LangSmith
LangSmith is the observability, debugging, and evaluation platform for LLM applications, built by LangChain. The LangSmith API exposes tracing, dataset management, evaluation, prompt-hub, and Fleet agent functionality for AI engineering teams.
APIs
LangSmith Tracing API
Capture, ingest, and inspect traces for LLM, agent, and chain executions. Traces include nested runs (spans), latency, token counts, errors, inputs/outputs, and metadata. Tracin...
LangSmith Datasets API
Manage datasets and example records used as ground-truth or test inputs for evaluating LLM applications. Supports CRUD on datasets, examples, and dataset splits.
LangSmith Evaluations API
Run offline and online evaluations against datasets, attach feedback and scores to runs, and compare experiments. Supports LLM-as-judge, code-based, and human evaluators.
LangSmith Prompt Hub API
Versioned prompt repository (Prompt Hub) for storing, retrieving, and collaborating on LLM prompts. Supports tagged versions, public/private prompts, and pull/push from SDKs.
LangSmith Feedback API
Attach human or programmatic feedback (scores, comments, correction labels) to runs and trace nodes for evaluation, monitoring, and reinforcement signal collection.
LangSmith Annotation Queues API
Route runs to human reviewers via annotation queues. Reviewers grade outputs, attach corrections, and feed labels back into datasets for evaluation and fine-tuning.
LangSmith Fleet (Agent Deployment) API
Deploy and manage LangGraph agents in production via Fleet. Provides agent invocation, run management, scheduled jobs, and uptime billing for hosted agent deployments.