openai[minor]: change to secretstr (langchain-ai#16803)

libs/partners/openai/Makefile

@@ -6,10 +6,9 @@ all: help
 # Define a variable for the test file path.
 TEST_FILE ?= tests/unit_tests/
 
-test:
-	poetry run pytest $(TEST_FILE)
+integration_tests: TEST_FILE=tests/integration_tests/
 
-tests:
+test tests integration_tests:
 	poetry run pytest $(TEST_FILE)
 
 

libs/partners/openai/langchain_openai/chat_models/azure.py

@@ -3,12 +3,12 @@
 
 import logging
 import os
-from typing import Any, Callable, Dict, List, Union
+from typing import Any, Callable, Dict, List, Optional, Union
 
 import openai
 from langchain_core.outputs import ChatResult
-from langchain_core.pydantic_v1 import BaseModel, Field, root_validator
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr, root_validator
+from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
 
 from langchain_openai.chat_models.base import ChatOpenAI
 
@@ -71,9 +71,9 @@ class AzureChatOpenAI(ChatOpenAI):
     """
     openai_api_version: str = Field(default="", alias="api_version")
     """Automatically inferred from env var `OPENAI_API_VERSION` if not provided."""
-    openai_api_key: Union[str, None] = Field(default=None, alias="api_key")
+    openai_api_key: Optional[SecretStr] = Field(default=None, alias="api_key")
     """Automatically inferred from env var `AZURE_OPENAI_API_KEY` if not provided."""
-    azure_ad_token: Union[str, None] = None
+    azure_ad_token: Optional[SecretStr] = None
     """Your Azure Active Directory token.
     
         Automatically inferred from env var `AZURE_OPENAI_AD_TOKEN` if not provided.
@@ -111,11 +111,14 @@ def validate_environment(cls, values: Dict) -> Dict:
         # Check OPENAI_KEY for backwards compatibility.
         # TODO: Remove OPENAI_API_KEY support to avoid possible conflict when using
         # other forms of azure credentials.
-        values["openai_api_key"] = (
+        openai_api_key = (
             values["openai_api_key"]
             or os.getenv("AZURE_OPENAI_API_KEY")
             or os.getenv("OPENAI_API_KEY")
         )
+        values["openai_api_key"] = (
+            convert_to_secret_str(openai_api_key) if openai_api_key else None
+        )
         values["openai_api_base"] = values["openai_api_base"] or os.getenv(
             "OPENAI_API_BASE"
         )
@@ -131,8 +134,9 @@ def validate_environment(cls, values: Dict) -> Dict:
         values["azure_endpoint"] = values["azure_endpoint"] or os.getenv(
             "AZURE_OPENAI_ENDPOINT"
         )
-        values["azure_ad_token"] = values["azure_ad_token"] or os.getenv(
-            "AZURE_OPENAI_AD_TOKEN"
+        azure_ad_token = values["azure_ad_token"] or os.getenv("AZURE_OPENAI_AD_TOKEN")
+        values["azure_ad_token"] = (
+            convert_to_secret_str(azure_ad_token) if azure_ad_token else None
         )
 
         values["openai_api_type"] = get_from_dict_or_env(
@@ -168,8 +172,12 @@ def validate_environment(cls, values: Dict) -> Dict:
             "api_version": values["openai_api_version"],
             "azure_endpoint": values["azure_endpoint"],
             "azure_deployment": values["deployment_name"],
-            "api_key": values["openai_api_key"],
-            "azure_ad_token": values["azure_ad_token"],
+            "api_key": values["openai_api_key"].get_secret_value()
+            if values["openai_api_key"]
+            else None,
+            "azure_ad_token": values["azure_ad_token"].get_secret_value()
+            if values["azure_ad_token"]
+            else None,
             "azure_ad_token_provider": values["azure_ad_token_provider"],
             "organization": values["openai_organization"],
             "base_url": values["openai_api_base"],

