
Arize Dataset
- 1k installs
- 37.1k repo stars
- Updated July 28, 2026
- github/awesome-copilot
This is a copy of arize-dataset by arize-ai - installs and ranking accrue to the original listing.
arize-dataset is a Claude Code skill that repairs Arize ax CLI authentication and region profiles for developers who upload or manage evaluation datasets without 401 failures.
About
arize-dataset is an Arize ax CLI setup skill consulted when authentication fails with 401 errors, missing profiles, or unset API keys blocking dataset work. The workflow starts with ax profiles show to inspect API key, profile, endpoint, and region state, then walks through creating or updating profiles when keys are wrong, expired, or pointed at the wrong region. Developers reach for arize-dataset only after failures appear—not for proactive checks—when evaluation datasets cannot upload or sync to Arize. The skill targets the gap between local ax configuration and successful dataset management so LLM evaluation pipelines can resume without manual dashboard guesswork.
- Diagnostic flow: `ax profiles show` before changing keys or regions
- Patch misconfigured profiles with `ax profiles update` without wiping other fields
- Requires API keys via ARIZE_API_KEY env var—never pass raw keys on the CLI
- Region correction example: us-east-1b via update flags
- Consult-only on auth failure—not meant as a proactive health check ritual
Arize Dataset by the numbers
- 1,021 all-time installs (skills.sh)
- +24 installs in the week ending Jul 28, 2026 (Skillselion tracking)
- Security screen: MEDIUM risk (skills.sh audit)
- Data as of Jul 28, 2026 (Skillselion catalog sync)
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| Installs | 1k |
|---|---|
| repo stars | ★ 37.1k |
| Security audit | 2 / 3 scanners passed |
| Last updated | July 28, 2026 |
| Repository | github/awesome-copilot ↗ |
How do you fix Arize ax CLI 401 authentication errors?
Fix Arize `ax` CLI authentication and region profiles so you can upload or manage evaluation datasets without 401 failures.
Who is it for?
ML engineers hitting 401 Unauthorized or missing-profile errors while uploading Arize evaluation datasets via ax CLI.
Skip if: Developers who need general Arize dashboard analytics without ax CLI dataset upload failures.
When should I use this skill?
ax CLI returns 401, reports no profiles, shows a missing API key, or dataset upload commands fail authentication.
What you get
Working ax CLI profile with valid API key, correct region, and successful dataset upload commands.
- configured ax profile
- successful dataset upload
Files
Arize Dataset Skill
`SPACE` — All--spaceflags and theARIZE_SPACEenv var accept a space name (e.g.,my-workspace) or a base64 space ID (e.g.,U3BhY2U6...). Find yours withax spaces list.
Concepts
- Dataset = a versioned collection of examples used for evaluation and experimentation
- Dataset Version = a snapshot of a dataset at a point in time; updates can be in-place or create a new version
- Example = a single record in a dataset with arbitrary user-defined fields (e.g.,
question,answer,context) - Space = an organizational container; datasets belong to a space
System-managed fields on examples (id, created_at, updated_at) are auto-generated by the server -- never include them in create or append payloads.
Prerequisites
Proceed directly with the task — run the ax command you need. Do NOT check versions, env vars, or profiles upfront.
If an ax command fails, troubleshoot based on the error:
command not foundor version error → see references/ax-setup.md401 Unauthorized/ missing API key → runax profiles showto inspect the current profile. If the profile is missing or the API key is wrong, follow references/ax-profiles.md to create/update it. If the user doesn't have their key, direct them to https://app.arize.com/admin > API Keys- Space unknown → run
ax spaces listto pick by name, or ask the user - Project unclear → ask the user, or run
ax projects list -o json --limit 100and present as selectable options - Security: Never read
.envfiles or search the filesystem for credentials. Useax profilesfor Arize credentials andax ai-integrationsfor LLM provider keys. If credentials are not available through these channels, ask the user.
