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update:优化代码

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hrz
2025-11-08 16:00:37 +08:00
parent d09fa0c1f6
commit c02f2105d7
4 changed files with 141 additions and 105 deletions
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main/manager-api/src/main/java/xiaozhi/modules/agent/service/impl/AgentPluginMappingServiceImpl.java
+37 -10
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@@ -1,5 +1,6 @@
package xiaozhi.modules.agent.service.impl;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
@@ -7,11 +8,11 @@ import java.util.Map;
import org.apache.commons.lang3.StringUtils;
import org.springframework.stereotype.Service;
import com.alibaba.druid.support.json.JSONUtils;
import com.baomidou.mybatisplus.core.conditions.update.UpdateWrapper;
import com.baomidou.mybatisplus.extension.service.impl.ServiceImpl;
import lombok.RequiredArgsConstructor;
import xiaozhi.common.utils.JsonUtils;
import xiaozhi.modules.agent.dao.AgentPluginMappingMapper;
import xiaozhi.modules.agent.entity.AgentPluginMapping;
import xiaozhi.modules.agent.service.AgentPluginMappingService;
@@ -35,7 +36,8 @@ public class AgentPluginMappingServiceImpl extends ServiceImpl<AgentPluginMappin
@Override
public List<AgentPluginMapping> agentPluginParamsByAgentId(String agentId) {
List<AgentPluginMapping> list = agentPluginMappingMapper.selectPluginsByAgentId(agentId);
int index = 0;
Map<String, List<KnowledgeBaseEntity>> knowledgeBaseMap = new HashMap<>();
Map<String, ModelConfigEntity> modelConfigMap = new HashMap<>();
for (int i = list.size() - 1; i >= 0; i--) {
AgentPluginMapping mapping = list.get(i);
if (StringUtils.isBlank(mapping.getProviderCode())) {
@@ -51,14 +53,39 @@ public class AgentPluginMappingServiceImpl extends ServiceImpl<AgentPluginMappin
list.remove(i);
continue;
}
Map<String, String> paramInfo = new HashMap<>(2);
paramInfo.put("name", knowledgeBaseEntity.getName());
paramInfo.put("description", knowledgeBaseEntity.getDescription());
mapping.setParamInfo(JSONUtils.toJSONString(paramInfo));
String providerCode = "xzKnowledgeBase_search_from_" + modelConfigEntity.getModelCode() + "_"
+ index;
index++;
mapping.setProviderCode(providerCode);
List<KnowledgeBaseEntity> knowledgeBaseList = knowledgeBaseMap.get(modelConfigEntity.getModelCode());
if (knowledgeBaseList == null) {
knowledgeBaseList = new ArrayList<>();
}
modelConfigMap.put(modelConfigEntity.getModelCode(), modelConfigEntity);
knowledgeBaseList.add(knowledgeBaseEntity);
knowledgeBaseMap.put(modelConfigEntity.getModelCode(), knowledgeBaseList);
list.remove(i);
}
}
if (knowledgeBaseMap.size() > 0) {
for (String pluginCode : knowledgeBaseMap.keySet()) {
List<KnowledgeBaseEntity> knowledgeBaseList = knowledgeBaseMap.get(pluginCode);
if (knowledgeBaseList == null || knowledgeBaseList.isEmpty()) {
continue;
}
AgentPluginMapping agentPluginMapping = new AgentPluginMapping();
agentPluginMapping.setAgentId(agentId);
agentPluginMapping.setPluginId(pluginCode);
agentPluginMapping.setProviderCode("search_from_" + pluginCode);
agentPluginMapping.setId(Long.valueOf(list.size() + 1));
Map<String, Object> paramInfo = new HashMap<>(4);
ModelConfigEntity modelConfigEntity = modelConfigMap.get(pluginCode);
paramInfo.put("base_url", modelConfigEntity.getConfigJson().getStr("base_url"));
paramInfo.put("api_key", modelConfigEntity.getConfigJson().getStr("api_key"));
paramInfo.put("dataset_ids",
knowledgeBaseList.stream().map(KnowledgeBaseEntity::getDatasetId).toList());
paramInfo.put("description",
String.join(",", knowledgeBaseList.stream().map(KnowledgeBaseEntity::getDescription).toList()));
agentPluginMapping.setParamInfo(JsonUtils.toJsonString(paramInfo));
