adding mongodb vector_io module

updated mongodb.py from print to log

add documentation for mongodb vector search module

changed insert to update mongodb

bug fix mongodb json object conversion error
This commit is contained in:
Ashwin Gangadhar 2025-02-19 21:48:05 +05:30
parent d224ae0c8e
commit 80d9d50954
8 changed files with 503 additions and 65 deletions

View file

@ -0,0 +1,116 @@
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
import pytest
from ..conftest import (
get_provider_fixture_overrides,
get_provider_fixture_overrides_from_test_config,
get_test_config_for_api,
)
from ..inference.fixtures import INFERENCE_FIXTURES
from .fixtures import VECTOR_IO_FIXTURES
DEFAULT_PROVIDER_COMBINATIONS = [
pytest.param(
{
"inference": "sentence_transformers",
"vector_io": "faiss",
},
id="sentence_transformers",
marks=pytest.mark.sentence_transformers,
),
pytest.param(
{
"inference": "ollama",
"vector_io": "pgvector",
},
id="pgvector",
marks=pytest.mark.pgvector,
),
pytest.param(
{
"inference": "ollama",
"vector_io": "faiss",
},
id="ollama",
marks=pytest.mark.ollama,
),
pytest.param(
{
"inference": "ollama",
"vector_io": "sqlite_vec",
},
id="sqlite_vec",
marks=pytest.mark.ollama,
),
pytest.param(
{
"inference": "sentence_transformers",
"vector_io": "chroma",
},
id="chroma",
marks=pytest.mark.chroma,
),
pytest.param(
{
"inference": "ollama",
"vector_io": "qdrant",
},
id="qdrant",
marks=pytest.mark.qdrant,
),
pytest.param(
{
"inference": "fireworks",
"vector_io": "weaviate",
},
id="weaviate",
marks=pytest.mark.weaviate,
),
pytest.param(
{
"inference": "bedrock",
"vector_io": "mongodb",
},
id="mongodb",
marks=pytest.mark.mongodb,
),
]
def pytest_configure(config):
for fixture_name in VECTOR_IO_FIXTURES:
config.addinivalue_line(
"markers",
f"{fixture_name}: marks tests as {fixture_name} specific",
)
def pytest_generate_tests(metafunc):
test_config = get_test_config_for_api(metafunc.config, "vector_io")
if "embedding_model" in metafunc.fixturenames:
model = getattr(test_config, "embedding_model", None)
# Fall back to the default if not specified by the config file
model = model or metafunc.config.getoption("--embedding-model")
if model:
params = [pytest.param(model, id="")]
else:
params = [pytest.param("all-minilm:l6-v2", id="")]
metafunc.parametrize("embedding_model", params, indirect=True)
if "vector_io_stack" in metafunc.fixturenames:
available_fixtures = {
"inference": INFERENCE_FIXTURES,
"vector_io": VECTOR_IO_FIXTURES,
}
combinations = (
get_provider_fixture_overrides_from_test_config(metafunc.config, "vector_io", DEFAULT_PROVIDER_COMBINATIONS)
or get_provider_fixture_overrides(metafunc.config, available_fixtures)
or DEFAULT_PROVIDER_COMBINATIONS
)
metafunc.parametrize("vector_io_stack", combinations, indirect=True)