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Add GPT4Vision Image loader (#1089)

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Co-authored-by: Deshraj Yadav <deshrajdry@gmail.com>
This commit is contained in:
Sidharth Mohanty
2024-01-02 03:57:23 +05:30
committed by GitHub
parent 367d6b70e2
commit c62663f2e4
29 changed files with 291 additions and 714 deletions
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65
tests/vectordb/test_zilliz_db.py
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@@ -108,65 +108,7 @@ class TestZillizDBCollection:
@patch("embedchain.vectordb.zilliz.MilvusClient", autospec=True)
@patch("embedchain.vectordb.zilliz.connections", autospec=True)
def test_query_with_skip_embedding(self, mock_connect, mock_client, mock_config):
"""
Test if the `ZillizVectorDB` instance is takes in the query with skip_embeddings.
"""
# Create an instance of ZillizVectorDB with mock config
zilliz_db = ZillizVectorDB(config=mock_config)
# Add a 'collection' attribute to the ZillizVectorDB instance for testing
zilliz_db.collection = Mock(is_empty=False) # Mock the 'collection' object
assert zilliz_db.client == mock_client()
# Mock the MilvusClient search method
with patch.object(zilliz_db.client, "search") as mock_search:
# Mock the search result
mock_search.return_value = [
[
{
"distance": 0.5,
"entity": {"text": "result_doc", "url": "url_1", "doc_id": "doc_id_1", "embeddings": [1, 2, 3]},
}
]
]
# Call the query method with skip_embedding=True
query_result = zilliz_db.query(input_query=["query_text"], n_results=1, where={}, skip_embedding=True)
# Assert that MilvusClient.search was called with the correct parameters
mock_search.assert_called_with(
collection_name=mock_config.collection_name,
data=["query_text"],
limit=1,
output_fields=["*"],
)
# Assert that the query result matches the expected result
assert query_result == ["result_doc"]
query_result_with_citations = zilliz_db.query(
input_query=["query_text"], n_results=1, where={}, skip_embedding=True, citations=True
)
mock_search.assert_called_with(
collection_name=mock_config.collection_name,
data=["query_text"],
limit=1,
output_fields=["*"],
)
assert query_result_with_citations == [
("result_doc", {"text": "result_doc", "url": "url_1", "doc_id": "doc_id_1", "score": 0.5})
]
@patch("embedchain.vectordb.zilliz.MilvusClient", autospec=True)
@patch("embedchain.vectordb.zilliz.connections", autospec=True)
def test_query_without_skip_embedding(self, mock_connect, mock_client, mock_embedder, mock_config):
"""
Test if the `ZillizVectorDB` instance is takes in the query without skip_embeddings.
"""
def test_query(self, mock_connect, mock_client, mock_embedder, mock_config):
# Create an instance of ZillizVectorDB with mock config
zilliz_db = ZillizVectorDB(config=mock_config)
@@ -193,8 +135,7 @@ class TestZillizDBCollection:
]
]
# Call the query method with skip_embedding=False
query_result = zilliz_db.query(input_query=["query_text"], n_results=1, where={}, skip_embedding=False)
query_result = zilliz_db.query(input_query=["query_text"], n_results=1, where={})
# Assert that MilvusClient.search was called with the correct parameters
mock_search.assert_called_with(
@@ -208,7 +149,7 @@ class TestZillizDBCollection:
assert query_result == ["result_doc"]
query_result_with_citations = zilliz_db.query(
input_query=["query_text"], n_results=1, where={}, skip_embedding=False, citations=True
input_query=["query_text"], n_results=1, where={}, citations=True
)
mock_search.assert_called_with(