List Datasets: ax datasets list
Browse datasets in a space. Output goes to stdout.
ax datasets list
ax datasets list --space SPACE --limit 20
ax datasets list --cursor CURSOR_TOKEN
ax datasets list -o jsonFlags
| Flag | Type | Default | Description |
|---|---|---|---|
--space | string | from profile | Filter by space |
--limit, -l | int | 15 | Max results (1-100) |
--cursor | string | none | Pagination cursor from previous response |
-o, --output | string | table | Output format: table, json, csv, parquet, or file path |
-p, --profile | string | default | Configuration profile |
Get Dataset: ax datasets get
Quick metadata lookup -- returns dataset name, space, timestamps, and version list.
ax datasets get NAME_OR_ID
ax datasets get NAME_OR_ID -o json
ax datasets get NAME_OR_ID --space SPACE # required when using dataset name instead of IDFlags
| Flag | Type | Default | Description |
|---|---|---|---|
NAME_OR_ID | string | required | Dataset name or ID (positional) |
--space | string | none | Space name or ID (required if using dataset name instead of ID) |
-o, --output | string | table | Output format |
-p, --profile | string | default | Configuration profile |
Response fields
| Field | Type | Description |
|---|---|---|
id | string | Dataset ID |
name | string | Dataset name |
space_id | string | Space this dataset belongs to |
created_at | datetime | When the dataset was created |
updated_at | datetime | Last modification time |
versions | array | List of dataset versions (id, name, dataset_id, created_at, updated_at) |
Export Dataset: ax datasets export
Download all examples to a file. Use --all for datasets larger than 500 examples (unlimited bulk export).
ax datasets export NAME_OR_ID
# -> dataset_abc123_20260305_141500/examples.json
ax datasets export NAME_OR_ID --all
ax datasets export NAME_OR_ID --version-id VERSION_ID
ax datasets export NAME_OR_ID --output-dir ./data
ax datasets export NAME_OR_ID --stdout
ax datasets export NAME_OR_ID --stdout | jq '.[0]'
ax datasets export NAME_OR_ID --space SPACE # required when using dataset name instead of IDFlags
| Flag | Type | Default | Description |
|---|---|---|---|
NAME_OR_ID | string | required | Dataset name or ID (positional) |
--space | string | none | Space name or ID (required if using dataset name instead of ID) |
--version-id | string | latest | Export a specific dataset version |
--all | bool | false | Unlimited bulk export (use for datasets > 500 examples) |
--output-dir | string | . | Output directory |
--stdout | bool | false | Print JSON to stdout instead of file |
-p, --profile | string | default | Configuration profile |
Agent auto-escalation rule: If an export returns exactly 500 examples, the result is likely truncated — re-run with --all to get the full dataset.
Export completeness verification: After exporting, confirm the row count matches what the server reports:
# Get the server-reported count from dataset metadata
ax datasets get DATASET_NAME --space SPACE -o json | jq '.versions[-1] | {version: .id, examples: .example_count}'
# Compare to what was exported
jq 'length' dataset_*/examples.json
# If counts differ, re-export with --allOutput is a JSON array of example objects. Each example has system fields (id, created_at, updated_at) plus all user-defined fields:
[
{
"id": "ex_001",
"created_at": "2026-01-15T10:00:00Z",
"updated_at": "2026-01-15T10:00:00Z",
"question": "What is 2+2?",
"answer": "4",
"topic": "math"
}
]Create Dataset: ax datasets create
Create a new dataset from a data file.
ax datasets create --name "My Dataset" --space SPACE --file data.csv
ax datasets create --name "My Dataset" --space SPACE --file data.json
ax datasets create --name "My Dataset" --space SPACE --file data.jsonl
ax datasets create --name "My Dataset" --space SPACE --file data.parquetFlags
| Flag | Type | Required | Description |
|---|---|---|---|
--name, -n | string | yes | Dataset name |
--space | string | yes | Space to create the dataset in |
--file, -f | path | yes | Data file: CSV, JSON, JSONL, or Parquet |
-o, --output | string | no | Output format for the returned dataset metadata |
-p, --profile | string | no | Configuration profile |
Passing data via stdin
Use --file - to pipe data directly — no temp file needed:
echo '[{"question": "What is 2+2?", "answer": "4"}]' | ax datasets create --name "my-dataset" --space SPACE --file -
# Or with a heredoc
ax datasets create --name "my-dataset" --space SPACE --file - << 'EOF'
[{"question": "What is 2+2?", "answer": "4"}]
EOFTo add rows to an existing dataset, use ax datasets append --json '[...]' instead — no file needed.
