Update app.py

app.py

@@ -9,11 +9,7 @@ callback_manager = CallbackManager()
 
 api_base_url =  "https://internlm-chat.intern-ai.org.cn/puyu/api/v1/"
 model = "internlm2.5-latest"
-api_key = "eyJ0eXBlIjoiSldUIiwiYWxnIjoiSFM1MTIifQ.eyJqdGkiOiI2NDIwNzQyMiIsInJvbCI6IlJPTEVfUkVHSVNURVIiLCJpc3MiOiJPcGVuWExhYiIsImlhdCI6MTczMDgwNTgyNiwiY2xpZW50SWQiOiJlYm1ydm9kNnlvMG5semFlazF5cCIsInBob25lIjoiMTM0NTUxMjAyOTciLCJ1dWlkIjoiYTA4N2JhNjQtYjI0Zi00NGM3LTlhYWQtMjZmNDRkZDljNDBmIiwiZW1haWwiOiIiLCJleHAiOjE3NDYzNTc4MjZ9._5eSNmjRIkWLjoGDCLaL26urtRP45f6x-cWXjZdC0DrN9svKGegFMbUj04v0cz_rXvOBYSgMzRoXGEk2KEoskA"
-
-# api_base_url =  "https://api.siliconflow.cn/v1"
-# model = "internlm/internlm2_5-7b-chat"
-# api_key = "eyJ0eXBlIjoiSldUIiwiYWxnIjoiSFM1MTIifQ.eyJqdGkiOiI2NDIwNzQyMiIsInJvbCI6IlJPTEVfUkVHSVNURVIiLCJpc3MiOiJPcGVuWExhYiIsImlhdCI6MTczMDgwNTgyNiwiY2xpZW50SWQiOiJlYm1ydm9kNnlvMG5semFlazF5cCIsInBob25lIjoiMTM0NTUxMjAyOTciLCJ1dWlkIjoiYTA4N2JhNjQtYjI0Zi00NGM3LTlhYWQtMjZmNDRkZDljNDBmIiwiZW1haWwiOiIiLCJleHAiOjE3NDYzNTc4MjZ9._5eSNmjRIkWLjoGDCLaL26urtRP45f6x-cWXjZdC0DrN9svKGegFMbUj04v0cz_rXvOBYSgMzRoXGEk2KEoskA"
+api_key = os.getenv('INTERN_KEY')
 
 llm =OpenAILike(model=model, api_base=api_base_url, api_key=api_key, is_chat_model=True,callback_manager=callback_manager)
 
@@ -22,18 +18,21 @@ llm =OpenAILike(model=model, api_base=api_base_url, api_key=api_key, is_chat_mod
 st.set_page_config(page_title="llama_index_demo", page_icon="🦜🔗")
 st.title("llama_index_demo")
 
+#os.system("git lfs install")
+#os.system("git clone https://www.modelscope.cn/Ceceliachenen/paraphrase-multilingual-MiniLM-L12-v2.git")
+
 # 初始化模型
 @st.cache_resource
 def init_models():
     embed_model = HuggingFaceEmbedding(
-        model_name="old_models/paraphrase-multilingual-MiniLM-L12-v2/0_Transformer"
+        model_name="paraphrase-multilingual-MiniLM-L12-v2"
     )
     Settings.embed_model = embed_model
 
     #用初始化llm
     Settings.llm = llm
 
-    documents = SimpleDirectoryReader("/home/user/app/data").load_data()
+    documents = SimpleDirectoryReader("./data").load_data()
     index = VectorStoreIndex.from_documents(documents)
     query_engine = index.as_query_engine()