search_logged_models
Search for logged models across one or more experiments using SQL-like filters, dataset conditions, and sorting to find specific models.
Instructions
Search for logged models across one or more experiments. Results can be large — use wise limits.
Args: experiment_ids: List of experiment IDs to search in (at least one required). filter_string: SQL-like filter, e.g. 'metrics.accuracy > 0.9' or "tags.release = 'v1.0'". Multiple conditions use AND only (OR not supported). max_results: Maximum number of models to return (default 5). datasets: Filter by datasets the model was evaluated on. Each dict must include 'name' (str) and 'digest' (str), e.g. [{'name': 'val', 'digest': 'abc123'}]. order_by: List of sort clauses, each a dict with 'field_name' (str) and 'ascending' (bool), e.g. [{'field_name': 'metrics.accuracy', 'ascending': False}].
Examples: search_logged_models(["1"], filter_string="metrics.accuracy > 0.9") search_logged_models(["1", "2"], order_by=[{"field_name": "metrics.f1", "ascending": False}])
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| experiment_ids | Yes | ||
| filter_string | No | ||
| max_results | No | ||
| datasets | No | ||
| order_by | No |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |