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import random
import uuid
from random import randint
from typing import cast, List, Any, Dict
import pytest
import hypothesis.strategies as st
from hypothesis import given, settings
from chromadb.api import ServerAPI
from chromadb.api.types import Embeddings, Metadatas
import chromadb.test.property.strategies as strategies
import chromadb.test.property.invariants as invariants
from chromadb.utils.batch_utils import create_batches
collection_st = st.shared(strategies.collections(with_hnsw_params=True), key="coll")
@given(collection=collection_st, record_set=strategies.recordsets(collection_st))
@settings(deadline=None)
def test_add(
api: ServerAPI,
collection: strategies.Collection,
record_set: strategies.RecordSet,
) -> None:
api.reset()
# TODO: Generative embedding functions
coll = api.create_collection(
name=collection.name,
metadata=collection.metadata, # type: ignore
embedding_function=collection.embedding_function,
)
normalized_record_set = invariants.wrap_all(record_set)
if not invariants.is_metadata_valid(normalized_record_set):
with pytest.raises(Exception):
coll.add(**normalized_record_set)
return
coll.add(**record_set)
invariants.count(coll, cast(strategies.RecordSet, normalized_record_set))
n_results = max(1, (len(normalized_record_set["ids"]) // 10))
invariants.ann_accuracy(
coll,
cast(strategies.RecordSet, normalized_record_set),
n_results=n_results,
embedding_function=collection.embedding_function,
)
def create_large_recordset(
min_size: int = 45000,
max_size: int = 50000,
) -> strategies.RecordSet:
size = randint(min_size, max_size)
ids = [str(uuid.uuid4()) for _ in range(size)]
metadatas = [{"some_key": f"{i}"} for i in range(size)]
documents = [f"Document {i}" for i in range(size)]
embeddings = [[1, 2, 3] for _ in range(size)]
record_set: Dict[str, List[Any]] = {
"ids": ids,
"embeddings": cast(Embeddings, embeddings),
"metadatas": metadatas,
"documents": documents,
}
return cast(strategies.RecordSet, record_set)
@given(collection=collection_st)
@settings(deadline=None, max_examples=1)
def test_add_large(api: ServerAPI, collection: strategies.Collection) -> None:
api.reset()
record_set = create_large_recordset(
min_size=api.max_batch_size,
max_size=api.max_batch_size + int(api.max_batch_size * random.random()),
)
coll = api.create_collection(
name=collection.name,
metadata=collection.metadata, # type: ignore
embedding_function=collection.embedding_function,
)
normalized_record_set = invariants.wrap_all(record_set)
if not invariants.is_metadata_valid(normalized_record_set):
with pytest.raises(Exception):
coll.add(**normalized_record_set)
return
for batch in create_batches(
api=api,
ids=cast(List[str], record_set["ids"]),
embeddings=cast(Embeddings, record_set["embeddings"]),
metadatas=cast(Metadatas, record_set["metadatas"]),
documents=cast(List[str], record_set["documents"]),
):
coll.add(*batch)
invariants.count(coll, cast(strategies.RecordSet, normalized_record_set))
@given(collection=collection_st)
@settings(deadline=None, max_examples=1)
def test_add_large_exceeding(api: ServerAPI, collection: strategies.Collection) -> None:
api.reset()
record_set = create_large_recordset(
min_size=api.max_batch_size,
max_size=api.max_batch_size + int(api.max_batch_size * random.random()),
)
coll = api.create_collection(
name=collection.name,
metadata=collection.metadata, # type: ignore
embedding_function=collection.embedding_function,
)
normalized_record_set = invariants.wrap_all(record_set)
if not invariants.is_metadata_valid(normalized_record_set):
with pytest.raises(Exception):
coll.add(**normalized_record_set)
return
with pytest.raises(Exception) as e:
coll.add(**record_set)
assert "exceeds maximum batch size" in str(e.value)
# TODO: This test fails right now because the ids are not sorted by the input order
@pytest.mark.xfail(
reason="This is expected to fail right now. We should change the API to sort the \
ids by input order."
)
def test_out_of_order_ids(api: ServerAPI) -> None:
api.reset()
ooo_ids = [
"40",
"05",
"8",
"6",
"10",
"01",
"00",
"3",
"04",
"20",
"02",
"9",
"30",
"11",
"13",
"2",
"0",
"7",
"06",
"5",
"50",
"12",
"03",
"4",
"1",
]
coll = api.create_collection(
"test", embedding_function=lambda input: [[1, 2, 3] for _ in input] # type: ignore
)
embeddings: Embeddings = [[1, 2, 3] for _ in ooo_ids]
coll.add(ids=ooo_ids, embeddings=embeddings)
get_ids = coll.get(ids=ooo_ids)["ids"]
assert get_ids == ooo_ids
def test_add_partial(api: ServerAPI) -> None:
"""Tests adding a record set with some of the fields set to None."""
api.reset()
coll = api.create_collection("test")
# TODO: We need to clean up the api types to support this typing
coll.add(
ids=["1", "2", "3"],
embeddings=[[1, 2, 3], [1, 2, 3], [1, 2, 3]], # type: ignore
metadatas=[{"a": 1}, None, {"a": 3}], # type: ignore
documents=["a", "b", None], # type: ignore
)
results = coll.get()
assert results["ids"] == ["1", "2", "3"]
assert results["metadatas"] == [{"a": 1}, None, {"a": 3}]
assert results["documents"] == ["a", "b", None]
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