Fix: redundant casting to SecretStr API keys

libs/community/langchain_community/chat_models/javelin_ai_gateway.py

@@ -1,5 +1,5 @@
 import logging
-from typing import Any, Dict, List, Mapping, Optional, cast
+from typing import Any, Dict, List, Mapping, Optional
 
 from langchain_core.callbacks import (
     AsyncCallbackManagerForLLMRun,
@@ -19,6 +19,7 @@
     ChatResult,
 )
 from langchain_core.pydantic_v1 import BaseModel, Extra, SecretStr
+from langchain_core.utils import extract_secret_value
 
 logger = logging.getLogger(__name__)
 
@@ -85,7 +86,7 @@ def __init__(self, **kwargs: Any):
             try:
                 self.client = JavelinClient(
                     base_url=self.gateway_uri,
-                    api_key=cast(SecretStr, self.javelin_api_key).get_secret_value(),
+                    api_key=extract_secret_value(self.javelin_api_key),
                 )
             except UnauthorizedError as e:
                 raise ValueError("Javelin: Incorrect API Key.") from e
@@ -94,7 +95,7 @@ def __init__(self, **kwargs: Any):
     def _default_params(self) -> Dict[str, Any]:
         params: Dict[str, Any] = {
             "gateway_uri": self.gateway_uri,
-            "javelin_api_key": cast(SecretStr, self.javelin_api_key).get_secret_value(),
+            "javelin_api_key": extract_secret_value(self.javelin_api_key),
             "route": self.route,
             **(self.params.dict() if self.params else {}),
         }

libs/community/langchain_community/chat_models/jinachat.py

@@ -42,6 +42,7 @@
 from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
 from langchain_core.utils import (
     convert_to_secret_str,
+    extract_secret_value,
     get_from_dict_or_env,
     get_pydantic_field_names,
 )
@@ -397,8 +398,7 @@ async def _agenerate(
     def _invocation_params(self) -> Mapping[str, Any]:
         """Get the parameters used to invoke the model."""
         jinachat_creds: Dict[str, Any] = {
-            "api_key": self.jinachat_api_key
-            and self.jinachat_api_key.get_secret_value(),
+            "api_key": extract_secret_value(self.jinachat_api_key),
             "api_base": "https://api.chat.jina.ai/v1",
             "model": "jinachat",
         }

libs/community/langchain_community/embeddings/javelin_ai_gateway.py

@@ -3,7 +3,7 @@
 from typing import Any, Iterator, List, Optional
 
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel
+from langchain_core.pydantic_v1 import BaseModel, SecretStr
 
 
 def _chunk(texts: List[str], size: int) -> Iterator[List[str]]:
@@ -38,7 +38,7 @@ class JavelinAIGatewayEmbeddings(Embeddings, BaseModel):
     gateway_uri: Optional[str] = None
     """The URI for the Javelin AI Gateway API."""
 
-    javelin_api_key: Optional[str] = None
+    javelin_api_key: Optional[SecretStr] = None
     """The API key for the Javelin AI Gateway API."""
 
     def __init__(self, **kwargs: Any):

libs/community/langchain_community/embeddings/voyageai.py

@@ -10,13 +10,16 @@
     Optional,
     Tuple,
     Union,
-    cast,
 )
 
 import requests
 from langchain_core.embeddings import Embeddings
 from langchain_core.pydantic_v1 import BaseModel, Extra, SecretStr, root_validator
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import (
+    convert_to_secret_str,
+    extract_secret_value,
+    get_from_dict_or_env,
+)
 from tenacity import (
     before_sleep_log,
     retry,
@@ -103,7 +106,7 @@ def validate_environment(cls, values: Dict) -> Dict:
     def _invocation_params(
         self, input: List[str], input_type: Optional[str] = None
     ) -> Dict:
-        api_key = cast(SecretStr, self.voyage_api_key).get_secret_value()
+        api_key = extract_secret_value(self.voyage_api_key)
         params = {
             "url": self.voyage_api_base,
             "headers": {"Authorization": f"Bearer {api_key}"},

libs/community/langchain_community/llms/ai21.py

@@ -1,10 +1,14 @@
-from typing import Any, Dict, List, Optional, cast
+from typing import Any, Dict, List, Optional
 
 import requests
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import LLM
 from langchain_core.pydantic_v1 import BaseModel, Extra, SecretStr, root_validator
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import (
+    convert_to_secret_str,
+    extract_secret_value,
+    get_from_dict_or_env,
+)
 
 
 class AI21PenaltyData(BaseModel):
@@ -142,10 +146,12 @@ def _call(
             else:
                 base_url = "https://api.ai21.com/studio/v1"
         params = {**self._default_params, **kwargs}
-        self.ai21_api_key = cast(SecretStr, self.ai21_api_key)
+        self.ai21_api_key = convert_to_secret_str(self.ai21_api_key)
         response = requests.post(
             url=f"{base_url}/{self.model}/complete",
-            headers={"Authorization": f"Bearer {self.ai21_api_key.get_secret_value()}"},
+            headers={
+                "Authorization": f"Bearer {extract_secret_value(self.ai21_api_key)}"
+            },
             json={"prompt": prompt, "stopSequences": stop, **params},
         )
         if response.status_code != 200:

