mirror of
https://github.com/csunny/DB-GPT.git
synced 2025-08-27 12:29:29 +00:00
add multi language support.
This commit is contained in:
xuyuan23
parent
81e7533714
commit
7fa205aefc
@ -92,3 +92,7 @@ VECTOR_STORE_TYPE=Chroma
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#MILVUS_USERNAME
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#MILVUS_PASSWORD
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#MILVUS_SECURE=
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LANGUAGE=en
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#LANGUAGE=zh
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3
.gitignore
vendored
3
.gitignore
vendored
@ -141,3 +141,6 @@ logs
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nltk_data
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.vectordb
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pilot/data/
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logswebserver.log.*
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.history/*
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@ -246,8 +246,8 @@ Run the Python interpreter and type the commands:
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## 贡献者
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|[<img src="https://avatars.githubusercontent.com/u/17919400?v=4" width="100px;"/><br/><sub><b>csunny</b></sub>](https://github.com/csunny)<br/>|[<img src="https://avatars.githubusercontent.com/u/1011681?v=4" width="100px;"/><br/><sub><b>xudafeng</b></sub>](https://github.com/xudafeng)<br/>|[<img src="https://avatars.githubusercontent.com/u/7636723?s=96&v=4" width="100px;"/><br/><sub><b>明天</b></sub>](https://github.com/yhjun1026)<br/> | [<img src="https://avatars.githubusercontent.com/u/13723926?v=4" width="100px;"/><br/><sub><b>Aries-ckt</b></sub>](https://github.com/Aries-ckt)<br/>|[<img src="https://avatars.githubusercontent.com/u/95130644?v=4" width="100px;"/><br/><sub><b>thebigbone</b></sub>](https://github.com/thebigbone)<br/>|
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| :---: | :---: | :---: | :---: |:---: |
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|[<img src="https://avatars.githubusercontent.com/u/17919400?v=4" width="100px;"/><br/><sub><b>csunny</b></sub>](https://github.com/csunny)<br/>|[<img src="https://avatars.githubusercontent.com/u/1011681?v=4" width="100px;"/><br/><sub><b>xudafeng</b></sub>](https://github.com/xudafeng)<br/>|[<img src="https://avatars.githubusercontent.com/u/7636723?s=96&v=4" width="100px;"/><br/><sub><b>明天</b></sub>](https://github.com/yhjun1026)<br/> | [<img src="https://avatars.githubusercontent.com/u/13723926?v=4" width="100px;"/><br/><sub><b>Aries-ckt</b></sub>](https://github.com/Aries-ckt)<br/>|[<img src="https://avatars.githubusercontent.com/u/95130644?v=4" width="100px;"/><br/><sub><b>thebigbone</b></sub>](https://github.com/thebigbone)<br/>|[<img src="https://avatars.githubusercontent.com/u/26043513?v=4" width="100px;"/><br/><sub><b>Shinexy</b></sub>](https://github.com/xuyuan23)<br/> |
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| :---: | :---: | :---: | :---: |:---: |:---: |
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[git-contributor 说明](https://github.com/xudafeng/git-contributor)，自动生成时间：`Fri May 19 2023 00:24:18 GMT+0800`。
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@ -17,6 +17,9 @@ class Config(metaclass=Singleton):
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def __init__(self) -> None:
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"""Initialize the Config class"""
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# Gradio language version: en, cn
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self.LANGUAGE = os.getenv("LANGUAGE", "en")
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self.debug_mode = False
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self.skip_reprompt = False
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self.temperature = float(os.getenv("TEMPERATURE", 0.7))
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73
pilot/language/lang_content_mapping.py
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73
pilot/language/lang_content_mapping.py
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@ -0,0 +1,73 @@
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## 短期内在该文件中配置，长期考虑将会存储在默认的数据库中存储，并可以支持多种语言的配置
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lang_dicts = {
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"zh": {
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"unique_id": "中文内容",
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"db_gpt_introduction": "[DB-GPT](https://github.com/csunny/DB-GPT) 是一个开源的以数据库为基础的GPT实验项目，使用本地化的GPT大模型与您的数据和环境进行交互，无数据泄露风险，100% 私密，100% 安全。",
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"learn_more_markdown": "该服务是仅供非商业用途的研究预览。受 Vicuna-13B 模型 [License](https://github.com/facebookresearch/llama/blob/main/MODEL_CARD.md) 的约束",
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"model_control_param": "模型参数",
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"sql_generate_mode_direct": "直接生成结果",
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"sql_generate_mode_none": "不执行结果",
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"max_input_token_size": "最大输出Token数",
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"please_choose_database": "请选择数据",
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"sql_generate_diagnostics": "SQL生成与诊断",
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"knowledge_qa_type_llm_native_dialogue": "LLM原生对话",
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"knowledge_qa_type_default_knowledge_base_dialogue": "默认知识库对话",
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"knowledge_qa_type_add_knowledge_base_dialogue": "新增知识库对话",
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"create_knowledge_base": "新建知识库",
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"sql_schema_info": "数据库{dbname}的Schema信息如下: {message}\n",
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"current_dialogue_mode": "当前对话模式",
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"database_smart_assistant": "数据库智能助手",
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"sql_vs_setting": "自动执行模式下, DB-GPT可以具备执行SQL、从网络读取知识自动化存储学习的能力",
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"knowledge_qa": "知识问答",
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"configure_knowledge_base": "配置知识库",
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"new_klg_name": "新知识库名称",
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"add_as_new_klg": "添加为新知识库",
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"add_file_to_klg": "向知识库中添加文件",