libs/partners/openai/langchain_openai/chat_models/base.py

@@ -52,10 +52,11 @@
     ToolMessageChunk,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from langchain_core.pydantic_v1 import BaseModel, Field, root_validator
+from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr, root_validator
 from langchain_core.runnables import Runnable
 from langchain_core.tools import BaseTool
 from langchain_core.utils import (
+    convert_to_secret_str,
     get_from_dict_or_env,
     get_pydantic_field_names,
 )
@@ -240,10 +241,7 @@ def is_lc_serializable(cls) -> bool:
     """What sampling temperature to use."""
     model_kwargs: Dict[str, Any] = Field(default_factory=dict)
     """Holds any model parameters valid for `create` call not explicitly specified."""
-    # When updating this to use a SecretStr
-    # Check for classes that derive from this class (as some of them
-    # may assume openai_api_key is a str)
-    openai_api_key: Optional[str] = Field(default=None, alias="api_key")
+    openai_api_key: Optional[SecretStr] = Field(default=None, alias="api_key")
     """Automatically inferred from env var `OPENAI_API_KEY` if not provided."""
     openai_api_base: Optional[str] = Field(default=None, alias="base_url")
     """Base URL path for API requests, leave blank if not using a proxy or service 
@@ -321,8 +319,8 @@ def validate_environment(cls, values: Dict) -> Dict:
         if values["n"] > 1 and values["streaming"]:
             raise ValueError("n must be 1 when streaming.")
 
-        values["openai_api_key"] = get_from_dict_or_env(
-            values, "openai_api_key", "OPENAI_API_KEY"
+        values["openai_api_key"] = convert_to_secret_str(
+            get_from_dict_or_env(values, "openai_api_key", "OPENAI_API_KEY")
         )
         # Check OPENAI_ORGANIZATION for backwards compatibility.
         values["openai_organization"] = (
@@ -341,7 +339,9 @@ def validate_environment(cls, values: Dict) -> Dict:
         )
 
         client_params = {
-            "api_key": values["openai_api_key"],
+            "api_key": values["openai_api_key"].get_secret_value()
+            if values["openai_api_key"]
+            else None,
             "organization": values["openai_organization"],
             "base_url": values["openai_api_base"],
             "timeout": values["request_timeout"],

libs/partners/openai/langchain_openai/embeddings/azure.py

@@ -5,8 +5,8 @@
 from typing import Callable, Dict, Optional, Union
 
 import openai
-from langchain_core.pydantic_v1 import Field, root_validator
-from langchain_core.utils import get_from_dict_or_env
+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_openai.embeddings.base import OpenAIEmbeddings
 
@@ -39,9 +39,9 @@ class AzureOpenAIEmbeddings(OpenAIEmbeddings):
         If given sets the base client URL to include `/deployments/{azure_deployment}`.
         Note: this means you won't be able to use non-deployment endpoints.
     """
-    openai_api_key: Union[str, None] = Field(default=None, alias="api_key")
+    openai_api_key: Optional[SecretStr] = Field(default=None, alias="api_key")
     """Automatically inferred from env var `AZURE_OPENAI_API_KEY` if not provided."""
-    azure_ad_token: Union[str, None] = None
+    azure_ad_token: Optional[SecretStr] = None
     """Your Azure Active Directory token.
 
         Automatically inferred from env var `AZURE_OPENAI_AD_TOKEN` if not provided.
@@ -64,11 +64,14 @@ def validate_environment(cls, values: Dict) -> Dict:
         # Check OPENAI_KEY for backwards compatibility.
         # TODO: Remove OPENAI_API_KEY support to avoid possible conflict when using
         # other forms of azure credentials.
-        values["openai_api_key"] = (
+        openai_api_key = (
             values["openai_api_key"]
             or os.getenv("AZURE_OPENAI_API_KEY")
             or os.getenv("OPENAI_API_KEY")
         )
+        values["openai_api_key"] = (
+            convert_to_secret_str(openai_api_key) if openai_api_key else None
+        )
         values["openai_api_base"] = values["openai_api_base"] or os.getenv(
             "OPENAI_API_BASE"
         )
@@ -92,8 +95,9 @@ def validate_environment(cls, values: Dict) -> Dict:
         values["azure_endpoint"] = values["azure_endpoint"] or os.getenv(
             "AZURE_OPENAI_ENDPOINT"
         )
-        values["azure_ad_token"] = values["azure_ad_token"] or os.getenv(
-            "AZURE_OPENAI_AD_TOKEN"
+        azure_ad_token = values["azure_ad_token"] or os.getenv("AZURE_OPENAI_AD_TOKEN")
+        values["azure_ad_token"] = (
+            convert_to_secret_str(azure_ad_token) if azure_ad_token else None
         )
         # Azure OpenAI embedding models allow a maximum of 16 texts
         # at a time in each batch
@@ -122,8 +126,12 @@ def validate_environment(cls, values: Dict) -> Dict:
             "api_version": values["openai_api_version"],
             "azure_endpoint": values["azure_endpoint"],
             "azure_deployment": values["deployment"],
-            "api_key": values["openai_api_key"],
-            "azure_ad_token": values["azure_ad_token"],
+            "api_key": values["openai_api_key"].get_secret_value()
+            if values["openai_api_key"]
+            else None,
+            "azure_ad_token": values["azure_ad_token"].get_secret_value()
+            if values["azure_ad_token"]
+            else None,
             "azure_ad_token_provider": values["azure_ad_token_provider"],
             "organization": values["openai_organization"],
             "base_url": values["openai_api_base"],

