Arize Dataset

Arize Dataset Skill

`SPACE` — --space flags accept a space name (e.g., my-workspace) or a base64 space ID (e.g., U3BhY2U6...). Find yours with ax 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 found or version error → see references/ax-setup.md
• 401 Unauthorized / missing API key → run ax profiles show to 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 list to pick by name, or ask the user
• Project unclear → ask the user, or run ax projects list -o json --limit 100 and present as selectable options
• Security: Never read .env files or search the filesystem for credentials. Use ax profiles for Arize credentials and ax ai-integrations for LLM provider keys. Never ask the user to paste secrets into chat. For missing credentials, see references/ax-profiles.md.

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 json

Flags

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 ID

Flags

Response fields

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 ID

Flags

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 --all

Output 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.parquet

Flags

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"}]
EOF

To add rows to an existing dataset, use ax datasets append --json '[...]' instead — no file needed.

Supported file formats

Format gotchas:

• CSV: Loses type information — dates become strings, null becomes empty string. Use JSON/Parquet to preserve types.
• JSONL: Each line is a separate JSON object. A JSON array ([{...}, {...}]) in a .jsonl file will fail — use .json extension instead.
• Parquet: Preserves column types. Requires pandas/pyarrow to 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..."}
]'