python code style -- black, yapf

dbgpt/__init__.py

@@ -1,5 +1,6 @@
 """DB-GPT: Next Generation Data Interaction Solution with LLMs.
 """
+
 from dbgpt import _version  # noqa: E402
 from dbgpt.component import BaseComponent, SystemApp  # noqa: F401
 

dbgpt/_private/config.py

@@ -73,9 +73,9 @@ def __init__(self) -> None:
         self.wenxin_model_version = os.getenv("WEN_XIN_MODEL_VERSION")
         if self.wenxin_proxy_api_key and self.wenxin_proxy_api_secret:
             os.environ["wenxin_proxyllm_proxy_api_key"] = self.wenxin_proxy_api_key
-            os.environ[
-                "wenxin_proxyllm_proxy_api_secret"
-            ] = self.wenxin_proxy_api_secret
+            os.environ["wenxin_proxyllm_proxy_api_secret"] = (
+                self.wenxin_proxy_api_secret
+            )
             os.environ["wenxin_proxyllm_proxyllm_backend"] = (
                 self.wenxin_model_version or ""
             )
@@ -251,7 +251,7 @@ def __init__(self) -> None:
         self.ElasticSearch_PORT = os.getenv("ElasticSearch_PORT", "9200")
         self.ElasticSearch_USERNAME = os.getenv("ElasticSearch_USERNAME", None)
         self.ElasticSearch_PASSWORD = os.getenv("ElasticSearch_PASSWORD", None)
-        
+
         ## OceanBase Configuration
         self.OB_HOST = os.getenv("OB_HOST", "127.0.0.1")
         self.OB_PORT = int(os.getenv("OB_PORT", "2881"))

dbgpt/agent/core/agent_manage.py

@@ -53,9 +53,9 @@ def __init__(self, system_app: SystemApp):
         """Create a new AgentManager."""
         super().__init__(system_app)
         self.system_app = system_app
-        self._agents: Dict[
-            str, Tuple[Type[ConversableAgent], ConversableAgent]
-        ] = defaultdict()
+        self._agents: Dict[str, Tuple[Type[ConversableAgent], ConversableAgent]] = (
+            defaultdict()
+        )
 
         self._core_agents: Set[str] = set()
 

dbgpt/agent/core/schema.py

@@ -1,4 +1,5 @@
 """Schema definition for the agent."""
+
 from enum import Enum
 
 

dbgpt/agent/core/user_proxy_agent.py

@@ -1,4 +1,5 @@
 """A proxy agent for the user."""
+
 from .base_agent import ConversableAgent
 from .profile import ProfileConfig
 

dbgpt/agent/expand/actions/chart_action.py

@@ -71,10 +71,10 @@ async def run(
         try:
             if not self.resource_loader:
                 raise ValueError("ResourceLoader is not initialized！")
-            resource_db_client: Optional[
-                ResourceDbClient
-            ] = self.resource_loader.get_resource_api(
-                self.resource_need, ResourceDbClient
+            resource_db_client: Optional[ResourceDbClient] = (
+                self.resource_loader.get_resource_api(
+                    self.resource_need, ResourceDbClient
+                )
             )
             if not resource_db_client:
                 raise ValueError(

dbgpt/agent/expand/actions/dashboard_action.py

@@ -85,10 +85,10 @@ async def run(
         try:
             if not self.resource_loader:
                 raise ValueError("Resource loader is not initialized!")
-            resource_db_client: Optional[
-                ResourceDbClient
-            ] = self.resource_loader.get_resource_api(
-                self.resource_need, ResourceDbClient
+            resource_db_client: Optional[ResourceDbClient] = (
+                self.resource_loader.get_resource_api(
+                    self.resource_need, ResourceDbClient
+                )
             )
             if not resource_db_client:
                 raise ValueError(

dbgpt/agent/expand/actions/plugin_action.py

@@ -109,10 +109,10 @@ async def run(
         try:
             if not self.resource_loader:
                 raise ValueError("No resource_loader found!")
-            resource_plugin_client: Optional[
-                ResourcePluginClient
-            ] = self.resource_loader.get_resource_api(
-                self.resource_need, ResourcePluginClient
+            resource_plugin_client: Optional[ResourcePluginClient] = (
+                self.resource_loader.get_resource_api(
+                    self.resource_need, ResourcePluginClient
+                )
             )
             if not resource_plugin_client:
                 raise ValueError("No implementation of the use of plug-in resources！")

dbgpt/agent/expand/data_scientist_agent.py

@@ -112,10 +112,10 @@ async def correctness_check(
                 "generated is not found.",
             )
         try:
-            resource_db_client: Optional[
-                ResourceDbClient
-            ] = self.not_null_resource_loader.get_resource_api(
-                ResourceType(action_out.resource_type), ResourceDbClient
+            resource_db_client: Optional[ResourceDbClient] = (
+                self.not_null_resource_loader.get_resource_api(
+                    ResourceType(action_out.resource_type), ResourceDbClient
+                )
             )
             if not resource_db_client:
                 return (

dbgpt/agent/plugin/commands/built_in/display_type/__init__.py

@@ -1,2 +1,3 @@
 """Visualize Data."""
+
 from .show_chart_gen import static_message_img_path  # noqa: F401

dbgpt/agent/plugin/commands/built_in/display_type/show_chart_gen.py

@@ -1,4 +1,5 @@
 """Chart display command implementation."""
+
 import logging
 import os
 import uuid

dbgpt/agent/plugin/commands/built_in/display_type/show_table_gen.py

@@ -1,4 +1,5 @@
 """Generate a table display for the response."""
+
 import logging
 
 from pandas import DataFrame

dbgpt/agent/plugin/commands/built_in/display_type/show_text_gen.py

@@ -1,4 +1,5 @@
 """Generate text display content for the data frame."""
+
 import logging
 
 from pandas import DataFrame

dbgpt/agent/plugin/commands/command.py

@@ -1,4 +1,5 @@
 """Command module."""
+
 import json
 from typing import Any, Dict
 

dbgpt/agent/plugin/generator.py

@@ -1,4 +1,5 @@
 """A module for generating custom prompt strings."""
+
 from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional
 
 from dbgpt._private.pydantic import BaseModel, Field

dbgpt/agent/plugin/plugins_util.py

@@ -201,7 +201,9 @@ def update_from_git(
                 f.write(response.content)
             return plugin_repo_name
         else:
-            logger.error(f"Update plugins failed，response code：{response.status_code}")
+            logger.error(
+                f"Update plugins failed，response code：{response.status_code}"
+            )
             raise ValueError(f"Download plugin failed: {response.status_code}")
     except Exception as e:
         logger.error("update plugins from git exception!" + str(e))

dbgpt/agent/resource/__init__.py

@@ -1,4 +1,5 @@
 """Resource module for Agent."""
+
 from .resource_api import AgentResource, ResourceClient, ResourceType  # noqa: F401
 from .resource_db_api import ResourceDbClient, SqliteLoadClient  # noqa: F401
 from .resource_knowledge_api import ResourceKnowledgeClient  # noqa: F401

dbgpt/agent/resource/resource_api.py

@@ -1,4 +1,5 @@
 """Resource API for the agent."""
+
 import json
 from abc import ABC, abstractmethod
 from enum import Enum

dbgpt/agent/resource/resource_db_api.py

@@ -1,4 +1,5 @@
 """Database resource client API."""
+
 import logging
 from contextlib import contextmanager
 from typing import TYPE_CHECKING, Iterator, List, Optional, Union

dbgpt/agent/resource/resource_knowledge_api.py

@@ -1,4 +1,5 @@
 """Knowledge resource API for the agent."""
+
 from typing import Any, Optional
 
 from .resource_api import ResourceClient, ResourceType

dbgpt/agent/resource/resource_loader.py

@@ -1,4 +1,5 @@
 """Resource loader module."""
+
 from collections import defaultdict
 from typing import Optional, Type, TypeVar
 

dbgpt/agent/resource/resource_plugin_api.py

@@ -1,4 +1,5 @@
 """Resource plugin client API."""
+
 import logging
 import os
 from typing import Any, Dict, List, Optional, Union, cast

dbgpt/agent/util/__init__.py

@@ -1,4 +1,5 @@
 """Utils for the agent module."""
+
 from .cmp import cmp_string_equal  # noqa: F401
 
 __ALL__ = ["cmp_string_equal"]

dbgpt/agent/util/cmp.py

@@ -1,4 +1,5 @@
 """Compare string utility functions."""
+
 import string
 
 

dbgpt/agent/util/llm/llm.py

@@ -1,4 +1,5 @@
 """LLM module."""
+
 import logging
 from collections import defaultdict
 from enum import Enum

dbgpt/agent/util/llm/llm_client.py

@@ -1,4 +1,5 @@
 """AIWrapper for LLM."""
+
 import json
 import logging
 import traceback
@@ -75,14 +76,16 @@ def _construct_create_params(self, create_config: Dict, extra_kwargs: Dict) -> D
         elif context and messages and isinstance(messages, list):
             # Instantiate the messages
             params["messages"] = [
-                {
-                    **m,
-                    "content": self.instantiate(
-                        m["content"], context, allow_format_str_template
-                    ),
-                }
-                if m.get("content")
-                else m
+                (
+                    {
+                        **m,
+                        "content": self.instantiate(
+                            m["content"], context, allow_format_str_template
+                        ),
+                    }
+                    if m.get("content")
+                    else m
+                )
                 for m in messages
             ]
         return params

dbgpt/app/__init__.py

@@ -2,6 +2,7 @@
 
 This package will not be uploaded to PyPI. So, your can't import it if some other package depends on it.
 """
+
 import os
 import random
 import sys

dbgpt/app/chat_adapter.py

@@ -2,6 +2,7 @@
 This code file will be deprecated in the future. 
 We have integrated fastchat. For details, see: dbgpt/model/model_adapter.py
 """
+
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 

dbgpt/app/initialization/db_model_initialization.py

@@ -1,5 +1,6 @@
 """Import all models to make sure they are registered with SQLAlchemy.
 """
+
 from dbgpt.app.knowledge.chunk_db import DocumentChunkEntity
 from dbgpt.app.knowledge.document_db import KnowledgeDocumentEntity
 from dbgpt.app.openapi.api_v1.feedback.feed_back_db import ChatFeedBackEntity

dbgpt/app/knowledge/service.py

@@ -480,28 +480,35 @@ def delete_document(self, space_name: str, doc_name: str):
             raise Exception(f"there are no or more than one document called {doc_name}")
         vector_ids = documents[0].vector_ids
         if vector_ids is not None:
-            embedding_factory = CFG.SYSTEM_APP.get_component("embedding_factory", EmbeddingFactory)
-            embedding_fn = embedding_factory.create(model_name=EMBEDDING_MODEL_CONFIG[CFG.EMBEDDING_MODEL])    
-
+            embedding_factory = CFG.SYSTEM_APP.get_component(
+                "embedding_factory", EmbeddingFactory
+            )
+            embedding_fn = embedding_factory.create(
+                model_name=EMBEDDING_MODEL_CONFIG[CFG.EMBEDDING_MODEL]
+            )
+
             if CFG.VECTOR_STORE_TYPE == "Milvus":
                 logger.info(f"正在删除Milvus类型的文档。")
-                config = VectorStoreConfig(name=space_name,            
-                                        embedding_fn=embedding_fn,   
-                                        max_chunks_once_load=CFG.KNOWLEDGE_MAX_CHUNKS_ONCE_LOAD,    
-                                        user=CFG.MILVUS_USERNAME,
-                                        password=CFG.MILVUS_PASSWORD,
-                                        ) 
+                config = VectorStoreConfig(
+                    name=space_name,
+                    embedding_fn=embedding_fn,
+                    max_chunks_once_load=CFG.KNOWLEDGE_MAX_CHUNKS_ONCE_LOAD,
+                    user=CFG.MILVUS_USERNAME,
+                    password=CFG.MILVUS_PASSWORD,
+                )
             elif CFG.VECTOR_STORE_TYPE == "ElasticSearch":
                 logger.info(f"正在删除ES类型的文档。")
-                config = VectorStoreConfig(name=space_name, embedding_fn=embedding_fn,  ## wwt add
-                                        max_chunks_once_load=CFG.KNOWLEDGE_MAX_CHUNKS_ONCE_LOAD,   ## wwt add
-                                        user=CFG.ElasticSearch_USERNAME,
-                                        password=CFG.ElasticSearch_PASSWORD,
-                                        )
+                config = VectorStoreConfig(
+                    name=space_name,
+                    embedding_fn=embedding_fn,  ## wwt add
+                    max_chunks_once_load=CFG.KNOWLEDGE_MAX_CHUNKS_ONCE_LOAD,  ## wwt add
+                    user=CFG.ElasticSearch_USERNAME,
+                    password=CFG.ElasticSearch_PASSWORD,
+                )
             elif CFG.VECTOR_STORE_TYPE == "Chroma":
                 config = VectorStoreConfig(name=space_name)
             else:
-                config = VectorStoreConfig(name=space_name)  
+                config = VectorStoreConfig(name=space_name)
             vector_store_connector = VectorStoreConnector(
                 vector_store_type=CFG.VECTOR_STORE_TYPE,
                 vector_store_config=config,

