Update: v1.6

app.py

@@ -1,60 +1,34 @@
 import streamlit as st
-import logging
 from llama_index.core import VectorStoreIndex, SimpleDirectoryReader, Settings
 from llama_index.embeddings.huggingface import HuggingFaceEmbedding
 from llama_index.legacy.callbacks import CallbackManager
 from llama_index.llms.openai_like import OpenAILike
 import os
-import sys
-
-# 设置日志
-class StreamlitHandler(logging.Handler):
-    def emit(self, record):
-        st.write(f"📝 {self.format(record)}")
-
-# 配置日志输出到控制台和 Streamlit
-logging.basicConfig(
-    level=logging.INFO,
-    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
-    handlers=[
-        logging.StreamHandler(sys.stdout),  # 输出到控制台
-        StreamlitHandler()  # 输出到 Streamlit 界面
-    ]
-)
-logger = logging.getLogger(__name__)
-
-# 创建日志显示区域
-log_container = st.empty()
-
-# 页面配置
-st.set_page_config(
-    page_title="AI Assistant Demo",
-    page_icon="😄",
-    layout="wide"  # 使用宽布局
-)
+
+st.set_page_config(page_title="AI Assistant Demo", page_icon="😄")
 
 # 显示加载状态
 status_placeholder = st.empty()
 
 def init_models():
     try:
-        logger.info("Starting model initialization...")
+        print("Starting model initialization...")
         status_placeholder.text("正在初始化模型...")
         
         # 初始化 API 设置
         api_key = os.getenv("API_KEY")
         if not api_key:
-            logger.error("API_KEY environment variable is not set")
+            print("Error: API_KEY environment variable is not set")
             raise ValueError("API_KEY environment variable is not set")
             
-        logger.info("API key loaded successfully")
+        print("API key loaded successfully")
         api_base_url = "https://api.siliconflow.cn/v1"
         model = "internlm/internlm2_5-7b-chat"
         
-        logger.info("Initializing callback manager...")
+        print("Initializing callback manager...")
         callback_manager = CallbackManager()
 
-        logger.info("Initializing LLM...")
+        print("Initializing LLM...")
         llm = OpenAILike(
             model=model,
             api_base=api_base_url,
@@ -63,47 +37,36 @@ def init_models():
             callback_manager=callback_manager
         )
         Settings.llm = llm
-        logger.info("LLM initialized successfully")
+        print("LLM initialized successfully")
 
-        logger.info("Initializing embedding model...")
+        print("Initializing embedding model...")
         embed_model = HuggingFaceEmbedding(
             model_name="/home/user/model/paraphrase-multilingual-MiniLM-L12-v2"
         )
         Settings.embed_model = embed_model
-        logger.info("Embedding model initialized successfully")
+        print("Embedding model initialized successfully")
 
-        logger.info("Loading documents...")
+        print("Loading documents...")
         documents = SimpleDirectoryReader("/home/user/data").load_data()
-        logger.info(f"Loaded {len(documents)} documents")
+        print(f"Loaded {len(documents)} documents")
         
-        logger.info("Creating vector store index...")
+        print("Creating vector store index...")
         index = VectorStoreIndex.from_documents(documents)
         
-        logger.info("Creating query engine...")
+        print("Creating query engine...")
         query_engine = index.as_query_engine()
 
-        logger.info("Model initialization completed successfully!")
+        print("Model initialization completed successfully!")
         status_placeholder.empty()
         return query_engine
 
     except Exception as e:
         error_msg = f"Error during initialization: {str(e)}"
-        logger.error(error_msg)
+        print(error_msg)
         st.error(error_msg)
         raise
 
-# 创建两列布局
-col1, col2 = st.columns([2, 1])
-
-with col1:
-    # 初始化标题和说明
-    st.title("AI Assistant Demo")
-    st.markdown("---")
-
-with col2:
-    # 显示系统状态
-    st.subheader("System Status")
-    st.markdown("---")
+st.title("AI Assistant Demo")
 
 # 检查是否需要初始化模型
 if 'query_engine' not in st.session_state:
@@ -113,13 +76,13 @@ if 'query_engine' not in st.session_state:
 
 def generate_response(question):
     try:
-        logger.info(f"Generating response for question: {question}")
+        print(f"Generating response for question: {question}")
         response = st.session_state['query_engine'].query(question)
-        logger.info("Response generated successfully")
+        print("Response generated successfully")
         return response
     except Exception as e:
         error_msg = f"Error generating response: {str(e)}"
-        logger.error(error_msg)
+        print(error_msg)
         st.error(error_msg)
         return None
 
@@ -135,14 +98,14 @@ for message in st.session_state.messages:
 # 清除聊天历史的功能
 def clear_chat_history():
     st.session_state.messages = [{"role": "assistant", "content": "你好，我是你的助手，有什么我可以帮助���的吗？"}]
-    logger.info("Chat history cleared")
+    print("Chat history cleared")
 
 # 侧边栏按钮
 st.sidebar.button('清除聊天历史', on_click=clear_chat_history)
 
 # 用户输入处理
 if prompt := st.chat_input():
-    logger.info(f"Received user input: {prompt}")
+    print(f"Received user input: {prompt}")
     st.session_state.messages.append({"role": "user", "content": prompt})
     with st.chat_message("user"):
         st.write(prompt)
@@ -156,4 +119,4 @@ if prompt := st.chat_input():
                     st.markdown(response)
                     message = {"role": "assistant", "content": response.response}
                     st.session_state.messages.append(message)
-                    logger.info("Response added to chat history")
+                    print("Response added to chat history")