初始化仅前端版本

frontend/components/chat_window.py

@@ -0,0 +1,53 @@
+import streamlit as st
+import requests
+
+
+def render_chat_window(backend_url):
+    st.subheader("💬 流式对话")
+
+    # 聊天历史显示
+    chat_container = st.container()
+    with chat_container:
+        for message in st.session_state.messages:
+            with st.chat_message(message["role"]):
+                st.markdown(message["content"])
+                # 如果有关联图片，也可以在这里显示
+                if "images" in message:
+                    for img_url in message["images"]:
+                        st.image(img_url, width=200)
+
+    # 输入框
+    if prompt := st.chat_input("输入消息..."):
+        # 1. 显示用户消息
+        st.session_state.messages.append({"role": "user", "content": prompt})
+        with st.chat_message("user"):
+            st.markdown(prompt)
+
+        # 2. 调用后端流式接口
+        with st.chat_message("assistant"):
+            message_placeholder = st.empty()
+            full_response = ""
+
+            # 模拟流式接收 (实际需使用 requests stream 或 websocket)
+            # POST /api/chat/stream
+            try:
+                # 伪代码示例：
+                # with requests.post(f"{backend_url}/api/chat/stream", json={"message": prompt}, stream=True) as r:
+                #     for chunk in r.iter_content(chunk_size=None):
+                #         if chunk:
+                #             full_response += chunk.decode('utf-8')
+                #             message_placeholder.markdown(full_response + "▌")
+
+                # 演示用静态延迟
+                import time
+                response_text = "这是一个流式响应的演示。后端正在处理您的请求..."
+                for char in response_text:
+                    full_response += char
+                    message_placeholder.markdown(full_response + "▌")
+                    time.sleep(0.05)
+
+                message_placeholder.markdown(full_response)
+                st.session_state.messages.append({"role": "assistant", "content": full_response})
+
+            except Exception as e:
+                st.error(f"连接后端失败: {e}")