> ## Documentation Index
> Fetch the complete documentation index at: https://langchain-5e9cc07a-preview-cbfron-1772840960-d2a2597.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# LangSmith CLI

> Query and manage LangSmith projects, traces, runs, datasets, evaluators, experiments, and threads from the terminal

The LangSmith CLI is a fast, agent-friendly command-line tool for working with your LangSmith data and workflows directly from the terminal. It’s designed for both humans and AI coding agents to list, filter, retrieve, and export data — with predictable JSON output by default and a pretty table mode for humans.

<Callout icon="terminal" color="#504B5F">
  Built for agents and scripts: defaults to JSON, supports clean stdout/stderr separation, and offers `--yes` flags for non-interactive use.
</Callout>

## Installation

Use one of the follow methods for installation:

<CodeGroup>
  ```bash Install script (recommended) theme={null}
  curl -sSL https://raw.githubusercontent.com/langchain-ai/langsmith-cli/main/scripts/install.sh | sh
  ```

  ```bash Install to a custom directory theme={null}
  INSTALL_DIR=$HOME/.local/bin \
    curl -sSL https://raw.githubusercontent.com/langchain-ai/langsmith-cli/main/scripts/install.sh | sh
  ```

  ```bash GitHub Releases theme={null}
  # Download the latest binary for your platform
  # https://github.com/langchain-ai/langsmith-cli/releases
  ```

  ```bash Go install theme={null}
  go install github.com/langchain-ai/langsmith-cli/cmd/langsmith@latest
  ```
</CodeGroup>

## Authentication

Set your [API key](/langsmith/create-account-api-key) as an environment variable:

```bash theme={null}
export LANGSMITH_API_KEY="lsv2_..."
```

Optional defaults:

```bash theme={null}
export LANGSMITH_ENDPOINT="https://api.smith.langchain.com"  # self-hosted/hybrid
export LANGSMITH_PROJECT="my-default-project"                 # default project for queries
```

Or pass them as flags when running commands:

```bash theme={null}
langsmith --api-key lsv2_... trace list --project my-app
```

## Quickstart

The following commands cover the core resource types — projects, traces, runs, datasets, experiments, and threads:

```bash theme={null}
# List tracing projects (sessions)
langsmith project list

# List recent traces in a project
langsmith trace list --project my-app --limit 5

# Get a specific trace with full detail
langsmith trace get <trace-id> --project my-app --full

# List LLM runs with token counts
langsmith run list --project my-app --run-type llm --include-metadata

# Datasets and experiments
langsmith dataset list
langsmith experiment list --dataset my-eval-set

# Conversation threads in a project
langsmith thread list --project my-chatbot
```

## Output formats

* Default: JSON to stdout for easy piping and scripting
* Pretty tables: `--format pretty` for human-readable tables and trees
* Write to file: `-o <path>`

```bash theme={null}
langsmith trace list --project my-app                  # JSON array to stdout
langsmith --format pretty trace list --project my-app  # tables/trees
langsmith trace list --project my-app -o traces.json   # write JSON to file
```

## Commands overview

The CLI groups functionality by resource. Each command supports filters like `--limit`, `--last-n-minutes`, and more.

### project — list tracing projects

```bash theme={null}
langsmith project list                    # default limit: 20
langsmith project list --name-contains chatbot
langsmith --format pretty project list
```

### trace — query and export traces

```bash theme={null}
langsmith trace list --project my-app --limit 50 --last-n-minutes 60
langsmith trace list --project my-app --error --include-metadata
langsmith trace get <trace-id> --project my-app --full
langsmith trace export ./traces --project my-app --limit 20 --full
```

### run — query individual runs

```bash theme={null}
langsmith run list --project my-app --run-type llm
langsmith run list --project my-app --run-type tool --name search
langsmith run get <run-id> --full
langsmith run export llm_calls.jsonl --project my-app --run-type llm --full
```

### thread — query conversation threads

```bash theme={null}
langsmith thread list --project my-chatbot --last-n-minutes 120
langsmith thread get <thread-id> --project my-chatbot --full
```

### dataset — manage evaluation datasets

```bash theme={null}
langsmith dataset list --name-contains eval
langsmith dataset get my-dataset
langsmith dataset create --name my-eval-set --description "QA pairs for v2"
langsmith dataset export my-dataset ./data.json --limit 500
```

### evaluator — manage evaluators

```bash theme={null}
langsmith evaluator list
langsmith evaluator upload evals.py --name accuracy --function check_accuracy --dataset my-eval-set
langsmith evaluator delete accuracy --yes
```

### experiment — results and summaries

```bash theme={null}
langsmith experiment list --dataset my-eval-set
langsmith experiment get my-experiment-2024-01-15
```

***

<div className="source-links">
  <Callout icon="edit">
    [Edit this page on GitHub](https://github.com/langchain-ai/docs/edit/main/src/langsmith/langsmith-cli.mdx) or [file an issue](https://github.com/langchain-ai/docs/issues/new/choose).
  </Callout>

  <Callout icon="terminal-2">
    [Connect these docs](/use-these-docs) to Claude, VSCode, and more via MCP for real-time answers.
  </Callout>
</div>