added text moderation, dimensions to embeddings and new models

serverless_openai/apis.py

@@ -15,6 +15,7 @@ class OpenAIAPI(BaseModel):
     completion_url: HttpUrlString = "https://api.openai.com/v1/chat/completions"
     imagecreation_url: HttpUrlString = "https://api.openai.com/v1/images/generations"
     embeddings_url: HttpUrlString = "https://api.openai.com/v1/embeddings"
+    moderation_url: HttpUrlString = "https://api.openai.com/v1/moderations"
 
 
     @validator('headers', always=True)
@@ -280,12 +281,14 @@ def embeddings(
             self,
             prompt: EmbeddingPrompts,
             model: EmbeddingModels = EmbeddingModels.ada2,
+            dimensions: int = 1536,
             tries: int = 5,
             timeout: int = 500,
         ) -> OpenAIResults:
         data = {
             "model": model,
             "input": prompt,
+            "dimensions": dimensions
         }
 
         res = {}
@@ -298,6 +301,27 @@ def embeddings(
                 print("ERROR:", e)
         return OpenAIResults(result=False, result_json=res)
 
+    def moderation(
+            self,
+            prompt: str,
+            model: ModerationModels = ModerationModels.moderation_latest,
+            tries: int = 5,
+            timeout: int = 500,
+    ) -> OpenAIResults:
+        data = {
+            "model": model,
+            "input": prompt,
+        }
+        res = {}
+        for _ in range(tries):
+            try:
+                res = requests.post(self.moderation_url, headers=self.headers, json=data, timeout=timeout).json()
+                if 'results' in res:
+                    return OpenAIResults(result=res['results'][0]['flagged'], result_json=res)
+            except Exception as e:
+                print("ERROR:", e)
+        return OpenAIResults(result=False, result_json=res)
+
 class ScrapingBeeAPI(BaseModel):
     api_key: str
     scrape_url: HttpUrlString = "https://app.scrapingbee.com/api/v1"

serverless_openai/helpers.py

@@ -25,6 +25,9 @@ class Roles(str, ExtendedEnum):
 class TextCompletionModels(str, ExtendedEnum):
     gpt4_1106 : str = "gpt-4-1106-preview"
     gpt4 : str = "gpt-4"
+    gpt4_turbo : str = "gpt-4-turbo-preview"
+    gpt4_0125 : str = "gpt-4-0125-preview"
+    gpt35_turbo_0125: str = "gpt-3.5-turbo-0125"
     gpt35_turbo_1106 : str = "gpt-3.5-turbo-1106"
     gpt35_turbo_16k : str = "gpt-3.5-turbo-16k"
     gpt35_turbo : str = "gpt-3.5-turbo"
@@ -66,6 +69,10 @@ class EmbeddingModels(str, ExtendedEnum):
 class EmbeddingPrompts(BaseModel):
     prompt: Union[str, List[str]]
 
+class ModerationModels(str, ExtendedEnum):
+    moderation_stable : str = "text-moderation-stable"
+    moderation_latest : str = "text-moderation-latest"
+
 class Similarity(BaseModel):
     vector: List[List[float]]
     matrix: List[List[float]]

setup.py

@@ -1,6 +1,6 @@
 from setuptools import setup, find_packages
 
-VERSION = '1.2.8'
+VERSION = '1.2.9'
 DESCRIPTION = "A package for using Openai in serverless environment"
 LONG_DESCRIPTION = 'A package for using Openai with scraping and etc. in serverless application such as AWS Lambda and GCP Cloud Function'