feat: add zhipuai (#1188)

api/core/helper/moderation.py

@@ -1,32 +1,34 @@
 import logging
 
 import openai
-from flask import current_app
 
 from core.model_providers.error import LLMBadRequestError
 from core.model_providers.providers.base import BaseModelProvider
+from core.model_providers.providers.hosted import hosted_config, hosted_model_providers
 from models.provider import ProviderType
 
 
 def check_moderation(model_provider: BaseModelProvider, text: str) -> bool:
-    if current_app.config['HOSTED_MODERATION_ENABLED'] and current_app.config['HOSTED_MODERATION_PROVIDERS']:
-        moderation_providers = current_app.config['HOSTED_MODERATION_PROVIDERS'].split(',')
-
+    if hosted_config.moderation.enabled is True and hosted_model_providers.openai:
         if model_provider.provider.provider_type == ProviderType.SYSTEM.value \
-                and model_provider.provider_name in moderation_providers:
+                and model_provider.provider_name in hosted_config.moderation.providers:
             # 2000 text per chunk
             length = 2000
-            chunks = [text[i:i + length] for i in range(0, len(text), length)]
+            text_chunks = [text[i:i + length] for i in range(0, len(text), length)]
 
-            try:
-                moderation_result = openai.Moderation.create(input=chunks,
-                                                             api_key=current_app.config['HOSTED_OPENAI_API_KEY'])
-            except Exception as ex:
-                logging.exception(ex)
-                raise LLMBadRequestError('Rate limit exceeded, please try again later.')
+            max_text_chunks = 32
+            chunks = [text_chunks[i:i + max_text_chunks] for i in range(0, len(text_chunks), max_text_chunks)]
 
-            for result in moderation_result.results:
-                if result['flagged'] is True:
-                    return False
+            for text_chunk in chunks:
+                try:
+                    moderation_result = openai.Moderation.create(input=text_chunk,
+                                                                 api_key=hosted_model_providers.openai.api_key)
+                except Exception as ex:
+                    logging.exception(ex)
+                    raise LLMBadRequestError('Rate limit exceeded, please try again later.')
+
+                for result in moderation_result.results:
+                    if result['flagged'] is True:
+                        return False
 
     return True