feat: optimize hf inference endpoint (#975)

api/core/model_providers/models/llm/huggingface_hub_model.py

@@ -1,16 +1,14 @@
-import decimal
-from functools import wraps
 from typing import List, Optional, Any
 
 from langchain import HuggingFaceHub
 from langchain.callbacks.manager import Callbacks
-from langchain.llms import HuggingFaceEndpoint
 from langchain.schema import LLMResult
 
 from core.model_providers.error import LLMBadRequestError
 from core.model_providers.models.llm.base import BaseLLM
-from core.model_providers.models.entity.message import PromptMessage, MessageType
+from core.model_providers.models.entity.message import PromptMessage
 from core.model_providers.models.entity.model_params import ModelMode, ModelKwargs
+from core.third_party.langchain.llms.huggingface_endpoint_llm import HuggingFaceEndpointLLM
 
 
 class HuggingfaceHubModel(BaseLLM):
@@ -19,12 +17,12 @@ class HuggingfaceHubModel(BaseLLM):
     def _init_client(self) -> Any:
         provider_model_kwargs = self._to_model_kwargs_input(self.model_rules, self.model_kwargs)
         if self.credentials['huggingfacehub_api_type'] == 'inference_endpoints':
-            client = HuggingFaceEndpoint(
+            client = HuggingFaceEndpointLLM(
                 endpoint_url=self.credentials['huggingfacehub_endpoint_url'],
-                task='text2text-generation',
+                task=self.credentials['task_type'],
                 model_kwargs=provider_model_kwargs,
                 huggingfacehub_api_token=self.credentials['huggingfacehub_api_token'],
-                callbacks=self.callbacks,
+                callbacks=self.callbacks
             )
         else:
             client = HuggingFaceHub(