From 0cf08f37b0024c411c68ee1da867c32b3be2ace2 Mon Sep 17 00:00:00 2001
From: aries_ckt <916701291@qq.com>
Date: Thu, 21 Mar 2024 15:30:57 +0800
Subject: [PATCH] fix:update app schemas.

---
 dbgpt/client/schema.py | 104 +++++++++++++++++++++++++++++------------
 1 file changed, 75 insertions(+), 29 deletions(-)

diff --git a/dbgpt/client/schema.py b/dbgpt/client/schema.py
index de33e5351..b4e8ad397 100644
--- a/dbgpt/client/schema.py
+++ b/dbgpt/client/schema.py
@@ -1,16 +1,14 @@
 """this module contains the schemas for the dbgpt client."""
+import json
 from datetime import datetime
 from enum import Enum
-from typing import List, Optional, Union
+from typing import Any, Dict, List, Optional, Union
 
 from fastapi import File, UploadFile
 
 from dbgpt._private.pydantic import BaseModel, Field
-from dbgpt.agent.resource.resource_api import AgentResource
 from dbgpt.rag.chunk_manager import ChunkParameters
 
-"""Chat completion request body"""
-
 
 class ChatCompletionRequestBody(BaseModel):
     """ChatCompletion LLM http request body."""
@@ -26,7 +24,8 @@ class ChatCompletionRequestBody(BaseModel):
     temperature: Optional[float] = Field(
         default=None,
         description="What sampling temperature to use, between 0 and 2. Higher values "
-        "like 0.8 will make the output more random, while lower values like 0.2 will "
+        "like 0.8 will make the output more random, "
+        "while lower values like 0.2 will "
         "make it more focused and deterministic.",
     )
     max_new_tokens: Optional[int] = Field(
@@ -66,9 +65,6 @@ class ChatCompletionRequestBody(BaseModel):
     )
 
 
-"""Chat completion response"""
-
-
 class ChatMode(Enum):
     """Chat mode."""
 
@@ -78,27 +74,6 @@ class ChatMode(Enum):
     CHAT_KNOWLEDGE = "chat_knowledge"
 
 
-"""Agent model"""
-
-
-class AppDetailModel(BaseModel):
-    """App detail model."""
-
-    app_code: Optional[str] = Field(None, description="app code")
-    app_name: Optional[str] = Field(None, description="app name")
-    agent_name: Optional[str] = Field(None, description="agent name")
-    node_id: Optional[str] = Field(None, description="node id")
-    resources: Optional[list[AgentResource]] = Field(None, description="resources")
-    prompt_template: Optional[str] = Field(None, description="prompt template")
-    llm_strategy: Optional[str] = Field(None, description="llm strategy")
-    llm_strategy_value: Optional[str] = Field(None, description="llm strategy value")
-    created_at: datetime = datetime.now()
-    updated_at: datetime = datetime.now()
-
-
-"""Awel team model"""
-
-
 class AwelTeamModel(BaseModel):
     """Awel team model."""
 
@@ -151,6 +126,77 @@ class AwelTeamModel(BaseModel):
     )
 
 
+class AgentResourceType(Enum):
+    """Agent resource type."""
+
+    DB = "database"
+    Knowledge = "knowledge"
+    Internet = "internet"
+    Plugin = "plugin"
+    TextFile = "text_file"
+    ExcelFile = "excel_file"
+    ImageFile = "image_file"
+    AwelFlow = "awel_flow"
+
+
+class AgentResourceModel(BaseModel):
+    """Agent resource model."""
+
+    type: AgentResourceType
+    name: str
+    value: str
+    is_dynamic: bool = (
+        False  # Is the current resource predefined or dynamically passed in?
+    )
+
+    @staticmethod
+    def from_dict(d: Dict[str, Any]):
+        """From dict."""
+        if d is None:
+            return None
+        return AgentResourceModel(
+            type=AgentResourceType(d.get("type")),
+            name=d.get("name"),
+            introduce=d.get("introduce"),
+            value=d.get("value", None),
+            is_dynamic=d.get("is_dynamic", False),
+        )
+
+    @staticmethod
+    def from_json_list_str(d: Optional[str]):
+        """From json list str."""
+        if d is None:
+            return None
+        try:
+            json_array = json.loads(d)
+        except Exception as e:
+            raise ValueError(f"Illegal AgentResource json string！{d},{e}")
+        return [AgentResourceModel.from_dict(item) for item in json_array]
+
+    def to_dict(self) -> Dict[str, Any]:
+        """To dict."""
+        temp = self.dict()
+        for field, value in temp.items():
+            if isinstance(value, Enum):
+                temp[field] = value.value
+        return temp
+
+
+class AppDetailModel(BaseModel):
+    """App detail model."""
+
+    app_code: Optional[str] = Field(None, description="app code")
+    app_name: Optional[str] = Field(None, description="app name")
+    agent_name: Optional[str] = Field(None, description="agent name")
+    node_id: Optional[str] = Field(None, description="node id")
+    resources: Optional[list[AgentResourceModel]] = Field(None, description="resources")
+    prompt_template: Optional[str] = Field(None, description="prompt template")
+    llm_strategy: Optional[str] = Field(None, description="llm strategy")
+    llm_strategy_value: Optional[str] = Field(None, description="llm strategy value")
+    created_at: datetime = datetime.now()
+    updated_at: datetime = datetime.now()
+
+
 class AppModel(BaseModel):
     """App model."""