add paramter `max_tokens` to 4 chat api with default value 1024 (#1744)
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liunux4odoo
GitHub
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@ -25,6 +25,7 @@ async def agent_chat(query: str = Body(..., description="用户输入", examples
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stream: bool = Body(False, description="流式输出"),
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model_name: str = Body(LLM_MODEL, description="LLM 模型名称。"),
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temperature: float = Body(TEMPERATURE, description="LLM 采样温度", ge=0.0, le=1.0),
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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。
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prompt_name: str = Body("agent_chat",
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description="使用的prompt模板名称(在configs/prompt_config.py中配置)"),
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# top_p: float = Body(TOP_P, description="LLM 核采样。勿与temperature同时设置", gt=0.0, lt=1.0),
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@ -41,6 +42,7 @@ async def agent_chat(query: str = Body(..., description="用户输入", examples
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model = get_ChatOpenAI(
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model_name=model_name,
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temperature=temperature,
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max_tokens=max_tokens,
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)
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prompt_template = CustomPromptTemplate(
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@ -22,6 +22,7 @@ async def chat(query: str = Body(..., description="用户输入", examples=["恼
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stream: bool = Body(False, description="流式输出"),
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model_name: str = Body(LLM_MODEL, description="LLM 模型名称。"),
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temperature: float = Body(TEMPERATURE, description="LLM 采样温度", ge=0.0, le=1.0),
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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。
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# top_p: float = Body(TOP_P, description="LLM 核采样。勿与temperature同时设置", gt=0.0, lt=1.0),
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prompt_name: str = Body("llm_chat", description="使用的prompt模板名称(在configs/prompt_config.py中配置)"),
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):
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@ -36,6 +37,7 @@ async def chat(query: str = Body(..., description="用户输入", examples=["恼
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model = get_ChatOpenAI(
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model_name=model_name,
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temperature=temperature,
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max_tokens=max_tokens,
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callbacks=[callback],
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)
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@ -31,6 +31,7 @@ async def knowledge_base_chat(query: str = Body(..., description="用户输入",
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stream: bool = Body(False, description="流式输出"),
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model_name: str = Body(LLM_MODEL, description="LLM 模型名称。"),
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temperature: float = Body(TEMPERATURE, description="LLM 采样温度", ge=0.0, le=1.0),
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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。
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prompt_name: str = Body("knowledge_base_chat", description="使用的prompt模板名称(在configs/prompt_config.py中配置)"),
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local_doc_url: bool = Body(False, description="知识文件返回本地路径(true)或URL(false)"),
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request: Request = None,
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@ -51,6 +52,7 @@ async def knowledge_base_chat(query: str = Body(..., description="用户输入",
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model = get_ChatOpenAI(
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model_name=model_name,
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temperature=temperature,
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max_tokens=max_tokens,
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callbacks=[callback],
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)
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docs = search_docs(query, knowledge_base_name, top_k, score_threshold)
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@ -72,6 +72,7 @@ async def search_engine_chat(query: str = Body(..., description="用户输入",
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stream: bool = Body(False, description="流式输出"),
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model_name: str = Body(LLM_MODEL, description="LLM 模型名称。"),
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temperature: float = Body(TEMPERATURE, description="LLM 采样温度", ge=0.0, le=1.0),
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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。
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prompt_name: str = Body("knowledge_base_chat", description="使用的prompt模板名称(在configs/prompt_config.py中配置)"),
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):
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if search_engine_name not in SEARCH_ENGINES.keys():
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@ -93,6 +94,7 @@ async def search_engine_chat(query: str = Body(..., description="用户输入",
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model = get_ChatOpenAI(
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model_name=model_name,
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temperature=temperature,
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max_tokens=max_tokens,
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callbacks=[callback],
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)
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@ -34,6 +34,7 @@ async def wrap_done(fn: Awaitable, event: asyncio.Event):
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def get_ChatOpenAI(
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model_name: str,
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temperature: float,
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max_tokens: int = None,
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streaming: bool = True,
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callbacks: List[Callable] = [],
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verbose: bool = True,
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@ -48,6 +49,7 @@ def get_ChatOpenAI(
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openai_api_base=config.get("api_base_url", fschat_openai_api_address()),
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model_name=model_name,
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temperature=temperature,
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max_tokens=max_tokens,
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openai_proxy=config.get("openai_proxy"),
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**kwargs
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)
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@ -144,7 +146,7 @@ def run_async(cor):
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return loop.run_until_complete(cor)
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def iter_over_async(ait, loop):
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def iter_over_async(ait, loop=None):
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'''
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将异步生成器封装成同步生成器.
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'''
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@ -157,6 +159,12 @@ def iter_over_async(ait, loop):
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except StopAsyncIteration:
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return True, None
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if loop is None:
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try:
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loop = asyncio.get_event_loop()
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except:
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loop = asyncio.new_event_loop()
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while True:
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done, obj = loop.run_until_complete(get_next())
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if done:
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@ -166,7 +166,7 @@ def dialogue_page(api: ApiRequest):
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ans = ""
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support_agent = ["gpt", "Qwen", "qwen-api", "baichuan-api"] # 目前支持agent的模型
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if not any(agent in llm_model for agent in support_agent):
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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"
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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"
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chat_box.update_msg(ans, element_index=0, streaming=False)
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