Supported file formats
| Format | Extension | Notes |
|---|---|---|
| CSV | .csv | Column headers become field names |
| JSON | .json | Array of objects |
| JSON Lines | .jsonl | One object per line (NOT a JSON array) |
| Parquet | .parquet | Column names become field names; preserves types |
Format gotchas:
- CSV: Loses type information — dates become strings,
nullbecomes empty string. Use JSON/Parquet to preserve types. - JSONL: Each line is a separate JSON object. A JSON array (
[{...}, {...}]) in a.jsonlfile will fail — use.jsonextension instead. - Parquet: Preserves column types. Requires
pandas/pyarrowto read locally:pd.read_parquet("examples.parquet").
Append Examples: ax datasets append
Add examples to an existing dataset. Two input modes -- use whichever fits.
Inline JSON (agent-friendly)
Generate the payload directly -- no temp files needed:
ax datasets append DATASET_NAME --space SPACE --json '[{"question": "What is 2+2?", "answer": "4"}]'
ax datasets append DATASET_NAME --space SPACE --json '[
{"question": "What is gravity?", "answer": "A fundamental force..."},
{"question": "What is light?", "answer": "Electromagnetic radiation..."}
]'From a file
ax datasets append DATASET_NAME --space SPACE --file new_examples.csv
ax datasets append DATASET_NAME --space SPACE --file additions.jsonTo a specific version
ax datasets append DATASET_NAME --space SPACE --json '[{"q": "..."}]' --version-id VERSION_IDFlags
| Flag | Type | Required | Description |
|---|---|---|---|
NAME_OR_ID | string | yes | Dataset name or ID (positional); add --space when using name |
--space | string | no | Space name or ID (required if using dataset name instead of ID) |
--json | string | mutex | JSON array of example objects |
--file, -f | path | mutex | Data file (CSV, JSON, JSONL, Parquet) |
--version-id | string | no | Append to a specific version (default: latest) |
-o, --output | string | no | Output format for the returned dataset metadata |
-p, --profile | string | no | Configuration profile |
Exactly one of --json or --file is required.
Validation
- Each example must be a JSON object with at least one user-defined field
- Maximum 100,000 examples per request
Schema validation before append: If the dataset already has examples, inspect its schema before appending to avoid silent field mismatches:
# Check existing field names in the dataset
ax datasets export DATASET_NAME --space SPACE --stdout | jq '.[0] | keys'
# Verify your new data has matching field names
echo '[{"question": "..."}]' | jq '.[0] | keys'
# Both outputs should show the same user-defined fieldsFields are free-form: extra fields in new examples are added, and missing fields become null. However, typos in field names (e.g., queston vs question) create new columns silently -- verify spelling before appending.
Delete Dataset: ax datasets delete
ax datasets delete NAME_OR_ID
ax datasets delete NAME_OR_ID --space SPACE # required when using dataset name instead of ID
ax datasets delete NAME_OR_ID --force # skip confirmation promptFlags
| Flag | Type | Default | Description |
|---|---|---|---|
NAME_OR_ID | string | required | Dataset name or ID (positional) |
--space | string | none | Space name or ID (required if using dataset name instead of ID) |
--force, -f | bool | false | Skip confirmation prompt |
-p, --profile | string | default | Configuration profile |
Workflows
Find a dataset by name
All dataset commands accept a name or ID directly. You can pass a dataset name as the positional argument (add --space SPACE when not using an ID):
# Use name directly
ax datasets get "eval-set-v1" --space SPACE
ax datasets export "eval-set-v1" --space SPACE
# Or resolve name to ID via list if you need the base64 ID
ax datasets list -o json | jq '.[] | select(.name == "eval-set-v1") | .id'Create a dataset from file for evaluation
1. Prepare a CSV/JSON/Parquet file with your evaluation columns (e.g., input, expected_output)
- If generating data inline, pipe it via stdin using
--file -(see the Create Dataset section)
2. ax datasets create --name "eval-set-v1" --space SPACE --file eval_data.csv 3. Verify: ax datasets get DATASET_NAME --space SPACE 4. Use the dataset name to run experiments
Add examples to an existing dataset
# Find the dataset
ax datasets list --space SPACE
# Append inline or from a file using the dataset name (see Append Examples section for full syntax)
ax datasets append DATASET_NAME --space SPACE --json '[{"question": "...", "answer": "..."}]'
ax datasets append DATASET_NAME --space SPACE --file additional_examples.csvDownload dataset for offline analysis
1. ax datasets list --space SPACE -- find the dataset name 2. ax datasets export DATASET_NAME --space SPACE -- download to file 3. Parse the JSON: jq '.[] | .question' dataset_*/examples.json
Export a specific version
# List versions
ax datasets get DATASET_NAME --space SPACE -o json | jq '.versions'
# Export that version
ax datasets export DATASET_NAME --space SPACE --version-id VERSION_IDIterate on a dataset
1. Export current version: ax datasets export DATASET_NAME --space SPACE 2. Modify the examples locally 3. Append new rows: ax datasets append DATASET_NAME --space SPACE --file new_rows.csv 4. Or create a fresh version: ax datasets create --name "eval-set-v2" --space SPACE --file updated_data.json
Pipe export to other tools
# Count examples
ax datasets export DATASET_NAME --space SPACE --stdout | jq 'length'
# Extract a single field
ax datasets export DATASET_NAME --space SPACE --stdout | jq '.[].question'
# Convert to CSV with jq
ax datasets export DATASET_NAME --space SPACE --stdout | jq -r '.[] | [.question, .answer] | @csv'Dataset Example Schema
Examples are free-form JSON objects. There is no fixed schema -- columns are whatever fields you provide. System-managed fields are added by the server:
| Field | Type | Managed by | Notes |
|---|---|---|---|
id | string | server | Auto-generated UUID. Required on update, forbidden on create/append |
created_at | datetime | server | Immutable creation timestamp |
updated_at | datetime | server | Auto-updated on modification |
| (any user field) | any JSON type | user | String, number, boolean, null, nested object, array |
Related Skills
- arize-trace: Export production spans to understand what data to put in datasets → use
arize-trace - arize-experiment: Run evaluations against this dataset → next step is
arize-experiment - arize-prompt-optimization: Use dataset + experiment results to improve prompts → use
arize-prompt-optimization
Troubleshooting
| Problem | Solution |
|---|---|
ax: command not found | See references/ax-setup.md |
401 Unauthorized | API key is wrong, expired, or doesn't have access to this space. Fix the profile using references/ax-profiles.md. |
No profile found | No profile is configured. See references/ax-profiles.md to create one. |
Dataset not found | Verify dataset ID with ax datasets list |
File format error | Supported: CSV, JSON, JSONL, Parquet. Use --file - to read from stdin. |
platform-managed column | Remove id, created_at, updated_at from create/append payloads |
reserved column | Remove time, count, or any source_record_* field |
Provide either --json or --file | Append requires exactly one input source |
Examples array is empty | Ensure your JSON array or file contains at least one example |
not a JSON object | Each element in the --json array must be a {...} object, not a string or number |
Save Credentials for Future Use
See references/ax-profiles.md § Save Credentials for Future Use.
ax Profile Setup
Consult this when authentication fails (401, missing profile, missing API key). Do NOT run these checks proactively.
Use this when there is no profile, or a profile has incorrect settings (wrong API key, wrong region, etc.).
1. Inspect the current state
ax profiles showLook at the output to understand what's configured:
API Key: (not set)or missing → key needs to be created/updated- No profile output or "No profiles found" → no profile exists yet
- Connected but getting
401 Unauthorized→ key is wrong or expired - Connected but wrong endpoint/region → region needs to be updated
2. Fix a misconfigured profile
If a profile exists but one or more settings are wrong, patch only what's broken.
Never pass a raw API key value as a flag. Always reference it via the ARIZE_API_KEY environment variable. If the variable is not already set in the shell, instruct the user to set it first, then run the command:
# If ARIZE_API_KEY is already exported in the shell:
ax profiles update --api-key $ARIZE_API_KEY
# Fix the region (no secret involved — safe to run directly)
ax profiles update --region us-east-1b
# Fix both at once
ax profiles update --api-key $ARIZE_API_KEY --region us-east-1bupdate only changes the fields you specify — all other settings are preserved. If no profile name is given, the active profile is updated.
3. Create a new profile
If no profile exists, or if the existing profile needs to point to a completely different setup (different org, different region):
Always reference the key via `$ARIZE_API_KEY`, never inline a raw value.
# Requires ARIZE_API_KEY to be exported in the shell first
ax profiles create --api-key $ARIZE_API_KEY
# Create with a region
ax profiles create --api-key $ARIZE_API_KEY --region us-east-1b
# Create a named profile
ax profiles create work --api-key $ARIZE_API_KEY --region us-east-1bTo use a named profile with any ax command, add -p NAME:
ax spans export PROJECT -p work4. Getting the API key
Never ask the user to paste their API key into the chat. Never log, echo, or display an API key value.
If ARIZE_API_KEY is not already set, instruct the user to export it in their shell:
export ARIZE_API_KEY="..." # user pastes their key here in their own terminalThey can find their key at https://app.arize.com/admin > API Keys. Recommend they create a scoped service key (not a personal user key) — service keys are not tied to an individual account and are safer for programmatic use. Keys are space-scoped — make sure they copy the key for the correct space.
Once the user confirms the variable is set, proceed with ax profiles create --api-key $ARIZE_API_KEY or ax profiles update --api-key $ARIZE_API_KEY as described above.
5. Verify
After any create or update:
ax profiles showConfirm the API key and region are correct, then retry the original command.
Space
There is no profile flag for space. Save it as an environment variable — accepts a space name (e.g., my-workspace) or a base64 space ID (e.g., U3BhY2U6...). Find yours with ax spaces list -o json.
macOS/Linux — add to ~/.zshrc or ~/.bashrc:
export ARIZE_SPACE="my-workspace" # name or base64 IDThen source ~/.zshrc (or restart terminal).
Windows (PowerShell):
[System.Environment]::SetEnvironmentVariable('ARIZE_SPACE', 'my-workspace', 'User')Restart terminal for it to take effect.
Save Credentials for Future Use
At the end of the session, if the user manually provided any credentials during this conversation and those values were NOT already loaded from a saved profile or environment variable, offer to save them.
Skip this entirely if:
- The API key was already loaded from an existing profile or
ARIZE_API_KEYenv var - The space was already set via
ARIZE_SPACEenv var - The user only used base64 project IDs (no space was needed)
How to offer: Use AskQuestion: "Would you like to save your Arize credentials so you don't have to enter them next time?" with options "Yes, save them" / "No thanks".
If the user says yes:
1. API key — Run ax profiles show to check the current state. Then run ax profiles create --api-key $ARIZE_API_KEY or ax profiles update --api-key $ARIZE_API_KEY (the key must already be exported as an env var — never pass a raw key value).
2. Space — See the Space section above to persist it as an environment variable.
ax CLI — Troubleshooting
Consult this only when an ax command fails. Do NOT run these checks proactively.
Check version first
If ax is installed (not command not found), always run ax --version before investigating further. The version must be 0.14.0 or higher — many errors are caused by an outdated install. If the version is too old, see Version too old below.
ax: command not found
macOS/Linux: 1. Check common locations: ~/.local/bin/ax, ~/Library/Python/*/bin/ax 2. Install: uv tool install arize-ax-cli (preferred), pipx install arize-ax-cli, or pip install arize-ax-cli 3. Add to PATH if needed: export PATH="$HOME/.local/bin:$PATH"
Windows (PowerShell): 1. Check: Get-Command ax or where.exe ax 2. Common locations: %APPDATA%\Python\Scripts\ax.exe, %LOCALAPPDATA%\Programs\Python\Python*\Scripts\ax.exe 3. Install: pip install arize-ax-cli 4. Add to PATH: $env:PATH = "$env:APPDATA\Python\Scripts;$env:PATH"
Version too old (below 0.14.0)
Upgrade: uv tool install --force --reinstall arize-ax-cli, pipx upgrade arize-ax-cli, or pip install --upgrade arize-ax-cli
SSL/certificate error
- macOS:
export SSL_CERT_FILE=/etc/ssl/cert.pem - Linux:
export SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt - Fallback:
export SSL_CERT_FILE=$(python -c "import certifi; print(certifi.where())")
Subcommand not recognized
Upgrade ax (see above) or use the closest available alternative.
Still failing
Stop and ask the user for help.
Related skills
FAQ
When should I invoke arize-dataset?
arize-dataset runs when Arize ax CLI authentication fails—401 errors, missing profiles, unset API keys, or wrong region settings—blocking evaluation dataset uploads. The skill is not meant for proactive profile checks.
What command does arize-dataset inspect first?
arize-dataset starts with ax profiles show to read API key, profile, endpoint, and region state, then guides fixes when keys are missing, expired, or misconfigured for dataset management.
Is Arize Dataset safe to install?
skills.sh reports 2 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.