Spaces:
Build error
Build error
| # Import necessary modules | |
| import streamlit as st | |
| import streamlit.components.v1 as components # For embedding custom HTML | |
| from generate_knowledge_graph import generate_knowledge_graph | |
| # Set up Streamlit page configuration | |
| st.set_page_config( | |
| page_icon=None, | |
| layout="wide", # Use wide layout for better graph display | |
| initial_sidebar_state="auto", | |
| menu_items=None | |
| ) | |
| # Set the title of the app | |
| st.title("Knowledge Graph From Text") | |
| # Sidebar section for user input method | |
| st.sidebar.title("Input document") | |
| input_method = st.sidebar.radio( | |
| "Choose an input method:", | |
| ["Upload txt", "Input text"], # Options for uploading a file or manually inputting text | |
| ) | |
| # Case 1: User chooses to upload a .txt file | |
| if input_method == "Upload txt": | |
| # File uploader widget in the sidebar | |
| uploaded_file = st.sidebar.file_uploader(label="Upload file", type=["txt"]) | |
| if uploaded_file is not None: | |
| # Read the uploaded file content and decode it as UTF-8 text | |
| text = uploaded_file.read().decode("utf-8") | |
| # Button to generate the knowledge graph | |
| if st.sidebar.button("Generate Knowledge Graph"): | |
| with st.spinner("Generating knowledge graph..."): | |
| # Call the function to generate the graph from the text | |
| net = generate_knowledge_graph(text) | |
| st.success("Knowledge graph generated successfully!") | |
| # Save the graph to an HTML file | |
| output_file = "knowledge_graph.html" | |
| net.save_graph(output_file) | |
| # Open the HTML file and display it within the Streamlit app | |
| HtmlFile = open(output_file, 'r', encoding='utf-8') | |
| components.html(HtmlFile.read(), height=1000) | |
| # Case 2: User chooses to directly input text | |
| else: | |
| # Text area for manual input | |
| text = st.sidebar.text_area("Input text", height=300) | |
| if text: # Check if the text area is not empty | |
| if st.sidebar.button("Generate Knowledge Graph"): | |
| with st.spinner("Generating knowledge graph..."): | |
| # Call the function to generate the graph from the input text | |
| net = generate_knowledge_graph(text) | |
| st.success("Knowledge graph generated successfully!") | |
| # Save the graph to an HTML file | |
| output_file = "knowledge_graph.html" | |
| net.save_graph(output_file) | |
| # Open the HTML file and display it within the Streamlit app | |
| HtmlFile = open(output_file, 'r', encoding='utf-8') | |
| components.html(HtmlFile.read(), height=1000) |