text: if you choose to launch Qdrant locally with a Docker container, or select a Kubernetes deployment with the official Helm chart, the way you're going to connect to such an instance will be identical. You'll need to provide a URL pointing to the service.url = "<---qdrant url here --->"qdrant = Qdrant.from_documents(    docs,    embeddings,    url,    prefer_grpc=True,    collection_name="my_documents",)Qdrant Cloudâ€‹If you prefer not to keep yourself busy with managing the infrastructure, you can choose to set up a fully-managed Qdrant cluster on Qdrant Cloud. There is a free forever 1GB cluster included for trying out. The main difference with using a managed version of Qdrant is that you'll need to provide an API key to secure your deployment from being accessed publicly.url = "<---qdrant cloud cluster url here --->"api_key = "<---api key here--->"qdrant = Qdrant.from_documents(    docs,    embeddings,    url,    prefer_grpc=True,    api_key=api_key,    collection_name="my_documents",)Recreating the collectionâ€‹Both Qdrant.from_texts and Qdrant.from_documents methods are great to start using Qdrant with Langchain. In the previous versions the collection was recreated every time you called any of them. That behaviour has changed. Currently, the collection is going to be reused if it already exists. Setting force_recreate to True allows to remove the old collection and start from scratch.url = "<---qdrant url here --->"qdrant = Qdrant.from_documents(    docs,    embeddings,    url,    prefer_grpc=True,