fix: remove openllm pypi package because of this package too large (#931)

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

@@ -1,13 +1,13 @@
 from typing import List, Optional, Any
 
 from langchain.callbacks.manager import Callbacks
-from langchain.llms import OpenLLM
 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
 from core.model_providers.models.entity.model_params import ModelMode, ModelKwargs
+from core.third_party.langchain.llms.openllm import OpenLLM
 
 
 class OpenLLMModel(BaseLLM):
@@ -19,7 +19,7 @@ class OpenLLMModel(BaseLLM):
         client = OpenLLM(
             server_url=self.credentials.get('server_url'),
             callbacks=self.callbacks,
-            **self.provider_model_kwargs
+            llm_kwargs=self.provider_model_kwargs
         )
 
         return client

api/core/model_providers/providers/openllm_provider.py

@@ -1,14 +1,13 @@
 import json
 from typing import Type
 
-from langchain.llms import OpenLLM
-
 from core.helper import encrypter
 from core.model_providers.models.entity.model_params import KwargRule, ModelKwargsRules, ModelType
 from core.model_providers.models.llm.openllm_model import OpenLLMModel
 from core.model_providers.providers.base import BaseModelProvider, CredentialsValidateFailedError
 
 from core.model_providers.models.base import BaseProviderModel
+from core.third_party.langchain.llms.openllm import OpenLLM
 from models.provider import ProviderType
 
 
@@ -46,11 +45,11 @@ class OpenLLMProvider(BaseModelProvider):
         :return:
         """
         return ModelKwargsRules(
-            temperature=KwargRule[float](min=0, max=2, default=1),
+            temperature=KwargRule[float](min=0.01, max=2, default=1),
             top_p=KwargRule[float](min=0, max=1, default=0.7),
             presence_penalty=KwargRule[float](min=-2, max=2, default=0),
             frequency_penalty=KwargRule[float](min=-2, max=2, default=0),
-            max_tokens=KwargRule[int](min=10, max=4000, default=128),
+            max_tokens=KwargRule[int](alias='max_new_tokens', min=10, max=4000, default=128),
         )
 
     @classmethod
@@ -71,7 +70,9 @@ class OpenLLMProvider(BaseModelProvider):
             }
 
             llm = OpenLLM(
-                max_tokens=10,
+                llm_kwargs={
+                    'max_new_tokens': 10
+                },
                 **credential_kwargs
             )