Merge branch 'master' into frontier

config.py

@@ -87,7 +87,7 @@ AVAIL_LLM_MODELS = ["gpt-3.5-turbo-16k", "gpt-3.5-turbo", "azure-gpt-3.5",
                     "api2d-gpt-3.5-turbo", 'api2d-gpt-3.5-turbo-16k', "api2d-gpt-4",
                     "gpt-4", "gpt-4-32k", "azure-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",  "gpt-3.5-random"
-# "spark", "sparkv2", "chatglm_onnx", "claude-1-100k", "claude-2", "internlm", "jittorllms_pangualpha", "jittorllms_llama"]
+# "spark", "sparkv2", "sparkv3", "chatglm_onnx", "claude-1-100k", "claude-2", "internlm", "jittorllms_pangualpha", "jittorllms_llama"]
 
 
 # 百度千帆（LLM_MODEL="qianfan"）

request_llm/bridge_all.py

@@ -451,6 +451,22 @@ if "sparkv2" in AVAIL_LLM_MODELS:   # 讯飞星火认知大模型
         })
     except:
         print(trimmed_format_exc())
+if "sparkv3" 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({
+            "sparkv3": {
+                "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_chatglmft.py

@@ -87,7 +87,7 @@ class GetGLMFTHandle(Process):
                             new_prefix_state_dict[k[len("transformer.prefix_encoder."):]] = v
                     model.transformer.prefix_encoder.load_state_dict(new_prefix_state_dict)
 
-                    if model_args['quantization_bit'] is not None:
+                    if model_args['quantization_bit'] is not None and model_args['quantization_bit'] != 0:
                         print(f"Quantized to {model_args['quantization_bit']} bit")
                         model = model.quantize(model_args['quantization_bit'])
                     model = model.cuda()

request_llm/bridge_newbingfree.py

@@ -141,10 +141,10 @@ class NewBingHandle(Process):
             except:
                 self.success = False
                 tb_str = '\n```\n' + trimmed_format_exc() + '\n```\n'
-                self.child.send(f'[Local Message] 不能加载Newbing组件。{tb_str}')
+                self.child.send(f'[Local Message] 不能加载Newbing组件，请注意Newbing组件已不再维护。{tb_str}')
                 self.child.send('[Fail]')
                 self.child.send('[Finish]')
-                raise RuntimeError(f"不能加载Newbing组件。")
+                raise RuntimeError(f"不能加载Newbing组件，请注意Newbing组件已不再维护。")
 
         self.success = True
         try:

request_llm/com_sparkapi.py

@@ -64,6 +64,7 @@ class SparkRequestInstance():
         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.gpt_url_v3 = "ws://spark-api.xf-yun.com/v3.1/chat"
 
         self.time_to_yield_event = threading.Event()
         self.time_to_exit_event = threading.Event()
@@ -87,6 +88,8 @@ class SparkRequestInstance():
     def create_blocking_request(self, inputs, llm_kwargs, history, system_prompt):
         if llm_kwargs['llm_model'] == 'sparkv2':
             gpt_url = self.gpt_url_v2
+        elif llm_kwargs['llm_model'] == 'sparkv3':
+            gpt_url = self.gpt_url_v3
         else:
             gpt_url = self.gpt_url
 
@@ -168,6 +171,11 @@ def gen_params(appid, inputs, llm_kwargs, history, system_prompt):
     """
     通过appid和用户的提问来生成请参数
     """
+    domains = {
+        "spark": "general",
+        "sparkv2": "generalv2",
+        "sparkv3": "generalv3",
+    }
     data = {
         "header": {
             "app_id": appid,
@@ -175,7 +183,7 @@ def gen_params(appid, inputs, llm_kwargs, history, system_prompt):
         },
         "parameter": {
             "chat": {
-                "domain": "generalv2" if llm_kwargs['llm_model'] == 'sparkv2' else "general",
+                "domain": domains[llm_kwargs['llm_model']],
                 "temperature": llm_kwargs["temperature"],
                 "random_threshold": 0.5,
                 "max_tokens": 4096,