from .model_config import LLM_MODEL, LLM_DEVICE import os, json try: with open("./local_config.json", "r") as f: update_config = json.load(f) except: update_config = {} # API 是否开启跨域,默认为False,如果需要开启,请设置为True # is open cross domain OPEN_CROSS_DOMAIN = False # 是否用容器来启动服务 try: DOCKER_SERVICE = json.loads(os.environ["DOCKER_SERVICE"]) or update_config.get("DOCKER_SERVICE") or False except: DOCKER_SERVICE = True # 是否采用容器沙箱 try: SANDBOX_DO_REMOTE = json.loads(os.environ["SANDBOX_DO_REMOTE"]) or update_config.get("SANDBOX_DO_REMOTE") or False except: SANDBOX_DO_REMOTE = True # 是否采用api服务来进行 NO_REMOTE_API = True # 各服务器默认绑定host DEFAULT_BIND_HOST = "127.0.0.1" os.environ["DEFAULT_BIND_HOST"] = DEFAULT_BIND_HOST # CONTRAINER_NAME = "devopsgpt_webui" IMAGE_NAME = "devopsgpt:py39" # webui.py server WEBUI_SERVER = { "host": DEFAULT_BIND_HOST, "port": 8501, "docker_port": 8501 } # api.py server API_SERVER = { "host": DEFAULT_BIND_HOST, "port": 7861, "docker_port": 7861 } # sdfile_api.py server SDFILE_API_SERVER = { "host": DEFAULT_BIND_HOST, "port": 7862, "docker_port": 7862 } # fastchat openai_api server FSCHAT_OPENAI_API = { "host": DEFAULT_BIND_HOST, "port": 8888, # model_config.llm_model_dict中模型配置的api_base_url需要与这里一致。 "docker_port": 8888, # model_config.llm_model_dict中模型配置的api_base_url需要与这里一致。 } # nebula conf NEBULA_HOST = DEFAULT_BIND_HOST NEBULA_PORT = 9669 NEBULA_STORAGED_PORT = 9779 NEBULA_USER = 'root' NEBULA_PASSWORD = '' NEBULA_GRAPH_SERVER = { "host": DEFAULT_BIND_HOST, "port": NEBULA_PORT, "docker_port": NEBULA_PORT } # sandbox api server SANDBOX_CONTRAINER_NAME = "devopsgpt_sandbox" SANDBOX_IMAGE_NAME = "devopsgpt:py39" SANDBOX_HOST = os.environ.get("SANDBOX_HOST") or update_config.get("SANDBOX_HOST") or DEFAULT_BIND_HOST # "172.25.0.3" SANDBOX_SERVER = { "host": f"http://{SANDBOX_HOST}", "port": 5050, "docker_port": 5050, "url": f"http://{SANDBOX_HOST}:5050", "do_remote": SANDBOX_DO_REMOTE, } # fastchat model_worker server # 这些模型必须是在model_config.llm_model_dict中正确配置的。 # 在启动startup.py时,可用通过`--model-worker --model-name xxxx`指定模型,不指定则为LLM_MODEL # 建议使用chat模型,不要使用base,无法获取正确输出 FSCHAT_MODEL_WORKERS = json.loads(os.environ.get("FSCHAT_MODEL_WORKERS")) if os.environ.get("FSCHAT_MODEL_WORKERS") else {} FSCHAT_MODEL_WORKERS = FSCHAT_MODEL_WORKERS or update_config.get("FSCHAT_MODEL_WORKERS") FSCHAT_MODEL_WORKERS = FSCHAT_MODEL_WORKERS or { "default": { "host": DEFAULT_BIND_HOST, "port": 20002, "device": LLM_DEVICE, # todo: 多卡加载需要配置的参数 "gpus": None, "numgpus": 1, # 以下为非常用参数,可根据需要配置 # "max_gpu_memory": "20GiB", # "load_8bit": False, # "cpu_offloading": None, # "gptq_ckpt": None, # "gptq_wbits": 16, # "gptq_groupsize": -1, # "gptq_act_order": False, # "awq_ckpt": None, # "awq_wbits": 16, # "awq_groupsize": -1, # "model_names": [LLM_MODEL], # "conv_template": None, # "limit_worker_concurrency": 5, # "stream_interval": 2, # "no_register": False, }, 'codellama_34b': {'host': DEFAULT_BIND_HOST, 'port': 20002}, 'Baichuan2-13B-Base': {'host': DEFAULT_BIND_HOST, 'port': 20003}, 'Baichuan2-13B-Chat': {'host': DEFAULT_BIND_HOST, 'port': 20004}, 'baichuan2-7b-base': {'host': DEFAULT_BIND_HOST, 'port': 20005}, 'baichuan2-7b-chat': {'host': DEFAULT_BIND_HOST, 'port': 20006}, 'internlm-7b-base': {'host': DEFAULT_BIND_HOST, 'port': 20007}, 'internlm-chat-7b': {'host': DEFAULT_BIND_HOST, 'port': 20008}, 'chatglm2-6b': {'host': DEFAULT_BIND_HOST, 'port': 20009}, 'qwen-14b-base': {'host': DEFAULT_BIND_HOST, 'port': 20010}, 'qwen-14b-chat': {'host': DEFAULT_BIND_HOST, 'port': 20011}, 'qwen-1-8B-Chat': {'host': DEFAULT_BIND_HOST, 'port': 20012}, 'Qwen-7B': {'host': DEFAULT_BIND_HOST, 'port': 20013}, 'Qwen-7B-Chat': {'host': DEFAULT_BIND_HOST, 'port': 20014}, 'qwen-7b-base-v1.1': {'host': DEFAULT_BIND_HOST, 'port': 20015}, 'qwen-7b-chat-v1.1': {'host': DEFAULT_BIND_HOST, 'port': 20016}, 'chatglm3-6b': {'host': DEFAULT_BIND_HOST, 'port': 20017}, 'chatglm3-6b-32k': {'host': DEFAULT_BIND_HOST, 'port': 20018}, 'chatglm3-6b-base': {'host': DEFAULT_BIND_HOST, 'port': 20019}, 'Qwen-72B-Chat-Int4': {'host': DEFAULT_BIND_HOST, 'port': 20020}, 'gpt-3.5-turbo': {'host': DEFAULT_BIND_HOST, 'port': 20021}, 'example': {'host': DEFAULT_BIND_HOST, 'port': 20022}, 'openai-api': {'host': DEFAULT_BIND_HOST, 'port': 20023} } # fastchat multi model worker server FSCHAT_MULTI_MODEL_WORKERS = { # todo } # fastchat controller server FSCHAT_CONTROLLER = { "host": DEFAULT_BIND_HOST, "port": 20001, "dispatch_method": "shortest_queue", } # 以下不要更改 def fschat_controller_address() -> str: host = FSCHAT_CONTROLLER["host"] port = FSCHAT_CONTROLLER["port"] return f"http://{host}:{port}" def fschat_model_worker_address(model_name: str = LLM_MODEL) -> str: if model := FSCHAT_MODEL_WORKERS.get(model_name): host = model["host"] port = model["port"] return f"http://{host}:{port}" def fschat_openai_api_address() -> str: host = FSCHAT_OPENAI_API["host"] port = FSCHAT_OPENAI_API["port"] return f"http://{host}:{port}" def api_address() -> str: host = API_SERVER["host"] port = API_SERVER["port"] return f"http://{host}:{port}" def webui_address() -> str: host = WEBUI_SERVER["host"] port = WEBUI_SERVER["port"] return f"http://{host}:{port}"