Update app.py

app.py

@@ -1,23 +1,7 @@
 import streamlit as st
 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
-
-# Create an instance of CallbackManager
-callback_manager = CallbackManager()
-
-api_base_url =  "https://internlm-chat.intern-ai.org.cn/puyu/api/v1/"
-model = "internlm2.5-latest"
-api_key = "eyJ0eXBlIjoiSldUIiwiYWxnIjoiSFM1MTIifQ.eyJqdGkiOiI1MDIxNzY4OSIsInJvbCI6IlJPTEVfUkVHSVNURVIiLCJpc3MiOiJPcGVuWExhYiIsImlhdCI6MTczMDM4MDY2MSwiY2xpZW50SWQiOiJlYm1ydm9kNnlvMG5semFlazF5cCIsInBob25lIjoiMTU3MjYzNjM5ODAiLCJ1dWlkIjoiZWFkYTY5ZDUtYjllNC00ZWM3LTk5OWUtZGY5OGQ0OGQwNjBiIiwiZW1haWwiOiIiLCJleHAiOjE3NDU5MzI2NjF9.hmpE8L-WDXmFMCnQag-rGMW1YDeU0cU9M2StKQBUKAsYUNxmodtOO_YbHoTyHBDRbRMx8rDooWCznebk9l6rWA"
-
-# api_base_url =  "https://api.siliconflow.cn/v1"
-# model = "internlm/internlm2_5-7b-chat"
-# api_key = "请填写 API Key"
-
-llm =OpenAILike(model=model, api_base=api_base_url, api_key=api_key, is_chat_model=True,callback_manager=callback_manager)
-
-
+from llama_index.llms.huggingface import HuggingFaceLLM
 
 st.set_page_config(page_title="llama_index_demo", page_icon="🦜🔗")
 st.title("llama_index_demo")
@@ -30,10 +14,15 @@ def init_models():
     )
     Settings.embed_model = embed_model
 
-    #用初始化llm
+    llm = HuggingFaceLLM(
+        model_name="internlm/internlm2_5-1_8b-chat",
+        tokenizer_name="internlm/internlm2_5-1_8b-chat",
+        model_kwargs={"trust_remote_code": True},
+        tokenizer_kwargs={"trust_remote_code": True}
+    )
     Settings.llm = llm
 
-    documents = SimpleDirectoryReader("").load_data()
+    documents = SimpleDirectoryReader("/root/llamaindex_demo/data").load_data()
     index = VectorStoreIndex.from_documents(documents)
     query_engine = index.as_query_engine()
 
@@ -47,10 +36,10 @@ def greet2(question):
     response = st.session_state['query_engine'].query(question)
     return response
 
-      
+
 # Store LLM generated responses
 if "messages" not in st.session_state.keys():
-    st.session_state.messages = [{"role": "assistant", "content": "你好，我是你的助手，有什么我可以帮助你的吗？"}]    
+    st.session_state.messages = [{"role": "assistant", "content": "你好，我是你的助手，有什么我可以帮助你的吗？"}]
 
     # Display or clear chat messages
 for message in st.session_state.messages: