Update docs of DeepsetCloudDocumentStore (#2460)

* Update docs of DeepsetCloudDocumentStore

* Update Documentation & Code Style

* Update docstring

Co-authored-by: tstadel <60758086+tstadel@users.noreply.github.com>

* Update Documentation & Code Style

* move DEFAULT_API_ENDPOINT

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: tstadel <60758086+tstadel@users.noreply.github.com>

docs/_src/api/api/document_store.md

@@ -3994,8 +3994,10 @@ See https://haystack.deepset.ai/components/document-store for more information.
 
 - `api_key`: Secret value of the API key.
 If not specified, will be read from DEEPSET_CLOUD_API_KEY environment variable.
-- `workspace`: workspace in Deepset Cloud
-- `index`: index to access within the Deepset Cloud workspace
+See docs on how to generate an API key for your workspace: https://docs.cloud.deepset.ai/docs/connect-deepset-cloud-to-your-application
+- `workspace`: workspace name in Deepset Cloud
+- `index`: name of the index to access within the Deepset Cloud workspace. This equals typically the name of your pipeline.
+You can run Pipeline.list_pipelines_on_deepset_cloud() to see all available ones.
 - `duplicate_documents`: Handle duplicates document based on parameter options.
 Parameter options : ( 'skip','overwrite','fail')
 skip: Ignore the duplicates documents
@@ -4004,8 +4006,9 @@ fail: an error is raised if the document ID of the document being added already
 exists.
 - `api_endpoint`: The URL of the Deepset Cloud API.
 If not specified, will be read from DEEPSET_CLOUD_API_ENDPOINT environment variable.
+If DEEPSET_CLOUD_API_ENDPOINT environment variable is not specified either, defaults to "https://api.cloud.deepset.ai/api/v1".
 - `similarity`: The similarity function used to compare document vectors. 'dot_product' is the default since it is
-more performant with DPR embeddings. 'cosine' is recommended if you are using a Sentence BERT model.
+more performant with DPR embeddings. 'cosine' is recommended if you are using a Sentence Transformer model.
 - `label_index`: index for the evaluation set interface
 - `return_embedding`: To return document embedding.
 

haystack/document_stores/deepsetcloud.py

@@ -9,8 +9,6 @@
 from haystack.utils import DeepsetCloud
 
 
-DEFAULT_API_ENDPOINT = f"DC_API_PLACEHOLDER/v1"  # TODO
-
 logger = logging.getLogger(__name__)
 
 
@@ -35,8 +33,10 @@ def __init__(
 
         :param api_key: Secret value of the API key.
                         If not specified, will be read from DEEPSET_CLOUD_API_KEY environment variable.
-        :param workspace: workspace in Deepset Cloud
-        :param index: index to access within the Deepset Cloud workspace
+                        See docs on how to generate an API key for your workspace: https://docs.cloud.deepset.ai/docs/connect-deepset-cloud-to-your-application
+        :param workspace: workspace name in Deepset Cloud
+        :param index: name of the index to access within the Deepset Cloud workspace. This equals typically the name of your pipeline.
+                      You can run Pipeline.list_pipelines_on_deepset_cloud() to see all available ones.
         :param duplicate_documents: Handle duplicates document based on parameter options.
                                     Parameter options : ( 'skip','overwrite','fail')
                                     skip: Ignore the duplicates documents
@@ -45,8 +45,9 @@ def __init__(
                                     exists.
         :param api_endpoint: The URL of the Deepset Cloud API.
                              If not specified, will be read from DEEPSET_CLOUD_API_ENDPOINT environment variable.
+                             If DEEPSET_CLOUD_API_ENDPOINT environment variable is not specified either, defaults to "https://api.cloud.deepset.ai/api/v1".
         :param similarity: The similarity function used to compare document vectors. 'dot_product' is the default since it is
-                           more performant with DPR embeddings. 'cosine' is recommended if you are using a Sentence BERT model.
+                           more performant with DPR embeddings. 'cosine' is recommended if you are using a Sentence Transformer model.
         :param label_index: index for the evaluation set interface
 
         :param return_embedding: To return document embedding.

haystack/utils/deepsetcloud.py

@@ -16,7 +16,7 @@
 from haystack.schema import Label, Document, Answer
 
 
-DEFAULT_API_ENDPOINT = f"DC_API_PLACEHOLDER/v1"  # TODO
+DEFAULT_API_ENDPOINT = "https://api.cloud.deepset.ai/api/v1"
 
 
 class PipelineStatus(Enum):