import streamlit as st from llama_index import SimpleDirectoryReader, GPTVectorStoreIndex import os import shutil def save_file(files): directory_name = 'tmp_docs' # Remove existing files in the directory if os.path.exists(directory_name): for filename in os.listdir(directory_name): file_path = os.path.join(directory_name, filename) try: if os.path.isfile(file_path): os.remove(file_path) except Exception as e: print(f"Error: {e}") # Save the new file with original filename if files is not None: for file in files: file_name = file.name file_path = os.path.join(directory_name, file_name) with open(file_path, 'wb') as f: shutil.copyfileobj(file, f) def ingest(docs_dir): documents = SimpleDirectoryReader(docs_dir).load_data() index = GPTVectorStoreIndex.from_documents(documents) return index def get_answer(index, message): response = query(index, message) return [('Chatbot', ''.join(response.response))] def query(index, query_text): query_engine = index.as_query_engine() response = query_engine.query(query_text) return response # Initialize chatbot history chatbot = [] # Display file upload component files = st.file_uploader('Upload Files', accept_multiple_files=True) if files is not None: save_file(files) index = ingest('tmp_docs') # Display message input component message = st.text_input('Enter message') # If message is entered, ingest documents and get chatbot response if message: chatbot.append(('You', message)) chatbot += get_answer(index, message) # Display chat history st.text_area('Chatbot:', value='\n'.join( [f'{x[0]}: {x[1]}' for x in chatbot]), height=250)