feat: add proxy configuration for Cohere model (#4152)

api/core/model_runtime/model_providers/cohere/cohere.yaml

         zh_Hans: 在此输入您的 API Key
         en_US: Enter your API Key
       show_on: [ ]
+    - variable: base_url
+      label:
+        zh_Hans: API Base
+        en_US: API Base
+      type: text-input
+      required: false
+      placeholder:
+        zh_Hans: 在此输入您的 API Base，如 https://api.cohere.ai/v1
+        en_US: Enter your API Base, e.g. https://api.cohere.ai/v1
 model_credential_schema:
   model:
     label:
       placeholder:
         zh_Hans: 在此输入您的 API Key
         en_US: Enter your API Key
+    - variable: base_url
+      label:
+        zh_Hans: API Base
+        en_US: API Base
+      type: text-input
+      required: false
+      placeholder:
+        zh_Hans: 在此输入您的 API Base，如 https://api.cohere.ai/v1
+        en_US: Enter your API Base, e.g. https://api.cohere.ai/v1

api/core/model_runtime/model_providers/cohere/llm/llm.py

         :return: full response or stream response chunk generator result
         """
         # initialize client
-        client = cohere.Client(credentials.get('api_key'))
+        client = cohere.Client(credentials.get('api_key'), base_url=credentials.get('base_url'))
 
         if stop:
             model_parameters['end_sequences'] = stop
 
         return response
 
-    def _handle_generate_stream_response(self, model: str, credentials: dict, response: Iterator[GenerateStreamedResponse],
+    def _handle_generate_stream_response(self, model: str, credentials: dict,
+                                         response: Iterator[GenerateStreamedResponse],
                                          prompt_messages: list[PromptMessage]) -> Generator:
         """
         Handle llm stream response
         :return: full response or stream response chunk generator result
         """
         # initialize client
-        client = cohere.Client(credentials.get('api_key'))
+        client = cohere.Client(credentials.get('api_key'), base_url=credentials.get('base_url'))
 
         if stop:
             model_parameters['stop_sequences'] = stop
         :return: number of tokens
         """
         # initialize client
-        client = cohere.Client(credentials.get('api_key'))
+        client = cohere.Client(credentials.get('api_key'), base_url=credentials.get('base_url'))
 
         response = client.tokenize(
             text=text,

api/core/model_runtime/model_providers/cohere/rerank/rerank.py

             )
 
         # initialize client
-        client = cohere.Client(credentials.get('api_key'))
+        client = cohere.Client(credentials.get('api_key'), base_url=credentials.get('base_url'))
         response = client.rerank(
             query=query,
             documents=docs,

api/core/model_runtime/model_providers/cohere/text_embedding/text_embedding.py

             return []
 
         # initialize client
-        client = cohere.Client(credentials.get('api_key'))
+        client = cohere.Client(credentials.get('api_key'), base_url=credentials.get('base_url'))
 
         response = client.tokenize(
             text=text,
         :return: embeddings and used tokens
         """
         # initialize client
-        client = cohere.Client(credentials.get('api_key'))
+        client = cohere.Client(credentials.get('api_key'), base_url=credentials.get('base_url'))
 
         # call embedding model
         response = client.embed(