Add SecretStr for Symbl.ai Nebula API (#12896)

Description: This PR masks API key secrets for the Nebula model from
Symbl.ai
Issue: #12165 
Maintainer: @eyurtsev

---------

Co-authored-by: Praveen Venkateswaran <praveen.venkateswaran@ibm.com>

libs/langchain/langchain/llms/symblai_nebula.py

@@ -15,8 +15,9 @@ from tenacity import (
 from langchain.callbacks.manager import CallbackManagerForLLMRun
 from langchain.llms.base import LLM
 from langchain.llms.utils import enforce_stop_tokens
-from langchain.pydantic_v1 import Extra, root_validator
-from langchain.utils import get_from_dict_or_env
+from langchain.pydantic_v1 import Extra, SecretStr, root_validator
+from langchain.utils import convert_to_secret_str
+from langchain.utils.env import get_from_dict_or_env
 
 DEFAULT_NEBULA_SERVICE_URL = "https://api-nebula.symbl.ai"
 DEFAULT_NEBULA_SERVICE_PATH = "/v1/model/generate"
@@ -50,7 +51,7 @@ class Nebula(LLM):
 
     nebula_service_url: Optional[str] = None
     nebula_service_path: Optional[str] = None
-    nebula_api_key: Optional[str] = None
+    nebula_api_key: Optional[SecretStr] = None
     model: Optional[str] = None
     max_new_tokens: Optional[int] = 128
     temperature: Optional[float] = 0.6
@@ -81,8 +82,8 @@ class Nebula(LLM):
             "NEBULA_SERVICE_PATH",
             DEFAULT_NEBULA_SERVICE_PATH,
         )
-        nebula_api_key = get_from_dict_or_env(
-            values, "nebula_api_key", "NEBULA_API_KEY", None
+        nebula_api_key = convert_to_secret_str(
+            get_from_dict_or_env(values, "nebula_api_key", "NEBULA_API_KEY", None)
         )
 
         if nebula_service_url.endswith("/"):
@@ -187,9 +188,12 @@ def make_request(
 ) -> Any:
     """Generate text from the model."""
     params = params or {}
+    api_key = None
+    if self.nebula_api_key is not None:
+        api_key = self.nebula_api_key.get_secret_value()
     headers = {
         "Content-Type": "application/json",
-        "ApiKey": f"{self.nebula_api_key}",
+        "ApiKey": f"{api_key}",
     }
 
     body = {

libs/langchain/tests/unit_tests/llms/test_symblai_nebula.py

@@ -0,0 +1,29 @@
+"""Test the Nebula model by Symbl.ai"""
+
+from pytest import CaptureFixture, MonkeyPatch
+
+from langchain.llms.symblai_nebula import Nebula
+from langchain.pydantic_v1 import SecretStr
+
+
+def test_api_key_is_secret_string() -> None:
+    llm = Nebula(nebula_api_key="secret-api-key")
+    assert isinstance(llm.nebula_api_key, SecretStr)
+    assert llm.nebula_api_key.get_secret_value() == "secret-api-key"
+
+
+def test_api_key_masked_when_passed_from_env(
+    monkeypatch: MonkeyPatch, capsys: CaptureFixture
+) -> None:
+    monkeypatch.setenv("NEBULA_API_KEY", "secret-api-key")
+    llm = Nebula()
+    print(llm.nebula_api_key, end="")
+    captured = capsys.readouterr()
+    assert captured.out == "**********"
+
+
+def test_api_key_masked_when_passed_via_constructor(capsys: CaptureFixture) -> None:
+    llm = Nebula(nebula_api_key="secret-api-key")
+    print(llm.nebula_api_key, end="")
+    captured = capsys.readouterr()
+    assert captured.out == "**********"