mirror of
https://github.com/xinnan-tech/xiaozhi-esp32-server.git
synced 2026-07-22 07:03:53 +08:00
Merge branch 'main' into MVP
This commit is contained in:
+3
-3
@@ -5,15 +5,15 @@ WORKDIR /app
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COPY main/xiaozhi-server/requirements.txt .
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# 优化apt安装
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# 安装Python依赖
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RUN pip install --no-cache-dir -r requirements.txt
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# 第三阶段:生产镜像
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# 第二阶段:生产镜像
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FROM python:3.10-slim
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WORKDIR /opt/xiaozhi-esp32-server
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# 优化apt安装
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# 安装系统依赖
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RUN apt-get update && \
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apt-get install -y --no-install-recommends libopus0 ffmpeg && \
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apt-get clean && \
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@@ -11,6 +11,7 @@ manager-api 该项目基于SpringBoot框架开发。
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JDK 21
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Maven 3.8+
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MySQL 8.0+
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Redis 5.0+
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Vue 3.x
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# 创建数据库
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@@ -43,6 +44,37 @@ spring:
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password: 123456
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```
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# 连接Redis
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||||
如果还没有Redis,你可以通过docker安装redis
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```
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docker run --name xiaozhi-esp32-server-redis -d -p 6379:6379 redis
|
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```
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||||
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# 确认项目Redis连接信息
|
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在`src/main/resources/application-dev.yml`中配置Redis连接信息
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```
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spring:
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data:
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redis:
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host: localhost
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port: 6379
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password:
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database: 0
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```
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在`src/main/resources/application.yml`中配置Redis启用状态
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```
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renren:
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redis:
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open: true
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||||
```
|
||||
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||||
# 测试启动
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本项目为SpringBoot项目,启动方式为:
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@@ -39,8 +39,8 @@ export default {
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||||
},
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||||
methods: {
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confirm() {
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if (!this.deviceCode.trim()) {
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this.$message.error('请输入设备验证码');
|
||||
if (!/^\d{6}$/.test(this.deviceCode)) {
|
||||
this.$message.error('请输入6位数字设备验证码');
|
||||
return;
|
||||
}
|
||||
this.$emit('confirm',this.deviceCode)
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||||
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||||
@@ -3,7 +3,7 @@ import sys
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from loguru import logger
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from config.settings import load_config
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SERVER_VERSION = "0.1.15"
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SERVER_VERSION = "0.1.16"
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def setup_logging():
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"""从配置文件中读取日志配置,并设置日志输出格式和级别"""
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||||
@@ -13,7 +13,7 @@ def setup_logging():
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log_format_file = log_config.get("log_format_file", "{time:YYYY-MM-DD HH:mm:ss} - {version_{selected_module}} - {name} - {level} - {extra[tag]} - {message}")
|
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|
||||
selected_module = config.get("selected_module")
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||||
selected_module_str = ''.join([key[0] + value[0] for key, value in selected_module.items()])
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selected_module_str = ''.join([value[0] + value[1] for key, value in selected_module.items()])
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||||
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log_format = log_format.replace("{version}", SERVER_VERSION)
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log_format = log_format.replace("{selected_module}", selected_module_str)
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@@ -18,10 +18,11 @@ from concurrent.futures import ThreadPoolExecutor, TimeoutError
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from core.handle.sendAudioHandle import sendAudioMessage
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from core.handle.receiveAudioHandle import handleAudioMessage
