import os
import sys
sys.path.append(os.path.join(os.path.dirname(__file__), ".."))
import asyncio
import uuid
import streamlit as st
from python_a2a import AgentNetwork, Message, TextContent, MessageRole, Task
from langchain_openai import ChatOpenAI
import json
from datetime import datetime
import pytz
import re # 用于清理响应
from SmartVoyage.config import Config
from SmartVoyage.create_logger import logger
from SmartVoyage.main_prompts import SmartVoyagePrompts
conf = Config()
# 设置页面配置
st.set_page_config(page_title="基于A2A的SmartVoyage旅行助手系统", layout="wide", page_icon="🤖")
# 自定义 CSS 打造高端大气科技感，优化对比度
st.markdown("""
<style>
/* 聊天消息框样式 */
.stChatMessage {
background-color: #2c3e50 !important;
border-radius: 12px !important;
padding: 15px !important;
margin-bottom: 15px !important;
box-shadow: 0 3px 6px rgba(0,0,0,0.2) !important;
}
/* 用户消息框稍亮 */
.stChatMessage.user {
background-color: #34495e !important;
}
/* ✅ 核心：强制所有文字变为白色（包括 markdown 内部） */
.stChatMessage .stMarkdown,
.stChatMessage .stMarkdown p,
.stChatMessage .stMarkdown span,
.stChatMessage .stMarkdown div,
.stChatMessage .stMarkdown strong,
.stChatMessage .stMarkdown em,
.stChatMessage .stMarkdown code {
color: #ffffff !important;
}
/* 如果你想让 emoji 图标更亮一点 */
.stChatMessage [data-testid="stChatMessageAvatarIcon"] {
filter: brightness(1.2);
}
</style>
""", unsafe_allow_html=True)
# 初始化会话状态
if "messages" not in st.session_state:
st.session_state.messages = []
if "agent_network" not in st.session_state:
# 存储代理URL信息，便于查看
st.session_state.agent_urls = {
"WeatherQueryAssistant": "http://localhost:5005",
"TicketQueryAssistant": "http://localhost:5006",
"TicketOrderAssistant": "http://localhost:5007"
}
# 初始化网络
network = AgentNetwork(name="Travel Assistant Network")
network.add("WeatherQueryAssistant", "http://localhost:5005")
network.add("TicketQueryAssistant", "http://localhost:5006")
network.add("TicketOrderAssistant", "http://localhost:5007")
st.session_state.agent_network = network
# 加载配置并创建LLM
st.session_state.llm = ChatOpenAI(
model=conf.model_name,
api_key=conf.api_key,
base_url=conf.base_url,
temperature=0.1
)
# 存储对话历史用于意图识别
st.session_state.conversation_history = ""
# 意图识别agent
def intent_agent(user_input):
# 创建意图识别链：提示模板 + LLM
chain = SmartVoyagePrompts.intent_prompt() | st.session_state.llm
# 调用LLM进行意图识别
current_date = datetime.now(pytz.timezone('Asia/Shanghai')).strftime('%Y-%m-%d') # 获取当前日期（Asia/Shanghai时区）
intent_response = chain.invoke(
{"conversation_history": '\n'.join(st.session_state.conversation_history.split("\n")[-6:]), "query": user_input,
"current_date": current_date}).content.strip()
logger.info(f"意图识别原始响应: {intent_response}")
# 清理响应：移除可能的Markdown代码块标记
intent_response = re.sub(r'^```json\s*|\s*```$', '', intent_response).strip()
logger.info(f"清理后响应: {intent_response}")
intent_output = json.loads(intent_response)
# 提取意图、改写问题和追问消息
intents = intent_output.get("intents", [])
user_queries = intent_output.get("user_queries", {})
follow_up_message = intent_output.get("follow_up_message", "")
logger.info(f"intents: {intents}||user_queries: {user_queries}||follow_up_message: {follow_up_message} ")
return intents, user_queries, follow_up_message
# 主界面布局
st.title("🤖 基于A2A的SmartVoyage旅行智能助手")
st.markdown("欢迎体验智能对话！输入问题，系统将精准识别意图并提供服务。")
# 两栏布局：左侧对话，右侧 Agent Card
col1, col2 = st.columns([2, 1])
# 左侧对话区域
with col1:
st.subheader("💬 对话")
# 对话历史
for message in st.session_state.messages:
with st.chat_message(message["role"]):
st.markdown(message["content"])
# 输入框
if prompt := st.chat_input("请输入您的问题..."):
# 显示用户消息
with st.chat_message("user"):
st.markdown(prompt)
st.session_state.messages.append({"role": "user", "content": prompt})
st.session_state.conversation_history += f"\nUser: {prompt}"
# 获取 LLM 和当前日期
llm = st.session_state.llm
current_date = datetime.now(pytz.timezone('Asia/Shanghai')).strftime('%Y-%m-%d')
# 意图识别
with st.spinner("正在分析您的意图..."):
try:
# 意图识别过程
intents, user_queries, follow_up_message = intent_agent(prompt)
# 根据意图输出生成响应
if "out_of_scope" in intents:
# 如果意图超出范围，返回大模型直接回复
response = follow_up_message
