refactor: update API key handling to use get_secret_value method

pkgs/base/swarmauri_base/embeddings/EmbeddingBase.py

@@ -1,13 +1,13 @@
-from typing import Optional, Literal
-from pydantic import Field
+from typing import Literal, Optional
 
-from swarmauri_core.embeddings.IVectorize import IVectorize
+from pydantic import Field
+from swarmauri_core.ComponentBase import ComponentBase, ResourceTypes
 from swarmauri_core.embeddings.IFeature import IFeature
 from swarmauri_core.embeddings.ISaveModel import ISaveModel
-from swarmauri_core.ComponentBase import ComponentBase, ResourceTypes
+from swarmauri_core.embeddings.IVectorize import IVectorize
+
 
 @ComponentBase.register_model()
 class EmbeddingBase(IVectorize, IFeature, ISaveModel, ComponentBase):
-    resource: Optional[str] =  Field(default=ResourceTypes.EMBEDDING.value, frozen=True)
-    type: Literal['EmbeddingBase'] = 'EmbeddingBase'
-
+    resource: Optional[str] = Field(default=ResourceTypes.EMBEDDING.value, frozen=True)
+    type: Literal["EmbeddingBase"] = "EmbeddingBase"

pkgs/base/swarmauri_base/vector_stores/VectorStoreCloudMixin.py

@@ -1,6 +1,6 @@
 from typing import Optional
-from pydantic import Field, BaseModel
 
+from pydantic import BaseModel, Field, SecretStr
 from swarmauri_core.vector_stores.ICloudVectorStore import ICloudVectorStore
 
 
@@ -9,7 +9,9 @@ class VectorStoreCloudMixin(ICloudVectorStore, BaseModel):
     Mixin class for cloud-based vector stores.
     """
 
-    api_key: str
+    api_key: Optional[SecretStr] = Field(
+        None, description="API key for the cloud-based store"
+    )
     collection_name: str
     url: Optional[str] = Field(
         None, description="URL of the cloud-based store to connect to"
@@ -20,4 +22,4 @@ class VectorStoreCloudMixin(ICloudVectorStore, BaseModel):
     )
     client: Optional[object] = Field(
         None, description="Client object for interacting with the cloud-based store"
-    )
+    )

pkgs/community/swarmauri_vectorstore_annoy/swarmauri_vectorstore_annoy/AnnoyVectorStore.py

@@ -1,21 +1,20 @@
-from typing import List, Union, Literal, Optional
-import numpy as np
-from annoy import AnnoyIndex
 import os
+from typing import List, Literal, Optional, Union
 
-from swarmauri_core.ComponentBase import ComponentBase
-from swarmauri_standard.documents.Document import Document
-from swarmauri_embedding_doc2vec.Doc2VecEmbedding import Doc2VecEmbedding
-from swarmauri_standard.distances.CosineDistance import CosineDistance
-
+import numpy as np
+from annoy import AnnoyIndex
 from swarmauri_base.vector_stores.VectorStoreBase import VectorStoreBase
+from swarmauri_base.vector_stores.VectorStoreCloudMixin import VectorStoreCloudMixin
 from swarmauri_base.vector_stores.VectorStoreRetrieveMixin import (
     VectorStoreRetrieveMixin,
 )
-from swarmauri_base.vector_stores.VectorStoreCloudMixin import VectorStoreCloudMixin
 from swarmauri_base.vector_stores.VectorStoreSaveLoadMixin import (
     VectorStoreSaveLoadMixin,
 )
+from swarmauri_core.ComponentBase import ComponentBase
+from swarmauri_embedding_doc2vec.Doc2VecEmbedding import Doc2VecEmbedding
+from swarmauri_standard.distances.CosineDistance import CosineDistance
+from swarmauri_standard.documents.Document import Document
 
 
 @ComponentBase.register_type(VectorStoreBase, "AnnoyVectorStore")
@@ -34,27 +33,19 @@ class AnnoyVectorStore(
     """
 
     type: Literal["AnnoyVectorStore"] = "AnnoyVectorStore"
-    api_key: str = (
-        "not_required"  # Annoy doesn't need an API key, but base class requires it
-    )
 
     def __init__(self, **kwargs):
         """
         Initialize the AnnoyVectorStore.
         Args:
             **kwargs: Additional keyword arguments.
         """
-        # Set default api_key if not provided
-        if "api_key" not in kwargs:
-            kwargs["api_key"] = "not_required"
 
         super().__init__(**kwargs)
         self._embedder = Doc2VecEmbedding(vector_size=self.vector_size)
         self._distance = CosineDistance()
         self.client = None
-        self._documents = (
-            {}
-        )  # Store documents in memory since Annoy only stores vectors
+        self._documents = {}  # Store documents in memory since Annoy only stores vectors
         self._current_index = 0  # Track the next available index
         self._id_to_index = {}  # Map document IDs to Annoy indices
         self._index_to_id = {}  # Map Annoy indices to document IDs

pkgs/community/swarmauri_vectorstore_cloudweaviate/swarmauri_vectorstore_cloudweaviate/CloudWeaviateVectorStore.py

@@ -49,7 +49,7 @@ def connect(self, **kwargs):
         if self._client is None:
             self._client = weaviate.connect_to_weaviate_cloud(
                 cluster_url=self.url,
-                auth_credentials=Auth.api_key(self.api_key),
+                auth_credentials=Auth.api_key(self.api_key.get_secret_value()),
                 headers=kwargs.get("headers", {}),
             )
 

pkgs/community/swarmauri_vectorstore_pinecone/swarmauri_vectorstore_pinecone/PineconeVectorStore.py

@@ -54,7 +54,7 @@ def delete(self):
 
         """
         try:
-            pc = Pinecone(api_key=self.api_key)
+            pc = Pinecone(api_key=self.api_key.get_secret_value())
             pc.delete_index(self.collection_name)
             self.client = None
         except Exception as e:
@@ -73,7 +73,7 @@ def connect(self, metric: Optional[str] = "cosine", cloud: Optional[str] = "aws"
 
         """
         try:
-            pc = Pinecone(api_key=self.api_key)
+            pc = Pinecone(api_key=self.api_key.get_secret_value())
             if not pc.has_index(self.collection_name):
                 pc.create_index(
                     name=self.collection_name,

pkgs/community/swarmauri_vectorstore_qdrant/swarmauri_vectorstore_qdrant/CloudQdrantVectorStore.py

@@ -60,7 +60,7 @@ def connect(self) -> None:
         """
         if self.client is None:
             self.client = QdrantClient(
-                api_key=self.api_key,
+                api_key=self.api_key.get_secret_value(),
                 url=self.url,
             )
 

pkgs/standards/swarmauri_standard/swarmauri_standard/embeddings/CohereEmbedding.py

@@ -1,11 +1,15 @@
-import httpx
+import logging
 from typing import List, Literal, Optional, Union
-from pydantic import PrivateAttr
-from swarmauri_standard.vectors.Vector import Vector
+
+import httpx
+from pydantic import PrivateAttr, SecretStr
 from swarmauri_base.embeddings.EmbeddingBase import EmbeddingBase
 from swarmauri_core.ComponentBase import ComponentBase
 
-@ComponentBase.register_type(EmbeddingBase, 'CohereEmbedding')
+from swarmauri_standard.vectors.Vector import Vector
+
+
+@ComponentBase.register_type(EmbeddingBase, "CohereEmbedding")
 class CohereEmbedding(EmbeddingBase):
     """
     A class for generating embeddings using the Cohere REST API.
@@ -17,7 +21,7 @@ class CohereEmbedding(EmbeddingBase):
     Attributes:
         type (Literal["CohereEmbedding"]): The type identifier for this embedding class.
         model (str): The Cohere embedding model to use.
-        api_key (str): The API key for accessing the Cohere API.
+        api_key (SecretStr): The API key for accessing the Cohere API.
         allowed_task_types (List[str]): List of supported task types for embeddings
 
