refactor: The first refactored version for sdk release (#907)

Co-authored-by: chengfangyin2 <chengfangyin3@jd.com>

dbgpt/app/scene/base.py

@@ -0,0 +1,137 @@
+from enum import Enum
+from typing import List
+
+
+class Scene:
+    def __init__(
+        self,
+        code,
+        name,
+        describe,
+        param_types: List = [],
+        is_inner: bool = False,
+        show_disable=False,
+        prepare_scene_code: str = None,
+    ):
+        self.code = code
+        self.name = name
+        self.describe = describe
+        self.param_types = param_types
+        self.is_inner = is_inner
+        self.show_disable = show_disable
+        self.prepare_scene_code = prepare_scene_code
+
+
+class ChatScene(Enum):
+    ChatWithDbExecute = Scene(
+        code="chat_with_db_execute",
+        name="Chat Data",
+        describe="Dialogue with your private data through natural language.",
+        param_types=["DB Select"],
+    )
+    ExcelLearning = Scene(
+        code="excel_learning",
+        name="Excel Learning",
+        describe="Analyze and summarize your excel files.",
+        is_inner=True,
+    )
+    ChatExcel = Scene(
+        code="chat_excel",
+        name="Chat Excel",
+        describe="Dialogue with your excel, use natural language.",
+        param_types=["File Select"],
+        prepare_scene_code="excel_learning",
+    )
+
+    ChatWithDbQA = Scene(
+        code="chat_with_db_qa",
+        name="Chat DB",
+        describe="Have a Professional Conversation with Metadata.",
+        param_types=["DB Select"],
+    )
+    ChatExecution = Scene(
+        code="chat_execution",
+        name="Use Plugin",
+        describe="Use tools through dialogue to accomplish your goals.",
+        param_types=["Plugin Select"],
+    )
+
+    ChatAgent = Scene(
+        code="chat_agent",
+        name="Agent Chat",
+        describe="Use tools through dialogue to accomplish your goals.",
+        param_types=["Plugin Select"],
+    )
+
+    InnerChatDBSummary = Scene(
+        "inner_chat_db_summary", "DB Summary", "Db Summary.", True
+    )
+
+    ChatNormal = Scene(
+        "chat_normal", "Chat Normal", "Native LLM large model AI dialogue."
+    )
+    ChatDashboard = Scene(
+        "chat_dashboard",
+        "Dashboard",
+        "Provide you with professional analysis reports through natural language.",
+        ["DB Select"],
+    )
+    ChatKnowledge = Scene(
+        "chat_knowledge",
+        "Chat Knowledge",
+        "Dialogue through natural language and private documents and knowledge bases.",
+        ["Knowledge Space Select"],
+    )
+    ExtractTriplet = Scene(
+        "extract_triplet",
+        "Extract Triplet",
+        "Extract Triplet",
+        ["Extract Select"],
+        True,
+    )
+    ExtractSummary = Scene(
+        "extract_summary",
+        "Extract Summary",
+        "Extract Summary",
+        ["Extract Select"],
+        True,
+    )
+    ExtractRefineSummary = Scene(
+        "extract_refine_summary",
+        "Extract Summary",
+        "Extract Summary",
+        ["Extract Select"],
+        True,
+    )
+    ExtractEntity = Scene(
+        "extract_entity", "Extract Entity", "Extract Entity", ["Extract Select"], True
+    )
+    QueryRewrite = Scene(
+        "query_rewrite", "query_rewrite", "query_rewrite", ["query_rewrite"], True
+    )
+
+    @staticmethod
+    def of_mode(mode):
+        return [x for x in ChatScene if mode == x.value()][0]
+
+    @staticmethod
+    def is_valid_mode(mode):
+        return any(mode == item.value() for item in ChatScene)
+
+    def value(self):
+        return self._value_.code
+
+    def scene_name(self):
+        return self._value_.name
+
+    def describe(self):
+        return self._value_.describe
+
+    def param_types(self):
+        return self._value_.param_types
+
+    def show_disable(self):
+        return self._value_.show_disable
+
+    def is_inner(self):
+        return self._value_.is_inner