Pinecone unary queries upgrade (#2657)

* update query and response process for unary query update

* added metadata_config parameter

* Update Documentation & Code Style

Co-authored-by: James Briggs <jamesbriggs@Jamess-MacBook-Pro-2.local>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

docs/_src/api/api/document_store.md

@@ -4651,7 +4651,7 @@ the vector embeddings and metadata (for filtering) are indexed in a Pinecone Ind
 #### PineconeDocumentStore.\_\_init\_\_
 
 ```python
-def __init__(api_key: str, environment: str = "us-west1-gcp", sql_url: str = "sqlite:///pinecone_document_store.db", pinecone_index: Optional[pinecone.Index] = None, embedding_dim: int = 768, return_embedding: bool = False, index: str = "document", similarity: str = "cosine", replicas: int = 1, shards: int = 1, embedding_field: str = "embedding", progress_bar: bool = True, duplicate_documents: str = "overwrite", recreate_index: bool = False)
+def __init__(api_key: str, environment: str = "us-west1-gcp", sql_url: str = "sqlite:///pinecone_document_store.db", pinecone_index: Optional[pinecone.Index] = None, embedding_dim: int = 768, return_embedding: bool = False, index: str = "document", similarity: str = "cosine", replicas: int = 1, shards: int = 1, embedding_field: str = "embedding", progress_bar: bool = True, duplicate_documents: str = "overwrite", recreate_index: bool = False, metadata_config: dict = {"indexed": []})
 ```
 
 **Arguments**:
@@ -4686,6 +4686,8 @@ Parameter options:
 created using the config you are using for initialization. Be aware that all data in the old index will be
 lost if you choose to recreate the index. Be aware that both the document_index and the label_index will
 be recreated.
+- `metadata_config`: Which metadata fields should be indexed. Should be in the format
+`{"indexed": ["metadata-field-1", "metadata-field-2", "metadata-field-n"]}`.
 
 <a id="pinecone.PineconeDocumentStore.write_documents"></a>
 

haystack/document_stores/pinecone.py

@@ -52,6 +52,7 @@ class PineconeDocumentStore(SQLDocumentStore):
         progress_bar: bool = True,
         duplicate_documents: str = "overwrite",
         recreate_index: bool = False,
+        metadata_config: dict = {"indexed": []},
     ):
         """
         :param api_key: Pinecone vector database API key ([https://app.pinecone.io](https://app.pinecone.io)).
@@ -85,6 +86,8 @@ class PineconeDocumentStore(SQLDocumentStore):
             created using the config you are using for initialization. Be aware that all data in the old index will be
             lost if you choose to recreate the index. Be aware that both the document_index and the label_index will
             be recreated.
+        :param metadata_config: Which metadata fields should be indexed. Should be in the format
+            `{"indexed": ["metadata-field-1", "metadata-field-2", "metadata-field-n"]}`.
         """
         # Connect to Pinecone server using python client binding
         pinecone.init(api_key=api_key, environment=environment)
@@ -113,6 +116,7 @@ class PineconeDocumentStore(SQLDocumentStore):
         # Pinecone index params
         self.replicas = replicas
         self.shards = shards
+        self.metadata_config = metadata_config
 
         # Initialize dictionary of index connections
         self.pinecone_indexes: Dict[str, pinecone.Index] = {}
@@ -134,6 +138,7 @@ class PineconeDocumentStore(SQLDocumentStore):
                 replicas=self.replicas,
                 shards=self.shards,
                 recreate_index=recreate_index,
+                metadata_config=self.metadata_config,
             )
 
     def _sanitize_index_name(self, index: str) -> str:
@@ -147,6 +152,7 @@ class PineconeDocumentStore(SQLDocumentStore):
         replicas: Optional[int] = 1,
         shards: Optional[int] = 1,
         recreate_index: bool = False,
+        metadata_config: dict = {},
     ):
         """
         Create a new index for storing documents in case an
@@ -166,7 +172,12 @@ class PineconeDocumentStore(SQLDocumentStore):
             # Search pinecone hosted indexes and create an index if it does not exist
             if index not in pinecone.list_indexes():
                 pinecone.create_index(
-                    name=index, dimension=embedding_dim, metric=metric_type, replicas=replicas, shards=shards
+                    name=index,
+                    dimension=embedding_dim,
+                    metric=metric_type,
+                    replicas=replicas,
+                    shards=shards,
+                    metadata_config=metadata_config,
                 )
             index_connection = pinecone.Index(index)
 
@@ -670,8 +681,8 @@ class PineconeDocumentStore(SQLDocumentStore):
                 f"Index named '{index}' does not exist. Try reinitializing PineconeDocumentStore() and running "
                 f"'update_embeddings()' to create and populate an index."
             )
+        query_emb = query_emb.astype(np.float32)
 
-        query_emb = query_emb.reshape(1, -1).astype(np.float32)
         if self.similarity == "cosine":
             self.normalize_embedding(query_emb)
 
@@ -679,7 +690,7 @@ class PineconeDocumentStore(SQLDocumentStore):
 
         score_matrix = []
         vector_id_matrix = []
-        for match in res["results"][0]["matches"]:
+        for match in res["matches"]:
             score_matrix.append(match["score"])
             vector_id_matrix.append(match["id"])
         documents = self.get_documents_by_id(vector_id_matrix, index=index, return_embedding=return_embedding)

haystack/json-schemas/haystack-pipeline-master.schema.json

@@ -1487,6 +1487,13 @@
               "title": "Recreate Index",
               "default": false,
               "type": "boolean"
+            },
+            "metadata_config": {
+              "title": "Metadata Config",
+              "default": {
+                "indexed": []
+              },
+              "type": "object"
             }
           },
           "required": [