Spaces:
Running
on
CPU Upgrade
Running
on
CPU Upgrade
| from __future__ import annotations | |
| import logging | |
| import os | |
| import colorama | |
| import commentjson as cjson | |
| from modules import config | |
| from ..index_func import * | |
| from ..presets import * | |
| from ..utils import * | |
| from .base_model import BaseLLMModel, ModelType | |
| def get_model( | |
| model_name, | |
| lora_model_path=None, | |
| access_key=None, | |
| temperature=None, | |
| top_p=None, | |
| system_prompt=None, | |
| user_name="", | |
| original_model = None | |
| ) -> BaseLLMModel: | |
| msg = i18n("模型设置为了：") + f" {model_name}" | |
| model_type = ModelType.get_type(model_name) | |
| lora_selector_visibility = False | |
| lora_choices = ["No LoRA"] | |
| dont_change_lora_selector = False | |
| if model_type != ModelType.OpenAI: | |
| config.local_embedding = True | |
| # del current_model.model | |
| model = original_model | |
| chatbot = gr.Chatbot.update(label=model_name) | |
| try: | |
| if model_type == ModelType.OpenAI: | |
| logging.info(f"正在加载OpenAI模型: {model_name}") | |
| from .OpenAI import OpenAIClient | |
| access_key = os.environ.get("OPENAI_API_KEY", access_key) | |
| model = OpenAIClient( | |
| model_name=model_name, | |
| api_key=access_key, | |
| system_prompt=system_prompt, | |
| temperature=temperature, | |
| top_p=top_p, | |
| user_name=user_name, | |
| ) | |
| elif model_type == ModelType.OpenAIInstruct: | |
| logging.info(f"正在加载OpenAI Instruct模型: {model_name}") | |
| from .OpenAIInstruct import OpenAI_Instruct_Client | |
| access_key = os.environ.get("OPENAI_API_KEY", access_key) | |
| model = OpenAI_Instruct_Client( | |
| model_name, api_key=access_key, user_name=user_name) | |
| elif model_type == ModelType.OpenAIVision: | |
| logging.info(f"正在加载OpenAI Vision模型: {model_name}") | |
| from .OpenAIVision import OpenAIVisionClient | |
| access_key = os.environ.get("OPENAI_API_KEY", access_key) | |
| model = OpenAIVisionClient( | |
| model_name, api_key=access_key, user_name=user_name) | |
| elif model_type == ModelType.ChatGLM: | |
| logging.info(f"正在加载ChatGLM模型: {model_name}") | |
| from .ChatGLM import ChatGLM_Client | |
| model = ChatGLM_Client(model_name, user_name=user_name) | |
| elif model_type == ModelType.LLaMA and lora_model_path == "": | |
| msg = f"现在请为 {model_name} 选择LoRA模型" | |
| logging.info(msg) | |
| lora_selector_visibility = True | |
| if os.path.isdir("lora"): | |
| lora_choices = ["No LoRA"] + get_file_names_by_pinyin("lora", filetypes=[""]) | |
| elif model_type == ModelType.LLaMA and lora_model_path != "": | |
| logging.info(f"正在加载LLaMA模型: {model_name} + {lora_model_path}") | |
| from .LLaMA import LLaMA_Client | |
| dont_change_lora_selector = True | |
| if lora_model_path == "No LoRA": | |
| lora_model_path = None | |
| msg += " + No LoRA" | |
| else: | |
| msg += f" + {lora_model_path}" | |
| model = LLaMA_Client( | |
| model_name, lora_model_path, user_name=user_name) | |
| elif model_type == ModelType.XMChat: | |
| from .XMChat import XMChat | |
| if os.environ.get("XMCHAT_API_KEY") != "": | |
| access_key = os.environ.get("XMCHAT_API_KEY") | |
| model = XMChat(api_key=access_key, user_name=user_name) | |
| elif model_type == ModelType.StableLM: | |
| from .StableLM import StableLM_Client | |
| model = StableLM_Client(model_name, user_name=user_name) | |
| elif model_type == ModelType.MOSS: | |
| from .MOSS import MOSS_Client | |
| model = MOSS_Client(model_name, user_name=user_name) | |
| elif model_type == ModelType.YuanAI: | |
| from .inspurai import Yuan_Client | |
| model = Yuan_Client(model_name, api_key=access_key, | |
| user_name=user_name, system_prompt=system_prompt) | |
| elif model_type == ModelType.Minimax: | |
| from .minimax import MiniMax_Client | |
| if os.environ.get("MINIMAX_API_KEY") != "": | |
| access_key = os.environ.get("MINIMAX_API_KEY") | |
| model = MiniMax_Client( | |