libs/partners/openai/langchain_openai/embeddings/base.py

@@ -22,8 +22,18 @@
 import openai
 import tiktoken
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra, Field, root_validator
-from langchain_core.utils import get_from_dict_or_env, get_pydantic_field_names
+from langchain_core.pydantic_v1 import (
+    BaseModel,
+    Extra,
+    Field,
+    SecretStr,
+    root_validator,
+)
+from langchain_core.utils import (
+    convert_to_secret_str,
+    get_from_dict_or_env,
+    get_pydantic_field_names,
+)
 
 logger = logging.getLogger(__name__)
 
@@ -70,7 +80,7 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
     openai_proxy: Optional[str] = None
     embedding_ctx_length: int = 8191
     """The maximum number of tokens to embed at once."""
-    openai_api_key: Optional[str] = Field(default=None, alias="api_key")
+    openai_api_key: Optional[SecretStr] = Field(default=None, alias="api_key")
     """Automatically inferred from env var `OPENAI_API_KEY` if not provided."""
     openai_organization: Optional[str] = Field(default=None, alias="organization")
     """Automatically inferred from env var `OPENAI_ORG_ID` if not provided."""
@@ -152,9 +162,12 @@ def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:
     @root_validator()
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
-        values["openai_api_key"] = get_from_dict_or_env(
+        openai_api_key = get_from_dict_or_env(
             values, "openai_api_key", "OPENAI_API_KEY"
         )
+        values["openai_api_key"] = (
+            convert_to_secret_str(openai_api_key) if openai_api_key else None
+        )
         values["openai_api_base"] = values["openai_api_base"] or os.getenv(
             "OPENAI_API_BASE"
         )
@@ -196,7 +209,9 @@ def validate_environment(cls, values: Dict) -> Dict:
                 "please use the `AzureOpenAIEmbeddings` class."
             )
         client_params = {
-            "api_key": values["openai_api_key"],
+            "api_key": values["openai_api_key"].get_secret_value()
+            if values["openai_api_key"]
+            else None,
             "organization": values["openai_organization"],
             "base_url": values["openai_api_base"],
             "timeout": values["request_timeout"],

libs/partners/openai/langchain_openai/llms/azure.py

@@ -2,18 +2,11 @@
 
 import logging
 import os
-from typing import (
-    Any,
-    Callable,
-    Dict,
-    List,
-    Mapping,
-    Union,
-)
+from typing import Any, Callable, Dict, List, Mapping, Optional, Union
 
 import openai
-from langchain_core.pydantic_v1 import Field, root_validator
-from langchain_core.utils import get_from_dict_or_env
+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_openai.llms.base import BaseOpenAI
 
@@ -52,9 +45,9 @@ class AzureOpenAI(BaseOpenAI):
     """
     openai_api_version: str = Field(default="", alias="api_version")
     """Automatically inferred from env var `OPENAI_API_VERSION` if not provided."""
-    openai_api_key: Union[str, None] = Field(default=None, alias="api_key")
+    openai_api_key: Optional[SecretStr] = Field(default=None, alias="api_key")
     """Automatically inferred from env var `AZURE_OPENAI_API_KEY` if not provided."""
-    azure_ad_token: Union[str, None] = None
+    azure_ad_token: Optional[SecretStr] = None
     """Your Azure Active Directory token.
 
         Automatically inferred from env var `AZURE_OPENAI_AD_TOKEN` if not provided.
@@ -92,17 +85,21 @@ def validate_environment(cls, values: Dict) -> Dict:
         # Check OPENAI_KEY for backwards compatibility.
         # TODO: Remove OPENAI_API_KEY support to avoid possible conflict when using
         # other forms of azure credentials.
-        values["openai_api_key"] = (
+        openai_api_key = (
             values["openai_api_key"]
             or os.getenv("AZURE_OPENAI_API_KEY")
             or os.getenv("OPENAI_API_KEY")
         )
+        values["openai_api_key"] = (
+            convert_to_secret_str(openai_api_key) if openai_api_key else None
+        )
 
