coding

app.py

@@ -1,9 +1,10 @@
 import streamlit as st
+import random
 from langchain_community.llms import HuggingFaceHub
 from langchain_community.embeddings import SentenceTransformerEmbeddings
 from langchain_community.vectorstores import FAISS
 from datasets import load_dataset
-import random
+from transformers import pipeline
 
 # 使用 進擊的巨人 数据集
 try:
@@ -31,6 +32,7 @@ def answer_question(repo_id, temperature, max_length, question):
     try:
         with st.spinner("正在初始化 Gemma 模型..."):
             llm = HuggingFaceHub(repo_id=repo_id, model_kwargs={"temperature": temperature, "max_length": max_length})
+            st.success("Gemma 模型初始化完成！")
     except Exception as e:
         st.error(f"Gemma 模型加载失败：{e}")
         st.stop()
@@ -49,10 +51,13 @@ def answer_question(repo_id, temperature, max_length, question):
             prompt = f"请根据以下知识库回答问题：\n{context}\n问题：{question}"
             print('prompt: ' + prompt)
 
+            st.success("本地数据集筛选完成！")
+
         with st.spinner("正在生成答案..."):
             answer = llm.invoke(prompt)
             # 去掉 prompt 的内容
             answer = answer.replace(prompt, "").strip()
+            st.success("答案已经生成！")
         return {"prompt": prompt, "answer": answer}
     except Exception as e:
         st.error(f"问答过程出错：{e}")