tessl install tessl/pypi-deeplake@4.3.0Database for AI powered by a storage format optimized for deep-learning applications.
Agent Success
Agent success rate when using this tile
75%
Improvement
Agent success rate improvement when using this tile compared to baseline
1.6x
Baseline
Agent success rate without this tile
47%
{
"context": "This criteria evaluates how effectively an engineer uses the deeplake package's dataset management APIs to implement basic dataset lifecycle operations including creation, opening, existence checking, and deletion.",
"type": "weighted_checklist",
"checklist": [
{
"name": "Uses deeplake.create()",
"description": "Correctly uses the deeplake.create() function to create new datasets, passing the path parameter appropriately.",
"max_score": 25
},
{
"name": "Uses deeplake.open()",
"description": "Correctly uses the deeplake.open() function to open existing datasets for read-write access.",
"max_score": 25
},
{
"name": "Uses deeplake.exists()",
"description": "Correctly uses the deeplake.exists() function to check if a dataset exists at a given path, returning boolean values.",
"max_score": 25
},
{
"name": "Uses deeplake.delete()",
"description": "Correctly uses the deeplake.delete() function to permanently remove datasets from storage.",
"max_score": 25
}
]
}