libs/community/langchain_community/llms/anyscale.py

@@ -9,7 +9,6 @@
     Optional,
     Set,
     Tuple,
-    cast,
 )
 
 from langchain_core.callbacks import (
@@ -18,7 +17,11 @@
 )
 from langchain_core.outputs import Generation, GenerationChunk, LLMResult
 from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import (
+    convert_to_secret_str,
+    extract_secret_value,
+    get_from_dict_or_env,
+)
 
 from langchain_community.llms.openai import (
     BaseOpenAI,
@@ -132,7 +135,7 @@ def _identifying_params(self) -> Mapping[str, Any]:
     def _invocation_params(self) -> Dict[str, Any]:
         """Get the parameters used to invoke the model."""
         openai_creds: Dict[str, Any] = {
-            "api_key": cast(SecretStr, self.anyscale_api_key).get_secret_value(),
+            "api_key": extract_secret_value(self.anyscale_api_key),
             "api_base": self.anyscale_api_base,
         }
         return {**openai_creds, **{"model": self.model_name}, **super()._default_params}

libs/community/langchain_community/llms/arcee.py

@@ -1,9 +1,13 @@
-from typing import Any, Dict, List, Optional, Union, cast
+from typing import Any, Dict, List, Optional, Union
 
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import LLM
 from langchain_core.pydantic_v1 import Extra, SecretStr, root_validator
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import (
+    convert_to_secret_str,
+    extract_secret_value,
+    get_from_dict_or_env,
+)
 
 from langchain_community.utilities.arcee import ArceeWrapper, DALMFilter
 
@@ -66,7 +70,7 @@ def __init__(self, **data: Any) -> None:
         """Initializes private fields."""
 
         super().__init__(**data)
-        api_key = cast(SecretStr, self.arcee_api_key)
+        api_key = extract_secret_value(self.arcee_api_key)
         self._client = ArceeWrapper(
             arcee_api_key=api_key,
             arcee_api_url=self.arcee_api_url,

libs/community/langchain_community/llms/cerebriumai.py

@@ -1,11 +1,15 @@
 import logging
-from typing import Any, Dict, List, Mapping, Optional, cast
+from typing import Any, Dict, List, Mapping, Optional
 
 import requests
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import LLM
 from langchain_core.pydantic_v1 import Extra, Field, SecretStr, root_validator
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import (
+    convert_to_secret_str,
+    extract_secret_value,
+    get_from_dict_or_env,
+)
 
 from langchain_community.llms.utils import enforce_stop_tokens
 
@@ -92,9 +96,7 @@ def _call(
         **kwargs: Any,
     ) -> str:
         headers: Dict = {
-            "Authorization": cast(
-                SecretStr, self.cerebriumai_api_key
-            ).get_secret_value(),
+            "Authorization": extract_secret_value(self.cerebriumai_api_key),
             "Content-Type": "application/json",
         }
         params = self.model_kwargs or {}

libs/community/langchain_community/utilities/google_finance.py

@@ -1,8 +1,12 @@
 """Util that calls Google Finance Search."""
-from typing import Any, Dict, Optional, cast
+from typing import Any, Dict, Optional
 
 from langchain_core.pydantic_v1 import BaseModel, Extra, SecretStr, root_validator
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import (
+    convert_to_secret_str,
+    extract_secret_value,
+    get_from_dict_or_env,
+)
 
 
 class GoogleFinanceAPIWrapper(BaseModel):
@@ -52,10 +56,9 @@ def validate_environment(cls, values: Dict) -> Dict:
 
     def run(self, query: str) -> str:
         """Run query through Google Finance with Serpapi"""
-        serpapi_api_key = cast(SecretStr, self.serp_api_key)
         params = {
             "engine": "google_finance",
-            "api_key": serpapi_api_key.get_secret_value(),
+            "api_key": extract_secret_value(self.serpapi_api_key),
             "q": query,
         }
 

libs/community/langchain_community/utilities/google_jobs.py

@@ -1,8 +1,12 @@
 """Util that calls Google Scholar Search."""
-from typing import Any, Dict, Optional, cast
+from typing import Any, Dict, Optional
 
 from langchain_core.pydantic_v1 import BaseModel, Extra, SecretStr, root_validator
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import (
+    convert_to_secret_str,
+    extract_secret_value,
+    get_from_dict_or_env,
+)
 
 
 class GoogleJobsAPIWrapper(BaseModel):
@@ -54,10 +58,9 @@ def run(self, query: str) -> str:
         """Run query through Google Trends with Serpapi"""
 