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from core.handle.functionHandler import FunctionHandler
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from plugins_func.register import Action
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from plugins_func.register import Action, ActionResponse
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from config.private_config import PrivateConfig
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from core.auth import AuthMiddleware, AuthenticationError
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from core.utils.auth_code_gen import AuthCodeGenerator
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from core.mcp.manager import MCPManager
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TAG = __name__
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@@ -100,6 +101,8 @@ class ConnectionHandler:
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||||
self.use_function_call_mode = False
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if self.config["selected_module"]["Intent"] == 'function_call':
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self.use_function_call_mode = True
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self.mcp_manager = MCPManager(self)
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async def handle_connection(self, ws):
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try:
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||||
@@ -194,7 +197,31 @@ class ConnectionHandler:
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"""加载记忆"""
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device_id = self.headers.get("device-id", None)
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self.memory.init_memory(device_id, self.llm)
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self.intent.set_llm(self.llm)
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"""为意图识别设置LLM,优先使用专用LLM"""
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# 检查是否配置了专用的意图识别LLM
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intent_llm_name = self.config["Intent"]["intent_llm"]["llm"]
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# 记录开始初始化意图识别LLM的时间
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intent_llm_init_start = time.time()
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if not self.use_function_call_mode and intent_llm_name and intent_llm_name in self.config["LLM"]:
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# 如果配置了专用LLM,则创建独立的LLM实例
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from core.utils import llm as llm_utils
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intent_llm_config = self.config["LLM"][intent_llm_name]
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intent_llm_type = intent_llm_config.get("type", intent_llm_name)
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intent_llm = llm_utils.create_instance(intent_llm_type, intent_llm_config)
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self.logger.bind(tag=TAG).info(f"为意图识别创建了专用LLM: {intent_llm_name}, 类型: {intent_llm_type}")
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self.intent.set_llm(intent_llm)
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else:
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# 否则使用主LLM
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self.intent.set_llm(self.llm)
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self.logger.bind(tag=TAG).info("意图识别使用主LLM")
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# 记录意图识别LLM初始化耗时
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intent_llm_init_time = time.time() - intent_llm_init_start
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self.logger.bind(tag=TAG).info(f"意图识别LLM初始化完成,耗时: {intent_llm_init_time:.4f}秒")
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"""加载位置信息"""
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||||
self.client_ip_info = get_ip_info(self.client_ip)
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@@ -203,6 +230,9 @@ class ConnectionHandler:
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||||
self.prompt = self.prompt + f"\nuser location:{self.client_ip_info}"
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||||
self.dialogue.update_system_message(self.prompt)
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|
||||
"""加载MCP工具"""
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asyncio.run_coroutine_threadsafe(self.mcp_manager.initialize_servers(), self.loop)
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def change_system_prompt(self, prompt):
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||||
self.prompt = prompt
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||||
# 找到原来的role==system,替换原来的系统提示
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||||
@@ -324,7 +354,6 @@ class ConnectionHandler:
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||||
functions = None
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||||
if hasattr(self, 'func_handler'):
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||||
functions = self.func_handler.get_functions()
|
||||
|
||||
response_message = []
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||||
processed_chars = 0 # 跟踪已处理的字符位置
|
||||
|
||||
@@ -358,6 +387,9 @@ class ConnectionHandler:
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||||
content_arguments = ""
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||||
for response in llm_responses:
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||||
content, tools_call = response
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||||
if "content" in response:
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||||
content = response["content"]
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||||
tools_call = None
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||||
if content is not None and len(content) > 0:
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||||
if len(response_message) <= 0 and (content == "```" or "<tool_call>" in content):
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||||
tool_call_flag = True
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||||
@@ -436,8 +468,14 @@ class ConnectionHandler:
