PyPI 官网下载 | qdrant_client-0.3.8.tar.gz

# Python Qdrant client library Client library for the [Qdrant](https://github.com/qdrant/qdrant) vector search engine. Library contains type definitions for all Qdrant API and allows to make both Sync and Async requests. `Pydantic` is used for describing request models and `httpx` for handling http queries. Client allows calls for all [Qdrant API methods](https://qdrant.github.io/qdrant/redoc/index.html) directly. It also provides some additional helper methods for frequently required operations, e.g. initial collection uploading. ## Installation ``` pip install qdrant-client ``` ## Examples Instance a client ```python from qdrant_client import QdrantClient client = QdrantClient(host="localhost", port=6333) ``` Create a new collection ```python client.recreate_collection( collection_name="my_collection", vector_size=100 ) ``` Get info about created collection ```python my_collection_info = client.http.collections_api.get_collection("my_collection") print(my_collection_info.dict()) ``` Search for similar vectors ```python query_vector = np.random.rand(100) hits = client.search( collection_name="my_collection", query_vector=query_vector, query_filter=None, # Don't use any filters for now, search across all indexed points append_payload=True, # Also return a stored payload for found points top=5 # Return 5 closest points ) ``` Search for similar vectors with filtering condition ```python from qdrant_openapi_client.models.models import Filter, FieldCondition, Range hits = client.search( collection_name="my_collection", query_vector=query_vector, query_filter=Filter( must=[ # These conditions are required for search results FieldCondition( key='rand_number', # Condition based on values of `rand_number` field. range=Range( gte=0.5 # Select only those results where `rand_number` >= 0.5 ) ) ] ), append_payload=True, # Also return a stored payload for found points top=5 # Return 5 closest points ) ``` Check out [full example code](tests/test_qdrant_client.py)