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"upload_file": "上传文件",
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"add_file": "添加文件",
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"upload_and_load_to_klg": "上传并加载到知识库",
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"upload_folder": "上传文件夹",
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"add_folder": "添加文件夹",
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"send": "发送",
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"regenerate": "重新生成",
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"clear_box": "清理"
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},
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"en": {
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"unique_id": "English Content",
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"db_gpt_introduction": "[DB-GPT](https://github.com/csunny/DB-GPT) is an experimental open-source project that uses localized GPT large models to interact with your data and environment. With this solution, you can be assured that there is no risk of data leakage, and your data is 100% private and secure.",
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"learn_more_markdown": "The service is a research preview intended for non-commercial use only. subject to the model [License](https://github.com/facebookresearch/llama/blob/main/MODEL_CARD.md) of Vicuna-13B",
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"model_control_param": "Model Parameters",
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"sql_generate_mode_direct": "Execute directly",
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"sql_generate_mode_none": "Execute without model",
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"max_input_token_size": "Maximum output token size",
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"please_choose_database": "Please choose database",
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"sql_generate_diagnostics": "SQL Generation & Diagnostics",
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"knowledge_qa_type_llm_native_dialogue": "LLM native dialogue",
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"knowledge_qa_type_default_knowledge_base_dialogue": "Default Knowledge Base",
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"knowledge_qa_type_add_knowledge_base_dialogue": "Added Knowledge Base",
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"create_knowledge_base": "Create Knowledge Base",
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"sql_schema_info": "the schema information of database {}: {}\n",
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"current_dialogue_mode": "Current dialogue mode",
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"database_smart_assistant": "Database smart assistant",
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"sql_vs_setting": "In the automatic execution mode, DB-GPT can have the ability to execute SQL, read knowledge from the network, automatically store and learn",
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"knowledge_qa": "Knowledge QA",
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"configure_knowledge_base": "Configure Knowledge Base",
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"new_klg_name": "New Knowledge Base name",
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"add_as_new_klg": "Add as new knowledge base",
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"add_file_to_klg": "Add file to knowledge base",
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"upload_file": "Upload file",
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"add_file": "Add file",
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"upload_and_load_to_klg": "Upload and load to knowledge base",
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"upload_folder": "Upload folder",
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"add_folder": "Add folder",
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"send": "Send",
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"regenerate": "Regenerate",
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"clear_box": "Clear"
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}
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}
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def get_lang_content(key, language="zh"):
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return lang_dicts.get(language, {}).get(key, "")
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12
pilot/language/translation_handler.py
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12
pilot/language/translation_handler.py
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@ -0,0 +1,12 @@
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from pilot.configs.config import Config
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from pilot.language.lang_content_mapping import get_lang_content
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CFG = Config()
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def get_lang_text(key):
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return get_lang_content(key, CFG.LANGUAGE)
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@ -56,7 +56,11 @@ from pilot.vector_store.extract_tovec import (
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from pilot.commands.command import execute_ai_response_json
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from pilot.scene.base import ChatScene
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from pilot.scene.chat_factory import ChatFactory
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from pilot.language.translation_handler import get_lang_text
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# 加载插件
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CFG = Config()
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logger = build_logger("webserver", LOGDIR + "webserver.log")
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headers = {"User-Agent": "dbgpt Client"}
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@ -67,15 +71,13 @@ disable_btn = gr.Button.update(interactive=True)
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enable_moderation = False
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models = []
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dbs = []
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vs_list = ["新建知识库"] + get_vector_storelist()
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vs_list = [get_lang_text("create_knowledge_base")] + get_vector_storelist()
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autogpt = False
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vector_store_client = None