|
||||
"id": function_id,
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||||
"arguments": function_arguments
|
||||
}
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||||
result = self.func_handler.handle_llm_function_call(self, function_call_data)
|
||||
self._handle_function_result(result, function_call_data, text_index + 1)
|
||||
|
||||
# 处理MCP工具调用
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||||
if self.mcp_manager.is_mcp_tool(function_name):
|
||||
result = self._handle_mcp_tool_call(function_call_data)
|
||||
else:
|
||||
# 处理系统函数
|
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result = self.func_handler.handle_llm_function_call(self, function_call_data)
|
||||
self._handle_function_result(result, function_call_data, text_index+1)
|
||||
|
||||
# 处理最后剩余的文本
|
||||
full_text = "".join(response_message)
|
||||
@@ -459,6 +497,42 @@ class ConnectionHandler:
|
||||
|
||||
return True
|
||||
|
||||
def _handle_mcp_tool_call(self, function_call_data):
|
||||
function_arguments = function_call_data["arguments"]
|
||||
function_name = function_call_data["name"]
|
||||
try:
|
||||
args_dict = function_arguments
|
||||
if isinstance(function_arguments, str):
|
||||
try:
|
||||
args_dict = json.loads(function_arguments)
|
||||
except json.JSONDecodeError:
|
||||
self.logger.bind(tag=TAG).error(f"无法解析 function_arguments: {function_arguments}")
|
||||
return ActionResponse(action=Action.REQLLM, result="参数解析失败", response="")
|
||||
|
||||
tool_result = asyncio.run_coroutine_threadsafe(self.mcp_manager.execute_tool(
|
||||
function_name,
|
||||
args_dict
|
||||
), self.loop).result()
|
||||
# meta=None content=[TextContent(type='text', text='北京当前天气:\n温度: 21°C\n天气: 晴\n湿度: 6%\n风向: 西北 风\n风力等级: 5级', annotations=None)] isError=False
|
||||
content_text = ""
|
||||
if tool_result is not None and tool_result.content is not None:
|
||||
for content in tool_result.content:
|
||||
content_type = content.type
|
||||
if content_type == "text":
|
||||
content_text = content.text
|
||||
elif content_type == "image":
|
||||
pass
|
||||
|
||||
if len(content_text) > 0:
|
||||
return ActionResponse(action=Action.REQLLM, result=content_text, response="")
|
||||
|
||||
except Exception as e:
|
||||
self.logger.bind(tag=TAG).error(f"MCP工具调用错误: {e}")
|
||||
return ActionResponse(action=Action.REQLLM, result="工具调用出错", response="")
|
||||
|
||||
return ActionResponse(action=Action.REQLLM, result="工具调用出错", response="")
|
||||
|
||||
|
||||
def _handle_function_result(self, result, function_call_data, text_index):
|
||||
if result.action == Action.RESPONSE: # 直接回复前端
|
||||
text = result.response
|
||||
@@ -582,6 +656,8 @@ class ConnectionHandler:
|
||||
|
||||
async def close(self, ws=None):
|
||||
"""资源清理方法"""
|
||||
# 清理MCP资源
|
||||
await self.mcp_manager.cleanup_all()
|
||||
|
||||
# 触发停止事件并清理资源
|
||||
if self.stop_event:
|
||||
|
||||
@@ -4,6 +4,8 @@ import uuid
|
||||
from core.handle.sendAudioHandle import send_stt_message
|
||||
from core.handle.helloHandle import checkWakeupWords
|
||||
from core.utils.util import remove_punctuation_and_length
|
||||
from core.utils.dialogue import Message
|
||||
from loguru import logger
|
||||
|
||||
TAG = __name__
|
||||
logger = setup_logging()
|
||||
@@ -21,11 +23,11 @@ async def handle_user_intent(conn, text):
|
||||
# 使用支持function calling的聊天方法,不再进行意图分析
|
||||
return False
|
||||
# 使用LLM进行意图分析
|
||||
intent = await analyze_intent_with_llm(conn, text)
|
||||
if not intent:
|
||||
intent_result = await analyze_intent_with_llm(conn, text)
|
||||
if not intent_result:
|
||||
return False
|
||||
# 处理各种意图
|
||||
return await process_intent_result(conn, intent, text)
|
||||
return await process_intent_result(conn, intent_result, text)
|
||||
|
||||
|
||||
async def check_direct_exit(conn, text):
|
||||
@@ -40,7 +42,6 @@ async def check_direct_exit(conn, text):
|
||||
return False
|
||||
|
||||
|
||||
|
||||
async def analyze_intent_with_llm(conn, text):
|
||||
"""使用LLM分析用户意图"""
|
||||
if not hasattr(conn, 'intent') or not conn.intent:
|
||||
@@ -51,52 +52,65 @@ async def analyze_intent_with_llm(conn, text):
|
||||
dialogue = conn.dialogue
|
||||
try:
|
||||
intent_result = await conn.intent.detect_intent(conn, dialogue.dialogue, text)
|
||||
# 尝试解析JSON结果
|
||||
try:
|
||||
intent_data = json.loads(intent_result)
|
||||
if "intent" in intent_data:
|
||||
return intent_data["intent"]
|
||||
except json.JSONDecodeError:
|
||||
# 如果不是JSON格式,尝试直接获取意图文本
|
||||
return intent_result.strip()
|
||||
|
||||
return intent_result
|
||||
except Exception as e:
|
||||
logger.bind(tag=TAG).error(f"意图识别失败: {str(e)}")
|
||||
|
||||
return None
|
||||
|
||||
|
||||
async def process_intent_result(conn, intent, original_text):
|
||||
async def process_intent_result(conn, intent_result, original_text):
|
||||
"""处理意图识别结果"""
|
||||
# 处理退出意图
|
||||
if "结束聊天" in intent:
|
||||
logger.bind(tag=TAG).info(f"识别到退出意图: {intent}")
|
||||
# 如果是明确的离别意图,发送告别语并关闭连接
|
||||
await send_stt_message(conn, original_text)
|
||||
conn.executor.submit(conn.chat_and_close, original_text)
|
||||
return True
|
||||
try:
|
||||
# 尝试将结果解析为JSON
|
||||
intent_data = json.loads(intent_result)
|
||||
|
||||
# 处理播放音乐意图
|
||||
if "播放音乐" in intent:
|
||||
logger.bind(tag=TAG).info(f"识别到音乐播放意图: {intent}")
|
||||
# 调用play_music函数来播放音乐
|
||||
song_name = extract_text_in_brackets(intent)
|
||||
function_id = str(uuid.uuid4().hex)
|
||||
function_name = "play_music"
|
||||
function_arguments = '{ "song_name": "' + song_name + '" }'
|
||||
# 检查是否有function_call
|
||||
if "function_call" in intent_data:
|
||||
# 直接从意图识别获取了function_call
|
||||
logger.bind(tag=TAG).info(f"检测到function_call格式的意图结果: {intent_data['function_call']['name']}")
|
||||
function_name = intent_data["function_call"]["name"]
|
||||
if function_name == "continue_chat":
|
||||
return False
|
||||
function_args = None
|
||||
if "arguments" in intent_data["function_call"]:
|
||||
function_args = intent_data["function_call"]["arguments"]
|
||||
# 确保参数是字符串格式的JSON
|
||||
if isinstance(function_args, dict):
|
||||
function_args = json.dumps(function_args)
|
||||
|
||||
function_call_data = {
|
||||
"name": function_name,
|
||||
"id": function_id,
|
||||
"arguments": function_arguments
|
||||
}
|
||||
conn.func_handler.handle_llm_function_call(conn, function_call_data)
|
||||
return True
|
||||
function_call_data = {
|
||||
"name": function_name,
|
||||
"id": str(uuid.uuid4().hex),
|
||||
"arguments": function_args
|
||||
}
|
||||
|
||||
# 其他意图处理可以在这里扩展
|
||||
await send_stt_message(conn, original_text)
|
||||
|
||||
# 默认返回False,表示继续常规聊天流程
|
||||
return False
|
||||
# 使用executor执行函数调用和结果处理
|
||||
def process_function_call():
|
||||
conn.dialogue.put(Message(role="user", content=original_text))
|
||||
result = conn.func_handler.handle_llm_function_call(conn, function_call_data)
|
||||
if result and function_name != 'play_music':
|
||||
# 获取当前最新的文本索引
|
||||
text = result.response
|
||||
if text is None:
|
||||
text = result.result
|
||||
if text is not None:
|
||||
text_index = conn.tts_last_text_index + 1 if hasattr(conn, 'tts_last_text_index') else 0
|
||||
conn.recode_first_last_text(text, text_index)
|
||||
future = conn.executor.submit(conn.speak_and_play, text, text_index)
|
||||
conn.llm_finish_task = True
|
||||
conn.tts_queue.put(future)
|
||||
conn.dialogue.put(Message(role="assistant", content=text))
|
||||
|
||||
# 将函数执行放在线程池中
|
||||
conn.executor.submit(process_function_call)
|
||||
return True
|
||||
return False
|
||||
except json.JSONDecodeError as e:
|
||||
logger.bind(tag=TAG).error(f"处理意图结果时出错: {e}")
|
||||
return False
|
||||
|
||||
|
||||
def extract_text_in_brackets(s):
|
||||
@@ -112,4 +126,4 @@ def extract_text_in_brackets(s):
|
||||
if left_bracket_index != -1 and right_bracket_index != -1 and left_bracket_index < right_bracket_index:
|
||||
return s[left_bracket_index + 1:right_bracket_index]
|
||||
else:
|
||||
return ""
|
||||
return ""
|
||||
|
||||
@@ -0,0 +1,86 @@
|
||||
from datetime import timedelta
|
||||
from typing import Optional
|
||||
from contextlib import AsyncExitStack
|
||||
import os, shutil
|
||||
from mcp import ClientSession, StdioServerParameters
|
||||
from mcp.client.stdio import stdio_client
|
||||
|
||||
from config.logger import setup_logging
|
||||
|
||||
TAG = __name__
|
||||
|
||||
class MCPClient:
|
||||
def __init__(self, config):
|
||||
# Initialize session and client objects
|
||||
self.session: Optional[ClientSession] = None
|
||||
self.exit_stack = AsyncExitStack()
|
||||
self.logger = setup_logging()
|
||||
self.config = config
|
||||
self.tolls = []
|
||||
|
||||
async def initialize(self):
|
||||
args = self.config.get("args", [])
|
||||
|
||||
command = (
|
||||
shutil.which("npx")
|
||||
if self.config["command"] == "npx"
|
||||
else self.config["command"]
|
||||
)
|
||||
|
||||
env={**os.environ}
|
||||
if self.config.get("env"):
|
||||
env.update(self.config["env"])
|
||||
|
||||
server_params = StdioServerParameters(
|
||||
command=command,
|
||||
args=args,
|
||||
env=env
|
||||
)
|
||||
|
||||
stdio_transport = await self.exit_stack.enter_async_context(stdio_client(server_params))
|
||||
self.stdio, self.write = stdio_transport
|
||||
time_out_delta = timedelta(seconds=15)
|
||||
self.session = await self.exit_stack.enter_async_context(ClientSession(read_stream=self.stdio, write_stream=self.write, read_timeout_seconds=time_out_delta))
|
||||
|
||||
await self.session.initialize()
|
||||
|
||||
# List available tools
|
||||
response = await self.session.list_tools()
|
||||
tools = response.tools
|
||||
self.tools = tools
|
||||
self.logger.bind(tag=TAG).info(f"Connected to server with tools:{[tool.name for tool in tools]}")
|
||||
|
||||
def has_tool(self, tool_name):
|
||||
return any(tool.name == tool_name for tool in self.tools)
|
||||
|
||||
def get_available_tools(self):
|
||||
available_tools = [{"type": "function", "function":{
|
||||
"name": tool.name,
|
||||
"description": tool.description,
|
||||
"parameters": tool.inputSchema
|
||||
} } for tool in self.tools]
|
||||
|
||||
return available_tools
|
||||
|
||||
async def call_tool(self, tool_name: str, tool_args: dict):
|
||||
self.logger.bind(tag=TAG).info(f"MCPClient Calling tool {tool_name} with args: {tool_args}")
|
||||
try:
|
||||
response = await self.session.call_tool(tool_name, tool_args)
|
||||
except Exception as e:
|
||||
self.logger.bind(tag=TAG).error(f"Error calling tool {tool_name}: {e}")
|
||||
from types import SimpleNamespace
|
||||
error_content = SimpleNamespace(
|
||||
type='text',
|
||||
text=f"Error calling tool {tool_name}: {e}"
|
||||
)
|
||||
error_response = SimpleNamespace(
|
||||
content=[error_content],
|
||||
isError=True
|
||||
)
|
||||
return error_response
|
||||
self.logger.bind(tag=TAG).info(f"MCPClient Response from tool {tool_name}: {response}")
|
||||
return response
|
||||
|
||||
async def cleanup(self):
|
||||
"""Clean up resources"""
|
||||
await self.exit_stack.aclose()
|
||||
@@ -0,0 +1,110 @@
|
||||
"""MCP服务管理器"""
|
||||
import os, json
|
||||
from typing import Dict, Any, List
|
||||
from .MCPClient import MCPClient
|
||||
from config.logger import setup_logging
|
||||
from core.utils.util import get_project_dir
|
||||
from plugins_func.register import register_function, ActionResponse, Action, ToolType
|
||||
|
||||
TAG = __name__
|
||||
|
||||
class MCPManager:
|
||||
"""管理多个MCP服务的集中管理器"""
|
||||
|
||||
def __init__(self,conn) -> None:
|
||||
"""
|
||||
初始化MCP管理器
|
||||
"""
|
||||
self.conn = conn
|
||||
self.logger = setup_logging()
|
||||
self.config_path = get_project_dir() + 'data/.mcp_server_settings.json'
|
||||
if os.path.exists(self.config_path) == False:
|
||||
self.config_path = ""
|
||||
self.logger.bind(tag=TAG).warning(f"请检查mcp服务配置文件:data/.mcp_server_settings.json")
|
||||
self.client: Dict[str, MCPClient] = {}
|
||||
self.tools = []
|
||||
|
||||
def load_config(self) -> Dict[str, Any]:
|
||||
"""加载MCP服务配置
|
||||
Returns:
|
||||
Dict[str, Any]: 服务配置字典
|
||||
"""
|
||||
if len(self.config_path) == 0:
|
||||
return {}
|
||||
|
||||
try:
|
||||
with open(self.config_path, 'r', encoding='utf-8') as f:
|
||||
config = json.load(f)
|
||||
return config.get('mcpServers', {})
|
||||
except Exception as e:
|
||||
self.logger.bind(tag=TAG).error(f"Error loading MCP config from {self.config_path}: {e}")
|
||||
return {}
|
||||
|
||||
async def initialize_servers(self) -> None:
|
||||
"""初始化所有MCP服务"""
|
||||
config = self.load_config()
|
||||
for name, srv_config in config.items():
|
||||
if not srv_config.get("command"):
|
||||
self.logger.bind(tag=TAG).warning(f"Skipping server {name}: command not specified")
|
||||
continue
|
||||
|
||||
try:
|
||||
client = MCPClient(srv_config)
|
||||
await client.initialize()
|
||||
self.client[name] = client
|
||||
self.logger.bind(tag=TAG).info(f"Initialized MCP client: {name}")
|
||||
client_tools = client.get_available_tools()
|
||||
self.tools.extend(client_tools)
|
||||
for tool in client_tools:
|
||||
func_name = "mcp_"+tool["function"]["name"]
|
||||
register_function(func_name, tool, ToolType.MCP_CLIENT)(self.execute_tool)
|
||||
self.conn.func_handler.function_registry.register_function(func_name)
|
||||
|
||||
except Exception as e:
|
||||
self.logger.bind(tag=TAG).error(f"Failed to initialize MCP server {name}: {e}")
|
||||
self.conn.func_handler.upload_functions_desc()
|
||||
|
||||
def get_all_tools(self) -> List[Dict[str, Any]]:
|
||||
"""获取所有服务的工具function定义
|
||||
Returns:
|
||||
List[Dict[str, Any]]: 所有工具的function定义列表
|
||||
"""
|
||||
return self.tools
|
||||
|
||||
def is_mcp_tool(self, tool_name: str) -> bool:
|
||||
"""检查是否是MCP工具
|
||||
Args:
|
||||
tool_name: 工具名称
|
||||
Returns:
|
||||
bool: 是否是MCP工具
|
||||
"""
|
||||
for tool in self.tools:
|
||||
if tool.get("function") != None and tool["function"].get("name") == tool_name:
|
||||
return True
|
||||
return False
|
||||
|
||||
async def execute_tool(self, tool_name: str, arguments: Dict[str, Any]) -> Any:
|
||||
"""执行工具调用
|
||||
Args:
|
||||
tool_name: 工具名称
|
||||
arguments: 工具参数
|
||||
Returns:
|
||||
Any: 工具执行结果
|
||||
Raises:
|
||||
ValueError: 工具未找到时抛出
|
||||
"""
|
||||
self.logger.bind(tag=TAG).info(f"Executing tool {tool_name} with arguments: {arguments}")
|
||||
for client in self.client.values():
|
||||
if client.has_tool(tool_name):
|
||||
return await client.call_tool(tool_name, arguments)
|
||||
|
||||
raise ValueError(f"Tool {tool_name} not found in any MCP server")
|
||||
|
||||
async def cleanup_all(self) -> None:
|
||||
for name, client in self.client.items():
|
||||
try:
|
||||
await client.cleanup()
|
||||
self.logger.bind(tag=TAG).info(f"Cleaned up MCP client: {name}")
|
||||
except Exception as e:
|
||||
self.logger.bind(tag=TAG).error(f"Error cleaning up MCP client {name}: {e}")
|
||||
self.client.clear()
|
||||
@@ -10,14 +10,21 @@ class IntentProviderBase(ABC):
|
||||
def __init__(self, config):
|
||||
self.config = config
|
||||
self.intent_options = config.get("intent_options", {
|
||||
"handle_exit_intent": "结束聊天, 用户发来如再见之类的表示结束的话, 不想再进行对话的时候",
|
||||
"play_music": "播放音乐, 用户希望你可以播放音乐, 只用于播放音乐的意图",
|
||||
"get_weather": "查询天气, 用户希望查询某个地点的天气情况",
|
||||
"get_news": "查询新闻, 用户希望查询最新新闻或特定类型的新闻",
|
||||
"get_lunar": "用于获取今天的阴历/农历和黄历信息",
|
||||
"get_time": "获取今天日期或者当前时间信息",
|
||||
"continue_chat": "继续聊天",
|
||||
"end_chat": "结束聊天",
|
||||
"play_music": "播放音乐"
|
||||
})
|
||||
|
||||
def set_llm(self, llm):
|
||||
self.llm = llm
|
||||
logger.bind(tag=TAG).debug("Set LLM for intent provider")
|
||||
# 获取模型名称和类型信息
|
||||
model_name = getattr(llm, 'model_name', str(llm.__class__.__name__))
|
||||
# 记录更详细的日志
|
||||
logger.bind(tag=TAG).info(f"意图识别设置LLM: {model_name}")
|
||||
|
||||
@abstractmethod
|
||||
async def detect_intent(self, conn, dialogue_history: List[Dict], text: str) -> str:
|
||||
@@ -30,5 +37,6 @@ class IntentProviderBase(ABC):
|
||||
- "继续聊天"
|
||||
- "结束聊天"
|
||||
- "播放音乐 歌名" 或 "随机播放音乐"
|
||||
- "查询天气 地点名" 或 "查询天气 [当前位置]"
|
||||
"""
|
||||
pass
|
||||
|
||||
@@ -0,0 +1,20 @@
|
||||
from ..base import IntentProviderBase
|
||||
from typing import List, Dict
|
||||
from config.logger import setup_logging
|
||||
|
||||
TAG = __name__
|
||||
logger = setup_logging()
|
||||
|
||||
|
||||
class IntentProvider(IntentProviderBase):
|
||||
async def detect_intent(self, conn, dialogue_history: List[Dict], text: str) -> str:
|
||||
"""
|
||||
默认的意图识别实现,始终返回继续聊天
|
||||
Args:
|
||||
dialogue_history: 对话历史记录列表
|
||||
text: 本次对话记录
|
||||
Returns:
|
||||
固定返回"继续聊天"
|
||||
"""
|
||||
logger.bind(tag=TAG).debug("Using functionCallProvider, always returning continue chat")
|
||||
return self.intent_options["continue_chat"]
|
||||
@@ -3,6 +3,9 @@ from ..base import IntentProviderBase
|
||||
from plugins_func.functions.play_music import initialize_music_handler
|
||||
from config.logger import setup_logging
|
||||
import re
|
||||
import json
|
||||
import hashlib
|
||||
import time
|
||||
|
||||
TAG = __name__
|
||||
logger = setup_logging()
|
||||
@@ -13,6 +16,10 @@ class IntentProvider(IntentProviderBase):
|
||||
super().__init__(config)
|
||||
self.llm = None
|
||||
self.promot = self.get_intent_system_prompt()
|
||||
# 添加缓存管理
|
||||
self.intent_cache = {} # 缓存意图识别结果
|
||||
self.cache_expiry = 600 # 缓存有效期10分钟
|
||||
self.cache_max_size = 100 # 最多缓存100个意图
|
||||
|
||||
def get_intent_system_prompt(self) -> str:
|
||||
"""
|
||||
@@ -22,62 +29,119 @@ class IntentProvider(IntentProviderBase):
|
||||
"""
|
||||
intent_list = []
|
||||
|
||||
"""
|
||||
"continue_chat": "1.继续聊天, 除了播放音乐和结束聊天的时候的选项, 比如日常的聊天和问候, 对话等",
|
||||
"end_chat": "2.结束聊天, 用户发来如再见之类的表示结束的话, 不想再进行对话的时候",
|
||||
"play_music": "3.播放音乐, 用户希望你可以播放音乐, 只用于播放音乐的意图"
|
||||
"""
|
||||
for key, value in self.intent_options.items():
|
||||
if key == "play_music":
|
||||
intent_list.append("3.播放音乐, 用户希望你可以播放音乐, 只用于播放音乐的意图")
|
||||
elif key == "end_chat":
|
||||
intent_list.append("2.结束聊天, 用户发来如再见之类的表示结束的话, 不想再进行对话的时候")
|
||||
elif key == "continue_chat":
|
||||
intent_list.append("1.继续聊天, 除了播放音乐和结束聊天的时候的选项, 比如日常的聊天和问候, 对话等")
|
||||
else:
|
||||
intent_list.append(value)
|
||||
|
||||
# "如果是唱歌、听歌、播放音乐,请指定歌名,格式为'播放音乐 [识别出的歌名]'。\n"
|
||||
# "如果听不出具体歌名,可以返回'随机播放音乐'。\n"
|
||||
# "只需要返回意图结果的json,不要解释。"
|
||||
# "返回格式如下:\n"
|
||||
prompt = (
|
||||
"你是一个意图识别助手。你需要根据和用户的对话记录,重点分析用户的最后一句话,判断用户意图属于以下哪一类(使用<start>和<end>标志):\n"
|
||||
"你是一个意图识别助手。请分析用户的最后一句话,判断用户意图属于以下哪一类:\n"
|
||||
"<start>"
|
||||
f"{', '.join(intent_list)}"
|
||||
"<end>\n"
|
||||
"你需要按照以下的步骤处理用户的对话"
|
||||
"1. 思考出对话的意图是哪一类的"
|
||||
"2. 属于1和2的意图, 直接返回,返回格式如下:\n"
|
||||
"{intent: '用户意图'}\n"
|
||||
"3. 属于3的意图,则继续分析用户希望播放的音乐\n"
|
||||
"4. 如果无法识别出具体歌名,可以返回'随机播放音乐'\n"
|
||||
"{intent: '播放音乐 [获取的音乐名字]'}\n"
|
||||
"下面是几个处理的示例(思考的内容不返回, 只返回json部分, 无额外的内容)\n"
|
||||
"```"
|
||||
"处理步骤:"
|
||||
"1. 思考意图类型,生成function_call格式"
