x

libs/community/langchain_community/chat_models/jinachat.py

@@ -217,7 +217,7 @@ class JinaChat(BaseChatModel):
         values["model_kwargs"] = extra
         return values
 
-    @root_validator()
+    @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         values["jinachat_api_key"] = convert_to_secret_str(

libs/community/langchain_community/chat_models/kinetica.py

@@ -341,7 +341,7 @@ class ChatKinetica(BaseChatModel):
     kdbc: Any = Field(exclude=True)
     """ Kinetica DB connection. """
 
-    @root_validator()
+    @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:
         """Pydantic object validator."""
 

libs/community/langchain_community/chat_models/konko.py

@@ -84,8 +84,8 @@ class ChatKonko(ChatOpenAI):
     max_tokens: int = 20
     """Maximum number of tokens to generate."""
 
-    @root_validator()
-    def validate_environment(cls, values: Dict) -> Dict:
+    @root_validator(pre=True)
+    def pre_init(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         values["konko_api_key"] = convert_to_secret_str(
             get_from_dict_or_env(values, "konko_api_key", "KONKO_API_KEY")
@@ -115,7 +115,10 @@ class ChatKonko(ChatOpenAI):
                 "You are using an older version of the 'konko' package. "
                 "Please consider upgrading to access new features."
             )
+        return values
 
+    @root_validator(pre=False, skip_on_failure=True)
+    def validate_n(cls, values: Dict) -> Dict:
         if values["n"] < 1:
             raise ValueError("n must be at least 1.")
         if values["n"] > 1 and values["streaming"]:

libs/community/langchain_community/chat_models/litellm.py

@@ -239,7 +239,7 @@ class ChatLiteLLM(BaseChatModel):
 
         return _completion_with_retry(**kwargs)
 
-    @root_validator()
+    @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate api key, python package exists, temperature, top_p, and top_k."""
         try:
@@ -275,6 +275,11 @@ class ChatLiteLLM(BaseChatModel):
             values, "together_ai_api_key", "TOGETHERAI_API_KEY", default=""
         )
         values["client"] = litellm
+        return values
+
+    @root_validator(pre=False, skip_on_failure=True)
+    def post_init(cls, values: Dict) -> Dict:
+        """Validate api key, python package exists, temperature, top_p, and top_k."""
 
         if values["temperature"] is not None and not 0 <= values["temperature"] <= 1:
             raise ValueError("temperature must be in the range [0.0, 1.0]")

libs/community/langchain_community/chat_models/moonshot.py

@@ -28,7 +28,7 @@ class MoonshotChat(MoonshotCommon, ChatOpenAI):  # type: ignore[misc]
             moonshot = MoonshotChat(model="moonshot-v1-8k")
     """
 
-    @root_validator()
+    @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that the environment is set up correctly."""
         values["moonshot_api_key"] = convert_to_secret_str(

libs/community/langchain_community/chat_models/octoai.py

@@ -47,7 +47,7 @@ class ChatOctoAI(ChatOpenAI):
     def is_lc_serializable(cls) -> bool:
         return False
 
-    @root_validator()
+    @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         values["octoai_api_base"] = get_from_dict_or_env(

libs/community/langchain_community/chat_models/openai.py

@@ -145,6 +145,9 @@ def _convert_delta_to_message_chunk(
         return default_class(content=content)  # type: ignore[call-arg]
 
 
+DEFAULT_MAX_RETRIES = 2
+
+
 @deprecated(
     since="0.0.10", removal="0.3.0", alternative_import="langchain_openai.ChatOpenAI"
 )
@@ -218,7 +221,7 @@ class ChatOpenAI(BaseChatModel):
     )
     """Timeout for requests to OpenAI completion API. Can be float, httpx.Timeout or 
         None."""
-    max_retries: int = Field(default=2)
+    max_retries: int = Field(default=DEFAULT_MAX_RETRIES)
     """Maximum number of retries to make when generating."""
     streaming: bool = False
     """Whether to stream the results or not."""
@@ -274,14 +277,9 @@ class ChatOpenAI(BaseChatModel):
         values["model_kwargs"] = extra
         return values
 
-    @root_validator()
-    def validate_environment(cls, values: Dict) -> Dict:
+    @root_validator(pre=True)
+    def pre_init(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
-        if values["n"] < 1:
-            raise ValueError("n must be at least 1.")
-        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"
         )
@@ -291,7 +289,7 @@ class ChatOpenAI(BaseChatModel):
             or os.getenv("OPENAI_ORG_ID")
             or os.getenv("OPENAI_ORGANIZATION")
         )
-        values["openai_api_base"] = values["openai_api_base"] or os.getenv(
+        values["openai_api_base"] = values.get("openai_api_base") or os.getenv(
             "OPENAI_API_BASE"
         )
         values["openai_proxy"] = get_from_dict_or_env(
@@ -311,14 +309,14 @@ class ChatOpenAI(BaseChatModel):
 
         if is_openai_v1():
             client_params = {
-                "api_key": values["openai_api_key"],
-                "organization": values["openai_organization"],
-                "base_url": values["openai_api_base"],
-                "timeout": values["request_timeout"],
-                "max_retries": values["max_retries"],
-                "default_headers": values["default_headers"],
-                "default_query": values["default_query"],
-                "http_client": values["http_client"],
+                "api_key": values.get("openai_api_key"),
+                "organization": values.get("openai_organization"),
+                "base_url": values.get("openai_api_base"),
+                "timeout": values.get("request_timeout"),
+                "max_retries": values.get("max_retries", DEFAULT_MAX_RETRIES),
+                "default_headers": values.get("default_headers"),
+                "default_query": values.get("default_query"),
+                "http_client": values.get("http_client"),
             }
 
             if not values.get("client"):
@@ -333,6 +331,14 @@ class ChatOpenAI(BaseChatModel):
             pass
         return values
 
+    @root_validator(pre=True, skip_on_failure=True)
+    def validate_environment(self, values: Dict) -> Dict:
+        if values["n"] < 1:
+            raise ValueError("n must be at least 1.")
+        if values["n"] > 1 and values["streaming"]:
+            raise ValueError("n must be 1 when streaming.")
+        return values
+
     @property
     def _default_params(self) -> Dict[str, Any]:
         """Get the default parameters for calling OpenAI API."""

libs/community/langchain_community/chat_models/yuan2.py

@@ -169,7 +169,7 @@ class ChatYuan2(BaseChatModel):
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         values["yuan2_api_key"] = get_from_dict_or_env(
-            values, "yuan2_api_key", "YUAN2_API_KEY"
+            values, "yuan2_api_key", "YUAN2_API_KEY", default="EMPTY"
         )
 
         try:

libs/community/langchain_community/embeddings/azure_openai.py

@@ -96,8 +96,7 @@ class AzureOpenAIEmbeddings(OpenAIEmbeddings):
         # See: https://learn.microsoft.com/en-us/azure/ai-services/openai/reference#embeddings
         values["chunk_size"] = min(values["chunk_size"], 16)
         try:
-            import openai
-
+            import openai  # noqa: F401
         except ImportError:
             raise ImportError(
                 "Could not import openai python package. "