Update app.py

app.py

@@ -3,6 +3,7 @@ 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
 
 # Create an instance of CallbackManager
 callback_manager = CallbackManager()
@@ -11,25 +12,29 @@ api_base_url =  "https://internlm-chat.intern-ai.org.cn/puyu/api/v1/"
 model = "internlm2.5-latest"
 api_key = os.getenv('API_KEY')
 
-llm =OpenAILike(model=model, api_base=api_base_url, api_key=api_key, is_chat_model=True,callback_manager=callback_manager)
+llm = OpenAILike(
+    model=model, 
+    api_base=api_base_url, 
+    api_key=api_key, 
+    is_chat_model=True,
+    callback_manager=callback_manager
+)
 
-
-
-st.set_page_config(page_title="llama_index_demo", page_icon="������������")
+st.set_page_config(page_title="llama_index_demo", page_icon="🦙")
 st.title("llama_index_demo")
 
-# 初始化模型
+# 修改初始化模型函数
 @st.cache_resource
 def init_models():
+    # 使用 Hugging Face Hub 上的模型
     embed_model = HuggingFaceEmbedding(
-        model_name="/root/model/sentence-transformer"
+        model_name="sentence-transformers/all-MiniLM-L6-v2"
     )
     Settings.embed_model = embed_model
-
-    #用初始化llm
     Settings.llm = llm
 
-    documents = SimpleDirectoryReader("/root/llamaindex_demo/data").load_data()
+    # 使用相对路径加载数据
+    documents = SimpleDirectoryReader("data").load_data()
     index = VectorStoreIndex.from_documents(documents)
     query_engine = index.as_query_engine()