Delete app.py

app.py

@@ -1,50 +0,0 @@
-from sentence_transformers import SentenceTransformer
-import faiss
-import numpy as np
-import streamlit as st
-
-# Title
-st.title("Custom Data Chatbot")
-
-def chatbot(query):
-    query_embedding = model.encode(query).reshape(1, -1)
-    D, I = index.search(query_embedding, 1)
-    similarity_score = D[0][0]
-    st.write(f'similarity_score: {similarity_score}')
-    if similarity_score < 0:
-        return "I'm not sure I understand. Please try again with different wording."
-    else:
-        retrieved_answer = answers[I[0][0]]
-        return retrieved_answer
-    
-# Title
-st.write("### File Upload")
-
-uploaded_file = st.file_uploader("Choose a file", type=["csv"])
-
-if uploaded_file is not None:
-    if uploaded_file.type == 'text/csv':
-        st.write("### File Details:")
-        st.write(f"Filename: {uploaded_file.name}")
-        if uploaded_file.type in ["text/plain", "text/csv"]:
-            file_content = uploaded_file.read().decode("utf-8")
-
-            answers = file_content.splitlines()
-            st.write('Total Content:' , len(answers))
-            
-            user_input = st.text_input("Enter text base on content you upload:")
-            
-            model = SentenceTransformer('all-MiniLM-L6-v2')
-            answers_embeddings = model.encode(answers)
-            d = answers_embeddings.shape[1]
-            index = faiss.IndexFlatL2(d)
-            index.add(np.array(answers_embeddings))
-            
-            if user_input.strip():
-                st.write("You:", user_input)
-                st.write("Bot:",chatbot(user_input))
-            else:
-                st.write("Please enter some text.")
-        
-            
-