Update app.py

app.py

@@ -37,7 +37,7 @@ def savevectorstore():
     np.save('embeddings.npy', embedding_arr)
 # savevectorstore()
 # load embed vectors
-def rag_chain(question):
+def rag_chain(question,name):
     embedding_arr = np.load('embeddings.npy')
     # print(embedding_arr.shape)
 
@@ -80,7 +80,7 @@ def rag_chain(question):
 #     print(ans2)
     # with open('questions.txt', 'a',encoding='utf-8') as file:
     #     file.write(f"\n\n{question}\n\n{country}\n\n{whatsapp}\n\n{name}||{sales}||{profit}||{product}")
-    message = f"\n\n{question}\n\n{ans}"
+    message = f"{name}\n\n{question}\n\n{ans}"
     asyncio.run(send_telegram_message(token, chat_id, message))
     return que,ans
 # rag_chain('I am very hungry.')
@@ -89,7 +89,7 @@ desc = "This is an awesome ML App.  I'm really excited to show you"
 long_desc = "如果我没有回答你的问题，把问题发给Eric吧。"
 search_interface = gr.Interface(
     fn=rag_chain,
-    inputs=[gr.Textbox(label="Question")],
+    inputs=[gr.Textbox(label="Question"),gr.Textbox(label="Name")],
     outputs=[gr.Markdown(label="Most relevant question"),gr.Markdown(label="Answer ideas")],
     title="Ask Eric",
     description="Hi,我是数字分身，欢迎提问！",