         # set up query
-        serpapi_api_key = cast(SecretStr, self.serp_api_key)
         params = {
             "engine": "google_jobs",
-            "api_key": serpapi_api_key.get_secret_value(),
+            "api_key": extract_secret_value(self.serpapi_api_key),
             "q": query,
         }
 

libs/community/langchain_community/utilities/google_lens.py

@@ -1,9 +1,13 @@
 """Util that calls Google Lens Search."""
-from typing import Any, Dict, Optional, cast
+from typing import Any, Dict, Optional
 
 import requests
 from langchain_core.pydantic_v1 import BaseModel, Extra, SecretStr, root_validator
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import (
+    convert_to_secret_str,
+    extract_secret_value,
+    get_from_dict_or_env,
+)
 
 
 class GoogleLensAPIWrapper(BaseModel):
@@ -45,11 +49,9 @@ def validate_environment(cls, values: Dict) -> Dict:
 
     def run(self, query: str) -> str:
         """Run query through Google Trends with Serpapi"""
-        serpapi_api_key = cast(SecretStr, self.serp_api_key)
-
         params = {
             "engine": "google_lens",
-            "api_key": serpapi_api_key.get_secret_value(),
+            "api_key": extract_secret_value(self.serpapi_api_key),
             "url": query,
         }
         queryURL = f"https://serpapi.com/search?engine={params['engine']}&api_key={params['api_key']}&url={params['url']}"

libs/community/langchain_community/utilities/google_trends.py

@@ -1,8 +1,12 @@
 """Util that calls Google Scholar Search."""
-from typing import Any, Dict, Optional, cast
+from typing import Any, Dict, Optional
 
 from langchain_core.pydantic_v1 import BaseModel, Extra, SecretStr, root_validator
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import (
+    convert_to_secret_str,
+    extract_secret_value,
+    get_from_dict_or_env,
+)
 
 
 class GoogleTrendsAPIWrapper(BaseModel):
@@ -56,10 +60,10 @@ def validate_environment(cls, values: Dict) -> Dict:
 
     def run(self, query: str) -> str:
         """Run query through Google Trends with Serpapi"""
-        serpapi_api_key = cast(SecretStr, self.serp_api_key)
+        api_key = extract_secret_value(self.serpapi_api_key)
         params = {
             "engine": "google_trends",
-            "api_key": serpapi_api_key.get_secret_value(),
+            "api_key": api_key,
             "q": query,
         }
 
@@ -86,7 +90,7 @@ def run(self, query: str) -> str:
 
         params = {
             "engine": "google_trends",
-            "api_key": serpapi_api_key.get_secret_value(),
+            "api_key": api_key,
             "data_type": "RELATED_QUERIES",
             "q": query,
         }

libs/community/tests/integration_tests/chat_models/test_jinachat.py

@@ -1,7 +1,5 @@
 """Test JinaChat wrapper."""
 
-from typing import cast
-
 import pytest
 from langchain_core.callbacks import CallbackManager
 from langchain_core.messages import BaseMessage, HumanMessage, SystemMessage
@@ -13,7 +11,7 @@
 from tests.unit_tests.callbacks.fake_callback_handler import FakeCallbackHandler
 
 
-def test_jinachat_api_key_is_secret_string() -> None:
+def test_jinachat_api_key_is_secretstr() -> None:
     llm = JinaChat(jinachat_api_key="secret-api-key")
     assert isinstance(llm.jinachat_api_key, SecretStr)
 
@@ -44,7 +42,7 @@ def test_jinachat_api_key_masked_when_passed_via_constructor(
 def test_uses_actual_secret_value_from_secretstr() -> None:
     """Test that actual secret is retrieved using `.get_secret_value()`."""
     llm = JinaChat(jinachat_api_key="secret-api-key")
-    assert cast(SecretStr, llm.jinachat_api_key).get_secret_value() == "secret-api-key"
+    assert llm.jinachat_api_key.get_secret_value() == "secret-api-key"
 
 
 def test_jinachat() -> None:

libs/community/tests/integration_tests/llms/test_nlpcloud.py

@@ -1,7 +1,6 @@
 """Test NLPCloud API wrapper."""
 
 from pathlib import Path
-from typing import cast
 
 from langchain_core.pydantic_v1 import SecretStr
 from pytest import CaptureFixture, MonkeyPatch
@@ -34,8 +33,7 @@ def test_nlpcloud_api_key(monkeypatch: MonkeyPatch, capsys: CaptureFixture) -> N
     monkeypatch.setenv("NLPCLOUD_API_KEY", "secret-api-key")
     llm = NLPCloud()
     assert isinstance(llm.nlpcloud_api_key, SecretStr)
-
-    assert cast(SecretStr, llm.nlpcloud_api_key).get_secret_value() == "secret-api-key"
+    assert llm.nlpcloud_api_key.get_secret_value() == "secret-api-key"
 
     print(llm.nlpcloud_api_key, end="")
     captured = capsys.readouterr()

libs/community/tests/unit_tests/chat_models/test_azureml_endpoint.py

@@ -37,7 +37,7 @@ def api_passed_via_constructor_fixture() -> AzureMLChatOnlineEndpoint:
     ["api_passed_via_constructor_fixture", "api_passed_via_environment_fixture"],
 )
 class TestAzureMLChatOnlineEndpoint:
-    def test_api_key_is_secret_string(
+    def test_api_key_is_secretstr(
         self, fixture_name: str, request: FixtureRequest
     ) -> None:
         """Test that the API key is a SecretStr instance"""