list.add(agentPluginMapping);
}
}
return list;
main/xiaozhi-server/config.yaml
+10 -1
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@@ -147,7 +147,15 @@ plugins:
- ".wav"
- ".p3"
refresh_time: 300 # 刷新音乐列表的时间间隔，单位为秒
search_from_ragflow:
# 知识库的描述信息，方便大语言模型知道什么时候调用
description: "当用户问xxx时，调用本方法，使用知识库中的信息回答问题"
# ragflow接口配置
base_url: "http://192.168.0.8"
# ragflow api访问令牌
api_key: "ragflow-xxx"
# ragflow知识库id
dataset_ids: ["123456789"]
# 声纹识别配置
voiceprint:
# 声纹接口地址
@@ -239,6 +247,7 @@ Intent:
functions:
- change_role
- get_weather
# - search_from_ragflow
# - get_news_from_chinanews
- get_news_from_newsnow
# play_music是服务器自带的音乐播放，hass_play_music是通过home assistant控制的独立外部程序音乐播放
main/xiaozhi-server/core/providers/tools/server_plugins/plugin_executor.py
+15 -80
View File
@@ -1,6 +1,6 @@
"""服务端插件工具执行器"""
from typing import Dict, Any, Optional, Tuple
from typing import Dict, Any
from ..base import ToolType, ToolDefinition, ToolExecutor
from plugins_func.register import all_function_registry, Action, ActionResponse
@@ -11,53 +11,12 @@ class ServerPluginExecutor(ToolExecutor):
def __init__(self, conn):
self.conn = conn
self.config = conn.config
# 存储知识库工具名称到真实插件名称的映射
self._knowledge_base_mapping: Dict[str, str] = {}
def _parse_knowledge_base_config(self, config_name: str) -> Optional[str]:
"""
解析知识库配置名称，提取真实的插件名称
Args:
config_name: 配置名称，格式为 xzKnowledgeBase_<plugin_name>_<index>
Returns:
真实的插件名称，如果不是知识库配置则返回 None
Example:
"xzKnowledgeBase_search_from_ragflow_0" -> "search_from_ragflow"
"xzKnowledgeBase_search_from_ragflow_1" -> "search_from_ragflow"
"""
if not config_name.startswith("xzKnowledgeBase_"):
return None
# 移除前缀
name_without_prefix = config_name[len("xzKnowledgeBase_"):]
# 找到最后一个下划线的位置
last_underscore_index = name_without_prefix.rfind("_")
if last_underscore_index == -1:
return None
# 提取真实插件名称（从开头到最后一个下划线之前）
real_plugin_name = name_without_prefix[:last_underscore_index]
return real_plugin_name
async def execute(
self, conn, tool_name: str, arguments: Dict[str, Any]
) -> ActionResponse:
"""执行服务端插件工具"""
# 检查是否是知识库工具调用
real_plugin_name = self._knowledge_base_mapping.get(tool_name)
if real_plugin_name:
# 使用真实的插件名称获取函数
func_item = all_function_registry.get(real_plugin_name)
else:
# 普通插件调用
func_item = all_function_registry.get(tool_name)
func_item = all_function_registry.get(tool_name)
if not func_item:
return ActionResponse(
action=Action.NOTFOUND, response=f"插件函数 {tool_name} 不存在"
@@ -112,51 +71,27 @@ class ServerPluginExecutor(ToolExecutor):
for func_name in all_required_functions:
func_item = all_function_registry.get(func_name)
if func_item:
# 从函数注册中获取描述
fun_description = (
self.config.get("plugins", {})
.get(func_name, {})
.get("description", "")
)
if fun_description is not None and len(fun_description) > 0:
if "function" in func_item.description and isinstance(
func_item.description["function"], dict
):
func_item.description["function"][
"description"
] = fun_description
tools[func_name] = ToolDefinition(
name=func_name,
description=func_item.description,
tool_type=ToolType.SERVER_PLUGIN,
)
# 处理知识库配置
plugins_config = self.config.get("plugins", {})
for config_name, config_value in plugins_config.items():
# 检查是否是知识库配置
real_plugin_name = self._parse_knowledge_base_config(config_name)
if real_plugin_name:
# 获取真实的插件函数
func_item = all_function_registry.get(real_plugin_name)
if func_item and isinstance(config_value, dict):
# 从配置中获取自定义的 name 和 description
custom_name = config_value.get("name", "")
custom_description = config_value.get("description", "")
# 创建动态的工具名称（使用配置名称去掉前缀部分作为工具名）
tool_name = config_name[len("xzKnowledgeBase_"):]
# 复制原始函数描述并修改
custom_func_desc = func_item.description.copy()