| model_name, api_key=access_key, user_name=user_name, system_prompt=system_prompt) | |
| elif model_type == ModelType.ChuanhuAgent: | |
| from .ChuanhuAgent import ChuanhuAgent_Client | |
| model = ChuanhuAgent_Client(model_name, access_key, user_name=user_name) | |
| msg = i18n("启用的工具：") + ", ".join([i.name for i in model.tools]) | |
| elif model_type == ModelType.GooglePaLM: | |
| from .GooglePaLM import Google_PaLM_Client | |
| access_key = os.environ.get("GOOGLE_PALM_API_KEY", access_key) | |
| model = Google_PaLM_Client( | |
| model_name, access_key, user_name=user_name) | |
| elif model_type == ModelType.LangchainChat: | |
| from .Azure import Azure_OpenAI_Client | |
| model = Azure_OpenAI_Client(model_name, user_name=user_name) | |
| elif model_type == ModelType.Midjourney: | |
| from .midjourney import Midjourney_Client | |
| mj_proxy_api_secret = os.getenv("MIDJOURNEY_PROXY_API_SECRET") | |
| model = Midjourney_Client( | |
| model_name, mj_proxy_api_secret, user_name=user_name) | |
| elif model_type == ModelType.Spark: | |
| from .spark import Spark_Client | |
| model = Spark_Client(model_name, os.getenv("SPARK_APPID"), os.getenv( | |
| "SPARK_API_KEY"), os.getenv("SPARK_API_SECRET"), user_name=user_name) | |
| elif model_type == ModelType.Claude: | |
| from .Claude import Claude_Client | |
| model = Claude_Client(model_name="claude-2", api_secret=os.getenv("CLAUDE_API_SECRET")) | |
| elif model_type == ModelType.Qwen: | |
| from .Qwen import Qwen_Client | |
| model = Qwen_Client(model_name, user_name=user_name) | |
| elif model_type == ModelType.ERNIE: | |
| from .ERNIE import ERNIE_Client | |
| model = ERNIE_Client(model_name, api_key=os.getenv("ERNIE_APIKEY"),secret_key=os.getenv("ERNIE_SECRETKEY")) | |
| elif model_type == ModelType.Unknown: | |
| raise ValueError(f"未知模型: {model_name}") | |
| logging.info(msg) | |
| except Exception as e: | |
| import traceback | |
| traceback.print_exc() | |
| msg = f"{STANDARD_ERROR_MSG}: {e}" | |
| presudo_key = hide_middle_chars(access_key) | |
| if original_model is not None and model is not None: | |
| model.history = original_model.history | |
| model.history_file_path = original_model.history_file_path | |
| if dont_change_lora_selector: | |
| return model, msg, chatbot, gr.update(), access_key, presudo_key | |
| else: | |
| return model, msg, chatbot, gr.Dropdown.update(choices=lora_choices, visible=lora_selector_visibility), access_key, presudo_key | |
| if __name__ == "__main__": | |
| with open("config.json", "r", encoding="utf-8") as f: | |
| openai_api_key = cjson.load(f)["openai_api_key"] | |
| # set logging level to debug | |
| logging.basicConfig(level=logging.DEBUG) | |
| # client = ModelManager(model_name="gpt-3.5-turbo", access_key=openai_api_key) | |
| client = get_model(model_name="chatglm-6b-int4") | |
| chatbot = [] | |
| stream = False | |
| # 测试账单功能 | |
| logging.info(colorama.Back.GREEN + "测试账单功能" + colorama.Back.RESET) | |
| logging.info(client.billing_info()) | |
| # 测试问答 | |
| logging.info(colorama.Back.GREEN + "测试问答" + colorama.Back.RESET) | |
| question = "巴黎是中国的首都吗？" | |
| for i in client.predict(inputs=question, chatbot=chatbot, stream=stream): | |
| logging.info(i) | |
| logging.info(f"测试问答后history : {client.history}") | |
| # 测试记忆力 | |
| logging.info(colorama.Back.GREEN + "测试记忆力" + colorama.Back.RESET) | |
| question = "我刚刚问了你什么问题？" | |
| for i in client.predict(inputs=question, chatbot=chatbot, stream=stream): | |
| logging.info(i) | |
| logging.info(f"测试记忆力后history : {client.history}") | |
| # 测试重试功能 | |
| logging.info(colorama.Back.GREEN + "测试重试功能" + colorama.Back.RESET) | |
| for i in client.retry(chatbot=chatbot, stream=stream): | |
| logging.info(i) | |
| logging.info(f"重试后history : {client.history}") | |
| # # 测试总结功能 | |
| # print(colorama.Back.GREEN + "测试总结功能" + colorama.Back.RESET) | |
| # chatbot, msg = client.reduce_token_size(chatbot=chatbot) | |
| # print(chatbot, msg) | |
| # print(f"总结后history: {client.history}") | |