升级agent,pydantic升级到2

server/agent/tools_factory/arxiv.py

@@ -1,9 +1,9 @@
 # LangChain 的 ArxivQueryRun 工具
-from pydantic import BaseModel, Field
+from pydantic.v1 import BaseModel, Field
 from langchain.tools.arxiv.tool import ArxivQueryRun
 def arxiv(query: str):
     tool = ArxivQueryRun()
     return tool.run(tool_input=query)
 
 class ArxivInput(BaseModel):
-    query: str = Field(description="The search query title")
+    query: str = Field(description="The search query title")

server/agent/tools_factory/audio_factory/aqa.py

@@ -1,6 +1,6 @@
 import base64
 import os
-from pydantic import BaseModel, Field
+from pydantic.v1 import BaseModel, Field
 
 def save_base64_audio(base64_audio, file_path):
     audio_data = base64.b64decode(base64_audio)

server/agent/tools_factory/calculate.py

@@ -1,4 +1,4 @@
-from pydantic import BaseModel, Field
+from pydantic.v1 import BaseModel, Field
 
 def calculate(a: float, b: float, operator: str) -> float:
     if operator == "+":

server/agent/tools_factory/search_internet.py

@@ -1,4 +1,4 @@
-from pydantic import BaseModel, Field
+from pydantic.v1 import BaseModel, Field
 from langchain.utilities.bing_search import BingSearchAPIWrapper
 from langchain.utilities.duckduckgo_search import DuckDuckGoSearchAPIWrapper
 from configs import TOOL_CONFIG

server/agent/tools_factory/search_local_knowledgebase.py

@@ -1,5 +1,5 @@
 from urllib.parse import urlencode
-from pydantic import BaseModel, Field
+from pydantic.v1 import BaseModel, Field
 
 from server.knowledge_base.kb_doc_api import search_docs
 from configs import TOOL_CONFIG
@@ -36,4 +36,4 @@ class SearchKnowledgeInput(BaseModel):
 
 def search_local_knowledgebase(database: str, query: str):
     tool_config = TOOL_CONFIG["search_local_knowledgebase"]
-    return search_knowledgebase(query=query, database=database, config=tool_config)
+    return search_knowledgebase(query=query, database=database, config=tool_config)

server/agent/tools_factory/search_youtube.py

@@ -1,8 +1,8 @@
 from langchain_community.tools import YouTubeSearchTool
-from pydantic import BaseModel, Field
+from pydantic.v1 import BaseModel, Field
 def search_youtube(query: str):
     tool = YouTubeSearchTool()
     return tool.run(tool_input=query)
 
 class YoutubeInput(BaseModel):
-    query: str = Field(description="Query for Videos search")
+    query: str = Field(description="Query for Videos search")

server/agent/tools_factory/shell.py

@@ -1,9 +1,9 @@
 # LangChain 的 Shell 工具
-from pydantic import BaseModel, Field
+from pydantic.v1 import BaseModel, Field
 from langchain_community.tools import ShellTool
 def shell(query: str):
     tool = ShellTool()
     return tool.run(tool_input=query)
 
 class ShellInput(BaseModel):
-    query: str = Field(description="The command to execute")
+    query: str = Field(description="The command to execute")

server/agent/tools_factory/text2image.py

@@ -6,7 +6,7 @@ from typing import List
 import uuid
 
 from langchain.agents import tool
-from langchain.pydantic_v1 import Field
+from pydantic.v1 import BaseModel, Field
 import openai
 from pydantic.fields import FieldInfo
 

server/agent/tools_factory/vision_factory/vqa.py

@@ -5,7 +5,7 @@ import base64
 from io import BytesIO
 import torch
 from PIL import Image, ImageDraw
-from pydantic import BaseModel, Field
+from pydantic.v1 import BaseModel, Field
 from configs import TOOL_CONFIG
 import re
 from server.agent.container import container

server/agent/tools_factory/weather_check.py

@@ -1,7 +1,7 @@
 """
 简单的单参数输入工具实现，用于查询现在天气的情况
 """
-from pydantic import BaseModel, Field
+from pydantic.v1 import BaseModel, Field
 import requests
 
 def weather(location: str, api_key: str):

server/agent/tools_factory/wolfram.py

@@ -1,6 +1,6 @@
 # Langchain 自带的 Wolfram Alpha API 封装
 from langchain.utilities.wolfram_alpha import WolframAlphaAPIWrapper
-from pydantic import BaseModel, Field
+from pydantic.v1 import BaseModel, Field
 wolfram_alpha_appid = "your key"
 def wolfram(query: str):
     wolfram = WolframAlphaAPIWrapper(wolfram_alpha_appid=wolfram_alpha_appid)
@@ -8,4 +8,4 @@ def wolfram(query: str):
     return ans
 
 class WolframInput(BaseModel):
-    formula: str = Field(description="The formula to be calculated")
+    formula: str = Field(description="The formula to be calculated")