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Langchain-Chatchat
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bug修复和提示词修改 (#2230) 

* 更新Langchain依赖到0.0.343以上版本

* 更改了一些提示词和依赖，修改了openai异常的问题

* 注释data的打印日志
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zR 2023-11-30 12:09:53 +08:00 committed by GitHub
parent c4fe3393b3
commit 40918c21de
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6 changed files with 35 additions and 89 deletions
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4
configs/prompt_config.py.example
View File

@ -1,7 +1,6 @@
# prompt模板使用Jinja2语法，简单点就是用双大括号代替f-string的单大括号
# 本配置文件支持热加载，修改prompt模板后无需重启服务。
# LLM对话支持的变量：
# - input: 用户输入内容
@ -76,9 +75,6 @@ Answer the following questions as best you can. If it is in order, you can use s
{tools}
Please note that the "知识库查询工具" is information about the "西交利物浦大学" ,and if a question is asked about it, you must answer with the knowledge base，
Please note that the "天气查询工具" can only be used once since Question begin.
Use the following format:
Question: the input question you must answer1
Thought: you should always think about what to do and what tools to use.

2
requirements.txt
View File

@ -1,6 +1,6 @@
# API requirements
langchain>=0.0.342
langchain>=0.0.343
langchain-experimental>=0.0.42
fschat[model_worker]>=0.2.33
xformers>=0.0.22.post7

2
requirements_api.txt
View File

@ -1,6 +1,6 @@
# API requirements
langchain>=0.0.342
langchain>=0.0.343
langchain-experimental>=0.0.42
fschat[model_worker]>=0.2.33
xformers>=0.0.22.post7

2
requirements_lite.txt
View File

@ -1,4 +1,4 @@
langchain>=0.0.342
langchain>=0.0.343
fschat>=0.2.33
openai>=1.3.5
# sentence_transformers

90
server/utils.py
View File

@ -40,11 +40,9 @@ def get_ChatOpenAI(
verbose: bool = True,
**kwargs: Any,
) -> ChatOpenAI:
## 以下模型是Langchain原生支持的模型，这些模型不会走Fschat封装
config_models = list_config_llm_models()
## 非Langchain原生支持的模型，走Fschat封装
config = get_model_worker_config(model_name)
if config.get("openai-api"):
model_name = config.get("model_name")
model = ChatOpenAI(
streaming=streaming,
verbose=verbose,
@ -57,10 +55,7 @@ def get_ChatOpenAI(
openai_proxy=config.get("openai_proxy"),
**kwargs
)
return model
def get_OpenAI(
model_name: str,
temperature: float,
@ -71,67 +66,22 @@ def get_OpenAI(
verbose: bool = True,
**kwargs: Any,
) -> OpenAI:
## 以下模型是Langchain原生支持的模型，这些模型不会走Fschat封装
config_models = list_config_llm_models()
if model_name in config_models.get("langchain", {}):
config = config_models["langchain"][model_name]
if model_name == "Azure-OpenAI":
model = AzureOpenAI(
streaming=streaming,
verbose=verbose,
callbacks=callbacks,
deployment_name=config.get("deployment_name"),
model_version=config.get("model_version"),
openai_api_type=config.get("openai_api_type"),
openai_api_base=config.get("api_base_url"),
openai_api_version=config.get("api_version"),
openai_api_key=config.get("api_key"),
openai_proxy=config.get("openai_proxy"),
temperature=temperature,
max_tokens=max_tokens,
echo=echo,
)
elif model_name == "OpenAI":
model = OpenAI(
streaming=streaming,
verbose=verbose,
callbacks=callbacks,
model_name=config.get("model_name"),
openai_api_base=config.get("api_base_url"),
openai_api_key=config.get("api_key"),
openai_proxy=config.get("openai_proxy"),
temperature=temperature,
max_tokens=max_tokens,
echo=echo,
)
elif model_name == "Anthropic":
model = Anthropic(
streaming=streaming,
verbose=verbose,
callbacks=callbacks,
model_name=config.get("model_name"),
anthropic_api_key=config.get("api_key"),
echo=echo,
)
## TODO 支持其他的Langchain原生支持的模型
else:
## 非Langchain原生支持的模型，走Fschat封装
config = get_model_worker_config(model_name)
model = OpenAI(
streaming=streaming,
verbose=verbose,
callbacks=callbacks,
openai_api_key=config.get("api_key", "EMPTY"),
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"),
echo=echo,
**kwargs
)
config = get_model_worker_config(model_name)
if config.get("openai-api"):
model_name = config.get("model_name")
model = OpenAI(
streaming=streaming,
verbose=verbose,
callbacks=callbacks,
openai_api_key=config.get("api_key", "EMPTY"),
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"),
echo=echo,
**kwargs
)
return model
@ -630,7 +580,7 @@ def get_httpx_client(
for host in os.environ.get("no_proxy", "").split(","):
if host := host.strip():
# default_proxies.update({host: None}) # Origin code
default_proxies.update({'all://' + host: None}) # PR 1838 fix, if not add 'all://', httpx will raise error
default_proxies.update({'all://' + host: None}) # PR 1838 fix, if not add 'all://', httpx will raise error
# merge default proxies with user provided proxies
if isinstance(proxies, str):
@ -714,7 +664,7 @@ def get_temp_dir(id: str = None) -> Tuple[str, str]:
from configs.basic_config import BASE_TEMP_DIR
import tempfile
if id is not None: # 如果指定的临时目录已存在，直接返回
if id is not None: # 如果指定的临时目录已存在，直接返回
path = os.path.join(BASE_TEMP_DIR, id)
if os.path.isdir(path):
return path, id

24
webui_pages/utils.py
View File

@ -276,8 +276,8 @@ class ApiRequest:
"max_tokens": max_tokens,
}
print(f"received input message:")
pprint(data)
# print(f"received input message:")
# pprint(data)
response = self.post(
"/chat/fastchat",
@ -288,16 +288,16 @@ class ApiRequest:
return self._httpx_stream2generator(response)
def chat_chat(
self,
query: str,
conversation_id: str = None,
history: List[Dict] = [],
stream: bool = True,
model: str = LLM_MODELS[0],
temperature: float = TEMPERATURE,
max_tokens: int = None,
prompt_name: str = "default",
**kwargs,
self,
query: str,
conversation_id: str = None,
history: List[Dict] = [],
stream: bool = True,
model: str = LLM_MODELS[0],
temperature: float = TEMPERATURE,
max_tokens: int = None,
prompt_name: str = "default",
**kwargs,
):
'''
对应api.py/chat/chat接口 #TODO: 考虑是否返回json