添加接入 火山引擎在线大模型 内容的支持 (#2165)

* use oai adaptive bridge function to handle vol engine

* add vol engine deepseek v3

---------

Co-authored-by: binary-husky <qingxu.fu@outlook.com>

request_llms/oai_std_model_template.py

@@ -57,7 +57,7 @@ def decode_chunk(chunk):
             finish_reason = chunk["error"]["code"]
         except:
             finish_reason = "API_ERROR"
-        return response, reasoning_content, finish_reason
+        return response, reasoning_content, finish_reason, str(chunk)
 
     try:
         if chunk["choices"][0]["delta"]["content"] is not None:
@@ -122,7 +122,8 @@ def generate_message(input, model, key, history, max_output_token, system_prompt
 def get_predict_function(
         api_key_conf_name,
         max_output_token,
-        disable_proxy = False
+        disable_proxy = False,
+        model_remove_prefix = [],
     ):
     """
     为openai格式的API生成响应函数，其中传入参数：
@@ -137,6 +138,16 @@ def get_predict_function(
 
     APIKEY = get_conf(api_key_conf_name)
 
+    def remove_prefix(model_name):
+        # 去除模型名字的前缀，输入 volcengine-deepseek-r1-250120 会返回 deepseek-r1-250120
+        if not model_remove_prefix:
+            return model_name
+        model_without_prefix = model_name
+        for prefix in model_remove_prefix:
+            if model_without_prefix.startswith(prefix):
+                model_without_prefix = model_without_prefix[len(prefix):]
+        return model_without_prefix
+
     def predict_no_ui_long_connection(
         inputs,
         llm_kwargs,
@@ -164,9 +175,11 @@ def get_predict_function(
             raise RuntimeError(f"APIKEY为空,请检查配置文件的{APIKEY}")
         if inputs == "":
             inputs = "你好👋"
+
+
         headers, payload = generate_message(
             input=inputs,
-            model=llm_kwargs["llm_model"],
+            model=remove_prefix(llm_kwargs["llm_model"]),
             key=APIKEY,
             history=history,
             max_output_token=max_output_token,
@@ -302,7 +315,7 @@ def get_predict_function(
 
         headers, payload = generate_message(
             input=inputs,
-            model=llm_kwargs["llm_model"],
+            model=remove_prefix(llm_kwargs["llm_model"]),
             key=APIKEY,
             history=history,
             max_output_token=max_output_token,