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"""Router for the dataset database."""
from typing import Optional, Sequence, Union, cast
from urllib.parse import unquote
from fastapi import APIRouter, Response
from fastapi.responses import ORJSONResponse
from pydantic import BaseModel, validator
from .config import data_path
from .data.dataset import BinaryOp
from .data.dataset import Column as DBColumn
from .data.dataset import DatasetManifest, FeatureListValue, FeatureValue
from .data.dataset import Filter as PyFilter
from .data.dataset import (
GroupsSortBy,
ListOp,
Search,
SelectGroupsResult,
SelectRowsSchemaResult,
SortOrder,
StatsResult,
UnaryOp,
)
from .data.dataset_duckdb import DatasetDuckDB
from .db_manager import get_dataset, remove_dataset_from_cache, set_default_dataset_cls
from .router_utils import RouteErrorHandler
from .schema import Bin, Path, normalize_path
from .signals.concept_labels import ConceptLabelsSignal
from .signals.concept_scorer import ConceptScoreSignal
from .signals.default_signals import register_default_signals
from .signals.semantic_similarity import SemanticSimilaritySignal
from .signals.signal import (
Signal,
TextEmbeddingModelSignal,
TextEmbeddingSignal,
TextSignal,
resolve_signal,
)
from .signals.substring_search import SubstringSignal
from .tasks import TaskId, task_manager
from .utils import DatasetInfo, list_datasets
router = APIRouter(route_class=RouteErrorHandler)
register_default_signals()
set_default_dataset_cls(DatasetDuckDB)
@router.get('/', response_model_exclude_none=True)
def get_datasets() -> list[DatasetInfo]:
"""List the datasets."""
return list_datasets(data_path())
class WebManifest(BaseModel):
"""Information about a dataset."""
dataset_manifest: DatasetManifest
@router.get('/{namespace}/{dataset_name}')
def get_manifest(namespace: str, dataset_name: str) -> WebManifest:
"""Get the web manifest for the dataset."""
dataset = get_dataset(namespace, dataset_name)
res = WebManifest(dataset_manifest=dataset.manifest())
# Avoids the error that Signal abstract class is not serializable.
return cast(WebManifest, ORJSONResponse(res.dict(exclude_none=True)))
class ComputeSignalOptions(BaseModel):
"""The request for the compute signal endpoint."""
signal: Signal
# The leaf path to compute the signal on.
leaf_path: Path
@validator('signal', pre=True)
def parse_signal(cls, signal: dict) -> Signal:
"""Parse a signal to its specific subclass instance."""
return resolve_signal(signal)
@router.delete('/{namespace}/{dataset_name}')
def delete_dataset(namespace: str, dataset_name: str) -> None:
"""Delete the dataset."""
dataset = get_dataset(namespace, dataset_name)
dataset.delete()
remove_dataset_from_cache(namespace, dataset_name)
class ComputeSignalResponse(BaseModel):
"""Response of the compute signal column endpoint."""
task_id: TaskId
@router.post('/{namespace}/{dataset_name}/compute_signal')
def compute_signal(namespace: str, dataset_name: str,
options: ComputeSignalOptions) -> ComputeSignalResponse:
"""Compute a signal for a dataset."""
def _task_compute_signal(namespace: str, dataset_name: str, options_dict: dict,
task_id: TaskId) -> None:
# NOTE: We manually call .dict() to avoid the dask serializer, which doesn't call the underlying
# pydantic serializer.
options = ComputeSignalOptions(**options_dict)
dataset = get_dataset(namespace, dataset_name)
dataset.compute_signal(options.signal, options.leaf_path, task_step_id=(task_id, 0))
path_str = '.'.join(map(str, options.leaf_path))
task_id = task_manager().task_id(
name=f'[{namespace}/{dataset_name}] Compute signal "{options.signal.name}" on "{path_str}"',
description=f'Config: {options.signal}')
task_manager().execute(task_id, _task_compute_signal, namespace, dataset_name, options.dict(),
task_id)
return ComputeSignalResponse(task_id=task_id)
class DeleteSignalOptions(BaseModel):
"""The request for the delete signal endpoint."""
# The signal path holding the data from the signal.
signal_path: Path
class DeleteSignalResponse(BaseModel):
"""Response of the compute signal column endpoint."""
completed: bool
@router.delete('/{namespace}/{dataset_name}/delete_signal')
def delete_signal(namespace: str, dataset_name: str,
options: DeleteSignalOptions) -> DeleteSignalResponse:
"""Delete a signal from a dataset."""
dataset = get_dataset(namespace, dataset_name)
dataset.delete_signal(options.signal_path)
return DeleteSignalResponse(completed=True)
class GetStatsOptions(BaseModel):
"""The request for the get stats endpoint."""
leaf_path: Path
@router.post('/{namespace}/{dataset_name}/stats')
def get_stats(namespace: str, dataset_name: str, options: GetStatsOptions) -> StatsResult:
"""Get the stats for the dataset."""
dataset = get_dataset(namespace, dataset_name)
return dataset.stats(options.leaf_path)
class BinaryFilter(BaseModel):
"""A filter on a column."""
path: Path
op: BinaryOp
value: FeatureValue
class UnaryFilter(BaseModel):
"""A filter on a column."""
path: Path
op: UnaryOp
value: None = None
class ListFilter(BaseModel):
"""A filter on a column."""
path: Path
op: ListOp
value: FeatureListValue
Filter = Union[BinaryFilter, UnaryFilter, ListFilter]
AllSignalTypes = Union[ConceptScoreSignal, ConceptLabelsSignal, SubstringSignal,
SemanticSimilaritySignal, TextEmbeddingModelSignal, TextEmbeddingSignal,
TextSignal, Signal]
# We override the `Column` class so we can add explicitly all signal types for better OpenAPI spec.
class Column(DBColumn):
"""A column in the dataset."""
signal_udf: Optional[AllSignalTypes] = None
class SelectRowsOptions(BaseModel):
"""The request for the select rows endpoint."""
columns: Optional[Sequence[Union[Path, Column]]]
searches: Optional[Sequence[Search]]
filters: Optional[Sequence[Filter]]
sort_by: Optional[Sequence[Path]]
sort_order: Optional[SortOrder] = SortOrder.DESC
limit: Optional[int]
offset: Optional[int]
combine_columns: Optional[bool]
class SelectRowsSchemaOptions(BaseModel):
"""The request for the select rows schema endpoint."""
columns: Optional[Sequence[Union[Path, Column]]]
searches: Optional[Sequence[Search]]
sort_by: Optional[Sequence[Path]]
sort_order: Optional[SortOrder] = SortOrder.DESC
combine_columns: Optional[bool]
class SelectRowsResponse(BaseModel):
"""The response for the select rows endpoint."""
rows: list[dict]
total_num_rows: int
@router.get('/{namespace}/{dataset_name}/select_rows_download', response_model=None)
def select_rows_download(namespace: str, dataset_name: str, url_safe_options: str) -> list[dict]:
"""Select rows from the dataset database and downloads them."""
options = SelectRowsOptions.parse_raw(unquote(url_safe_options))
return select_rows(namespace, dataset_name, options).rows
@router.post('/{namespace}/{dataset_name}/select_rows', response_model_exclude_none=True)
def select_rows(namespace: str, dataset_name: str,
options: SelectRowsOptions) -> SelectRowsResponse:
"""Select rows from the dataset database."""
dataset = get_dataset(namespace, dataset_name)
sanitized_filters = [
PyFilter(path=normalize_path(f.path), op=f.op, value=f.value) for f in (options.filters or [])
]
res = dataset.select_rows(
columns=options.columns,
searches=options.searches or [],
filters=sanitized_filters,
sort_by=options.sort_by,
sort_order=options.sort_order,
limit=options.limit,
offset=options.offset,
combine_columns=options.combine_columns or False)
return SelectRowsResponse(rows=list(res), total_num_rows=res.total_num_rows)
@router.post('/{namespace}/{dataset_name}/select_rows_schema', response_model_exclude_none=True)
def select_rows_schema(namespace: str, dataset_name: str,
options: SelectRowsSchemaOptions) -> SelectRowsSchemaResult:
"""Select rows from the dataset database."""
dataset = get_dataset(namespace, dataset_name)
return dataset.select_rows_schema(
columns=options.columns,
searches=options.searches or [],
sort_by=options.sort_by,
sort_order=options.sort_order,
combine_columns=options.combine_columns or False)
class SelectGroupsOptions(BaseModel):
"""The request for the select groups endpoint."""
leaf_path: Path
filters: Optional[Sequence[Filter]]
sort_by: Optional[GroupsSortBy] = GroupsSortBy.COUNT
sort_order: Optional[SortOrder] = SortOrder.DESC
limit: Optional[int] = 100
bins: Optional[list[Bin]]
@router.post('/{namespace}/{dataset_name}/select_groups')
def select_groups(namespace: str, dataset_name: str,
options: SelectGroupsOptions) -> SelectGroupsResult:
"""Select groups from the dataset database."""
dataset = get_dataset(namespace, dataset_name)
sanitized_filters = [
PyFilter(path=normalize_path(f.path), op=f.op, value=f.value) for f in (options.filters or [])
]
return dataset.select_groups(options.leaf_path, sanitized_filters, options.sort_by,
options.sort_order, options.limit, options.bins)
@router.get('/{namespace}/{dataset_name}/media')
def get_media(namespace: str, dataset_name: str, item_id: str, leaf_path: str) -> Response:
"""Get the media for the dataset."""
dataset = get_dataset(namespace, dataset_name)
path = tuple(leaf_path.split('.'))
result = dataset.media(item_id, path)
# Return the response via HTTP.
return Response(content=result.data)
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