LangSmith CLI

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

The LangSmith CLI is a command-line tool for querying and managing your LangSmith data. It’s designed for both developers and AI coding agents and outputs JSON by default for scripting, with a --format pretty option for human-readable tables. Use it when you need scriptable access to your LangSmith data, such as bulk exports, automation, or giving a coding agent direct access to your traces, runs, and datasets.

The LangSmith CLI is in alpha. Commands, flags, and output schemas may change between releases. Report issues on GitHub.

Install

macOS / Linux (recommended)

curl -fsSL https://cli.langsmith.com/install.sh | sh

irm https://cli.langsmith.com/install.ps1 | iex

brew install langchain-ai/tap/langsmith-cli

scoop install langsmith-cli

# Download the latest binary for your platform:
# https://github.com/langchain-ai/langsmith-cli/releases

go install github.com/langchain-ai/langsmith-cli/cmd/langsmith@latest

To upgrade at any time:

langsmith self-update

Use the --dry-run flag to preview the update without installing.

Authenticate

langsmith auth login requires LangSmith CLI v0.2.30 or later. langsmith profile commands require LangSmith CLI v0.2.26 or later.

The recommended local setup is to authenticate with OAuth:

langsmith auth login currently supports LangSmith Cloud (SaaS) only. For self-hosted or other non-SaaS LangSmith endpoints, authenticate with an API key or create an API-key profile.

langsmith auth login

This opens a browser-based authorization flow and stores OAuth tokens in ~/.langsmith/config.json under the selected profile. Select a profile with --profile or LANGSMITH_PROFILE:

langsmith auth login --profile dev
langsmith --profile dev project list

In headless environments, pass --no-browser and open the printed URL manually:

langsmith auth login --no-browser --workspace-id <workspace-id>

To manage saved profiles:

langsmith profile list
langsmith profile create dev --workspace-id <workspace-id> --set-current
langsmith profile use dev
langsmith profile set-workspace <workspace-id>

For the full profile configuration reference, see Profile configuration.

You can also authenticate with an API key directly.

Set your API key as an environment variable:

export LANGSMITH_API_KEY="lsv2_..."

Optionally, set a default project for queries:

export LANGSMITH_PROJECT="my-default-project"

If you’re using LangSmith self-hosted, also set the endpoint:

export LANGSMITH_ENDPOINT="https://your-langsmith-instance.com"

Or, pass them as flags per command:

langsmith --api-key lsv2_... trace list --project my-app

Quickstart

The following commands cover the core resource types:

# List tracing projects
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
langsmith thread list --project my-chatbot

# Sandboxes
langsmith sandbox list
langsmith sandbox tunnel my-vm --remote-port 5432

Output formats

Default

JSON to stdout — easy to pipe, script, or feed to an agent:

langsmith trace list --project my-app

Pretty tables

--format pretty for human-readable output:

langsmith --format pretty trace list --project my-app

Write to file

-o <path>:

langsmith trace list --project my-app -o traces.json

Commands

Each command group targets a specific LangSmith resource. Most commands support --limit, --offset, and a shared set of filter flags.

List projects

Returns up to 20 projects by default, sorted by most recent activity. Lists tracing projects only. (Use experiment list to list evaluation experiments.)

langsmith project list
langsmith project list --limit 50 --name-contains chatbot
langsmith --format pretty project list

Query traces

Defaults to the last 7 days, newest first. Use --since or --last-n-minutes to change the time window.

langsmith trace list --project my-app --limit 50 --last-n-minutes 60
langsmith trace list --project my-app --error                     # errors only
langsmith trace list --project my-app --min-latency 5             # slow traces (>5s)
langsmith trace list --project my-app --tags production           # filter by tag
langsmith trace list --project my-app --full                      # all fields
langsmith trace list --project my-app --show-hierarchy --limit 3  # include full run tree
langsmith trace get <trace-id> --project my-app --full
langsmith trace export ./traces --project my-app --limit 20 --full

Query runs

Defaults to 50 results (most other commands default to 20). The same 7-day time window applies. Use --since or --last-n-minutes to override.

langsmith run list --project my-app --run-type llm
langsmith run list --project my-app --run-type tool --name search
langsmith run list --project my-app --min-tokens 1000 --include-metadata
langsmith run get <run-id> --full
langsmith run export llm_calls.jsonl --project my-app --run-type llm --full

Query threads

--project is required for all thread commands.

langsmith thread list --project my-chatbot --last-n-minutes 120
langsmith thread get <thread-id> --project my-chatbot --full

Manage datasets

dataset export exports the examples (rows) within a dataset, not the dataset metadata itself.

langsmith dataset list
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 delete my-old-dataset --yes
langsmith dataset export my-dataset ./data.json --limit 500
langsmith dataset upload data.json --name new-dataset