|
||||
"\n\n"
|
||||
"返回格式示例:\n"
|
||||
"1. 播放音乐意图: {\"function_call\": {\"name\": \"play_music\", \"arguments\": {\"song_name\": \"音乐名称\"}}}\n"
|
||||
"2. 查询天气意图: {\"function_call\": {\"name\": \"get_weather\", \"arguments\": {\"location\": \"地点名称\", \"lang\": \"zh_CN\"}}}\n"
|
||||
"3. 查询新闻意图: {\"function_call\": {\"name\": \"get_news\", \"arguments\": {\"category\": \"新闻类别\", \"detail\": false, \"lang\": \"zh_CN\"}}}\n"
|
||||
"4. 结束对话意图: {\"function_call\": {\"name\": \"handle_exit_intent\", \"arguments\": {\"say_goodbye\": \"goodbye\"}}}\n"
|
||||
"5. 获取当天日期时间: {\"function_call\": {\"name\": \"get_time\"}}\n"
|
||||
"6. 获取当前黄历意图: {\"function_call\": {\"name\": \"get_lunar\"}}\n"
|
||||
"7. 继续聊天意图: {\"function_call\": {\"name\": \"continue_chat\"}}\n"
|
||||
"\n"
|
||||
"注意:\n"
|
||||
"- 播放音乐:无歌名时,song_name设为\"random\"\n"
|
||||
"- 查询天气:无地点时,location设为null\n"
|
||||
"- 查询新闻:无类别时,category设为null;查询详情时,detail设为true\n"
|
||||
"- 如果没有明显的意图,应按照继续聊天意图处理\n"
|
||||
"- 只返回纯JSON,不要任何其他内容\n"
|
||||
"\n"
|
||||
"示例分析:\n"
|
||||
"```\n"
|
||||
"用户: 你好小智\n"
|
||||
"返回: {\"function_call\": {\"name\": \"continue_chat\"}}\n"
|
||||
"```\n"
|
||||
"```\n"
|
||||
"用户: 你今天怎么样?\n"
|
||||
"思考(不返回): 用户发来的数据是一个问候语,属于继续聊天的意图, 是种类1, 种类1的需求是直接返回\n"
|
||||
"返回结果: {intent: '继续聊天'}\n"
|
||||
"```"
|
||||
"用户: 我今天有点累了, 我们明天再聊吧\n"
|
||||
"思考(不返回): 用户表达了今天不想继续对话,属于结束聊天的意图, 是种类2, 种类2的需求是直接返回\n"
|
||||
"返回结果: {intent: '结束聊天'}\n"
|
||||
"```"
|
||||
"用户: 我今天有点累了, 我们明天再聊吧\n"
|
||||
"思考(不返回): 用户表达了今天不想继续对话,属于结束聊天的意图, 是种类2, 种类2的需求是直接返回\n"
|
||||
"返回结果: {intent: '结束聊天'}\n"
|
||||
"```"
|
||||
"用户: 你可以播放一首中秋月给我听吗\n"
|
||||
"思考(不返回): 用户表达了想听音乐的续签,属于播放音乐的意图, 是种类3, 种类3的需求需要继续判断播放的音乐, 这里用户希望的歌曲名明确给出是中秋月\n"
|
||||
"返回结果: {intent: '播放音乐 [中秋月]'}\n"
|
||||
"```"
|
||||
"你现在可以使用的音乐的名称如下(使用<start>和<end>标志):\n"
|
||||
"返回: {\"function_call\": {\"name\": \"continue_chat\"}}\n"
|
||||
"```\n"
|
||||
"```\n"
|
||||
"用户: 现在是几号了?现在几点了?\n"
|
||||
"返回: {\"function_call\": {\"name\": \"get_time\"}}\n"
|
||||
"```\n"
|
||||
"```\n"
|
||||
"用户: 今天农历是多少?\n"
|
||||
"返回: {\"function_call\": {\"name\": \"get_lunar\"}}\n"
|
||||
"```\n"
|
||||
"```\n"
|
||||
"用户: 我们明天再聊吧\n"
|
||||
"返回: {\"function_call\": {\"name\": \"handle_exit_intent\"}}\n"
|
||||
"```\n"
|
||||
"```\n"
|
||||
"用户: 播放中秋月\n"
|
||||
"返回: {\"function_call\": {\"name\": \"play_music\", \"arguments\": {\"song_name\": \"中秋月\"}}}\n"
|
||||
"```\n"
|
||||
"```\n"
|
||||
"用户: 北京天气怎么样\n"
|
||||
"返回: {\"function_call\": {\"name\": \"get_weather\", \"arguments\": {\"location\": \"北京\", \"lang\": \"zh_CN\"}}}\n"
|
||||
"```\n"
|
||||
"```\n"
|
||||
"用户: 今天天气怎么样\n"
|
||||
"返回: {\"function_call\": {\"name\": \"get_weather\", \"arguments\": {\"location\": null, \"lang\": \"zh_CN\"}}}\n"
|
||||
"```\n"
|
||||
"```\n"
|
||||
"用户: 播报财经新闻\n"
|
||||
"返回: {\"function_call\": {\"name\": \"get_news\", \"arguments\": {\"category\": \"财经\", \"detail\": false, \"lang\": \"zh_CN\"}}}\n"
|
||||
"```\n"
|
||||
"```\n"
|
||||
"用户: 有什么最新新闻\n"
|
||||
"返回: {\"function_call\": {\"name\": \"get_news\", \"arguments\": {\"category\": null, \"detail\": false, \"lang\": \"zh_CN\"}}}\n"
|
||||
"```\n"
|
||||
"```\n"
|
||||
"用户: 详细介绍一下这条新闻\n"
|
||||
"返回: {\"function_call\": {\"name\": \"get_news\", \"arguments\": {\"detail\": true, \"lang\": \"zh_CN\"}}}\n"
|
||||
"```\n"
|
||||
"可用的音乐名称:\n"
|
||||
)
|
||||
return prompt
|
||||
|
||||
def clean_cache(self):
|
||||
"""清理过期缓存"""
|
||||
now = time.time()
|
||||
# 找出过期键
|
||||
expired_keys = [k for k, v in self.intent_cache.items() if now - v['timestamp'] > self.cache_expiry]
|
||||
for key in expired_keys:
|
||||
del self.intent_cache[key]
|
||||
|
||||
# 如果缓存太大,移除最旧的条目
|
||||
if len(self.intent_cache) > self.cache_max_size:
|
||||
# 按时间戳排序并保留最新的条目
|
||||
sorted_items = sorted(self.intent_cache.items(), key=lambda x: x[1]['timestamp'])
|
||||
for key, _ in sorted_items[:len(sorted_items) - self.cache_max_size]:
|
||||
del self.intent_cache[key]
|
||||
|
||||
async def detect_intent(self, conn, dialogue_history: List[Dict], text: str) -> str:
|
||||
if not self.llm:
|
||||
raise ValueError("LLM provider not set")
|
||||
|
||||
# 记录整体开始时间
|
||||
total_start_time = time.time()
|
||||
|
||||
# 打印使用的模型信息
|
||||
model_info = getattr(self.llm, 'model_name', str(self.llm.__class__.__name__))
|
||||
logger.bind(tag=TAG).info(f"使用意图识别模型: {model_info}")
|
||||
|
||||
# 计算缓存键
|
||||
cache_key = hashlib.md5(text.encode()).hexdigest()
|
||||
|
||||
# 检查缓存
|
||||
if cache_key in self.intent_cache:
|
||||
cache_entry = self.intent_cache[cache_key]
|
||||
# 检查缓存是否过期
|
||||
if time.time() - cache_entry['timestamp'] <= self.cache_expiry:
|
||||
cache_time = time.time() - total_start_time
|
||||
logger.bind(tag=TAG).info(f"使用缓存的意图: {cache_key} -> {cache_entry['intent']}, 耗时: {cache_time:.4f}秒")
|
||||
return cache_entry['intent']
|
||||
|
||||
# 清理缓存
|
||||
self.clean_cache()
|
||||
|
||||
# 构建用户最后一句话的提示
|
||||
msgStr = ""
|
||||
@@ -94,18 +158,78 @@ class IntentProvider(IntentProviderBase):
|
||||
music_file_names = music_config["music_file_names"]
|
||||
prompt_music = f"{self.promot}\n<start>{music_file_names}\n<end>"
|
||||
logger.bind(tag=TAG).debug(f"User prompt: {prompt_music}")
|
||||
|
||||
# 记录预处理完成时间
|
||||
preprocess_time = time.time() - total_start_time
|
||||
logger.bind(tag=TAG).debug(f"意图识别预处理耗时: {preprocess_time:.4f}秒")
|
||||
|
||||
# 使用LLM进行意图识别
|
||||
llm_start_time = time.time()
|
||||
logger.bind(tag=TAG).info(f"开始LLM意图识别调用, 模型: {model_info}")
|
||||
|
||||
intent = self.llm.response_no_stream(
|
||||
system_prompt=prompt_music,
|
||||
user_prompt=user_prompt
|
||||
)
|
||||
# 使用正则表达式提取大括号中的内容
|
||||
# 使用正则表达式提取 {} 中的内容
|
||||
match = re.search(r'\{.*?\}', intent)
|
||||
|
||||
# 记录LLM调用完成时间
|
||||
llm_time = time.time() - llm_start_time
|
||||
logger.bind(tag=TAG).info(f"LLM意图识别完成, 模型: {model_info}, 调用耗时: {llm_time:.4f}秒")
|
||||
|
||||
# 记录后处理开始时间
|
||||
postprocess_start_time = time.time()
|
||||
|
||||
# 清理和解析响应
|
||||
intent = intent.strip()
|
||||
# 尝试提取JSON部分
|
||||
match = re.search(r'\{.*\}', intent, re.DOTALL)
|
||||
if match:
|
||||
result = match.group(0)
|
||||
intent = result
|
||||
else:
|
||||
intent = "{intent: '继续聊天'}"
|
||||
logger.bind(tag=TAG).info(f"Detected intent: {intent}")
|
||||
return intent.strip()
|
||||
