langchain: cherry-pick moderation fix into v0.1 (#21544)

```
git checkout v0.1
git pull
git checkout -b cc/cherry_pick_into_v01
git cherry-pick d3ca2cc
```

Co-authored-by: Matt Florence <matt@mattflo.com>
Co-authored-by: Emilia Katari <emilia@outpace.com>
Co-authored-by: Erick Friis <erickfriis@gmail.com>
Co-authored-by: Erick Friis <erick@langchain.dev>

libs/langchain/langchain/chains/moderation.py

@@ -1,9 +1,13 @@
 """Pass input through a moderation endpoint."""
+
 from typing import Any, Dict, List, Optional
 
-from langchain_core.callbacks import CallbackManagerForChainRun
-from langchain_core.pydantic_v1 import root_validator
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.callbacks import (
+    AsyncCallbackManagerForChainRun,
+    CallbackManagerForChainRun,
+)
+from langchain_core.pydantic_v1 import Field, root_validator
+from langchain_core.utils import check_package_version, get_from_dict_or_env
 
 from langchain.chains.base import Chain
 
@@ -25,6 +29,7 @@ class OpenAIModerationChain(Chain):
     """
 
     client: Any  #: :meta private:
+    async_client: Any  #: :meta private:
     model_name: Optional[str] = None
     """Moderation model name to use."""
     error: bool = False
@@ -33,6 +38,7 @@ class OpenAIModerationChain(Chain):
     output_key: str = "output"  #: :meta private:
     openai_api_key: Optional[str] = None
     openai_organization: Optional[str] = None
+    _openai_pre_1_0: bool = Field(default=None)
 
     @root_validator()
     def validate_environment(cls, values: Dict) -> Dict:
@@ -52,7 +58,16 @@ def validate_environment(cls, values: Dict) -> Dict:
             openai.api_key = openai_api_key
             if openai_organization:
                 openai.organization = openai_organization
-            values["client"] = openai.Moderation  # type: ignore
+            values["_openai_pre_1_0"] = False
+            try:
+                check_package_version("openai", gte_version="1.0")
+            except ValueError:
+                values["_openai_pre_1_0"] = True
+            if values["_openai_pre_1_0"]:
+                values["client"] = openai.Moderation
+            else:
+                values["client"] = openai.OpenAI()
+                values["async_client"] = openai.AsyncOpenAI()
         except ImportError:
             raise ImportError(
                 "Could not import openai python package. "
@@ -76,8 +91,12 @@ def output_keys(self) -> List[str]:
         """
         return [self.output_key]
 
-    def _moderate(self, text: str, results: dict) -> str:
-        if results["flagged"]:
+    def _moderate(self, text: str, results: Any) -> str:
+        if self._openai_pre_1_0:
+            condition = results["flagged"]
+        else:
+            condition = results.flagged
+        if condition:
             error_str = "Text was found that violates OpenAI's content policy."
             if self.error:
                 raise ValueError(error_str)
@@ -87,10 +106,26 @@ def _moderate(self, text: str, results: dict) -> str:
 
     def _call(
         self,
-        inputs: Dict[str, str],
+        inputs: Dict[str, Any],
         run_manager: Optional[CallbackManagerForChainRun] = None,
-    ) -> Dict[str, str]:
+    ) -> Dict[str, Any]:
+        text = inputs[self.input_key]
+        if self._openai_pre_1_0:
+            results = self.client.create(text)
+            output = self._moderate(text, results["results"][0])
+        else:
+            results = self.client.moderations.create(input=text)
+            output = self._moderate(text, results.results[0])
+        return {self.output_key: output}
+
+    async def _acall(
+        self,
+        inputs: Dict[str, Any],
+        run_manager: Optional[AsyncCallbackManagerForChainRun] = None,
+    ) -> Dict[str, Any]:
+        if self._openai_pre_1_0:
+            return await super()._acall(inputs, run_manager=run_manager)
         text = inputs[self.input_key]
-        results = self.client.create(text)
-        output = self._moderate(text, results["results"][0])
+        results = await self.async_client.moderations.create(input=text)
+        output = self._moderate(text, results.results[0])
         return {self.output_key: output}