community[patch]: make ak and sk optional in qianfan endpoint (#14835)

- **Description:** The Qianfan SDK offers multiple authentication
methods, but in the `QianfanEndpoint` of Langchain, it currently only
supports authentication through AK and SK. In order to accommodate users
who wish to use alternative authentication methods, this pull request
makes AK and SK optional. This change should not impact existing users,
while allowing users to configure other authentication methods as per
the Qianfan SDK documentation.
  - **Issue:** /
  - **Dependencies:** No
  - **Tag maintainer:** No
  - **Twitter handle:**

libs/community/langchain_community/chat_models/baidu_qianfan_endpoint.py

@@ -122,6 +122,7 @@ class QianfanChatEndpoint(BaseChatModel):
                 values,
                 "qianfan_ak",
                 "QIANFAN_AK",
+                default="",
             )
         )
         values["qianfan_sk"] = convert_to_secret_str(
@@ -129,14 +130,17 @@ class QianfanChatEndpoint(BaseChatModel):
                 values,
                 "qianfan_sk",
                 "QIANFAN_SK",
+                default="",
             )
         )
         params = {
-            "ak": values["qianfan_ak"].get_secret_value(),
-            "sk": values["qianfan_sk"].get_secret_value(),
             "model": values["model"],
             "stream": values["streaming"],
         }
+        if values["qianfan_ak"].get_secret_value() != "":
+            params["ak"] = values["qianfan_ak"].get_secret_value()
+        if values["qianfan_sk"].get_secret_value() != "":
+            params["sk"] = values["qianfan_sk"].get_secret_value()
         if values["endpoint"] is not None and values["endpoint"] != "":
             params["endpoint"] = values["endpoint"]
         try:

libs/community/langchain_community/embeddings/baidu_qianfan_endpoint.py

@@ -5,7 +5,7 @@ from typing import Any, Dict, List, Optional
 
 from langchain_core.embeddings import Embeddings
 from langchain_core.pydantic_v1 import BaseModel, root_validator
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
 
 logger = logging.getLogger(__name__)
 
@@ -67,25 +67,33 @@ class QianfanEmbeddingsEndpoint(BaseModel, Embeddings):
             ValueError: qianfan package not found, please install it with `pip install
             qianfan`
         """
-        values["qianfan_ak"] = get_from_dict_or_env(
-            values,
-            "qianfan_ak",
-            "QIANFAN_AK",
+        values["qianfan_ak"] = convert_to_secret_str(
+            get_from_dict_or_env(
+                values,
+                "qianfan_ak",
+                "QIANFAN_AK",
+                default="",
+            )
         )
-        values["qianfan_sk"] = get_from_dict_or_env(
-            values,
-            "qianfan_sk",
-            "QIANFAN_SK",
+        values["qianfan_sk"] = convert_to_secret_str(
+            get_from_dict_or_env(
+                values,
+                "qianfan_sk",
+                "QIANFAN_SK",
+                default="",
+            )
         )
 
         try:
             import qianfan
 
             params = {
-                "ak": values["qianfan_ak"],
-                "sk": values["qianfan_sk"],
                 "model": values["model"],
             }
+            if values["qianfan_ak"].get_secret_value() != "":
+                params["ak"] = values["qianfan_ak"].get_secret_value()
+            if values["qianfan_sk"].get_secret_value() != "":
+                params["sk"] = values["qianfan_sk"].get_secret_value()
             if values["endpoint"] is not None and values["endpoint"] != "":
                 params["endpoint"] = values["endpoint"]
             values["client"] = qianfan.Embedding(**params)

libs/community/langchain_community/llms/baidu_qianfan_endpoint.py

@@ -17,7 +17,7 @@ from langchain_core.callbacks import (
 from langchain_core.language_models.llms import LLM
 from langchain_core.outputs import GenerationChunk
 from langchain_core.pydantic_v1 import Field, root_validator
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
 
 logger = logging.getLogger(__name__)
 
@@ -73,22 +73,30 @@ class QianfanLLMEndpoint(LLM):
 
     @root_validator()
     def validate_environment(cls, values: Dict) -> Dict:
-        values["qianfan_ak"] = get_from_dict_or_env(
-            values,
-            "qianfan_ak",
-            "QIANFAN_AK",
+        values["qianfan_ak"] = convert_to_secret_str(
+            get_from_dict_or_env(
+                values,
+                "qianfan_ak",
+                "QIANFAN_AK",
+                default="",
+            )
         )
-        values["qianfan_sk"] = get_from_dict_or_env(
-            values,
-            "qianfan_sk",
-            "QIANFAN_SK",
+        values["qianfan_sk"] = convert_to_secret_str(
+            get_from_dict_or_env(
+                values,
+                "qianfan_sk",
+                "QIANFAN_SK",
+                default="",
+            )
         )
 
         params = {
-            "ak": values["qianfan_ak"],
-            "sk": values["qianfan_sk"],
             "model": values["model"],
         }
+        if values["qianfan_ak"].get_secret_value() != "":
+            params["ak"] = values["qianfan_ak"].get_secret_value()
+        if values["qianfan_sk"].get_secret_value() != "":
+            params["sk"] = values["qianfan_sk"].get_secret_value()
         if values["endpoint"] is not None and values["endpoint"] != "":
             params["endpoint"] = values["endpoint"]
         try: