From 456fc42785eb3acac215e767b711a13971bd6a06 Mon Sep 17 00:00:00 2001
From: Annyfee <2287551746@qq.com>
Date: Sun, 4 Jan 2026 17:08:01 +0800
Subject: [PATCH] feat(module13): update code and environment dependencies

---
 m13_streamlit/__init__.py                |   0
 m13_streamlit/s01_st_basics.py           |  59 ++++++++
 m13_streamlit/s02_st_layout_demo.py      |  25 ++++
 m13_streamlit/s03_agent_single_mvp.py    |  75 ++++++++++
 m13_streamlit/s04_agent_multi_session.py | 167 +++++++++++++++++++++++
 5 files changed, 326 insertions(+)
 create mode 100644 m13_streamlit/__init__.py
 create mode 100644 m13_streamlit/s01_st_basics.py
 create mode 100644 m13_streamlit/s02_st_layout_demo.py
 create mode 100644 m13_streamlit/s03_agent_single_mvp.py
 create mode 100644 m13_streamlit/s04_agent_multi_session.py

diff --git a/m13_streamlit/__init__.py b/m13_streamlit/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/m13_streamlit/s01_st_basics.py b/m13_streamlit/s01_st_basics.py
new file mode 100644
index 0000000..a7cd726
--- /dev/null
+++ b/m13_streamlit/s01_st_basics.py
@@ -0,0 +1,59 @@
+import streamlit as st
+
+# === 输入框 === st.chat_input
+prompt =  st.chat_input("请输入问题")
+if prompt:
+    # 处理用户输入
+    st.write(f"你输入了:{prompt}")
+
+
+# === 气泡 === st.chat_messages:自动生成对话气泡
+# 用户气泡
+with st.chat_message("user", avatar="👤"):
+    st.write("你是人吗")
+
+# 助手气泡
+with st.chat_message("assistant", avatar="🤖"):
+    st.write("似乎不太像是人")
+
+
+# === 折叠状态栏 === st.status:收纳中间步骤
+with st.status("Agent 正在思考...",expanded=True): # expanded:默认是否打开折叠栏
+    st.write("正在查询数据库...")
+    st.write("正在转接专员...")
+    # 最终更新状态
+    st.success("处理完成")
+
+
+# === 动态占位符 === st.empty():先占位,后续更新
+import time
+response = st.empty()
+for msg in ["处理中...", "完成！"]:
+    response.markdown(msg)
+    time.sleep(1)
+
+
+# === 记忆中枢 === st.session_state:状态持久化
+# 初始化
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+# 读写
+st.session_state.messages.append({"role":"user","content":prompt})
+
+
+# === 侧边栏 === st.sidebar
+with st.sidebar:
+    st.write('我是侧边栏')
+    st.json({'User':"张三"})
+
+# === 状态同步器 === st.rerun():让UI与最新状态同步
+st.session_state.cur_agent = "Refund"
+# 注意：在聊天机器人等交互场景中，通常这样写（安全）：
+# if some_condition:      # 只有在用户提交新消息后
+#     st.session_state.cur_agent = "RefundAgent"
+#     st.rerun()          # 手动刷新，显示最新状态
+
+# 如果像上面这样无条件调用 st.rerun()，会造成无限循环刷新，
+# 所以这里注释掉，仅用于静态演示。
+# st.rerun()
\ No newline at end of file
diff --git a/m13_streamlit/s02_st_layout_demo.py b/m13_streamlit/s02_st_layout_demo.py
new file mode 100644
index 0000000..3b8f261
--- /dev/null
+++ b/m13_streamlit/s02_st_layout_demo.py
@@ -0,0 +1,25 @@
+import streamlit as st
+
+st.set_page_config(page_title="智能客服驾驶舱",layout="wide") # 标签页的命名
+st.title("✈️ 智能航天客服 Swarm") # 标题
+
+# 侧边栏
+with st.sidebar:
+    st.header("📦 驾驶舱监控") # 侧边栏标题
+    st.info("当前坐席:前台 TriageAgent") # 侧边栏高亮信息
+    st.subheader("用户画像") # 侧边栏副标题
+    st.json({"name":"张三","vip":True})
+
+# 画聊天历史(模拟)
+with st.chat_message("user",avatar="👤"): # 用一个小表情代表发言人头像
+    st.write("我要退票")
+
+with st.chat_message("assistant",avatar="🤖"):
+    st.write("好的，为您转接退票专员...")
+
+# 画输入框
+prompt = st.chat_input("请输入您的问题")
+if prompt:
+    # 当用户输入后，页面会刷新，显示下面的内容
+    with st.chat_message("user",avatar="👤"):
+        st.write(prompt)
\ No newline at end of file
diff --git a/m13_streamlit/s03_agent_single_mvp.py b/m13_streamlit/s03_agent_single_mvp.py
new file mode 100644
index 0000000..5992289
--- /dev/null
+++ b/m13_streamlit/s03_agent_single_mvp.py
@@ -0,0 +1,75 @@
+import sys
+import os
+
+# 添加项目根目录到 Python 路径
+sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+import streamlit as st
+from agents import Runner, set_tracing_disabled
+from agents.agent import Agent
+from agents.models.openai_chatcompletions import OpenAIChatCompletionsModel
+from openai import AsyncOpenAI
+from config import OPENAI_API_KEY
+
+set_tracing_disabled(True)
+
+# 初始化模型
+client = AsyncOpenAI(api_key=OPENAI_API_KEY,base_url="https://api.deepseek.com")
+model = OpenAIChatCompletionsModel(model="deepseek-chat",openai_client=client)
+
+# 定义一个通用Agent
+smart_agent = Agent(
+    name="SmartAssistant",
+    instructions="""
+        你是航空公司智能客服助手，客户姓名：张三（白金会员），航班号：CA1234。
+
+        你具备以下能力：
+        - 用户说“退票”“退款”“取消” → 回复：✅ 退款申请已提交，预计3个工作日内原路返回。
+        - 用户说“改签”“换航班” → 回复：✅ 明日同航线航班尚有余座，已为您预留，可随时确认改签。
+        - 其他任何问题 → 礼貌、专业地直接回答
+
+        回复要简洁、自然、带表情符号，让用户感到温暖。
+        """,
+    model=model
+)
+
+# Streamlit UI组件
+st.set_page_config(page_title="智能客服驾驶舱",layout="wide") # 标签页命名
+st.title("✈️ 智能航天客服 Swarm") # 页面标题
+
+# 侧边栏:驾驶舱监控(先固定不变动)
+with st.sidebar:
+    st.header("🖥️ 驾驶舱监控")
+    st.success("当前坐席: 智能助理 SmartAssistant 🤖") # success用作高亮块显示
+    st.subheader("用户画像")
+    st.json({"user_name": "张三(白金会员)", "flight_no": "CA1234"})
+
+# 会话状态与历史消息
+if "messages" not in st.session_state: # 首次运行时，初始化空列表，用于存储聊天消息。
+    st.session_state["messages"] = []
+
+for msg in st.session_state["messages"]: # 重新渲染历史消息，确保聊天上下文在页面刷新后依然可见
+    avatar = "👤" if msg['role'] == 'user' else "🤖"
+    with st.chat_message(msg['role'],avatar=avatar):
+        st.write(msg["content"])
+
+# 用户输入与核心交互
+prompt = st.chat_input("请输入您的问题（试试：我要退票 / 想改签 / 你好）")
+if prompt:
+    # 显示用户信息
+    st.session_state.messages.append({"role":"user","content":prompt})
+    with st.chat_message("user",avatar="👤"):
+        st.write(prompt)
+
+    # 调用Agents SDK
+    with st.spinner("思考中..."): # 执行耗时操作时，显示旋转的加载动画
+        result = Runner.run_sync( # 同步运行智能体
+            smart_agent, # 参数:agent
+            st.session_state.messages # 参数:对话历史
+        )
+
+    # 显示AI回复
+    reply = result.final_output # 最终AI回复内容
+    st.session_state.messages.append({"role":"assistant","content":reply})
+    with st.chat_message("assistant",avatar="🤖"):
+        st.write(reply)
\ No newline at end of file
diff --git a/m13_streamlit/s04_agent_multi_session.py b/m13_streamlit/s04_agent_multi_session.py
new file mode 100644
index 0000000..06367ad
--- /dev/null
+++ b/m13_streamlit/s04_agent_multi_session.py
@@ -0,0 +1,167 @@
+import sys
+import os
+import asyncio
+import nest_asyncio
+import uuid
+from agents import Runner, set_tracing_disabled, SQLiteSession
+from openai.types.responses import ResponseTextDeltaEvent
+
+sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+import streamlit as st
+
+from m12_agents_sdk_swarm.s01_tools import context_variables
+from m12_agents_sdk_swarm.s02_agent import triage_agent, amap_server
+
+nest_asyncio.apply()
+set_tracing_disabled(True)
+
+# 生成/获取动态 Session ID
+if "session_id" not in st.session_state:
+	st.session_state.session_id = f"session_{uuid.uuid4().hex[:8]}"
+
+
+async def init_mcp():
+	try:
+		await amap_server[0].connect()
+		return "✅ 高德地图（按需连接）"
+	except Exception as e:
+		return f"⚠️ MCP 连接失败"
+
+
+mcp_status = asyncio.run(init_mcp())
+
+st.set_page_config(page_title="智能客服驾驶舱", layout="wide")
+st.title("✈️ 智能航空客服 Multi-Agent 系统")
+st.caption(f"🚀 实战三：基于 Agents SDK 的多智能体协作 (ID: {st.session_state.session_id})") # 小字体显示文本
+
+# 初始化持久化 Session
+if "session" not in st.session_state:
+	st.session_state.session = SQLiteSession( # 持久化内存，将AI对话历史搬到数据库中
+		session_id=st.session_state.session_id,
+		db_path="./m13_streamlit/conversations.db"
+	)
+
+if "display_messages" not in st.session_state: # 存储对话记录
+	st.session_state.display_messages = []
+
+if "tool_logs_history" not in st.session_state: # 存储工具调用记录
+	st.session_state.tool_logs_history = []
+
+
+# 封装侧边栏渲染函数，以便在初次加载和转接发生时，都能向同一个占位符刷新内容
+def render_agent_status(placeholder, agent):
+	name = agent.name
+	if name == "TriageAgent":
+		placeholder.info("当前坐席: 前台 TriageAgent")
+	elif name == "RefundAgent":
+		placeholder.success("当前坐席: 退票专员 RefundAgent 🚨")
+	elif name == "ChangeAgent":
+		placeholder.warning("当前坐席: 改签专员 ChangeAgent 🔄")
+
+
+with st.sidebar:
+	st.header("🖥️ 驾驶舱监控")
+
+	# 确保有大脑（session_state）记住当前 Agent
+	if "current_agent" not in st.session_state:
+		st.session_state.current_agent = triage_agent
+
+	# 当代码执行到对应位置时，自动更新上方侧边栏内容
+	agent_status_placeholder = st.empty()
+
+	# 初始渲染：基于当前state里的Agent
+	render_agent_status(agent_status_placeholder, st.session_state.current_agent)
+
+	st.subheader("👤 用户画像")
+	st.json(context_variables)
+
+	st.subheader("🔌 MCP 状态")
+	st.caption(mcp_status)
+
+	st.subheader("📊 会话统计")
+	st.metric("消息数", len(st.session_state.display_messages))
+
+	if st.button("🗑️ 清空对话"):
+		asyncio.run(st.session_state.session.clear_session()) # 调用SQLiteSession对象的clear_session的方法，删除所有session_id等于当前ID的记录
+		st.session_state.session_id = f"session_{uuid.uuid4().hex[:8]}" # 生成新的session_id
+		st.session_state.display_messages = [] # 重置UI缓存
+		st.session_state.tool_logs_history = []