         values["azure_endpoint"] = values["azure_endpoint"] or os.getenv(
             "AZURE_OPENAI_ENDPOINT"
         )
-        values["azure_ad_token"] = values["azure_ad_token"] or os.getenv(
-            "AZURE_OPENAI_AD_TOKEN"
+        azure_ad_token = values["azure_ad_token"] or os.getenv("AZURE_OPENAI_AD_TOKEN")
+        values["azure_ad_token"] = (
+            convert_to_secret_str(azure_ad_token) if azure_ad_token else None
         )
         values["openai_api_base"] = values["openai_api_base"] or os.getenv(
             "OPENAI_API_BASE"
@@ -150,8 +147,12 @@ def validate_environment(cls, values: Dict) -> Dict:
             "api_version": values["openai_api_version"],
             "azure_endpoint": values["azure_endpoint"],
             "azure_deployment": values["deployment_name"],
-            "api_key": values["openai_api_key"],
-            "azure_ad_token": values["azure_ad_token"],
+            "api_key": values["openai_api_key"].get_secret_value()
+            if values["openai_api_key"]
+            else None,
+            "azure_ad_token": values["azure_ad_token"].get_secret_value()
+            if values["azure_ad_token"]
+            else None,
             "azure_ad_token_provider": values["azure_ad_token_provider"],
             "organization": values["openai_organization"],
             "base_url": values["openai_api_base"],

libs/partners/openai/langchain_openai/llms/base.py

@@ -27,8 +27,12 @@
 )
 from langchain_core.language_models.llms import BaseLLM
 from langchain_core.outputs import Generation, GenerationChunk, LLMResult
-from langchain_core.pydantic_v1 import Field, root_validator
-from langchain_core.utils import get_from_dict_or_env, get_pydantic_field_names
+from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
+from langchain_core.utils import (
+    convert_to_secret_str,
+    get_from_dict_or_env,
+    get_pydantic_field_names,
+)
 from langchain_core.utils.utils import build_extra_kwargs
 
 logger = logging.getLogger(__name__)
@@ -104,10 +108,7 @@ def lc_attributes(self) -> Dict[str, Any]:
     """Generates best_of completions server-side and returns the "best"."""
     model_kwargs: Dict[str, Any] = Field(default_factory=dict)
     """Holds any model parameters valid for `create` call not explicitly specified."""
-    # When updating this to use a SecretStr
-    # Check for classes that derive from this class (as some of them
-    # may assume openai_api_key is a str)
-    openai_api_key: Optional[str] = Field(default=None, alias="api_key")
+    openai_api_key: Optional[SecretStr] = Field(default=None, alias="api_key")
     """Automatically inferred from env var `OPENAI_API_KEY` if not provided."""
     openai_api_base: Optional[str] = Field(default=None, alias="base_url")
     """Base URL path for API requests, leave blank if not using a proxy or service 
@@ -175,9 +176,12 @@ def validate_environment(cls, values: Dict) -> Dict:
         if values["streaming"] and values["best_of"] > 1:
             raise ValueError("Cannot stream results when best_of > 1.")
 
-        values["openai_api_key"] = get_from_dict_or_env(
+        openai_api_key = get_from_dict_or_env(
             values, "openai_api_key", "OPENAI_API_KEY"
         )
+        values["openai_api_key"] = (
+            convert_to_secret_str(openai_api_key) if openai_api_key else None
+        )
         values["openai_api_base"] = values["openai_api_base"] or os.getenv(
             "OPENAI_API_BASE"
         )
@@ -194,7 +198,9 @@ def validate_environment(cls, values: Dict) -> Dict:
         )
 
         client_params = {
-            "api_key": values["openai_api_key"],
+            "api_key": values["openai_api_key"].get_secret_value()
+            if values["openai_api_key"]
+            else None,
             "organization": values["openai_organization"],
             "base_url": values["openai_api_base"],
             "timeout": values["request_timeout"],

libs/partners/openai/tests/integration_tests/embeddings/test_azure.py

@@ -22,7 +22,7 @@ def _get_embeddings(**kwargs: Any) -> AzureOpenAIEmbeddings:
     return AzureOpenAIEmbeddings(
         azure_deployment=DEPLOYMENT_NAME,
         api_version=OPENAI_API_VERSION,
-        openai_api_base=OPENAI_API_BASE,
+        azure_endpoint=OPENAI_API_BASE,
         openai_api_key=OPENAI_API_KEY,
         **kwargs,
     )
@@ -109,7 +109,7 @@ def test_azure_openai_embedding_with_empty_string() -> None:
         openai.AzureOpenAI(
             api_version=OPENAI_API_VERSION,
             api_key=OPENAI_API_KEY,
-            base_url=embedding.openai_api_base,
+            azure_endpoint=OPENAI_API_BASE,
             azure_deployment=DEPLOYMENT_NAME,
         )  # type: ignore
         .embeddings.create(input="", model="text-embedding-ada-002")