Working with pipelines in different environments requires a document store that can be shared among them and is compatible with all retrievers. This is why we created the DeepsetCloudDocumentStore. It makes it possible to interact with documents stored in deepset Cloud without having to index your data again.
DeepsetCloudDocumentStore is designed to access data that's already stored in deepset Cloud. It is not intended for use in production-like scenarios.
In most cases, you use
DeepsetCloudDocumentStore within a pipeline. However, if you want to initialize it on its own, run:
import os os.environ["DEEPSET_CLOUD_API_KEY"] = "<your_api_key>" os.environ["DEEPSET_CLOUD_API_ENDPOINT"] = "https://api.cloud.deepset.ai/api/v1" from haystack.document_stores import DeepsetCloudDocumentStore document_store = DeepsetCloudDocumentStore(index=pipeline_name)
These are the arguments the
|String||The secret value of the API key. This is the value that you copy in step 4 of Generating an API Key.|
If you do not specify it, it is read from the
|String||Specifies the deepset Cloud workspace containing the pipeline, string. Optional. Set this value to |
|String||The name of the pipeline to access within the deepset Cloud workspace.|
In deepset Cloud, indexes share the name with their respective pipelines.
|String||Specifies how to handle duplicate documents.|
|String||Specifies the URL of the deepset Cloud API. The API endpoint is: |
If you don't specify it, it's read from the
|String||Specifies the similarity function used to compare document vectors.|
|String||Specifies the name of the evaluation set uploaded to deepset Cloud.|
In deepset Cloud, label indexes share the name with their corresponding evaluation sets.
|Boolean||True/False||Returns document embeddings.|
DeepsetCloudDocumentStore is read-only and cannot be used for creating new pipelines. To use this document store, the pipeline must already exist.
Updated about 2 months ago