+		st.session_state.current_agent = triage_agent
+		st.rerun()
+
+# 渲染历史消息
+for i, msg in enumerate(st.session_state.display_messages):
+	avatar = "👤" if msg["role"] == "user" else "🤖"
+	with st.chat_message(msg["role"], avatar=avatar):
+		st.write(msg["content"])
+		if i < len(st.session_state.tool_logs_history) and st.session_state.tool_logs_history[i]: # 确保列表索引存在且实际工具调用有记录
+			with st.expander("🔧 查看工具调用", expanded=False): # 默认折叠
+				for log in st.session_state.tool_logs_history[i]:
+					st.caption(log)
+
+prompt = st.chat_input("请输入您的问题")
+
+if prompt:
+	st.session_state.display_messages.append({"role": "user", "content": prompt})
+	st.session_state.tool_logs_history.append([]) # 提前占座，保证索引顺序
+
+	with st.chat_message("user", avatar="👤"): # 直接写入气泡
+		st.write(prompt)
+
+	with st.chat_message("assistant", avatar="🤖"):
+		message_placeholder = st.empty() # 先占位，AI思考后再填入
+
+	with st.status("Agent 正在思考...", expanded=True) as status:
+		async def process_stream():
+			stream = Runner.run_streamed(
+				st.session_state.current_agent,
+				input=prompt, # 问题
+				context=context_variables, # 全局上下文
+				session=st.session_state.session # 读:从数据库提取聊天记录/写:回复结束，自动将新一轮对话存入数据库
+			)
+
+			# 收集局部变量，再一起叠加到全局变量中
+			reply = "" # 回复内容累加器
+			tool_logs = [] # 工具日志收集
+
+			current_agent_name = st.session_state.current_agent.name
+
+			async for event in stream.stream_events(): # 流式事件
+				if event.type == "raw_response_event":
+					if isinstance(event.data, ResponseTextDeltaEvent):
+						delta = event.data.delta or "" # 提取新字符
+						reply += delta
+						message_placeholder.write(reply) # 实时刷新UI
+
+				# 当agent转换时
+				elif event.type == "agent_updated_stream_event":
+					new_agent = event.new_agent
+					if current_agent_name != new_agent.name:
+						log_msg = f"🔀 转接: {current_agent_name} → {new_agent.name}"
+						status.write(log_msg) # 写入折叠栏
+						tool_logs.append(log_msg)
+
+						# 1. 更新“大脑”（状态持久化）
+						st.session_state.current_agent = new_agent
+						# 2. 实时更新“脸面”（让侧边栏占位符立刻变色/变字）
+						render_agent_status(agent_status_placeholder, new_agent)
+
+						current_agent_name = new_agent.name
+
+				elif event.type == "run_item_stream_event":
+					if event.name == "tool_called":
+						tool_name = event.item.raw_item.name # 提取被调用工具的名字
+						log_msg = f"🔧 调用: {tool_name}"
+						status.write(log_msg) # 写入折叠栏
+						tool_logs.append(log_msg)
+
+			return reply, tool_logs # 返回完整回复的字符串与收集到的动作日志
+
+
+		reply, tool_logs = asyncio.run(process_stream())
+		status.update(label="✅ 处理完成", state="complete", expanded=False) # 标识处理成功
+
+	# 将(本轮)对话记录/工具调用，分别存入(总)对话记录/工具调用
+	st.session_state.display_messages.append({"role": "assistant", "content": reply})
+	st.session_state.tool_logs_history.append(tool_logs)
\ No newline at end of file