st.session_state.conversation_history += f"\nAssistant: {response}"
elif follow_up_message != "":
# 如果有追问消息，则直接返回
response = follow_up_message
st.session_state.conversation_history += f"\nAssistant: {response}" # 更新历史
else: # 处理有效意图
responses = [] # 存储每个意图的响应列表
routed_agents = [] # 记录路由到的代理列表
for intent in intents:
logger.info(f"处理意图：{intent}")
# 根据意图确定代理名称
if intent == "weather":
agent_name = "WeatherQueryAssistant"
elif intent in ["flight", "train", "concert"]:
agent_name = "TicketQueryAssistant"
elif intent == "order":
agent_name = "TicketOrderAssistant"
else:
agent_name = None
# 不同意图处理方式
if intent == "attraction":
# 对于景点推荐，直接使用LLM生成
chain = SmartVoyagePrompts.attraction_prompt() | llm
rec_response = chain.invoke({"query": prompt}).content.strip()
responses.append(rec_response)
elif agent_name:
# 对于代理意图，则调用代理
# 1）获取问题
query_str = user_queries.get(intent, {})
logger.info(f"{agent_name} 查询：{query_str}")
# 2）获取代理实例
agent = st.session_state.agent_network.get_agent(agent_name)
# 3）构建历史对话信息+新查询，然后调用代理
chat_history = '\n'.join(st.session_state.conversation_history.split("\n")[-7:-1]) + f'\nUser: {query_str}'
message = Message(content=TextContent(text=chat_history), role=MessageRole.USER)
task = Task(id="task-" + str(uuid.uuid4()), message=message.to_dict())
raw_response = asyncio.run(agent.send_task_async(task))
logger.info(f"{agent_name} 原始响应: {raw_response}") # 记录原始响应日志
# 4）处理结果
if raw_response.status.state == 'completed': # 正常结果
agent_result = raw_response.artifacts[0]['parts'][0]['text']
else: # 异常结果
agent_result = raw_response.status.message['content']['text']
# 根据代理类型总结响应
if agent_name == "WeatherQueryAssistant":
chain = SmartVoyagePrompts.summarize_weather_prompt() | llm
final_response = chain.invoke(
{"query": query_str, "raw_response": agent_result}).content.strip()
elif agent_name == "TicketQueryAssistant":
chain = SmartVoyagePrompts.summarize_ticket_prompt() | llm
final_response = chain.invoke(
{"query": query_str, "raw_response": agent_result}).content.strip()
else:
final_response = agent_result
# 5）添加到历史
responses.append(final_response) # 添加到响应列表
routed_agents.append(agent_name) # 记录路由代理
else:
# 不支持的意图
responses.append("暂不支持此意图。")
response = "\n\n".join(responses)
if routed_agents:
logger.info(f"路由到代理：{routed_agents}")
st.session_state.conversation_history += f"\nAssistant: {response}"
# 显示助手消息
with st.chat_message("assistant"):
st.markdown(response)
st.session_state.messages.append({"role": "assistant", "content": response})
except json.JSONDecodeError as json_err:
logger.error(f"意图识别JSON解析失败")
error_message = f"意图识别JSON解析失败：{str(json_err)}。请重试。"
with st.chat_message("assistant"):
st.markdown(error_message)
st.session_state.messages.append({"role": "assistant", "content": error_message})
except Exception as e:
logger.error(f"处理异常: {str(e)}")
error_message = f"处理失败：{str(e)}。请重试。"
with st.chat_message("assistant"):
st.markdown(error_message)
st.session_state.messages.append({"role": "assistant", "content": error_message})
# 右侧 Agent Card 区域
with col2:
st.subheader("🛠️ AgentCard")
for agent_name in st.session_state.agent_network.agents.keys():
agent_card = st.session_state.agent_network.get_agent_card(agent_name)
agent_url = st.session_state.agent_urls.get(agent_name, "未知地址")
with st.expander(f"Agent: {agent_name}", expanded=False):
st.markdown(f"<div class='card-title'>技能</div>", unsafe_allow_html=True)
st.markdown(f"<div class='card-content'>{agent_card.skills}</div>", unsafe_allow_html=True)
st.markdown(f"<div class='card-title'>描述</div>", unsafe_allow_html=True)
st.markdown(f"<div class='card-content'>{agent_card.description}</div>", unsafe_allow_html=True)
st.markdown(f"<div class='card-title'>地址</div>", unsafe_allow_html=True)
st.markdown(f"<div class='card-content'>{agent_url}</div>", unsafe_allow_html=True)
st.markdown(f"<div class='card-title'>状态</div>", unsafe_allow_html=True)
st.markdown(f"<div class='card-content'>在线</div>", unsafe_allow_html=True)
# 页脚
st.markdown("---")
st.markdown('<div class="footer">Powered by 黑马程序员 | 基于Agent2Agent的旅行助手系统 v2.0</div>', unsafe_allow_html=True)