51 lines
1.6 KiB
Python
51 lines
1.6 KiB
Python
from datetime import datetime
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from typing import List, Optional, Union
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from ..context import get_context
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from ..views import Trace
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def query_ground_truth(
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conjunctive_tags: Union[List[str], str] = [],
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*,
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since: Optional[datetime] = None,
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until: Optional[datetime] = None,
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return_max_count: Optional[int] = None
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) -> List[Trace]:
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"""Return training samples.
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Combines, filters, and returns datapoints that have been either added by
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`add_ground_truth` or were the result of a prediction after which their trace got
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a feedback through the RESP API-s `/traces/{trace_id}/feedback` endpoint
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(end-to-end feedback).
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Filtering can be used to only return points matching all given tags (or the single
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given tag) and by time of creation.
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Examples:
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>>> query_ground_truth()
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[...]
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Args:
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conjunctive_tags: Single tag or a list of tags which the returned traces have to
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match. The relationship between the tags is conjunctive (AND).
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since: Only return traces created after the given timestamp. `None` means no
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filtering.
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until: Only return traces created before the given timestamp. `None` means no
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filtering.
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return_max_count: Return at-most this many traces. (take, limit)
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"""
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tags = (
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conjunctive_tags if isinstance(conjunctive_tags, list) else [conjunctive_tags]
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)
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db = get_context().tracing_database
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items, length = db.query(
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conjunctive_tags=tags,
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since=since,
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until=until,
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take=return_max_count,
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has_feedback=True,
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)
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return items
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