支持星火认知大模型v2

config.py

@@ -73,7 +73,7 @@ LLM_MODEL = "gpt-3.5-turbo" # 可选 ↓↓↓
 AVAIL_LLM_MODELS = ["gpt-3.5-turbo-16k", "gpt-3.5-turbo", "azure-gpt-3.5", "api2d-gpt-3.5-turbo", 
                     "gpt-4", "api2d-gpt-4", "chatglm", "moss", "newbing", "stack-claude"]
 # P.S. 其他可用的模型还包括 ["qianfan", "llama2", "qwen", "gpt-3.5-turbo-0613", "gpt-3.5-turbo-16k-0613", 
-# "spark", "chatglm_onnx", "claude-1-100k", "claude-2", "internlm", "jittorllms_pangualpha", "jittorllms_llama"]
+# "spark", "sparkv2", "chatglm_onnx", "claude-1-100k", "claude-2", "internlm", "jittorllms_pangualpha", "jittorllms_llama"]
 
 
 # 百度千帆（LLM_MODEL="qianfan"）
@@ -189,7 +189,7 @@ GROBID_URLS = [
 │   ├── AZURE_ENGINE
 │   └── API_URL_REDIRECT
 │
-├── "spark" 星火认知大模型
+├── "spark" 星火认知大模型 spark & sparkv2
 │   ├── XFYUN_APPID
 │   ├── XFYUN_API_SECRET
 │   └── XFYUN_API_KEY

request_llm/bridge_all.py

@@ -398,6 +398,22 @@ if "spark" in AVAIL_LLM_MODELS:   # 讯飞星火认知大模型
         })
     except:
         print(trimmed_format_exc())
+if "sparkv2" in AVAIL_LLM_MODELS:   # 讯飞星火认知大模型
+    try:
+        from .bridge_spark import predict_no_ui_long_connection as spark_noui
+        from .bridge_spark import predict as spark_ui
+        model_info.update({
+            "sparkv2": {
+                "fn_with_ui": spark_ui,
+                "fn_without_ui": spark_noui,
+                "endpoint": None,
+                "max_token": 4096,
+                "tokenizer": tokenizer_gpt35,
+                "token_cnt": get_token_num_gpt35,
+            }
+        })
+    except:
+        print(trimmed_format_exc())
 if "llama2" in AVAIL_LLM_MODELS:   # llama2
     try:
         from .bridge_llama2 import predict_no_ui_long_connection as llama2_noui

request_llm/bridge_spark.py

@@ -30,6 +30,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
         函数的说明请见 request_llm/bridge_all.py
     """
     chatbot.append((inputs, ""))
+    yield from update_ui(chatbot=chatbot, history=history)
 
     if additional_fn is not None:
         from core_functional import handle_core_functionality

request_llm/com_sparkapi.py

@@ -63,6 +63,8 @@ class SparkRequestInstance():
         self.api_secret = XFYUN_API_SECRET
         self.api_key = XFYUN_API_KEY
         self.gpt_url = "ws://spark-api.xf-yun.com/v1.1/chat"
+        self.gpt_url_v2 = "ws://spark-api.xf-yun.com/v2.1/chat"
+
         self.time_to_yield_event = threading.Event()
         self.time_to_exit_event = threading.Event()
 
@@ -83,7 +85,12 @@ class SparkRequestInstance():
 
 
     def create_blocking_request(self, inputs, llm_kwargs, history, system_prompt):
-        wsParam = Ws_Param(self.appid, self.api_key, self.api_secret, self.gpt_url)
+        if llm_kwargs['llm_model'] == 'sparkv2':
+            gpt_url = self.gpt_url_v2
+        else:
+            gpt_url = self.gpt_url
+
+        wsParam = Ws_Param(self.appid, self.api_key, self.api_secret, gpt_url)
         websocket.enableTrace(False)
         wsUrl = wsParam.create_url()
 
@@ -167,7 +174,7 @@ def gen_params(appid, inputs, llm_kwargs, history, system_prompt):
         },
         "parameter": {
             "chat": {
-                "domain": "general",
+                "domain": "generalv2" if llm_kwargs['llm_model'] == 'sparkv2' else "general",
                 "temperature": llm_kwargs["temperature"],
                 "random_threshold": 0.5,
                 "max_tokens": 4096,