add paramter max_tokens to 4 chat api with default value 1024 (#1744)

server/chat/agent_chat.py

@@ -25,6 +25,7 @@ async def agent_chat(query: str = Body(..., description="用户输入", examples
                      stream: bool = Body(False, description="流式输出"),
                      model_name: str = Body(LLM_MODEL, description="LLM 模型名称。"),
                      temperature: float = Body(TEMPERATURE, description="LLM 采样温度", ge=0.0, le=1.0),
+                     max_tokens: int = Body(1024, description="限制LLM生成Token数量，当前默认为1024"), # TODO: fastchat更新后默认值设为None，自动使用LLM支持的最大值。
                      prompt_name: str = Body("agent_chat",
                                              description="使用的prompt模板名称(在configs/prompt_config.py中配置)"),
                      # top_p: float = Body(TOP_P, description="LLM 核采样。勿与temperature同时设置", gt=0.0, lt=1.0),
@@ -41,6 +42,7 @@ async def agent_chat_iterator(
         model = get_ChatOpenAI(
             model_name=model_name,
             temperature=temperature,
+            max_tokens=max_tokens,
         )
 
         prompt_template = CustomPromptTemplate(

server/chat/chat.py

@@ -22,6 +22,7 @@ async def chat(query: str = Body(..., description="用户输入", examples=["恼
                 stream: bool = Body(False, description="流式输出"),
                 model_name: str = Body(LLM_MODEL, description="LLM 模型名称。"),
                 temperature: float = Body(TEMPERATURE, description="LLM 采样温度", ge=0.0, le=1.0),
+                max_tokens: int = Body(1024, description="限制LLM生成Token数量，当前默认为1024"), # TODO: fastchat更新后默认值设为None，自动使用LLM支持的最大值。
                 # top_p: float = Body(TOP_P, description="LLM 核采样。勿与temperature同时设置", gt=0.0, lt=1.0),
                 prompt_name: str = Body("llm_chat", description="使用的prompt模板名称(在configs/prompt_config.py中配置)"),
          ):
@@ -36,6 +37,7 @@ async def chat_iterator(query: str,
         model = get_ChatOpenAI(
             model_name=model_name,
             temperature=temperature,
+            max_tokens=max_tokens,
             callbacks=[callback],
         )
 

server/chat/knowledge_base_chat.py

@@ -31,6 +31,7 @@ async def knowledge_base_chat(query: str = Body(..., description="用户输入",
                             stream: bool = Body(False, description="流式输出"),
                             model_name: str = Body(LLM_MODEL, description="LLM 模型名称。"),
                             temperature: float = Body(TEMPERATURE, description="LLM 采样温度", ge=0.0, le=1.0),
+                            max_tokens: int = Body(1024, description="限制LLM生成Token数量，当前默认为1024"), # TODO: fastchat更新后默认值设为None，自动使用LLM支持的最大值。
                             prompt_name: str = Body("knowledge_base_chat", description="使用的prompt模板名称(在configs/prompt_config.py中配置)"),
                             local_doc_url: bool = Body(False, description="知识文件返回本地路径(true)或URL(false)"),
                             request: Request = None,
@@ -51,6 +52,7 @@ async def knowledge_base_chat_iterator(query: str,
         model = get_ChatOpenAI(
             model_name=model_name,
             temperature=temperature,
+            max_tokens=max_tokens,
             callbacks=[callback],
         )
         docs = search_docs(query, knowledge_base_name, top_k, score_threshold)

server/chat/search_engine_chat.py

@@ -72,6 +72,7 @@ async def search_engine_chat(query: str = Body(..., description="用户输入",
                             stream: bool = Body(False, description="流式输出"),
                             model_name: str = Body(LLM_MODEL, description="LLM 模型名称。"),
                             temperature: float = Body(TEMPERATURE, description="LLM 采样温度", ge=0.0, le=1.0),
+                            max_tokens: int = Body(1024, description="限制LLM生成Token数量，当前默认为1024"), # TODO: fastchat更新后默认值设为None，自动使用LLM支持的最大值。
                             prompt_name: str = Body("knowledge_base_chat", description="使用的prompt模板名称(在configs/prompt_config.py中配置)"),
                        ):
     if search_engine_name not in SEARCH_ENGINES.keys():
@@ -93,6 +94,7 @@ async def search_engine_chat_iterator(query: str,
         model = get_ChatOpenAI(
             model_name=model_name,
             temperature=temperature,
+            max_tokens=max_tokens,
             callbacks=[callback],
         )
 

server/utils.py

@@ -34,6 +34,7 @@ async def wrap_done(fn: Awaitable, event: asyncio.Event):
 def get_ChatOpenAI(
         model_name: str,
         temperature: float,
+        max_tokens: int = None,
         streaming: bool = True,
         callbacks: List[Callable] = [],
         verbose: bool = True,
@@ -48,6 +49,7 @@ def get_ChatOpenAI(
         openai_api_base=config.get("api_base_url", fschat_openai_api_address()),
         model_name=model_name,
         temperature=temperature,
+        max_tokens=max_tokens,
         openai_proxy=config.get("openai_proxy"),
         **kwargs
     )
@@ -144,7 +146,7 @@ def run_async(cor):
     return loop.run_until_complete(cor)
 
 
-def iter_over_async(ait, loop):
+def iter_over_async(ait, loop=None):
     '''
     将异步生成器封装成同步生成器.
     '''
@@ -157,6 +159,12 @@ async def get_next():
         except StopAsyncIteration:
             return True, None
 
+    if loop is None:
+        try:
+            loop = asyncio.get_event_loop()
+        except:
+            loop = asyncio.new_event_loop()
+
     while True:
         done, obj = loop.run_until_complete(get_next())
         if done:

webui_pages/dialogue/dialogue.py

@@ -166,7 +166,7 @@ def on_kb_change():
             ans = ""
             support_agent = ["gpt", "Qwen", "qwen-api", "baichuan-api"] # 目前支持agent的模型
             if not any(agent in llm_model for agent in support_agent):
-                ans += "正在思考... \n\n <span style='color:red'>改模型并没有进行Agent对齐，无法正常使用Agent功能！</span>\n\n\n<span style='color:red'>请更换 GPT4或Qwen-14B等支持Agent的模型获得更好的体验！ </span> \n\n\n"
+                ans += "正在思考... \n\n <span style='color:red'>该模型并没有进行Agent对齐，无法正常使用Agent功能！</span>\n\n\n<span style='color:red'>请更换 GPT4或Qwen-14B等支持Agent的模型获得更好的体验！ </span> \n\n\n"
                 chat_box.update_msg(ans, element_index=0, streaming=False)