mirror of
https://github.com/csunny/DB-GPT.git
synced 2025-08-16 15:31:19 +00:00
add plugin mode
This commit is contained in:
yhjun1026
parent
20edf6daaa
commit
9511cdb10a
@ -1,52 +0,0 @@
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from typing import Any, Callable, Dict, List, Optional
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class PromptGenerator:
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"""
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generating custom prompt strings based on constraints；
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Compatible with AutoGpt Plugin;
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"""
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def __init__(self) -> None:
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"""
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Initialize the PromptGenerator object with empty lists of constraints,
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commands, resources, and performance evaluations.
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"""
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self.constraints = []
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self.commands = []
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self.resources = []
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self.performance_evaluation = []
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self.goals = []
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self.command_registry = None
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self.name = "Bob"
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self.role = "AI"
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self.response_format = None
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def add_command(
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self,
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command_label: str,
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command_name: str,
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args=None,
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function: Optional[Callable] = None,
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) -> None:
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"""
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Add a command to the commands list with a label, name, and optional arguments.
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GB-GPT and Auto-GPT plugin registration command.
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Args:
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command_label (str): The label of the command.
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command_name (str): The name of the command.
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args (dict, optional): A dictionary containing argument names and their
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values. Defaults to None.
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function (callable, optional): A callable function to be called when
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the command is executed. Defaults to None.
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"""
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if args is None:
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args = {}
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command_args = {arg_key: arg_value for arg_key, arg_value in args.items()}
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command = {
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"label": command_label,
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"name": command_name,
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"args": command_args,
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"function": function,
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}
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self.commands.append(command)
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@ -42,6 +42,7 @@ from pilot.scene.chat_db.out_parser import DbChatOutputParser
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CFG = Config()
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class ChatWithDb(BaseChat):
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chat_scene: str = ChatScene.ChatWithDb.value
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@ -49,7 +50,7 @@ class ChatWithDb(BaseChat):
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def __init__(self, chat_session_id, db_name, user_input):
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""" """
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super().__init__(ChatScene.ChatWithDb, chat_session_id, user_input)
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super().__init__(chat_mode=ChatScene.ChatWithDb, chat_session_id=chat_session_id, current_user_input=user_input)
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if not db_name:
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raise ValueError(f"{ChatScene.ChatWithDb.value} mode should chose db!")
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self.db_name = db_name
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@ -60,17 +61,16 @@ class ChatWithDb(BaseChat):
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def generate_input_values(self):
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input_values = {
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"input": self.current_user_input,
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"top_k": str(self.top_k),
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"dialect": self.database.dialect,
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"table_info": self.database.table_simple_info(self.db_connect)
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}
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"input": self.current_user_input,
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"top_k": str(self.top_k),
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"dialect": self.database.dialect,
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"table_info": self.database.table_simple_info(self.db_connect)
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}
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return input_values
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def do_with_prompt_response(self, prompt_response):
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return self.database.run(self.db_connect, prompt_response.sql)
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# def call(self) -> str:
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# input_values = {
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# "input": self.current_user_input,
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@ -176,9 +176,6 @@ class ChatWithDb(BaseChat):
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return ret
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@property
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def chat_type(self) -> str:
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return ChatScene.ChatExecution.value
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@ -11,6 +11,8 @@ from pilot.configs.config import Config
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from pilot.commands.command import execute_command
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from pilot.prompts.generator import PluginPromptGenerator
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from pilot.scene.chat_execution.prompt import chat_plugin_prompt
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CFG = Config()
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class ChatWithPlugin(BaseChat):
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@ -18,15 +20,19 @@ class ChatWithPlugin(BaseChat):
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plugins_prompt_generator:PluginPromptGenerator
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select_plugin: str = None
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def __init__(self, chat_mode, chat_session_id, current_user_input, select_plugin:str=None):
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super().__init__(chat_mode, chat_session_id, current_user_input)
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def __init__(self, chat_session_id, user_input, plugin_selector:str=None):
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super().__init__(chat_mode=ChatScene.ChatExecution, chat_session_id=chat_session_id, current_user_input=user_input)
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self.plugins_prompt_generator = PluginPromptGenerator()
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self.plugins_prompt_generator.command_registry = self.command_registry
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self.plugins_prompt_generator.command_registry = CFG.command_registry
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# 加载插件中可用命令
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self.select_plugin = select_plugin
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self.select_plugin = plugin_selector
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if self.select_plugin:
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for plugin in CFG.plugins:
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if plugin.
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if plugin._name == plugin_selector :
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if not plugin.can_handle_post_prompt():
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continue
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self.plugins_prompt_generator = plugin.post_prompt(self.plugins_prompt_generator)
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else:
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for plugin in CFG.plugins:
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if not plugin.can_handle_post_prompt():
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@ -39,7 +45,7 @@ class ChatWithPlugin(BaseChat):
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def generate_input_values(self):
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input_values = {
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"input": self.current_user_input,
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"constraints": self.__list_to_prompt_str(self.plugins_prompt_generator.constraints),
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"constraints": self.__list_to_prompt_str(list(self.plugins_prompt_generator.constraints)),
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"commands_infos": self.plugins_prompt_generator.generate_commands_string()
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}
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return input_values
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@ -48,101 +54,12 @@ class ChatWithPlugin(BaseChat):
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## plugin command run
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return execute_command(str(prompt_response), self.plugins_prompt_generator)
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# def call(self):
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# input_values = {
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# "input": self.current_user_input,
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# "constraints": self.__list_to_prompt_str(self.plugins_prompt_generator.constraints),
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# "commands_infos": self.__get_comnands_promp_info()
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# }
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#
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# ### Chat sequence advance
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# self.current_message.chat_order = len(self.history_message) + 1
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# self.current_message.add_user_message(self.current_user_input)
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# self.current_message.start_date = datetime.datetime.now()
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# # TODO
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# self.current_message.tokens = 0
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#
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# current_prompt = self.prompt_template.format(**input_values)
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#
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# ### 构建当前对话， 是否安第一次对话prompt构造？ 是否考虑切换库
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# if self.history_message:
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# ## TODO 带历史对话记录的场景需要确定切换库后怎么处理
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# logger.info(
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# f"There are already {len(self.history_message)} rounds of conversations!"
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# )
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#
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# self.current_message.add_system_message(current_prompt)
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#
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# payload = {
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# "model": self.llm_model,
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# "prompt": self.generate_llm_text(),
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# "temperature": float(self.temperature),
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# "max_new_tokens": int(self.max_new_tokens),
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# "stop": self.prompt_template.sep,
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# }
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# logger.info(f"Requert: \n{payload}")
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# ai_response_text = ""
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# try:
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# ### 走非流式的模型服务接口
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#
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# response = requests.post(
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# urljoin(CFG.MODEL_SERVER, "generate"),
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# headers=headers,
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# json=payload,
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# timeout=120,
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# )
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# ai_response_text = (
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# self.prompt_template.output_parser.parse_model_server_out(response)
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# )
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# self.current_message.add_ai_message(ai_response_text)
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# prompt_define_response = self.prompt_template.output_parser.parse_prompt_response(ai_response_text)
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#
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#
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# ## plugin command run
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# result = execute_command(prompt_define_response, self.plugins_prompt_generator)
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#
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# if hasattr(prompt_define_response, "thoughts"):
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# if prompt_define_response.thoughts.get("speak"):
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# self.current_message.add_view_message(
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# self.prompt_template.output_parser.parse_view_response(
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# prompt_define_response.thoughts.get("speak"), result
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# )
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# )
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# elif prompt_define_response.thoughts.get("reasoning"):
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# self.current_message.add_view_message(
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# self.prompt_template.output_parser.parse_view_response(
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# prompt_define_response.thoughts.get("reasoning"), result
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# )
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# )
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# else:
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# self.current_message.add_view_message(
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# self.prompt_template.output_parser.parse_view_response(
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# prompt_define_response.thoughts, result
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# )
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# )
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# else:
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# self.current_message.add_view_message(
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# self.prompt_template.output_parser.parse_view_response(
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# prompt_define_response, result
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# )
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# )
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#
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# except Exception as e:
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# print(traceback.format_exc())
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# logger.error("model response parase faild！" + str(e))
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# self.current_message.add_view_message(
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# f"""<span style=\"color:red\">ERROR!</span>{str(e)}\n {ai_response_text} """
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# )
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# ### 对话记录存储
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# self.memory.append(self.current_message)
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def chat_show(self):
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super().chat_show()
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def __list_to_prompt_str(list: List) -> str:
