Spaces:
Build error
Build error
增加通用性
Browse files- toolbox.py +44 -41
toolbox.py
CHANGED
@@ -518,61 +518,64 @@ def select_api_key(keys, llm_model):
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api_key = random.choice(avail_key_list) # 随机负载均衡
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return api_key
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def
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# 格式为:username1:password1;username2:password2
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for item in os.environ[env_arg].split(";"):
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r.append(tuple(item.split(":")))
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elif arg == "API_URL_REDIRECT":
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# 对于API_URL_REDIRECT的环境变量,我们允许用户使用json格式配置多个url重定向
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# 格式为一个json字符串,例如:{"https://api.openai.com/v1/chat/completions": "https://ai.open.com/api/conversation"}
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import json
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r = json.loads(os.environ[env_arg])
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elif isinstance(default_value, bool):
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r = bool(os.environ[env_arg])
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elif isinstance(default_value, int):
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r = int(
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elif isinstance(default_value, float):
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r = float(
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elif isinstance(default_value, str):
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r =
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else:
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return r
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@lru_cache(maxsize=128)
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def read_single_conf_with_lru_cache(arg):
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from colorful import print亮红, print亮绿, print亮蓝
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default_r = getattr(importlib.import_module('config'), arg)
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try:
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except:
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try:
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r = getattr(importlib.import_module('config_private'), arg)
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except:
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# 在读取API_KEY时,检查一下是不是忘了改config
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if arg == 'API_KEY':
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print亮蓝(f"[API_KEY] 本项目现已支持OpenAI和API2D的api-key。也支持同时填写多个api-key,如API_KEY=\"openai-key1,openai-key2,api2d-key3\"")
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api_key = random.choice(avail_key_list) # 随机负载均衡
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return api_key
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def read_env_variable(arg, default_value):
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"""
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环境变量可以是 `GPT_ACADEMIC_CONFIG`(优先),也可以直接是`CONFIG`
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例如在windows cmd中,既可以写:
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set USE_PROXY=True
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set API_KEY=sk-j7caBpkRoxxxxxxxxxxxxxxxxxxxxxxxxxxxx
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set proxies={"http":"http://127.0.0.1:10085", "https":"http://127.0.0.1:10085",}
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set AVAIL_LLM_MODELS=["gpt-3.5-turbo", "chatglm"]
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set AUTHENTICATION=[("username", "password"), ("username2", "password2")]
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也可以写:
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set GPT_ACADEMIC_USE_PROXY=True
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set GPT_ACADEMIC_API_KEY=sk-j7caBpkRoxxxxxxxxxxxxxxxxxxxxxxxxxxxx
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set GPT_ACADEMIC_proxies={"http":"http://127.0.0.1:10085", "https":"http://127.0.0.1:10085",}
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set GPT_ACADEMIC_AVAIL_LLM_MODELS=["gpt-3.5-turbo", "chatglm"]
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set GPT_ACADEMIC_AUTHENTICATION=[("username", "password"), ("username2", "password2")]
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"""
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from colorful import print亮红, print亮绿
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arg_with_prefix = "GPT_ACADEMIC_" + arg
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if arg_with_prefix in os.environ: env_arg = os.environ[arg_with_prefix]
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elif arg in os.environ: env_arg = os.environ[arg]
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else:
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raise KeyError
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if isinstance(default_value, bool):
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r = bool(env_arg)
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elif isinstance(default_value, int):
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r = int(env_arg)
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elif isinstance(default_value, float):
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r = float(env_arg)
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elif isinstance(default_value, str):
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r = env_arg
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elif isinstance(default_value, dict):
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r = eval(env_arg)
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elif isinstance(default_value, list):
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r = eval(env_arg)
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elif default_value is None:
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assert arg == "proxies"
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r = eval(env_arg)
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else:
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print亮红(f"[ENV_VAR] 环境变量{arg}不支持通过环境变量设置!{default_value}")
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raise KeyError
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print亮绿(f"[ENV_VAR] 成功读取环境变量{arg}")
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return r
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@lru_cache(maxsize=128)
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def read_single_conf_with_lru_cache(arg):
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from colorful import print亮红, print亮绿, print亮蓝
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try:
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# 优先级1. 获取环境变量作为配置
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default_ref = getattr(importlib.import_module('config'), arg) # 读取默认值作为数据类型转换的参考
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r = read_env_variable(arg, default_ref)
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except:
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try:
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# 优先级2. 获取config_private中的配置
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r = getattr(importlib.import_module('config_private'), arg)
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except:
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# 优先级3. 获取config中的配置
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r = getattr(importlib.import_module('config'), arg)
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# 在读取API_KEY时,检查一下是不是忘了改config
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if arg == 'API_KEY':
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print亮蓝(f"[API_KEY] 本项目现已支持OpenAI和API2D的api-key。也支持同时填写多个api-key,如API_KEY=\"openai-key1,openai-key2,api2d-key3\"")
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