85 lines
3.1 KiB
Python
85 lines
3.1 KiB
Python
import click
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from pathlib import Path
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import shutil
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import typing as t
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from chatchat.startup import main as startup_main
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from chatchat.init_database import main as kb_main, create_tables, folder2db
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from chatchat.settings import Settings
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from chatchat.utils import build_logger
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from chatchat.server.utils import get_default_embedding
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logger = build_logger()
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@click.group(help="chatchat 命令行工具")
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def main():
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...
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@main.command("init", help="项目初始化")
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@click.option("-x", "--xinference-endpoint", "xf_endpoint",
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help="指定Xinference API 服务地址。默认为 http://127.0.0.1:9997/v1")
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@click.option("-l", "--llm-model",
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help="指定默认 LLM 模型。默认为 glm4-chat")
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@click.option("-e", "--embed-model",
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help="指定默认 Embedding 模型。默认为 bge-large-zh-v1.5")
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@click.option("-r", "--recreate-kb",
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is_flag=True,
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show_default=True,
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default=False,
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help="同时重建知识库（必须确保指定的 embed model 可用）。")
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@click.option("-k", "--kb-names", "kb_names",
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show_default=True,
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default="samples",
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help="要重建知识库的名称。可以指定多个知识库名称，以 , 分隔。")
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def init(
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xf_endpoint: str = "",
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llm_model: str = "",
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embed_model: str = "",
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recreate_kb: bool = False,
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kb_names: str = "",
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):
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Settings.set_auto_reload(False)
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bs = Settings.basic_settings
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kb_names = [x.strip() for x in kb_names.split(",")]
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logger.success(f"开始初始化项目数据目录：{Settings.CHATCHAT_ROOT}")
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Settings.basic_settings.make_dirs()
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logger.success("创建所有数据目录：成功。")
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if(bs.PACKAGE_ROOT / "data/knowledge_base/samples" != Path(bs.KB_ROOT_PATH) / "samples"):
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shutil.copytree(bs.PACKAGE_ROOT / "data/knowledge_base/samples", Path(bs.KB_ROOT_PATH) / "samples", dirs_exist_ok=True)
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logger.success("复制 samples 知识库文件：成功。")
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create_tables()
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logger.success("初始化知识库数据库：成功。")
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if xf_endpoint:
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Settings.model_settings.MODEL_PLATFORMS[0].api_base_url = xf_endpoint
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if llm_model:
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Settings.model_settings.DEFAULT_LLM_MODEL = llm_model
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if embed_model:
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Settings.model_settings.DEFAULT_EMBEDDING_MODEL = embed_model
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Settings.createl_all_templates()
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Settings.set_auto_reload(True)
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logger.success("生成默认配置文件：成功。")
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logger.success("请先检查确认 model_settings.yaml 里模型平台、LLM模型和Embed模型信息已经正确")
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if recreate_kb:
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folder2db(kb_names=kb_names,
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mode="recreate_vs",
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vs_type=Settings.kb_settings.DEFAULT_VS_TYPE,
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embed_model=get_default_embedding())
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logger.success("<green>所有初始化已完成，执行 chatchat start -a 启动服务。</green>")
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else:
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logger.success("执行 chatchat kb -r 初始化知识库，然后 chatchat start -a 启动服务。")
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main.add_command(startup_main, "start")
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main.add_command(kb_main, "kb")
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if __name__ == "__main__":
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main()
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