File size: 2,445 Bytes
2b8f617
 
74cb18d
301a401
2fa5708
74cb18d
f6e57b3
74cb18d
ba84b98
654939d
 
 
 
 
 
 
 
a08687d
654939d
 
74add6c
7d6b473
654939d
 
 
 
 
a08687d
654939d
 
 
7d6b473
654939d
 
 
a08687d
74cb18d
7d6b473
74cb18d
654939d
 
 
 
 
 
 
a08687d
529f14b
a08687d
 
529f14b
 
 
a08687d
654939d
 
1c29888
654939d
 
 
 
 
 
 
1c29888
654939d
 
1c29888
654939d
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
import streamlit as st
import streamlit.components.v1 as components  # Import Streamlit
from logic import *
import os

token = st.text_input("Open-AI-api-key")
base_url = st.text_input("Open-AI-api-base_url")

make_dir()
input_text = st.radio(
    "Input Options for text",
    ["PDF", "Links","No_Input(Already Created)"])
index = None
if(input_text == "PDF"):
    st.subheader("PDF")
    with st.form("PDF_form"):
        uploaded_file = st.file_uploader('Choose your .pdf file', type="pdf")
        KG_name = st.text_input("KG name")
        sub = st.form_submit_button("Submit")
        if sub: 
            save_uploadedfile(uploaded_file)
            index = get_index_pdf(token, KG_name, base_url)
    
elif(input_text == "Links"):
    st.subheader("LINKS")
    with st.form("links_form"):
        text = st.text_input("Input Links Seperated by ','")
        KG_name = st.text_input("KG name")    
        submitted = st.form_submit_button("Submit")
        if submitted:
            links = text.split(",")   
            index = get_index(links, token, KG_name, base_url)

elif(input_text == "No_Input(Already Created)"):
    st.subheader("NO INPUT")
    KG_name = st.text_input(" KG name")
    if(os.path.exists(KG_name)):
        index = load_index(token, KG_name, base_url)
    else:
        st.write("NO FOLDER BY NAME")

     
if (index != None):
    get_network_graph(index)
    emb = get_embeddings(index)
    fig = get_visualize_embeddings(emb)

    #rdf_graph = generate_rdf(index)
    
    # Visualize RDF structure
    #rdf_visualization = visualize_rdf(rdf_graph)
    #st.subheader("RDF Visualization")
    #st.text(rdf_visualization)

    # Plotly Chart
    st.plotly_chart(fig, use_container_width=True)
            
    # Render the h1 block, contained in a frame of size 200x200.
    HtmlFile = open("kuzugraph_draw3.html", 'r', encoding='utf-8')
    # Read the HTML file
    with open("kuzugraph_draw3.html", 'r', encoding='utf-8') as HtmlFile:
        source_code = HtmlFile.read()
    # st.markdown(f'<div style="width: 800px; height: 600px">{source_code}</div>', unsafe_allow_html=True)
    components.html(source_code,width=800, height=600, scrolling=False)
    
    with st.form("my_form"):
        user_query = st.text_input("Ask the KG ','")
              
        new_submitted = st.form_submit_button("Submit")
        if new_submitted:
            res = query_model(index,user_query)
            st.write(res)