. LangSmith SDK works with any LLM application. LangChain integration is native, but you can use the SDK with direct OpenAI SDK calls or other LLM clients via manual wrapping.

What is the cost model for LangSmith?

Not specified in the provided data. Requires review of LangSmith pricing documentation; the SDK itself is free and open-source, but platform usage incurs costs.

Can I self-host or run LangSmith on-premises?

The SDK is open-source, but LangSmith is a managed SaaS platform. Self-hosting or on-premises deployment of the backend is not described in the provided data; requires review of LangSmith licensing.

Does the SDK support other LLM providers (Anthropic, open-source models)?

Yes. The README states it works with 'any LLM Application'; the decorator and wrapper pattern supports Anthropic, open-source models, and custom LLM endpoints.

Work with a software development agency

Adopting langsmith-sdk is usually one piece of a larger software development effort. As a software development agency, DEV.co provides software development services and web development expertise — pairing senior software developers and web developers with your team to design, build, and operate open-source observability software in production.

Ready to instrument your LLM application?

Explore LangSmith SDK documentation, review data residency and compliance requirements, and assess pricing against your observability needs.

Talk to DEV.co Schedule a Consultation