intent = match.group(0)
|
||||
|
||||
# 记录总处理时间
|
||||
total_time = time.time() - total_start_time
|
||||
logger.bind(tag=TAG).info(f"【意图识别性能】模型: {model_info}, 总耗时: {total_time:.4f}秒, LLM调用: {llm_time:.4f}秒, 查询: '{text[:20]}...'")
|
||||
|
||||
# 尝试解析为JSON
|
||||
try:
|
||||
intent_data = json.loads(intent)
|
||||
# 如果包含function_call,则格式化为适合处理的格式
|
||||
if "function_call" in intent_data:
|
||||
function_data = intent_data["function_call"]
|
||||
function_name = function_data.get("name")
|
||||
function_args = function_data.get("arguments", {})
|
||||
|
||||
# 记录识别到的function call
|
||||
logger.bind(tag=TAG).info(f"识别到function call: {function_name}, 参数: {function_args}")
|
||||
|
||||
# 添加到缓存
|
||||
self.intent_cache[cache_key] = {
|
||||
'intent': intent,
|
||||
'timestamp': time.time()
|
||||
}
|
||||
|
||||
# 后处理时间
|
||||
postprocess_time = time.time() - postprocess_start_time
|
||||
logger.bind(tag=TAG).debug(f"意图后处理耗时: {postprocess_time:.4f}秒")
|
||||
|
||||
# 确保返回完全序列化的JSON字符串
|
||||
return intent
|
||||
else:
|
||||
# 添加到缓存
|
||||
self.intent_cache[cache_key] = {
|
||||
'intent': intent,
|
||||
'timestamp': time.time()
|
||||
}
|
||||
|
||||
# 后处理时间
|
||||
postprocess_time = time.time() - postprocess_start_time
|
||||
logger.bind(tag=TAG).debug(f"意图后处理耗时: {postprocess_time:.4f}秒")
|
||||
|
||||
# 返回普通意图
|
||||
return intent
|
||||
except json.JSONDecodeError:
|
||||
# 后处理时间
|
||||
postprocess_time = time.time() - postprocess_start_time
|
||||
logger.bind(tag=TAG).error(f"无法解析意图JSON: {intent}, 后处理耗时: {postprocess_time:.4f}秒")
|
||||
# 如果解析失败,默认返回继续聊天意图
|
||||
return "{\"intent\": \"继续聊天\"}"
|
||||
|
||||
@@ -0,0 +1,85 @@
|
||||
from config.logger import setup_logging
|
||||
from openai import OpenAI
|
||||
import json
|
||||
from core.providers.llm.base import LLMProviderBase
|
||||
|
||||
TAG = __name__
|
||||
logger = setup_logging()
|
||||
|
||||
|
||||
class LLMProvider(LLMProviderBase):
|
||||
def __init__(self, config):
|
||||
self.model_name = config.get("model_name")
|
||||
self.base_url = config.get("base_url", "http://localhost:9997")
|
||||
# Initialize OpenAI client with Xinference base URL
|
||||
# 如果没有v1,增加v1
|
||||
if not self.base_url.endswith("/v1"):
|
||||
self.base_url = f"{self.base_url}/v1"
|
||||
|
||||
logger.bind(tag=TAG).info(f"Initializing Xinference LLM provider with model: {self.model_name}, base_url: {self.base_url}")
|
||||
|
||||
try:
|
||||
self.client = OpenAI(
|
||||
base_url=self.base_url,
|
||||
api_key="xinference" # Xinference has a similar setup to Ollama where it doesn't need an actual key
|
||||
)
|
||||
logger.bind(tag=TAG).info("Xinference client initialized successfully")
|
||||
except Exception as e:
|
||||
logger.bind(tag=TAG).error(f"Error initializing Xinference client: {e}")
|
||||
raise
|
||||
|
||||
def response(self, session_id, dialogue):
|
||||
try:
|
||||
logger.bind(tag=TAG).debug(f"Sending request to Xinference with model: {self.model_name}, dialogue length: {len(dialogue)}")
|
||||
responses = self.client.chat.completions.create(
|
||||
model=self.model_name,
|
||||
messages=dialogue,
|
||||
stream=True
|
||||
)
|
||||
is_active=True
|
||||
for chunk in responses:
|
||||
try:
|
||||
delta = chunk.choices[0].delta if getattr(chunk, 'choices', None) else None
|
||||
content = delta.content if hasattr(delta, 'content') else ''
|
||||
if content:
|
||||
if '<think>' in content:
|
||||
is_active = False
|
||||
content = content.split('<think>')[0]
|
||||
if '</think>' in content:
|
||||
is_active = True
|
||||
content = content.split('</think>')[-1]
|
||||
if is_active:
|
||||
yield content
|
||||
except Exception as e:
|
||||
logger.bind(tag=TAG).error(f"Error processing chunk: {e}")
|
||||
|
||||
except Exception as e:
|
||||
logger.bind(tag=TAG).error(f"Error in Xinference response generation: {e}")
|
||||
yield "【Xinference服务响应异常】"
|
||||
|
||||
def response_with_functions(self, session_id, dialogue, functions=None):
|
||||
try:
|
||||
logger.bind(tag=TAG).debug(f"Sending function call request to Xinference with model: {self.model_name}, dialogue length: {len(dialogue)}")
|
||||
if functions:
|
||||
logger.bind(tag=TAG).debug(f"Function calls enabled with: {[f.get('function', {}).get('name') for f in functions]}")
|
||||
|
||||
stream = self.client.chat.completions.create(
|
||||
model=self.model_name,
|
||||
messages=dialogue,
|
||||
stream=True,
|
||||
tools=functions,
|
||||
)
|
||||
|
||||
for chunk in stream:
|
||||
delta = chunk.choices[0].delta
|
||||
content = delta.content
|
||||
tool_calls = delta.tool_calls
|
||||
|
||||
if content:
|
||||
yield content, tool_calls
|
||||
elif tool_calls:
|
||||
yield None, tool_calls
|
||||
|
||||
except Exception as e:
|
||||
logger.bind(tag=TAG).error(f"Error in Xinference function call: {e}")
|
||||
yield {"type": "content", "content": f"【Xinference服务响应异常: {str(e)}】"}
|
||||
@@ -0,0 +1,31 @@
|
||||
{
|
||||
"des": [
|
||||
"在data目录下创建.mcp_server_settings.json文件,可以选择下面的MCP服务,也可以自行添加新的MCP服务。",
|
||||
"后面不断测试补充好用的mcp服务,欢迎大家一起补充。",
|
||||
"记得删除注释行,des属性仅为说明,不会被解析。",
|
||||
"des和link属性,仅为说明安装方式,方便大家查看原始链接,不是必须项。"
|
||||
],
|
||||
"mcpServers": {
|
||||
"filesystem": {
|
||||
"command": "npx",
|
||||
"args": [
|
||||
"-y",
|
||||
"@modelcontextprotocol/server-filesystem",
|
||||
"/Users/username/Desktop",
|
||||
"/path/to/other/allowed/dir"
|
||||
],
|
||||
"link":"https://github.com/modelcontextprotocol/servers/tree/main/src/filesystem"
|
||||
},
|
||||
"playwright": {
|
||||
"command": "npx",
|
||||
"args": ["-y", "@executeautomation/playwright-mcp-server"],
|
||||
"des" : "run 'npx playwright install' first",
|
||||
"link": "https://github.com/executeautomation/mcp-playwright"
|
||||
},
|
||||
"windows-cli": {
|
||||
"command": "npx",
|
||||
"args": ["-y", "@simonb97/server-win-cli"],
|
||||
"link": "https://github.com/SimonB97/win-cli-mcp-server"
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -45,10 +45,10 @@ def fetch_news_from_rss(rss_url):
|
||||
try:
|
||||
response = requests.get(rss_url)
|
||||
response.raise_for_status()
|
||||
|
||||
|
||||
# 解析XML
|
||||
root = ET.fromstring(response.content)
|
||||
|
||||
|
||||
# 查找所有item元素(新闻条目)
|
||||
news_items = []
|
||||
for item in root.findall('.//item'):
|
||||
@@ -56,14 +56,14 @@ def fetch_news_from_rss(rss_url):
