adding custom from_dict

integrations/pgvector/README.md

@@ -20,11 +20,12 @@ pip install pgvector-haystack
 
 ## Testing
 
-Ensure you have PostgreSQL installed with the `pgvector` extension, for a quick setup using Docker:
+Ensure that you have a PostgreSQL running with the `pgvector` extension. For a quick setup using Docker, run:
 ```
 docker run -d -p 5432:5432 -e POSTGRES_USER=postgres -e POSTGRES_PASSWORD=postgres -e POSTGRES_DB=postgres ankane/pgvector
 ```
 
+then run the tests:
 
 ```console
 hatch run test

integrations/pgvector/src/haystack_integrations/components/retrievers/pgvector/embedding_retriever.py

@@ -68,9 +68,8 @@ def to_dict(self) -> Dict[str, Any]:
 
     @classmethod
     def from_dict(cls, data: Dict[str, Any]) -> "PgvectorEmbeddingRetriever":
-        data["init_parameters"]["document_store"] = default_from_dict(
-            PgvectorDocumentStore, data["init_parameters"]["document_store"]
-        )
+        doc_store_params = data["init_parameters"]["document_store"]
+        data["init_parameters"]["document_store"] = PgvectorDocumentStore.from_dict(doc_store_params)
         return default_from_dict(cls, data)
 
     @component.output_types(documents=List[Document])

integrations/pgvector/src/haystack_integrations/document_stores/pgvector/document_store.py

@@ -4,7 +4,7 @@
 import logging
 from typing import Any, Dict, List, Literal, Optional
 
-from haystack import default_to_dict
+from haystack import default_to_dict, default_from_dict
 from haystack.dataclasses.document import ByteStream, Document
 from haystack.document_stores.errors import DocumentStoreError, DuplicateDocumentError
 from haystack.document_stores.types import DuplicatePolicy
@@ -163,6 +163,13 @@ def to_dict(self) -> Dict[str, Any]:
             hnsw_ef_search=self.hnsw_ef_search,
         )
 
+    @classmethod
+    def from_dict(cls, init_parameters: Dict[str, Any]) -> "PgvectorDocumentStore":
+        conn_str_data = init_parameters['init_parameters']["connection_string"]
+        conn_str = Secret.from_dict(conn_str_data) if conn_str_data is not None else None
+        init_parameters['init_parameters']["connection_string"] = conn_str
+        return default_from_dict(cls, init_parameters)
+
     def _execute_sql(
         self, sql_query: Query, params: Optional[tuple] = None, error_msg: str = "", cursor: Optional[Cursor] = None
     ):
@@ -222,15 +229,15 @@ def _handle_hnsw(self):
             )
             self._execute_sql(sql_set_hnsw_ef_search, error_msg="Could not set hnsw.ef_search")
 
-        index_esists = bool(
+        index_exists = bool(
             self._execute_sql(
                 "SELECT 1 FROM pg_indexes WHERE tablename = %s AND indexname = %s",
                 (self.table_name, HNSW_INDEX_NAME),
                 "Could not check if HNSW index exists",
             ).fetchone()
         )
 
-        if index_esists and not self.hnsw_recreate_index_if_exists:
+        if index_exists and not self.hnsw_recreate_index_if_exists:
             logger.warning(
                 "HNSW index already exists and won't be recreated. "
                 "If you want to recreate it, pass 'hnsw_recreate_index_if_exists=True' to the "
@@ -374,7 +381,8 @@ def write_documents(self, documents: List[Document], policy: DuplicatePolicy = D
 
         return written_docs
 
-    def _from_haystack_to_pg_documents(self, documents: List[Document]) -> List[Dict[str, Any]]:
+    @staticmethod
+    def _from_haystack_to_pg_documents(documents: List[Document]) -> List[Dict[str, Any]]:
         """
         Internal method to convert a list of Haystack Documents to a list of dictionaries that can be used to insert
         documents into the PgvectorDocumentStore.
@@ -396,7 +404,8 @@ def _from_haystack_to_pg_documents(self, documents: List[Document]) -> List[Dict
 
         return db_documents
 
-    def _from_pg_to_haystack_documents(self, documents: List[Dict[str, Any]]) -> List[Document]:
+    @staticmethod
+    def _from_pg_to_haystack_documents(documents: List[Dict[str, Any]]) -> List[Document]:
         """
         Internal method to convert a list of dictionaries from pgvector to a list of Haystack Documents.
         """

integrations/pgvector/tests/test_retriever.py

@@ -1,12 +1,15 @@
 # SPDX-FileCopyrightText: 2023-present deepset GmbH <[email protected]>
 #
 # SPDX-License-Identifier: Apache-2.0
+import os
 from unittest.mock import Mock
 
 from haystack.dataclasses import Document
 from haystack_integrations.components.retrievers.pgvector import PgvectorEmbeddingRetriever
 from haystack_integrations.document_stores.pgvector import PgvectorDocumentStore
 
+from haystack.utils.auth import EnvVarSecret
+
 
 class TestRetriever:
     def test_init_default(self, document_store: PgvectorDocumentStore):
@@ -37,7 +40,7 @@ def test_to_dict(self, document_store: PgvectorDocumentStore):
                 "document_store": {
                     "type": "haystack_integrations.document_stores.pgvector.document_store.PgvectorDocumentStore",
                     "init_parameters": {
-                        "connection_string": "postgresql://postgres:postgres@localhost:5432/postgres",
+                        "connection_string": {'env_vars': ['PG_CONN_STR'], 'strict': True, 'type': 'env_var'},
                         "table_name": "haystack_test_to_dict",
                         "embedding_dimension": 768,
                         "vector_function": "cosine_similarity",
@@ -62,7 +65,7 @@ def test_from_dict(self):
                 "document_store": {
                     "type": "haystack_integrations.document_stores.pgvector.document_store.PgvectorDocumentStore",
                     "init_parameters": {
-                        "connection_string": "postgresql://postgres:postgres@localhost:5432/postgres",
+                        "connection_string": {'env_vars': ['PG_CONN_STR'], 'strict': True, 'type': 'env_var'},
                         "table_name": "haystack_test_to_dict",
                         "embedding_dimension": 768,
                         "vector_function": "cosine_similarity",
@@ -83,7 +86,7 @@ def test_from_dict(self):
         document_store = retriever.document_store
 
         assert isinstance(document_store, PgvectorDocumentStore)
-        assert document_store.connection_string == "postgresql://postgres:postgres@localhost:5432/postgres"
+        assert isinstance(document_store.connection_string, EnvVarSecret)
         assert document_store.table_name == "haystack_test_to_dict"
         assert document_store.embedding_dimension == 768
         assert document_store.vector_function == "cosine_similarity"