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vector_store_name = {"vs_name": ""}
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priority = {"vicuna-13b": "aaa"}
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# 加载插件
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CFG = Config()
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CHAT_FACTORY = ChatFactory()
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DB_SETTINGS = {
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@ -86,6 +88,11 @@ DB_SETTINGS = {
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}
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llm_native_dialogue = get_lang_text("knowledge_qa_type_llm_native_dialogue")
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default_knowledge_base_dialogue = get_lang_text("knowledge_qa_type_default_knowledge_base_dialogue")
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add_knowledge_base_dialogue = get_lang_text("knowledge_qa_type_add_knowledge_base_dialogue")
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knowledge_qa_type_list = [llm_native_dialogue, default_knowledge_base_dialogue, add_knowledge_base_dialogue]
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def get_simlar(q):
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docsearch = knownledge_tovec_st(os.path.join(DATASETS_DIR, "plan.md"))
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docs = docsearch.similarity_search_with_score(q, k=1)
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@ -102,7 +109,7 @@ def gen_sqlgen_conversation(dbname):
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schemas = mo.get_schema(dbname)
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for s in schemas:
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message += s["schema_info"] + ";"
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return f"数据库{dbname}的Schema信息如下: {message}\n"
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return get_lang_text("sql_schema_info").format(dbname, message)
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def get_database_list():
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@ -491,14 +498,14 @@ block_css = (
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def change_sql_mode(sql_mode):
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if sql_mode in ["直接执行结果"]:
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if sql_mode in [get_lang_text("sql_generate_mode_direct")]:
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return gr.update(visible=True)
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else:
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return gr.update(visible=False)
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def change_mode(mode):
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if mode in ["默认知识库对话", "LLM原生对话"]:
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if mode in [default_knowledge_base_dialogue, llm_native_dialogue]:
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return gr.update(visible=False)
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else:
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return gr.update(visible=True)
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@ -509,20 +516,13 @@ def change_tab():
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def build_single_model_ui():
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notice_markdown = """
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# DB-GPT
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[DB-GPT](https://github.com/csunny/DB-GPT) 是一个开源的以数据库为基础的GPT实验项目，使用本地化的GPT大模型与您的数据和环境进行交互，无数据泄露风险，100% 私密，100% 安全。
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"""
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learn_more_markdown = """
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### Licence
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The service is a research preview intended for non-commercial use only. subject to the model [License](https://github.com/facebookresearch/llama/blob/main/MODEL_CARD.md) of Vicuna-13B
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"""
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notice_markdown = get_lang_text("db_gpt_introduction")
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learn_more_markdown = get_lang_text("learn_more_markdown")
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state = gr.State()
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gr.Markdown(notice_markdown, elem_id="notice_markdown")
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with gr.Accordion("参数", open=False, visible=False) as parameter_row:
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with gr.Accordion(get_lang_text("model_control_param"), open=False, visible=False) as parameter_row:
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temperature = gr.Slider(
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minimum=0.0,
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maximum=1.0,
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@ -538,56 +538,56 @@ def build_single_model_ui():
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value=512,
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step=64,
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interactive=True,
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label="最大输出Token数",
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label=get_lang_text("max_input_token_size"),
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)
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tabs = gr.Tabs()
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with tabs:
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tab_sql = gr.TabItem("SQL生成与诊断", elem_id="SQL")
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tab_sql = gr.TabItem(get_lang_text("sql_generate_diagnostics"), elem_id="SQL")
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with tab_sql:
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# TODO A selector to choose database
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with gr.Row(elem_id="db_selector"):
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db_selector = gr.Dropdown(
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label="请选择数据库",
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label=get_lang_text("please_choose_database"),
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choices=dbs,
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value=dbs[0] if len(models) > 0 else "",
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interactive=True,