|
||||
link = item.find('link').text if item.find('link') is not None else "#"
|
||||
description = item.find('description').text if item.find('description') is not None else "无描述"
|
||||
pubDate = item.find('pubDate').text if item.find('pubDate') is not None else "未知时间"
|
||||
|
||||
|
||||
news_items.append({
|
||||
'title': title,
|
||||
'link': link,
|
||||
'description': description,
|
||||
'pubDate': pubDate
|
||||
})
|
||||
|
||||
|
||||
return news_items
|
||||
except Exception as e:
|
||||
logger.bind(tag=TAG).error(f"获取RSS新闻失败: {e}")
|
||||
@@ -75,9 +75,9 @@ def fetch_news_detail(url):
|
||||
try:
|
||||
response = requests.get(url)
|
||||
response.raise_for_status()
|
||||
|
||||
|
||||
soup = BeautifulSoup(response.content, 'html.parser')
|
||||
|
||||
|
||||
# 尝试提取正文内容 (这里的选择器需要根据实际网站结构调整)
|
||||
content_div = soup.select_one('.content_desc, .content, article, .article-content')
|
||||
if content_div:
|
||||
@@ -98,7 +98,7 @@ def map_category(category_text):
|
||||
"""将用户输入的中文类别映射到配置文件中的类别键"""
|
||||
if not category_text:
|
||||
return None
|
||||
|
||||
|
||||
# 类别映射字典,目前支持社会、国际、财经新闻,如需更多类型,参见配置文件
|
||||
category_map = {
|
||||
# 社会新闻
|
||||
@@ -113,10 +113,10 @@ def map_category(category_text):
|
||||
"金融": "finance",
|
||||
"经济": "finance"
|
||||
}
|
||||
|
||||
|
||||
# 转换为小写并去除空格
|
||||
normalized_category = category_text.lower().strip()
|
||||
|
||||
|
||||
# 返回映射结果,如果没有匹配项则返回原始输入
|
||||
return category_map.get(normalized_category, category_text)
|
||||
|
||||
@@ -129,21 +129,22 @@ def get_news(conn, category: str = None, detail: bool = False, lang: str = "zh_C
|
||||
if detail:
|
||||
if not hasattr(conn, 'last_news_link') or not conn.last_news_link or 'link' not in conn.last_news_link:
|
||||
return ActionResponse(Action.REQLLM, "抱歉,没有找到最近查询的新闻,请先获取一条新闻。", None)
|
||||
|
||||
|
||||
link = conn.last_news_link.get('link')
|
||||
title = conn.last_news_link.get('title', '未知标题')
|
||||
|
||||
|
||||
if link == '#':
|
||||
return ActionResponse(Action.REQLLM, "抱歉,该新闻没有可用的链接获取详细内容。", None)
|
||||
|
||||
|
||||
logger.bind(tag=TAG).debug(f"获取新闻详情: {title}, URL={link}")
|
||||
|
||||
|
||||
# 获取新闻详情
|
||||
detail_content = fetch_news_detail(link)
|
||||
|
||||
|
||||
if not detail_content or detail_content == "无法获取详细内容":
|
||||
return ActionResponse(Action.REQLLM, f"抱歉,无法获取《{title}》的详细内容,可能是链接已失效或网站结构发生变化。", None)
|
||||
|
||||
return ActionResponse(Action.REQLLM,
|
||||
f"抱歉,无法获取《{title}》的详细内容,可能是链接已失效或网站结构发生变化。", None)
|
||||
|
||||
# 构建详情报告
|
||||
detail_report = (
|
||||
f"根据下列数据,用{lang}回应用户的新闻详情查询请求:\n\n"
|
||||
@@ -152,33 +153,33 @@ def get_news(conn, category: str = None, detail: bool = False, lang: str = "zh_C
|
||||
f"(请对上述新闻内容进行总结,提取关键信息,以自然、流畅的方式向用户播报,"
|
||||
f"不要提及这是总结,就像是在讲述一个完整的新闻故事)"
|
||||
)
|
||||
|
||||
|
||||
return ActionResponse(Action.REQLLM, detail_report, None)
|
||||
|
||||
|
||||
# 否则,获取新闻列表并随机选择一条
|
||||
# 从配置中获取RSS URL
|
||||
rss_config = conn.config["plugins"]["get_news"]
|
||||
default_rss_url = rss_config.get("default_rss_url", "https://www.chinanews.com.cn/rss/society.xml")
|
||||
|
||||
|
||||
# 将用户输入的类别映射到配置中的类别键
|
||||
mapped_category = map_category(category)
|
||||
|
||||
|
||||
# 如果提供了类别,尝试从配置中获取对应的URL
|
||||
rss_url = default_rss_url
|
||||
if mapped_category and mapped_category in rss_config.get("category_urls", {}):
|
||||
rss_url = rss_config["category_urls"][mapped_category]
|
||||
|
||||
|
||||
logger.bind(tag=TAG).info(f"获取新闻: 原始类别={category}, 映射类别={mapped_category}, URL={rss_url}")
|
||||
|
||||
|
||||
# 获取新闻列表
|
||||
news_items = fetch_news_from_rss(rss_url)
|
||||
|
||||
|
||||
if not news_items:
|
||||
return ActionResponse(Action.REQLLM, "抱歉,未能获取到新闻信息,请稍后再试。", None)
|
||||
|
||||
|
||||
# 随机选择一条新闻
|
||||
selected_news = random.choice(news_items)
|
||||
|
||||
|
||||
# 保存当前新闻链接到连接对象,以便后续查询详情
|
||||
if not hasattr(conn, 'last_news_link'):
|
||||
conn.last_news_link = {}
|
||||
@@ -186,7 +187,7 @@ def get_news(conn, category: str = None, detail: bool = False, lang: str = "zh_C
|
||||
'link': selected_news.get('link', '#'),
|
||||
'title': selected_news.get('title', '未知标题')
|
||||
}
|
||||
|
||||
|
||||
# 构建新闻报告
|
||||
news_report = (
|
||||
f"根据下列数据,用{lang}回应用户的新闻查询请求:\n\n"
|
||||
@@ -197,9 +198,9 @@ def get_news(conn, category: str = None, detail: bool = False, lang: str = "zh_C
|
||||
f"直接读出新闻即可,不需要额外多余的内容。"
|
||||
f"如果用户询问更多详情,告知用户可以说'请详细介绍这条新闻'获取更多内容)"
|
||||
)
|
||||
|
||||
|
||||
return ActionResponse(Action.REQLLM, news_report, None)
|
||||
|
||||
|
||||
except Exception as e:
|
||||
logger.bind(tag=TAG).error(f"获取新闻出错: {e}")
|
||||
return ActionResponse(Action.REQLLM, "抱歉,获取新闻时发生错误,请稍后再试。", None)
|
||||
@@ -52,7 +52,7 @@ WEATHER_CODE_MAP = {
|
||||
"405": "雨雪天气", "406": "阵雨夹雪", "407": "阵雪", "408": "小到中雪", "409": "中到大雪", "410": "大到暴雪",
|
||||
"456": "阵雨夹雪", "457": "阵雪", "499": "雪",
|
||||
"500": "薄雾", "501": "雾", "502": "霾", "503": "扬沙", "504": "浮尘",
|
||||
"507": "沙尘暴", "508": "强沙尘暴",
|
||||
"507": "沙尘暴", "508": "强沙尘暴",
|
||||
"509": "浓雾", "510": "强浓雾", "511": "中度霾", "512": "重度霾", "513": "严重霾", "514": "大雾", "515": "特强浓雾",
|
||||
"900": "热", "901": "冷", "999": "未知"
|
||||
}
|
||||
@@ -120,4 +120,4 @@ def get_weather(conn, location: str = None, lang: str = "zh_CN"):
|
||||
"参数为0的值不需要报告给用户,每次都报告体感温度,根据语境选择合适的参数内容告知用户,并对参数给出相应评价)"
|
||||
)
|
||||
|
||||
return ActionResponse(Action.REQLLM, weather_report, None)
|
||||
return ActionResponse(Action.REQLLM, weather_report, None)
|
||||
@@ -69,7 +69,7 @@ handle_device_function_desc = {
|
||||
"description": "动作名称,可选值:get(获取),set(设置),raise(提高),lower(降低)"
|
||||
},
|
||||
"value": {
|
||||
"type": "int",
|
||||
"type": "number",
|
||||
"description": "值大小,可选值:0-100之间的整数"
|
||||
}
|
||||
},
|
||||
|
||||
@@ -12,6 +12,7 @@ class ToolType(Enum):
|
||||
CHANGE_SYS_PROMPT = (3, "修改系统提示词,切换角色性格或职责")
|
||||
SYSTEM_CTL = (4, "系统控制,影响正常的对话流程,如退出、播放音乐等,需要传递conn参数")
|
||||
IOT_CTL = (5, "IOT设备控制,需要传递conn参数")
|
||||
MCP_CLIENT = (6, "MCP客户端")
|
||||
|
||||
def __init__(self, code, message):
|
||||
self.code = code
|
||||
|
||||
@@ -22,4 +22,6 @@ mem0ai==0.1.62
|
||||
bs4==0.0.2
|
||||
modelscope==1.23.2
|
||||
sherpa_onnx==1.11.0
|
||||
cnlunar==0.2.0
|
||||
mcp==1.4.1
|
||||
|
||||
cnlunar==0.2.0
|
||||
|
||||
Reference in New Issue
Block a user