dbgpt/app/openapi/api_v1/api_v1.py

@@ -83,7 +83,9 @@ def get_db_list():
 def plugins_select_info():
     plugins_infos: dict = {}
     for plugin in CFG.plugins:
-        plugins_infos.update({f"【{plugin._name}】=>{plugin._description}": plugin._name})
+        plugins_infos.update(
+            {f"【{plugin._name}】=>{plugin._description}": plugin._name}
+        )
     return plugins_infos
 
 

dbgpt/app/openapi/api_v1/editor/_chat_history/chat_hisotry_factory.py

@@ -2,6 +2,7 @@
 
 It will remove in the future, just support db store type now.
 """
+
 import logging
 from typing import Type
 

dbgpt/app/scene/chat_dashboard/chat.py

@@ -76,7 +76,7 @@ async def generate_input_values(self) -> Dict:
             "input": self.current_user_input,
             "dialect": self.database.dialect,
             "table_info": self.database.table_simple_info(),
-            "supported_chat_type": self.dashboard_template["supported_chart_type"]
+            "supported_chat_type": self.dashboard_template["supported_chart_type"],
             # "table_info": client.get_similar_tables(dbname=self.db_name, query=self.current_user_input, topk=self.top_k)
         }
 

dbgpt/app/scene/chat_db/auto_execute/example.py

@@ -4,7 +4,10 @@
 EXAMPLES = [
     {
         "messages": [
-            {"type": "human", "data": {"content": "查询用户test1所在的城市", "example": True}},
+            {
+                "type": "human",
+                "data": {"content": "查询用户test1所在的城市", "example": True},
+            },
             {
                 "type": "ai",
                 "data": {
@@ -16,7 +19,10 @@
     },
     {
         "messages": [
-            {"type": "human", "data": {"content": "查询成都的用户的订单信息", "example": True}},
+            {
+                "type": "human",
+                "data": {"content": "查询成都的用户的订单信息", "example": True},
+            },
             {
                 "type": "ai",
                 "data": {

dbgpt/app/scene/chat_knowledge/refine_summary/prompt.py

@@ -11,9 +11,7 @@
 PROMPT_SCENE_DEFINE = """A chat between a curious user and an artificial intelligence assistant, who very familiar with database related knowledge. 
 The assistant gives helpful, detailed, professional and polite answers to the user's questions."""
 
-_DEFAULT_TEMPLATE_ZH = (
-    """我们已经提供了一个到某一点的现有总结:{existing_answer}\n 请根据你之前推理的内容进行最终的总结,总结回答的时候最好按照1.2.3.进行."""
-)
+_DEFAULT_TEMPLATE_ZH = """我们已经提供了一个到某一点的现有总结:{existing_answer}\n 请根据你之前推理的内容进行最终的总结,总结回答的时候最好按照1.2.3.进行."""
 
 _DEFAULT_TEMPLATE_EN = """
 We have provided an existing summary up to a certain point: {existing_answer}\nWe have the opportunity to refine the existing summary (only if needed) with some more context below. 

dbgpt/app/scene/exceptions.py

@@ -1,4 +1,5 @@
 """Exceptions for Application."""
+
 import logging
 
 logger = logging.getLogger(__name__)

dbgpt/client/app.py

@@ -1,4 +1,5 @@
 """App Client API."""
+
 from typing import List
 
 from dbgpt.core.schema.api import Result

dbgpt/client/client.py

@@ -1,4 +1,5 @@
 """This module contains the client for the DB-GPT API."""
+
 import atexit
 import json
 import os