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feat(agent tool): add agent tool plugin

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This commit is contained in:
谢俊男
2026-01-06 15:25:25 +08:00
parent 190155f438
commit 492401f9b7
11 changed files with 349 additions and 90 deletions
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62
api/app/services/app_chat_service.py
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@@ -10,6 +10,8 @@ from sqlalchemy.orm import Session
from app.core.agent.langchain_agent import LangChainAgent
from app.core.logging_config import get_business_logger
from app.services.tool_service import ToolService
from app.repositories.tool_repository import ToolRepository
from app.db import get_db
from app.models import MultiAgentConfig, AgentConfig
from app.schemas.prompt_schema import render_prompt_message, PromptMessageRole
@@ -40,6 +42,7 @@ class AppChatService:
memory: bool = True,
storage_type: Optional[str] = None,
user_rag_memory_id: Optional[str] = None,
workspace_id: Optional[str] = None
) -> Dict[str, Any]:
"""聊天（非流式）"""
@@ -64,6 +67,20 @@ class AppChatService:
# 准备工具列表
tools = []
# 获取工具服务
tool_service = ToolService(self.db)
# 从配置中获取启用的工具
if hasattr(config, 'tools') and config.tools:
for tool_id, tool_config in config.tools.items():
if tool_config.get("enabled", False):
# 根据工具名称查找工具实例
tool_instance = tool_service._get_tool_instance(tool_id, ToolRepository.get_tenant_id_by_workspace_id(self.db, workspace_id))
if tool_instance:
# 转换为LangChain工具
langchain_tool = tool_instance.to_langchain_tool(tool_config.get("config", {}).get("operation", None))
tools.append(langchain_tool)
# 添加知识库检索工具
knowledge_retrieval = config.knowledge_retrieval
@@ -83,21 +100,6 @@ class AppChatService:
memory_tool = create_long_term_memory_tool(memory_config, user_id)
tools.append(memory_tool)
web_tools = config.tools
# web_search_choice = web_tools.get("web_search", {})
# web_search_enable = web_search_choice.get("enabled", False)
# if web_search == True:
# if web_search_enable == True:
# search_tool = create_web_search_tool({})
# tools.append(search_tool)
#
# logger.debug(
# "已添加网络搜索工具",
# extra={
# "tool_count": len(tools)
# }
# )
# 获取模型参数
model_parameters = config.model_parameters
@@ -170,6 +172,7 @@ class AppChatService:
memory: bool = True,
storage_type: Optional[str] = None,
user_rag_memory_id: Optional[str] = None,
workspace_id: Optional[str] = None,
) -> AsyncGenerator[str, None]:
"""聊天（流式）"""
@@ -641,6 +644,20 @@ class AppChatService:
# 准备工具列表
tools = []
# 获取工具服务
tool_service = ToolService(self.db)
# 从配置中获取启用的工具
if hasattr(config, 'tools') and config.tools:
for tool_id, tool_config in config.tools.items():
if tool_config.get("enabled", False):
# 根据工具名称查找工具实例
tool_instance = tool_service._get_tool_instance(tool_id, ToolRepository.get_tenant_id_by_workspace_id(self.db, workspace_id))
if tool_instance:
# 转换为LangChain工具
langchain_tool = tool_instance.to_langchain_tool(tool_config.get("config", {}).get("operation", None))
tools.append(langchain_tool)
# 添加知识库检索工具
knowledge_retrieval = config.get("knowledge_retrieval")
@@ -660,21 +677,6 @@ class AppChatService:
memory_tool = create_long_term_memory_tool(memory_config, user_id)
tools.append(memory_tool)
web_tools = config.get("tools")
web_search_choice = web_tools.get("web_search", {})
web_search_enable = web_search_choice.get("enabled", False)
if web_search == True:
if web_search_enable == True:
search_tool = create_web_search_tool({})
tools.append(search_tool)
logger.debug(
"已添加网络搜索工具",
extra={
"tool_count": len(tools)
}
)
# 获取模型参数
model_parameters = config.get("model_parameters", {})