     Link to Allowed Models: https://docs.cohere.com/reference/embed
@@ -52,21 +56,16 @@ class CohereEmbedding(EmbeddingBase):
 
     # Public attributes
     model: str = "embed-english-v3.0"
-    api_key: str = None
+    api_key: SecretStr = None
+    task_type: str = "search_document"
+    embedding_types: Optional[str] = "float"
+    truncate: Optional[str] = "END"
 
     # Private configuration attributes
-    _task_type: str = PrivateAttr("search_document")
-    _embedding_types: Optional[str] = PrivateAttr("float")
-    _truncate: Optional[str] = PrivateAttr("END")
     _client: httpx.Client = PrivateAttr()
 
     def __init__(
         self,
-        api_key: str = None,
-        model: str = "embed-english-v3.0",
-        task_type: Optional[str] = "search_document",
-        embedding_types: Optional[str] = "float",
-        truncate: Optional[str] = "END",
         **kwargs,
     ):
         """
@@ -85,29 +84,23 @@ def __init__(
         """
         super().__init__(**kwargs)
 
-        if model not in self.allowed_models:
+        if self.model not in self.allowed_models:
             raise ValueError(
-                f"Invalid model '{model}'. Allowed models are: {', '.join(self.allowed_models)}"
+                f"Invalid model '{self.model}'. Allowed models are: {', '.join(self.allowed_models)}"
             )
 
-        if task_type not in self.allowed_task_types:
+        if self.task_type not in self.allowed_task_types:
             raise ValueError(
-                f"Invalid task_type '{task_type}'. Allowed task types are: {', '.join(self.allowed_task_types)}"
+                f"Invalid task_type '{self.task_type}'. Allowed task types are: {', '.join(self.allowed_task_types)}"
             )
-        if embedding_types not in self._allowed_embedding_types:
+        if self.embedding_types not in self._allowed_embedding_types:
             raise ValueError(
-                f"Invalid embedding_types '{embedding_types}'. Allowed embedding types are: {', '.join(self._allowed_embedding_types)}"
+                f"Invalid embedding_types '{self.embedding_types}'. Allowed embedding types are: {', '.join(self._allowed_embedding_types)}"
             )
-        if truncate not in ["END", "START", "NONE"]:
+        if self.truncate not in ["END", "START", "NONE"]:
             raise ValueError(
-                f"Invalid truncate '{truncate}'. Allowed truncate are: END, START, NONE"
+                f"Invalid truncate '{self.truncate}'. Allowed truncate are: END, START, NONE"
             )
-
-        self.model = model
-        self.api_key = api_key
-        self._task_type = task_type
-        self._embedding_types = embedding_types
-        self._truncate = truncate
         self._client = httpx.Client()
 
     def _make_request(self, payload: dict) -> dict:
@@ -126,9 +119,8 @@ def _make_request(self, payload: dict) -> dict:
         headers = {
             "accept": "application/json",
             "content-type": "application/json",
-            "Authorization": f"Bearer {self.api_key}",
+            "Authorization": f"Bearer {self.api_key.get_secret_value()}",
         }
-
         try:
             response = self._client.post(
                 f"{self._BASE_URL}/embed", headers=headers, json=payload
@@ -155,22 +147,22 @@ def infer_vector(self, data: Union[List[str], List[str]]) -> List[Vector]:
             # Prepare the payload based on input type
             payload = {
                 "model": self.model,
-                "embedding_types": [self._embedding_types],
+                "embedding_types": [self.embedding_types],
             }
 
-            if self._task_type == "image":
+            if self.task_type == "image":
                 payload["input_type"] = "image"
                 payload["images"] = data
             else:
-                payload["input_type"] = self._task_type
+                payload["input_type"] = self.task_type
                 payload["texts"] = data
-                payload["truncate"] = self._truncate
+                payload["truncate"] = self.truncate
 
             # Make the API request
             response = self._make_request(payload)
 
             # Extract embeddings from response
-            embeddings = response["embeddings"][self._embedding_types]
+            embeddings = response["embeddings"][self.embedding_types]
             return [Vector(value=item) for item in embeddings]
 
         except Exception as e: