perf: 优化代码声明

pkg/plugin/models.py

@@ -1 +1,26 @@
-from .context import BasePlugin as Plugin
+from __future__ import annotations
+
+import typing
+
+from .context import BasePlugin as Plugin
+from . import events
+
+def register(
+    name: str,
+    description: str,
+    version: str,
+    author
+) -> typing.Callable[[typing.Type[Plugin]], typing.Type[Plugin]]:
+    pass
+
+
+def on(
+    event: typing.Type[events.BaseEventModel]
+) -> typing.Callable[[typing.Callable], typing.Callable]:
+    pass
+
+
+def func(
+    name: str=None,
+) -> typing.Callable:
+    pass

pkg/provider/modelmgr.py

@@ -1,139 +0,0 @@
-"""OpenAI 接口底层封装
-
-目前使用的对话接口有：
-ChatCompletion - gpt-3.5-turbo 等模型
-Completion - text-davinci-003 等模型
-此模块封装此两个接口的请求实现，为上层提供统一的调用方式
-"""
-import tiktoken
-import openai
-
-from ..provider.api import model as api_model
-from ..provider.api import completion as api_completion
-from ..provider.api import chat_completion as api_chat_completion
-
-COMPLETION_MODELS = {
-    "gpt-3.5-turbo-instruct",
-}
-
-CHAT_COMPLETION_MODELS = {
-    # GPT 4 系列
-    "gpt-4-1106-preview",
-    "gpt-4-vision-preview",
-    "gpt-4",
-    "gpt-4-32k",
-    "gpt-4-0613",
-    "gpt-4-32k-0613",
-    "gpt-4-0314", # legacy
-    "gpt-4-32k-0314", # legacy
-    # GPT 3.5 系列
-    "gpt-3.5-turbo-1106",
-    "gpt-3.5-turbo",
-    "gpt-3.5-turbo-16k",
-    "gpt-3.5-turbo-0613", # legacy
-    "gpt-3.5-turbo-16k-0613", # legacy
-    "gpt-3.5-turbo-0301", # legacy
-    # One-API 接入
-    "SparkDesk",
-    "chatglm_pro",
-    "chatglm_std",
-    "chatglm_lite",
-    "qwen-v1",
-    "qwen-plus-v1",
-    "ERNIE-Bot",
-    "ERNIE-Bot-turbo",
-    "gemini-pro",
-}
-
-EDIT_MODELS = {
-
-}
-
-IMAGE_MODELS = {
-
-}
-
-
-def select_request_cls(client: openai.Client, model_name: str, messages: list, args: dict) -> api_model.RequestBase:
-    if model_name in CHAT_COMPLETION_MODELS:
-        return api_chat_completion.ChatCompletionRequest(client, model_name, messages, **args)
-    elif model_name in COMPLETION_MODELS:
-        return api_completion.CompletionRequest(client, model_name, messages, **args)
-    raise ValueError("不支持模型[{}]，请检查配置文件".format(model_name))
-
-
-def count_chat_completion_tokens(messages: list, model: str) -> int:
-    """Return the number of tokens used by a list of messages."""
-    try:
-        encoding = tiktoken.encoding_for_model(model)
-    except KeyError:
-        print("Warning: model not found. Using cl100k_base encoding.")
-        encoding = tiktoken.get_encoding("cl100k_base")
-    if model in {
-        "gpt-3.5-turbo-0613",
-        "gpt-3.5-turbo-16k-0613",
-        "gpt-4-0314",
-        "gpt-4-32k-0314",
-        "gpt-4-0613",
-        "gpt-4-32k-0613",
-        "SparkDesk",
-        "chatglm_pro",
-        "chatglm_std",
-        "chatglm_lite",
-        "qwen-v1",
-        "qwen-plus-v1",
-        "ERNIE-Bot",
-        "ERNIE-Bot-turbo",
-        "gemini-pro",
-        }:
-        tokens_per_message = 3
-        tokens_per_name = 1
-    elif model == "gpt-3.5-turbo-0301":
-        tokens_per_message = 4  # every message follows <|start|>{role/name}\n{content}<|end|>\n
-        tokens_per_name = -1  # if there's a name, the role is omitted
-    elif "gpt-3.5-turbo" in model:
-        # print("Warning: gpt-3.5-turbo may update over time. Returning num tokens assuming gpt-3.5-turbo-0613.")
-        return count_chat_completion_tokens(messages, model="gpt-3.5-turbo-0613")
-    elif "gpt-4" in model:
-        # print("Warning: gpt-4 may update over time. Returning num tokens assuming gpt-4-0613.")
-        return count_chat_completion_tokens(messages, model="gpt-4-0613")
-    else:
-        raise NotImplementedError(
-            f"""count_chat_completion_tokens() is not implemented for model {model}. See https://github.com/openai/openai-python/blob/main/chatml.md for information on how messages are converted to tokens."""
-        )
-    num_tokens = 0
-    for message in messages:
-        num_tokens += tokens_per_message
-        for key, value in message.items():
-            num_tokens += len(encoding.encode(value))
-            if key == "name":
-                num_tokens += tokens_per_name
-    num_tokens += 3  # every reply is primed with <|start|>assistant<|message|>
-    return num_tokens
-
-
-def count_completion_tokens(messages: list, model: str) -> int:
-
-    try:
-        encoding = tiktoken.encoding_for_model(model)
-    except KeyError:
-        print("Warning: model not found. Using cl100k_base encoding.")
-        encoding = tiktoken.get_encoding("cl100k_base")
-
-    text = ""
-
-    for message in messages:
-        text += message['role'] + message['content'] + "\n"
-
-    text += "assistant: "
-
-    return len(encoding.encode(text))
-
-
-def count_tokens(messages: list, model: str):
-
-    if model in CHAT_COMPLETION_MODELS:
-        return count_chat_completion_tokens(messages, model)
-    elif model in COMPLETION_MODELS:
-        return count_completion_tokens(messages, model)
-    raise ValueError("不支持模型[{}]，请检查配置文件".format(model))

pkg/utils/log.py

@@ -1,67 +0,0 @@
-import os
-import time
-import logging
-import shutil
-
-from . import context
-
-
-log_file_name = "qchatgpt.log"
-
-
-log_colors_config = {
-    'DEBUG': 'green',  # cyan white
-    'INFO': 'white',
-    'WARNING': 'yellow',
-    'ERROR': 'red',
-    'CRITICAL': 'cyan',
-}
-
-
-def init_runtime_log_file():
-    """为此次运行生成日志文件
-    格式: qchatgpt-yyyy-MM-dd-HH-mm-ss.log
-    """
-    global log_file_name
-
-    # 检查logs目录是否存在
-    if not os.path.exists("logs"):
-        os.mkdir("logs")
-
-    log_file_name = "logs/qchatgpt-%s.log" % time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime())
-    
-
-def reset_logging():
-    global log_file_name
-
-    import pkg.utils.context
-    import colorlog
-
-    if pkg.utils.context.context['logger_handler'] is not None:
-        logging.getLogger().removeHandler(pkg.utils.context.context['logger_handler'])
-
-    for handler in logging.getLogger().handlers:
-        logging.getLogger().removeHandler(handler)
-
-    config_mgr = context.get_config_manager()
-
-    logging_level = logging.INFO if config_mgr is None else config_mgr.data['logging_level']
-
-    logging.basicConfig(level=logging_level,  # 设置日志输出格式
-                        filename=log_file_name,  # log日志输出的文件位置和文件名
-                        format="[%(asctime)s.%(msecs)03d] %(pathname)s (%(lineno)d) - [%(levelname)s] :\n%(message)s",
-                        # 日志输出的格式
-                        # -8表示占位符，让输出左对齐，输出长度都为8位
-                        datefmt="%Y-%m-%d %H:%M:%S"  # 时间输出的格式
-                        )
-    sh = logging.StreamHandler()
-    sh.setLevel(logging_level)
-    sh.setFormatter(colorlog.ColoredFormatter(
-        fmt="%(log_color)s[%(asctime)s.%(msecs)03d] %(filename)s (%(lineno)d) - [%(levelname)s] : "
-            "%(message)s",
-        datefmt="%Y-%m-%d %H:%M:%S",
-        log_colors=log_colors_config
-    ))
-    logging.getLogger().addHandler(sh)
-    pkg.utils.context.context['logger_handler'] = sh
-    return sh

pkg/utils/updater.py

@@ -1,174 +0,0 @@
-from __future__ import annotations
-
-import datetime
-import logging
-import os.path
-import time
-
-import requests
-
-from . import constants
-
-
-def is_newer(new_tag: str, old_tag: str):
-    """判断版本是否更新，忽略第四位版本和第一位版本"""
-    if new_tag == old_tag:
-        return False
-
-    new_tag = new_tag.split(".")
-    old_tag = old_tag.split(".")
-    
-    # 判断主版本是否相同
-    if new_tag[0] != old_tag[0]:
-        return False
-
-    if len(new_tag) < 4:
-        return True
-
-    # 合成前三段，判断是否相同
-    new_tag = ".".join(new_tag[:3])
-    old_tag = ".".join(old_tag[:3])
-
-    return new_tag != old_tag
-
-
-def compare_version_str(v0: str, v1: str) -> int:
-    """比较两个版本号"""
-
-    # 删除版本号前的v
-    if v0.startswith("v"):
-        v0 = v0[1:]
-    if v1.startswith("v"):
-        v1 = v1[1:]
-
-    v0:list = v0.split(".")
-    v1:list = v1.split(".")
-
-    # 如果两个版本号节数不同，把短的后面用0补齐
-    if len(v0) < len(v1):
-        v0.extend(["0"]*(len(v1)-len(v0)))
-    elif len(v0) > len(v1):
-        v1.extend(["0"]*(len(v0)-len(v1)))
-
-    # 从高位向低位比较
-    for i in range(len(v0)):
-        if int(v0[i]) > int(v1[i]):
-            return 1
-        elif int(v0[i]) < int(v1[i]):
-            return -1
-    
-    return 0
-
-
-def update_all(cli: bool = False) -> bool:
-    """检查更新并下载源码"""
-    start_time = time.time()
-
-    current_tag = get_current_tag()
-    old_tag = current_tag
-
-    rls_list = get_release_list()
-
-    latest_rls = {}
-    rls_notes = []
-    latest_tag_name = ""
-    for rls in rls_list:
-        rls_notes.append(rls['name'])  # 使用发行名称作为note
-        if latest_tag_name == "":
-            latest_tag_name = rls['tag_name']
-
-        if rls['tag_name'] == current_tag:
-            break
-
-        if latest_rls == {}:
-            latest_rls = rls
-    if not cli:
-        logging.info("更新日志: {}".format(rls_notes))
-    else:
-        print("更新日志: {}".format(rls_notes))
-
-    if latest_rls == {} and not is_newer(latest_tag_name, current_tag):  # 没有新版本
-        return False
-
-    # 下载最新版本的zip到temp目录
-    if not cli:
-        logging.info("开始下载最新版本: {}".format(latest_rls['zipball_url']))
-    else:
-        print("开始下载最新版本: {}".format(latest_rls['zipball_url']))
-    zip_url = latest_rls['zipball_url']
-    zip_resp = requests.get(
-        url=zip_url,
-        proxies=network.wrapper_proxies()
-    )
-    zip_data = zip_resp.content
-
-    # 检查temp/updater目录
-    if not os.path.exists("temp"):
-        os.mkdir("temp")
-    if not os.path.exists("temp/updater"):
-        os.mkdir("temp/updater")
-    with open("temp/updater/{}.zip".format(latest_rls['tag_name']), "wb") as f:
-        f.write(zip_data)
-
-    if not cli:
-        logging.info("下载最新版本完成: {}".format("temp/updater/{}.zip".format(latest_rls['tag_name'])))
-    else:
-        print("下载最新版本完成: {}".format("temp/updater/{}.zip".format(latest_rls['tag_name'])))
-
-    # 解压zip到temp/updater/<tag_name>/
-    import zipfile
-    # 检查目标文件夹
-    if os.path.exists("temp/updater/{}".format(latest_rls['tag_name'])):
-        import shutil
-        shutil.rmtree("temp/updater/{}".format(latest_rls['tag_name']))
-    os.mkdir("temp/updater/{}".format(latest_rls['tag_name']))
-    with zipfile.ZipFile("temp/updater/{}.zip".format(latest_rls['tag_name']), 'r') as zip_ref:
-        zip_ref.extractall("temp/updater/{}".format(latest_rls['tag_name']))
-
-    # 覆盖源码
-    source_root = ""
-    # 找到temp/updater/<tag_name>/中的第一个子目录路径
-    for root, dirs, files in os.walk("temp/updater/{}".format(latest_rls['tag_name'])):
-        if root != "temp/updater/{}".format(latest_rls['tag_name']):
-            source_root = root
-            break
-
-    # 覆盖源码
-    import shutil
-    for root, dirs, files in os.walk(source_root):
-        # 覆盖所有子文件子目录
-        for file in files:
-            src = os.path.join(root, file)
-            dst = src.replace(source_root, ".")
-            if os.path.exists(dst):
-                os.remove(dst)
-
-            # 检查目标文件夹是否存在
-            if not os.path.exists(os.path.dirname(dst)):
-                os.makedirs(os.path.dirname(dst))
-            # 检查目标文件是否存在
-            if not os.path.exists(dst):
-                # 创建目标文件
-                open(dst, "w").close()
-
-            shutil.copy(src, dst)
-
-    # 把current_tag写入文件
-    current_tag = latest_rls['tag_name']
-    with open("current_tag", "w") as f:
-        f.write(current_tag)
-
-    context.get_center_v2_api().main.post_update_record(
-        spent_seconds=int(time.time()-start_time),
-        infer_reason="update",
-        old_version=old_tag,
-        new_version=current_tag,
-    )
-
-    # 通知管理员
-    if not cli:
-        import pkg.utils.context
-        pkg.utils.context.get_qqbot_manager().notify_admin("已更新到最新版本: {}\n更新日志:\n{}\n完整的更新日志请前往 https://github.com/RockChinQ/QChatGPT/releases 查看。\n请手动重启程序以使用新版本。".format(current_tag, "\n".join(rls_notes[:-1])))
-    else:
-        print("已更新到最新版本: {}\n更新日志:\n{}\n完整的更新日志请前往 https://github.com/RockChinQ/QChatGPT/releases 查看。请手动重启程序以使用新版本。".format(current_tag, "\n".join(rls_notes[:-1])))
-    return True