⚡️ Speed up method AstraDBVectorStoreComponent.create_collection_api by 1,648% in PR #6236 (LFOSS-492)

[codeflash-ai]

⚡️ This pull request contains optimizations for PR #6236

If you approve this dependent PR, these changes will be merged into the original PR branch LFOSS-492.

This PR will be automatically closed if the original PR is merged.

---

📄 1,648% (16.48x) speedup for AstraDBVectorStoreComponent.create_collection_api in src/backend/base/langflow/components/vectorstores/astradb.py

⏱️ Runtime : 492 microseconds → 28.1 microseconds (best of 10 runs)

📝 Explanation and details

Certainly! Below is the optimized version of the AstraDBVectorStoreComponent class method. The following improvements have been implemented for faster execution.

Here's the optimized code.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 12 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	undefined

🌀 Generated Regression Tests Details

from unittest.mock import MagicMock, patch

# imports
import pytest  # used for our unit tests
# function to test
from astrapy import DataAPIClient
from langchain_astradb import CollectionVectorServiceOptions
from langflow.base.vectorstores.model import LCVectorStoreComponent
from langflow.components.vectorstores.astradb import \
    AstraDBVectorStoreComponent


# unit tests
class TestCreateCollectionAPI:
    @pytest.fixture
    def mock_database(self):
        with patch('astrapy.DataAPIClient.get_database') as mock_get_database:
            mock_db = MagicMock()
            mock_get_database.return_value = mock_db
            yield mock_db

    def test_basic_functionality(self, mock_database):
        # Test creating a collection with valid parameters
        mock_database.create_collection.return_value = "collection_created"
        codeflash_output = AstraDBVectorStoreComponent.create_collection_api(
            token="valid_token",
            api_endpoint="http://api.example.com",
            new_collection_name="test_collection",
            dimension=128
        )
        mock_database.create_collection.assert_called_once_with(
            name="test_collection",
            dimension=128,
            service=None
        )

    

from unittest.mock import MagicMock, patch

# imports
import pytest  # used for our unit tests
# function to test
from astrapy import DataAPIClient
from langchain_astradb import CollectionVectorServiceOptions
from langflow.base.vectorstores.model import LCVectorStoreComponent
from langflow.components.vectorstores.astradb import \
    AstraDBVectorStoreComponent

# unit tests

# Basic Functionality




def test_create_collection_api_empty_strings():
    token = ""
    api_endpoint = ""
    new_collection_name = ""

    with pytest.raises(ValueError):
        AstraDBVectorStoreComponent.create_collection_api(
            token=token,
            api_endpoint=api_endpoint,
            new_collection_name=new_collection_name
        )

def test_create_collection_api_invalid_types():
    token = 12345
    api_endpoint = ["http://valid.endpoint"]
    new_collection_name = {"name": "test_collection"}

    with pytest.raises(TypeError):
        AstraDBVectorStoreComponent.create_collection_api(
            token=token,
            api_endpoint=api_endpoint,
            new_collection_name=new_collection_name
        )

# Vectorization Options