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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.

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Install

curl -fsSL https://cli.langsmith.com/install.sh | sh
To upgrade at any time: 
langsmith self-update
Use the --dry-run flag to preview the update without installing.

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Authenticate

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 or hybrid, 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

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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

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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

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Commands

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

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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

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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

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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

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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

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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

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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

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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

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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

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Filter flags

Most trace and run commands share these filters:
FlagDescriptionExample
--projectProject name--project my-app
--limit, -nMax results-n 10
--offsetPagination offset--offset 20
--last-n-minutesOverride the 7-day default--last-n-minutes 60
--sinceAfter ISO timestamp--since 2024-01-15T00:00:00Z
--error / --no-errorFilter by error status--error
--nameName search (case-insensitive)--name ChatOpenAI
--run-typeRun type (llm or tool)--run-type llm
--min-latency / --max-latencyLatency range in seconds--min-latency 2.5
--min-tokensMinimum total tokens--min-tokens 1000
--tagsTags, comma-separated (OR logic)--tags prod,v2
--filterRaw LangSmith filter DSL--filter 'eq(status, "error")'
--trace-idsSpecific trace IDs--trace-ids abc123,def456
Detail flags — control which fields are included in the response:
FlagAdds
--include-metadataStatus, duration, tokens, costs
--include-ioInputs, outputs, error
--include-feedbackFeedback stats
--fullAll of the above
--show-hierarchyFull run tree (traces only)
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