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if not list:
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def __list_to_prompt_str(self, list: List) -> str:
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if list:
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separator = '\n'
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return separator.join(list)
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else:
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@ -52,7 +52,7 @@ PROMPT_NEED_NEED_STREAM_OUT = False
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chat_plugin_prompt = PromptTemplate(
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template_scene=ChatScene.ChatExecution.value,
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input_variables=["input", "table_info", "dialect", "top_k", "response"],
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input_variables=["input", "constraints", "commands_infos", "response"],
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response_format=json.dumps(RESPONSE_FORMAT, indent=4),
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template_define=PROMPT_SCENE_DEFINE,
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template=PROMPT_SUFFIX + _DEFAULT_TEMPLATE + PROMPT_RESPONSE,
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@ -103,6 +103,11 @@ def gen_sqlgen_conversation(dbname):
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return f"数据库{dbname}的Schema信息如下: {message}\n"
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def plugins_select_info():
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plugins_infos: dict = {}
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for plugin in CFG.plugins:
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plugins_infos.update({f"【{plugin._name}】=>{plugin._description}": plugin._name})
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return plugins_infos
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get_window_url_params = """
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@ -188,26 +193,27 @@ def post_process_code(code):
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return code
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def get_chat_mode(mode, sql_mode, db_selector) -> ChatScene:
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if mode == conversation_types["default_knownledge"] and not db_selector:
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return ChatScene.ChatKnowledge
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elif mode == conversation_types["custome"] and not db_selector:
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return ChatScene.ChatNewKnowledge
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elif sql_mode == conversation_sql_mode["auto_execute_ai_response"] and db_selector:
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return ChatScene.ChatWithDb
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elif mode == conversation_types["auto_execute_plugin"] and not db_selector:
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def get_chat_mode(selected, mode, sql_mode, db_selector) -> ChatScene:
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if "插件模式" == selected:
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return ChatScene.ChatExecution
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elif "知识问答" == selected:
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if mode == conversation_types["default_knownledge"]:
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return ChatScene.ChatKnowledge
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elif mode == conversation_types["custome"]:
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return ChatScene.ChatNewKnowledge
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else:
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return ChatScene.ChatNormal
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if sql_mode == conversation_sql_mode["auto_execute_ai_response"] and db_selector:
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return ChatScene.ChatWithDb
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return ChatScene.ChatNormal
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def http_bot(
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state, mode, sql_mode, db_selector, temperature, max_new_tokens, request: gr.Request
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state, selected, plugin_selector, mode, sql_mode, db_selector, temperature, max_new_tokens, request: gr.Request
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):
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logger.info(f"User message send!{state.conv_id},{sql_mode},{db_selector}")
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logger.info(f"User message send!{state.conv_id},{selected},{mode},{sql_mode},{db_selector},{plugin_selector}")
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start_tstamp = time.time()
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scene: ChatScene = get_chat_mode(mode, sql_mode, db_selector)
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scene: ChatScene = get_chat_mode(selected, mode, sql_mode, db_selector)
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print(f"当前对话模式:{scene.value}")
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model_name = CFG.LLM_MODEL
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@ -216,6 +222,17 @@ def http_bot(
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chat_param = {
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"chat_session_id": state.conv_id,
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"db_name": db_selector,
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"current_user_input": state.last_user_input,
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}
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chat: BaseChat = CHAT_FACTORY.get_implementation(scene.value, **chat_param)
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chat.call()
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state.messages[-1][-1] = f"{chat.current_ai_response()}"
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yield (state, state.to_gradio_chatbot()) + (enable_btn,) * 5
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elif ChatScene.ChatExecution == scene:
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logger.info("插件模式对话走新的模式！")
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chat_param = {
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"chat_session_id": state.conv_id,
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"plugin_selector": plugin_selector,
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"user_input": state.last_user_input,
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}
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chat: BaseChat = CHAT_FACTORY.get_implementation(scene.value, **chat_param)
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@ -362,8 +379,8 @@ def http_bot(
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block_css = (
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code_highlight_css
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+ """
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code_highlight_css
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+ """
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pre {
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white-space: pre-wrap; /* Since CSS 2.1 */
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white-space: -moz-pre-wrap; /* Mozilla, since 1999 */
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@ -396,6 +413,11 @@ def change_tab():
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autogpt = True
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def change_func(xx):
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print("123")
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print(str(xx))
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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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@ -430,11 +452,18 @@ def build_single_model_ui():
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label="最大输出Token数",
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)
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tabs = gr.Tabs()
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def on_select(evt: gr.SelectData): # SelectData is a subclass of EventData
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print(f"You selected {evt.value} at {evt.index} from {evt.target}")
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return evt.value
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selected = gr.Textbox(show_label=False, visible=False, placeholder="Selected")
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tabs.select(on_select, None, selected)
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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.select(on_select, None, None)
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with tab_sql:
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print("tab_sql in...")