if "function" in custom_func_desc:
custom_func_desc["function"] = custom_func_desc["function"].copy()
custom_func_desc["function"]["name"] = tool_name
custom_func_desc["function"]["description"] = custom_description
# 注册工具
tools[tool_name] = ToolDefinition(
name=tool_name,
description=custom_func_desc,
tool_type=ToolType.SERVER_PLUGIN,
)
# 保存映射关系
self._knowledge_base_mapping[tool_name] = real_plugin_name
return tools
def has_tool(self, tool_name: str) -> bool:
"""检查是否有指定的服务端插件工具"""
# 检查是否是知识库工具
if tool_name in self._knowledge_base_mapping:
return True
# 检查是否是普通工具
return tool_name in all_function_registry
main/xiaozhi-server/plugins_func/functions/search_from_ragflow.py
+79 -14
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@@ -1,5 +1,11 @@
import requests
import sys
from config.logger import setup_logging
from plugins_func.register import register_function, ToolType, ActionResponse, Action
TAG = __name__
logger = setup_logging()
# 定义基础的函数描述模板
SEARCH_FROM_RAGFLOW_FUNCTION_DESC = {
"type": "function",
@@ -8,26 +14,85 @@ SEARCH_FROM_RAGFLOW_FUNCTION_DESC = {
"description": "从知识库中查询信息",
"parameters": {
"type": "object",
"properties": {"query": {"type": "string", "description": "查询的关键词"}},
"required": ["query"],
"properties": {"question": {"type": "string", "description": "查询的问题"}},
"required": ["question"],
},
},
}
@register_function(
"search_from_ragflow", SEARCH_FROM_RAGFLOW_FUNCTION_DESC, ToolType.WAIT
"search_from_ragflow", SEARCH_FROM_RAGFLOW_FUNCTION_DESC, ToolType.SYSTEM_CTL
)
def search_from_ragflow(query=None):
"""
用于从ragflow知识库中查询信息
"""
# TODO 从ragflow知识库中查询信息
if query and "医生" in query:
response_text = "医院有张山、里斯、王五3名全科医生，其中王五医生是主要擅长眼科"
elif query and "科室" in query:
response_text = "医院眼科、麻醉科"
def search_from_ragflow(conn, question=None):
# 确保字符串参数正确处理编码
if question and isinstance(question, str):
# 确保问题参数是UTF-8编码的字符串
pass
else:
response_text = "暂无相关信息"
question = str(question) if question is not None else ""
return ActionResponse(Action.REQLLM, response_text, None)
base_url = conn.config["plugins"]["search_from_ragflow"].get("base_url", "")
api_key = conn.config["plugins"]["search_from_ragflow"].get("api_key", "")
dataset_ids = conn.config["plugins"]["search_from_ragflow"].get("dataset_ids", [])
url = base_url + "/api/v1/retrieval"
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
# 确保payload中的字符串都是UTF-8编码
payload = {"question": question, "dataset_ids": dataset_ids}
try:
# 使用ensure_ascii=False确保JSON序列化时正确处理中文
response = requests.post(
url,
json=payload,
headers=headers,
timeout=5,
verify=False,
)
# 显式设置响应的编码为utf-8
response.encoding = "utf-8"
response.raise_for_status()
# 先获取文本内容，然后手动处理JSON解码
response_text = response.text
import json
result = json.loads(response_text)
if result.get("code") != 0:
error_detail = response.get("error", {}).get("detail", "")
# 安全地记录错误信息
logger.bind(tag=TAG).error(
"从RAGflow获取信息失败，原因：%s", str(error_detail)
)
return ActionResponse(Action.RESPONSE, None, "RAG接口返回异常")
chunks = result.get("data", {}).get("chunks", [])
contents = []
for chunk in chunks:
content = chunk.get("content", "")
if content:
# 安全地处理内容字符串
if isinstance(content, str):
contents.append(content)
elif isinstance(content, bytes):
contents.append(content.decode("utf-8", errors="replace"))
else:
contents.append(str(content))
# 构建适合大模型的上下文内容（每段前加编号，段间两个换行）
context_text = "\n\n".join(
f"{i+1}. {c.strip()}" for i, c in enumerate(contents[:5])
)
if not context_text:
context_text = "根据知识库查询结果，没有相关信息。"
return ActionResponse(Action.REQLLM, context_text, None)
except Exception as e:
# 使用安全的方式记录异常，避免编码问题
logger.bind(tag=TAG).error("从RAGflow获取信息失败，原因：%s", str(e))
return ActionResponse(Action.RESPONSE, None, "RAG接口返回异常")