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show_label=True,
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).style(container=False)
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sql_mode = gr.Radio(["直接执行结果", "不执行结果"], show_label=False, value="不执行结果")
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sql_vs_setting = gr.Markdown("自动执行模式下, DB-GPT可以具备执行SQL、从网络读取知识自动化存储学习的能力")
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sql_mode = gr.Radio([get_lang_text("sql_generate_mode_direct"), get_lang_text("sql_generate_mode_none")], show_label=False, value=get_lang_text("sql_generate_mode_none"))
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sql_vs_setting = gr.Markdown(get_lang_text("sql_vs_setting"))
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sql_mode.change(fn=change_sql_mode, inputs=sql_mode, outputs=sql_vs_setting)
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tab_qa = gr.TabItem("知识问答", elem_id="QA")
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tab_qa = gr.TabItem(get_lang_text("knowledge_qa"), elem_id="QA")
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with tab_qa:
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mode = gr.Radio(
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["LLM原生对话", "默认知识库对话", "新增知识库对话"], show_label=False, value="LLM原生对话"
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[llm_native_dialogue, default_knowledge_base_dialogue, add_knowledge_base_dialogue], show_label=False, value=llm_native_dialogue
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)
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vs_setting = gr.Accordion("配置知识库", open=False)
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vs_setting = gr.Accordion(get_lang_text("configure_knowledge_base"), open=False)
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mode.change(fn=change_mode, inputs=mode, outputs=vs_setting)
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with vs_setting:
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vs_name = gr.Textbox(label="新知识库名称", lines=1, interactive=True)
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vs_add = gr.Button("添加为新知识库")
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vs_name = gr.Textbox(label=get_lang_text("new_klg_name"), lines=1, interactive=True)
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vs_add = gr.Button(get_lang_text("add_as_new_klg"))
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with gr.Column() as doc2vec:
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gr.Markdown("向知识库中添加文件")
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with gr.Tab("上传文件"):
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gr.Markdown(get_lang_text("add_file_to_klg"))
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with gr.Tab(get_lang_text("upload_file")):
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files = gr.File(
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label="添加文件",
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label=get_lang_text("add_file"),
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file_types=[".txt", ".md", ".docx", ".pdf"],
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file_count="multiple",
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allow_flagged_uploads=True,
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show_label=False,
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)
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load_file_button = gr.Button("上传并加载到知识库")
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with gr.Tab("上传文件夹"):
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load_file_button = gr.Button(get_lang_text("upload_and_load_to_klg"))
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with gr.Tab(get_lang_text("upload_folder")):
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folder_files = gr.File(
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label="添加文件夹",
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label=get_lang_text("add_folder"),
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accept_multiple_files=True,
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file_count="directory",
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show_label=False,
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)
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load_folder_button = gr.Button("上传并加载到知识库")
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load_folder_button = gr.Button(get_lang_text("upload_and_load_to_klg"))
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with gr.Blocks():
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chatbot = grChatbot(elem_id="chatbot", visible=False).style(height=550)
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@ -599,11 +599,11 @@ def build_single_model_ui():
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visible=False,
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).style(container=False)
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with gr.Column(scale=2, min_width=50):
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send_btn = gr.Button(value="发送", visible=False)
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send_btn = gr.Button(value=get_lang_text("send"), visible=False)
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with gr.Row(visible=False) as button_row:
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regenerate_btn = gr.Button(value="重新生成", interactive=False)
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clear_btn = gr.Button(value="清理", interactive=False)
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regenerate_btn = gr.Button(value=get_lang_text("regenerate"), interactive=False)
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clear_btn = gr.Button(value=get_lang_text("clear_box"), interactive=False)
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gr.Markdown(learn_more_markdown)
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btn_list = [regenerate_btn, clear_btn]
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@ -649,7 +649,7 @@ def build_single_model_ui():
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def build_webdemo():
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with gr.Blocks(
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title="数据库智能助手",
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title=get_lang_text("database_smart_assistant"),
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# theme=gr.themes.Base(),
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theme=gr.themes.Default(),
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css=block_css,
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