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# TODO A selector to choose database
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@ -452,18 +481,26 @@ def build_single_model_ui():
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sql_mode.change(fn=change_sql_mode, inputs=sql_mode, outputs=sql_vs_setting)
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tab_plugin = gr.TabItem("插件模式", elem_id="PLUGIN")
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# tab_plugin.select(change_func)
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with tab_plugin:
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print("tab_plugin in...")
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with gr.Row(elem_id="plugin_selector"):
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# TODO
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plugin_selector = gr.Dropdown(
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label="请选择插件",
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choices=[""" [datadance-ddl-excutor]->use datadance deal the ddl task """, """[file-writer]-file read and write """, """ [image-excutor]-> image build"""],
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value="datadance-ddl-excutor",
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choices=list(plugins_select_info().keys()),
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value="",
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interactive=True,
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show_label=True,
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type="value"
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).style(container=False)
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def plugin_change(evt: gr.SelectData): # SelectData is a subclass of EventData
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print(f"You selected {evt.value} at {evt.index} from {evt.target}")
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return plugins_select_info().get(evt.value)
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plugin_selected = gr.Textbox(show_label=False, visible=False, placeholder="Selected")
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plugin_selector.select(plugin_change, None, plugin_selected)
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tab_qa = gr.TabItem("知识问答", elem_id="QA")
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with tab_qa:
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@ -517,7 +554,7 @@ def build_single_model_ui():
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btn_list = [regenerate_btn, clear_btn]
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regenerate_btn.click(regenerate, state, [state, chatbot, textbox] + btn_list).then(
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http_bot,
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[state, mode, sql_mode, db_selector, temperature, max_output_tokens],
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[state, selected, plugin_selected, mode, sql_mode, db_selector, temperature, max_output_tokens],
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[state, chatbot] + btn_list,
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)
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clear_btn.click(clear_history, None, [state, chatbot, textbox] + btn_list)
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@ -526,7 +563,7 @@ def build_single_model_ui():
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add_text, [state, textbox], [state, chatbot, textbox] + btn_list
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).then(
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http_bot,
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[state, mode, sql_mode, db_selector, temperature, max_output_tokens],
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[state, selected, plugin_selected, mode, sql_mode, db_selector, temperature, max_output_tokens],
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[state, chatbot] + btn_list,
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)
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@ -534,7 +571,7 @@ def build_single_model_ui():
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add_text, [state, textbox], [state, chatbot, textbox] + btn_list
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).then(
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http_bot,
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[state, mode, sql_mode, db_selector, temperature, max_output_tokens],
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[state, selected, plugin_selected, mode, sql_mode, db_selector, temperature, max_output_tokens],
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[state, chatbot] + btn_list,
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)
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vs_add.click(
|
||||
@ -557,10 +594,10 @@ def build_single_model_ui():
|
||||
|
||||
def build_webdemo():
|
||||
with gr.Blocks(
|
||||
title="数据库智能助手",
|
||||
# theme=gr.themes.Base(),
|
||||
theme=gr.themes.Default(),
|
||||
css=block_css,
|
||||
title="数据库智能助手",
|
||||
# theme=gr.themes.Base(),
|
||||
theme=gr.themes.Default(),
|
||||
css=block_css,
|
||||
) as demo:
|
||||
url_params = gr.JSON(visible=False)
|
||||
(
|
||||
|
||||
Loading…
Reference in New Issue
Block a user