diff --git a/README.md b/README.md index 35d4225e..98029aba 100644 --- a/README.md +++ b/README.md @@ -181,6 +181,7 @@ Insert vectors into a collection ```python import numpy as np + from qdrant_client.models import PointStruct vectors = np.random.rand(100, 100) @@ -204,9 +205,9 @@ Search for similar vectors ```python query_vector = np.random.rand(100) -hits = client.search( +hits = client.query_points( collection_name="my_collection", - query_vector=query_vector, + query=query_vector, limit=5 # Return 5 closest points ) ``` @@ -216,9 +217,9 @@ Search for similar vectors with filtering condition ```python from qdrant_client.models import Filter, FieldCondition, Range -hits = client.search( +hits = client.query_points( collection_name="my_collection", - query_vector=query_vector, + query=query_vector, query_filter=Filter( must=[ # These conditions are required for search results FieldCondition( @@ -253,10 +254,13 @@ Starting from version 1.6.1, all python client methods are available in async ve To use it, just import `AsyncQdrantClient` instead of `QdrantClient`: ```python -from qdrant_client import AsyncQdrantClient, models -import numpy as np import asyncio +import numpy as np + +from qdrant_client import AsyncQdrantClient, models + + async def main(): # Your async code using QdrantClient might be put here client = AsyncQdrantClient(url="http://localhost:6333") @@ -277,9 +281,9 @@ async def main(): ], ) - res = await client.search( + res = await client.query_points( collection_name="my_collection", - query_vector=np.random.rand(10).tolist(), # type: ignore + query=np.random.rand(10).tolist(), # type: ignore limit=10, ) @@ -296,5 +300,3 @@ More examples can be found [here](./tests/test_async_qdrant_client.py). This project uses git hooks to run code formatters. Install `pre-commit` with `pip3 install pre-commit` and set up hooks with `pre-commit install`. - -> pre-commit requires python>=3.8