Manage examples

Use --split to assign examples to named splits (such as test or train) when creating or listing.

langsmith example list --dataset my-dataset --limit 50
langsmith example list --dataset my-dataset --split test
langsmith example create --dataset my-dataset \
  --inputs '{"question": "What is LangSmith?"}' \
  --outputs '{"answer": "A platform for LLM observability"}' \
  --split test
langsmith example delete <example-id> --yes

Manage evaluators

Evaluators can be offline (run against a dataset during experiments) or online (run against a live project). Use --sampling-rate to evaluate only a fraction of production runs, and --replace to overwrite an existing evaluator by name.

langsmith evaluator list
langsmith evaluator upload evals.py --name accuracy \
  --function check_accuracy --dataset my-eval-set
langsmith evaluator upload evals.py --name latency-check \
  --function check_latency --project my-app --sampling-rate 0.5
langsmith evaluator upload evals.py --name accuracy \
  --function check_accuracy_v2 --dataset my-eval-set --replace --yes
langsmith evaluator delete accuracy --yes

View experiments

experiment list shows evaluation experiments, not tracing projects. (Use project list to list tracing projects.)

langsmith experiment list
langsmith experiment list --dataset my-eval-set
langsmith experiment get my-experiment-2024-01-15

Manage sandboxes

Sandbox commands let you build snapshots, create sandboxes, execute commands, open interactive consoles, and tunnel TCP ports to services running inside sandboxes.

See Sandbox CLI for the full sandbox command reference.

Call the LangSmith API directly

The api command is an authenticated, scriptable wrapper around the raw LangSmith REST API — useful for endpoints the typed commands above don’t cover, or for piping JSON into and out of shell scripts. It’s modeled after gh api and curl: pass the path as the only positional argument, and use -X to set the HTTP method (defaults to GET). Auth headers (x-api-key, x-tenant-id) are injected automatically.

# GET (default method) — query string supported in the path
langsmith api sessions?limit=5

# Discover endpoints from the OpenAPI spec
langsmith api ls --tag datasets
langsmith api info GET sessions

# Typed JSON fields with -F (numbers, booleans, null, objects, arrays parsed as JSON)
# Method auto-promotes to POST when -F/-f/--input/--body is supplied
langsmith api runs/query -F session_id=abc -F limit=10

# String-typed fields with -f (always sent as a JSON string, even if numeric)
langsmith api datasets -f name=my-dataset -f description="QA pairs"

# Other HTTP methods via -X
langsmith api sessions/abc-123 -X DELETE

# Send a request body from a file or stdin
langsmith api datasets --input create-dataset.json
echo '{"name":"test"}' | langsmith api sessions --input -

# Force GET with fields — fields go to the query string instead of a body
langsmith api runs -X GET -F limit=5 -F session=abc

# Inspect response status + headers
langsmith api sessions --include

# Add custom headers
langsmith api sessions -H "Accept: text/csv"

Key flags:

Flag	Short	Default	Description
--method	-X	GET	HTTP method
--field	-F	—	Typed JSON field as key=value. Repeatable. Use @<path> or @- for file/stdin values.
--raw-field	-f	—	String JSON field as key=value. Repeatable.
--input	—	—	File to use as the request body (- for stdin)
--body	—	—	Raw request body (JSON string, @file, or @- for stdin)
--header	-H	—	Additional headers as Key:Value. Repeatable.
--include	-i	false	Print response status line and headers before body

--input and --body are mutually exclusive. Subcommands langsmith api ls and langsmith api info browse and describe endpoints from the cached OpenAPI spec — pass --refresh to re-fetch.

Filter flags

Most trace and run commands share these filters:

Flag	Description	Example
--project	Project name	--project my-app
--limit, -n	Max results	-n 10
--offset	Pagination offset	--offset 20
--last-n-minutes	Override the 7-day default	--last-n-minutes 60
--since	After ISO timestamp	--since 2024-01-15T00:00:00Z
--error / --no-error	Filter by error status	--error
--name	Name search (case-insensitive)	--name ChatOpenAI
--run-type	Run type (llm or tool)	--run-type llm
--min-latency / --max-latency	Latency range in seconds	--min-latency 2.5
--min-tokens	Minimum total tokens	--min-tokens 1000
--tags	Tags, comma-separated (OR logic)	--tags prod,v2
--filter	Raw LangSmith filter DSL	--filter 'eq(status, "error")'
--trace-ids	Specific trace IDs	--trace-ids abc123,def456

Detail flags — control which fields are included in the response:

Flag	Adds
--include-metadata	Status, duration, tokens, costs
--include-io	Inputs, outputs, error
--include-feedback	Feedback stats
--full	All of the above
--show-hierarchy	Full run tree (traces only)

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