UI Drag & Drop
Drag & Drop a file through the Arize UI
Arize supports CSV, Parquet, and Avro. The required model schema parameters vary based on the specific model type selected. Learn more about model types here.
embeddings_features
are available for Parquet and Avro files.Uploading a local file is as simple as dropping a file into the upload container and can be broken down into a few easy steps.
- Go to the 'Upload Data' page from the left-side navigation and click on Local Files

Select "Local Files" from Upload Data Page
- You can get started by choosing the model type and downloading a sample file.
- Upload a file from your desktop by either:
- Dragging the file into the upload container
- Clicking 'Select File'

Drag file or click "Select File"

Fill out model schema
- Validate your file; errors will be displayed on this page

Validate file
- 'Start Job' to create a file import job for your local file
- You’ll be taken to the Job Status tab to see your local file uploads

Successful local file import
- Go to Job Status Tab to see your local file uploads

Job Status of All Local File imports
Model schema parameters are a way of organizing model inference data to ingest to Arize. When configuring your schema, be sure to match your file column headers with the model schema. Use a form or a simple JSON-based schema to specify the column mapping.
prediction_id | prediction_ts | user_id | feature/metropolitan_area | industry | prediction_score | actual_score | prediction_label | actual_label | tag/zone |
---|---|---|---|---|---|---|---|---|---|
1fcd50f4689 | 1637538845 | 82256 | 1PA | engineering | 0.07773696 | 0 | No Claims | No Claims | us-east-1 |
{
"prediction_id": "prediction_id",
"timestamp": "prediction_ts",
"features": "feature/", #with explicit features (must pick explicit or implicit)
"prediction_score": "prediction_score",
"prediction_label": "prediction_label",
"actual_score": "actual_score",
"actual_label": "actual_label",
"tags": "tag/",
"shap_values": "shap/",
"exclude": ["user_id"]
}
Property | Description | Required |
---|---|---|
prediction_ID | The unique identifier of a specific prediction | Required |
timestamp | The timestamp of the prediction in seconds or an RFC3339 timestamp | Optional, defaults to current timestamp at file ingestion time |
prediction_label | Column name for the prediction value | Required |
prediction_score | Column name for the predicted score | |
actual_label | Column name for the actual or ground truth value | Optional for production records |
actual_score | Column name for the ground truth score | |
prediction_group_id | Column name for ranking groups or lists in ranking models | |
rank | Column name for rank of each element on the its group or list | |
relevance_label | Column name for ranking actual or gound truth value | |
relevance_score | Column name for ranking ground truth score | |
features | A string prefix to describe a column feature/ . Features must be sent in the same file as predictions | Arize automatically infers columns as features. Choose between feature prefixing OR inferred features. |
tags | A string prefix to describe a column tag/ . Tags must be sent in the same file as predictions and features | Optional |
shap_values | A string prefix to describe a column shap/ . SHAP must be sent in the same file as predictions or with a matching prediction_id | Optional |
version | A column to specify model version. version/ assigns a version to the corresponding data withina column, or configure your version witin the UI | Optional, defaults to 'no_version' |
batch_id | Distinguish different batches of data under the same model_id and model_version. Must be specified as a constant during job setup or in the schema | Optional for validation records only |
exclude | A list of columns to exclude if the features property is not included in the ingestion schema | Optional |
embedding_features | A list of embedding columns, required vector column, optional raw data column, and optional link to data column. Learn more here | Optional |
We currently support uploading one file at a time, and a maximum file size of 300 mb.
Last modified 25d ago