arize-dataset

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Creates, manages, and queries Arize datasets and examples. Covers dataset CRUD, appending examples, exporting data, and file-based dataset creation using the ax CLI. Use when the user needs test data, evaluation examples, or mentions create dataset, list datasets, export dataset, append examples, dataset version, golden dataset, or test set.

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스킬 원문 파일

# 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

```bash
ax profiles show
```

Look 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.

Profile region controls API and Flight routing for `ax` commands. Prefer `--region` over hard-coding SaaS hosts; examples include `us-central-1a`, `us-east-1b`, `eu-west-1a`, and `ca-central-1a`. It does not configure where a separately running app exports traces.

For EU and Canada, `--region eu-west-1a` and `--region ca-central-1a` automatically set `flight_host` to `flight.eu-west-1a.arize.com` or `flight.ca-central-1a.arize.com` and `flight_port` to `443`. Do not set those fields separately for standard SaaS profiles. Set them directly only for custom/private routing, using interactive profile setup or a complete `--from-file` profile; keep `flight_host` hostname-only (no `:443`) and set `flight_port` separately.

**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:

```bash
# 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-1b
```

`update` 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.**

```bash
# 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-1b
```

To use a named profile, switch to it first with `ax profiles use NAME` (see **Managing Multiple Profiles** below).

## 4. 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:

```bash
export ARIZE_API_KEY="..."   # user pastes their key here in their own terminal
```

They 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:

```bash
ax profiles show

# Or validate connectivity and configuration explicitly:
ax profiles validate
```

Confirm the API key and region are correct, then retry the original command.

## Managing Multiple Profiles

List all available profiles, with the active one marked:

```bash
ax profiles list
```

Switch to a different profile:

```bash
ax profiles use work
```

Delete a profile. You cannot delete the currently active profile; switch to another first if needed.

```bash
ax profiles delete staging --force
```

## Space

There is no profile field or environment variable for space. Every `ax` command that needs one takes it per-invocation via `-s`/`--space`, accepting a space **name** (e.g., `my-workspace`) or a base64 space **ID** (e.g., `U3BhY2U6...`). Find yours with `ax spaces list -o json`.

```bash
ax spans export my-project --space my-workspace
```

**For app instrumentation (the `arize-otel` SDK), not the CLI:** the SDK reads the **`ARIZE_SPACE_ID`** env var — the **base64 Space ID**, not a name. That's a separate mechanism from the CLI's `--space` flag; see the **arize-instrumentation** skill for SDK env vars.

## 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_KEY` env var
- The user only used base64 project/space IDs and never needed to persist a space

**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).

# 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 `0.32.0` or higher — many errors are caused by an outdated install. (Some skills require a newer floor for specific features — check the skill's own `compatibility` note.) 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 0.32.0)

Upgrade: `ax upgrade` (auto-detects pip/pipx/uv), or explicitly `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.

---
name: arize-dataset
description: Creates, manages, and queries Arize datasets and examples. Covers dataset CRUD, appending examples, exporting data, and file-based dataset creation using the ax CLI. Use when the user needs test data, evaluation examples, or mentions create dataset, list datasets, export dataset, append examples, dataset version, golden dataset, or test set.
metadata:
  author: arize
  version: "1.0"
compatibility: Requires the ax CLI (≥ 0.27.0) and a configured Arize profile.
---

# 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](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](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](references/ax-profiles.md).

## List Datasets: `ax datasets list`

Browse datasets in a space. Output goes to stdout.

```bash
ax datasets list
ax datasets list --space SPACE --limit 20
ax datasets list --cursor CURSOR_TOKEN
ax datasets list -o json
```

### Flags

| Flag | Type | Default | Description |
|------|------|---------|-------------|
| `--space` | string | from profile | Filter by space |
| `--name, -n` | string | none | Substring filter on dataset name |
| `--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 |

## Get Dataset: `ax datasets get`

Quick metadata lookup -- returns dataset name, space, timestamps, and version list.

```bash
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

| 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 |

### 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).

```bash
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

| 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 |

**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:
```bash
# 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:

```json
[
  {
    "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.

```bash
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

| 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 |

### Passing data via stdin

Use `--file -` to pipe data directly — no temp file needed:

```bash
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 | 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, `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:

```bash
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

```bash
ax datasets append DATASET_NAME --space SPACE --file new_examples.csv
ax datasets append DATASET_NAME --space SPACE --file additions.json
```

### To a specific version

```bash
ax datasets append DATASET_NAME --space SPACE --json '[{"q": "..."}]' --version-id VERSION_ID
```

### Flags

| 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 |

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:

```bash
# 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 fields
```

Fields 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.

## Update Examples: `ax datasets update-examples`

`ax datasets update-examples` patches rows by example `id`; `ax datasets delete-examples` removes rows from a version. Uncommon — run `ax datasets update-examples --help` or `ax datasets delete-examples --help` for flags and input formats.

## Delete Dataset: `ax datasets delete`

```bash
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 prompt
```

### Flags

| 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 |

## Update Dataset: `ax datasets update`

Rename an existing dataset.

```bash
ax datasets update NAME_OR_ID --name "new-dataset-name"
ax datasets update NAME_OR_ID --name "new-dataset-name" --space SPACE
```

### Flags

| Flag | Type | Required | Description |
|------|------|----------|-------------|
| `NAME_OR_ID` | string | yes | Dataset name or ID (positional) |
| `--name` | string | yes | New dataset name |
| `--space` | string | no | Space name or ID (required if using dataset name instead of ID) |

## Annotate Examples: `ax datasets annotate-examples`

Write annotations onto dataset examples in bulk from a file. Upsert semantics — existing annotations with the same key are updated, new ones are created. Up to 1000 annotations per request.

```bash
ax datasets annotate-examples NAME_OR_ID --file annotations.json
ax datasets annotate-examples NAME_OR_ID --file annotations.csv --space SPACE
```

### Flags

| Flag | Type | Required | Description |
|------|------|----------|-------------|
| `NAME_OR_ID` | string | yes | Dataset name or ID (positional) |
| `--file, -f` | path | yes | Annotation file: JSON, JSONL, CSV, or Parquet (use `-` for stdin) |
| `--space` | string | no | Space name or ID (required if using dataset name instead of ID) |

## 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):

```bash
# 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

```bash
# 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.csv
```

### Download 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

```bash
# 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_ID
```

### Iterate 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

```bash
# 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](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](references/ax-profiles.md). |
| `No profile found` | No profile is configured. See [references/ax-profiles.md](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](references/ax-profiles.md) § Save Credentials for Future Use.