feat: refactor SiliconCloudEmbeddingModel to include optional parameters and improve API integration

Author: wxg0103

apps/models_provider/impl/siliconCloud_model_provider/model/embedding.py

@@ -3,40 +3,55 @@
     @project: MaxKB
     @Author：虎
     @file： embedding.py
-    @date：2024/7/12 17:44
+    @date：2024/10/16 16:34
     @desc:
 """
-from typing import Dict
+from typing import Dict, List
 
 import requests
-from langchain_community.embeddings import OpenAIEmbeddings
 
-from common.utils.logger import maxkb_logger
 from models_provider.base_model_provider import MaxKBBaseModel
 
 
-class SiliconCloudEmbeddingModel(MaxKBBaseModel, OpenAIEmbeddings):
+class SiliconCloudEmbeddingModel(MaxKBBaseModel):
+    model_name: str
+    openai_api_key: str
+    base_url: str
+    optional_params: dict
+
+    def __init__(self, api_key, model_name: str, base_url, optional_params: dict):
+        self.openai_api_key = api_key
+        self.base_url = base_url
+        self.model_name = model_name
+        self.optional_params = optional_params
+
+    def is_cache_model(self):
+        return False
+
     @staticmethod
     def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs):
+        optional_params = MaxKBBaseModel.filter_optional_params(model_kwargs)
         return SiliconCloudEmbeddingModel(
-            openai_api_key=model_credential.get('api_key'),
-            model=model_name,
-            openai_api_base=model_credential.get('api_base'),
+            api_key=model_credential.get('api_key'),
+            model_name=model_name,
+            optional_params=optional_params,
+            base_url=model_credential.get('api_base'),
         )
 
     def embed_query(self, text: str) -> list:
         payload = {
-            "model": self.model,
-            "input": text
+            "model": self.model_name,
+            "input": text,
+            **self.optional_params
         }
         headers = {
             "Authorization": f"Bearer {self.openai_api_key}",
             "Content-Type": "application/json"
         }
 
-        response = requests.post(self.openai_api_base + '/embeddings', json=payload, headers=headers)
+        response = requests.post(self.base_url + '/embeddings', json=payload, headers=headers)
+        print(response.text)
         data = response.json()
-        # print(data)
         if data['data'] is None or 'code' in data:
             raise ValueError(f"Embedding API returned no data: {data}")
         # 假设返回结构中有 'data[0].embedding'