Mask API key for Anyscale LLM (#12406)

Description: Add masking of API Key for Anyscale LLM when printed.
Issue: #12165 
Dependencies: None
Tag maintainer: @eyurtsev

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>

libs/langchain/langchain/chat_models/anyscale.py

@@ -13,9 +13,9 @@ from langchain.chat_models.openai import (
     ChatOpenAI,
     _import_tiktoken,
 )
-from langchain.pydantic_v1 import Field, root_validator
+from langchain.pydantic_v1 import Field, SecretStr, root_validator
 from langchain.schema.messages import BaseMessage
-from langchain.utils import get_from_dict_or_env
+from langchain.utils import convert_to_secret_str, get_from_dict_or_env
 
 if TYPE_CHECKING:
     import tiktoken
@@ -53,7 +53,7 @@ class ChatAnyscale(ChatOpenAI):
     def lc_secrets(self) -> Dict[str, str]:
         return {"anyscale_api_key": "ANYSCALE_API_KEY"}
 
-    anyscale_api_key: Optional[str] = None
+    anyscale_api_key: Optional[SecretStr] = None
     """AnyScale Endpoints API keys."""
     model_name: str = Field(default=DEFAULT_MODEL, alias="model")
     """Model name to use."""
@@ -98,10 +98,12 @@ class ChatAnyscale(ChatOpenAI):
     @root_validator(pre=True)
     def validate_environment_override(cls, values: dict) -> dict:
         """Validate that api key and python package exists in environment."""
-        values["openai_api_key"] = get_from_dict_or_env(
-            values,
-            "anyscale_api_key",
-            "ANYSCALE_API_KEY",
+        values["openai_api_key"] = convert_to_secret_str(
+            get_from_dict_or_env(
+                values,
+                "anyscale_api_key",
+                "ANYSCALE_API_KEY",
+            )
         )
         values["openai_api_base"] = get_from_dict_or_env(
             values,
@@ -138,7 +140,7 @@ class ChatAnyscale(ChatOpenAI):
         model_name = values["model_name"]
 
         available_models = cls.get_available_models(
-            values["openai_api_key"],
+            values["openai_api_key"].get_secret_value(),
             values["openai_api_base"],
         )
 

libs/langchain/langchain/llms/anyscale.py

@@ -9,6 +9,7 @@ from typing import (
     Optional,
     Set,
     Tuple,
+    cast,
 )
 
 from langchain.callbacks.manager import (
@@ -20,10 +21,10 @@ from langchain.llms.openai import (
     acompletion_with_retry,
     completion_with_retry,
 )
-from langchain.pydantic_v1 import Field, root_validator
+from langchain.pydantic_v1 import Field, SecretStr, root_validator
 from langchain.schema import Generation, LLMResult
 from langchain.schema.output import GenerationChunk
-from langchain.utils import get_from_dict_or_env
+from langchain.utils import convert_to_secret_str, get_from_dict_or_env
 
 
 def update_token_usage(
@@ -84,7 +85,7 @@ class Anyscale(BaseOpenAI):
 
     """Key word arguments to pass to the model."""
     anyscale_api_base: Optional[str] = None
-    anyscale_api_key: Optional[str] = None
+    anyscale_api_key: Optional[SecretStr] = None
 
     prefix_messages: List = Field(default_factory=list)
 
@@ -94,9 +95,10 @@ class Anyscale(BaseOpenAI):
         values["anyscale_api_base"] = get_from_dict_or_env(
             values, "anyscale_api_base", "ANYSCALE_API_BASE"
         )
-        values["anyscale_api_key"] = get_from_dict_or_env(
-            values, "anyscale_api_key", "ANYSCALE_API_KEY"
+        values["anyscale_api_key"] = convert_to_secret_str(
+            get_from_dict_or_env(values, "anyscale_api_key", "ANYSCALE_API_KEY")
         )
+
         try:
             import openai
 
@@ -126,7 +128,7 @@ class Anyscale(BaseOpenAI):
     def _invocation_params(self) -> Dict[str, Any]:
         """Get the parameters used to invoke the model."""
         openai_creds: Dict[str, Any] = {
-            "api_key": self.anyscale_api_key,
+            "api_key": cast(SecretStr, self.anyscale_api_key).get_secret_value(),
             "api_base": self.anyscale_api_base,
         }
         return {**openai_creds, **{"model": self.model_name}, **super()._default_params}

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

@@ -0,0 +1,41 @@
+"""Test Anyscale llm"""
+import pytest
+from pytest import CaptureFixture, MonkeyPatch
+
+from langchain.llms.anyscale import Anyscale
+from langchain.pydantic_v1 import SecretStr
+
+
+@pytest.mark.requires("openai")
+def test_api_key_is_secret_string() -> None:
+    llm = Anyscale(
+        anyscale_api_key="secret-api-key", anyscale_api_base="test", model_name="test"
+    )
+    assert isinstance(llm.anyscale_api_key, SecretStr)
+
+
+@pytest.mark.requires("openai")
+def test_api_key_masked_when_passed_from_env(
+    monkeypatch: MonkeyPatch, capsys: CaptureFixture
+) -> None:
+    """Test initialization with an API key provided via an env variable"""
+    monkeypatch.setenv("ANYSCALE_API_KEY", "secret-api-key")
+    llm = Anyscale(anyscale_api_base="test", model_name="test")
+    print(llm.anyscale_api_key, end="")
+    captured = capsys.readouterr()
+
+    assert captured.out == "**********"
+
+
+@pytest.mark.requires("openai")
+def test_api_key_masked_when_passed_via_constructor(
+    capsys: CaptureFixture,
+) -> None:
+    """Test initialization with an API key provided via the initializer"""
+    llm = Anyscale(
+        anyscale_api_key="secret-api-key", anyscale_api_base="test", model_name="test"
+    )
+    print(llm.anyscale_api_key, end="")
+    captured = capsys.readouterr()
+
+    assert captured.out == "**********"