remove unused templates

.streamlit/config.toml

@@ -0,0 +1,5 @@
+[theme]
+base="dark"
+primaryColor="#3fb0e8"
+#primaryColor="#0775db"
+#secondaryBackgroundColor="#2353A1"

app.py

@@ -1,5 +1,5 @@
 import streamlit as st
-from components import sidebar, template0, template1, template2, template3, template4, template5, template6, template7, template8
+from components import sidebar, template6
 
 def main():
 
@@ -11,26 +11,10 @@ def main():
     )
     
     sidebar.sidebar_head()
-    page = st.sidebar.selectbox("Select page", ['Template 0', 'Template 1', 'Template 2', 'Template 3', 'Template 4', 'Template 5', 'Template 6', 'Template 7', 'Template 8'])
+    page = st.sidebar.selectbox("Select page", ['Main'])
     st.sidebar.markdown('---')
-    if page == 'Template 0':
-        template0.run()
-    if page == 'Template 1':
-        template1.run()
-    if page == 'Template 2':
-        template2.run()
-    if page == 'Template 3':
-        template3.run()
-    if page == 'Template 4':
-        template4.run()
-    if page == 'Template 5':
-        template5.run()
-    if page == 'Template 6':
+    if page == 'Main':
         template6.run()
-    if page == 'Template 7':
-        template7.run()
-    if page == 'Template 8':
-        template8.run()
 
 if __name__ == '__main__':
     main()

components/template0.py

@@ -1,81 +0,0 @@
-import streamlit as st
-import base64
-from components import utils
-
-def run():
-    with open('images/logo2.png', 'rb') as f:
-            data = f.read()
-    bin_str = base64.b64encode(data).decode()
-    st.markdown(f'<div class="header"> <figure><embed type="image/png" src="data:image/png;base64,{bin_str}" width="800px" height="200px"/></div>', unsafe_allow_html=True)
-
-    # Initial State
-    def initial_state():
-        if 'model' not in st.session_state:
-            st.session_state['model'] = False
-
-        if 'uploading_way' not in st.session_state:
-            st.session_state['uploading_way'] = None    
-
-    initial_state()
-
-    col1, col2, col3 = st.columns([0.25,1,0.25])
-    utils.new_line(2)
-
-    # Description
-    st.markdown("""Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt 
-    ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. 
-    Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident,""", unsafe_allow_html=True)
-    st.divider()
-
-    # Dataframe selection
-    st.markdown("<h2 align='center'> <b> Getting Started", unsafe_allow_html=True)
-    utils.new_line(1)
-    st.write("The first step is to upload your data. You can upload your data in three ways: **Upload File**, **Select from Ours**, and **Download URL**. In all ways the data should be a csv file and should not exceed 200 MB.")
-    utils.new_line(1)
-
-    # Uploading Way
-    uploading_way = st.session_state.uploading_way
-    col1, col2, col3 = st.columns(3,gap='large')
-
-    # Upload
-    def upload_click(): st.session_state.uploading_way = "upload"
-    col1.markdown("<h5 align='center'> Upload File", unsafe_allow_html=True)
-    col1.button("Upload File", key="upload_file", use_container_width=True, on_click=upload_click)
-
-    # Select    
-    def select_click(): st.session_state.uploading_way = "select"
-    col2.markdown("<h5 align='center'> Select from Ours", unsafe_allow_html=True)
-    col2.button("Select from Ours", key="select_from_ours", use_container_width=True, on_click=select_click)
-            
-    # URL
-    def url_click(): st.session_state.uploading_way = "url"
-    col3.markdown("<h5 align='center'> Download URL", unsafe_allow_html=True)
-    col3.button("Download URL", key="write_url", use_container_width=True, on_click=url_click)
-
-
-    # Upload
-    if uploading_way == "upload":
-        uploaded_file = st.file_uploader("Upload the Dataset", type="csv")
-        if uploaded_file:
-            pass
-    # Select
-    elif uploading_way == "select":
-                selected = st.selectbox("Select Dataset", ["Select", "Sample 1", "Sample 2", "Sample 3", "Sample 4"])
-                if selected == "Sample 1":
-                    pass
-                elif selected == "Sample 2":
-                    pass
-                elif selected == "Sample 3":
-                    pass
-                elif selected == "Sample 4":
-                    pass
-    # URL
-    elif uploading_way == "url":
-        url = st.text_input("Enter URL to download the dataset")
-        if url:
-            pass
-
-
-    utils.local_css("test1.css")
-
-    utils.add_header('images/background2.png')

components/template1.py

@@ -1,81 +0,0 @@
-import streamlit as st
-import base64
-from components import utils
-
-def run():
-    with open('images/logo2.png', 'rb') as f:
-            data = f.read()
-    bin_str = base64.b64encode(data).decode()
-    st.markdown(f'<div class="header"> <figure><embed type="image/png" src="data:image/png;base64,{bin_str}" width="800px" height="200px"/></div>', unsafe_allow_html=True)
-
-    # Initial State
-    def initial_state():
-        if 'model' not in st.session_state:
-            st.session_state['model'] = False
-
-        if 'uploading_way' not in st.session_state:
-            st.session_state['uploading_way'] = None    
-
-    initial_state()
-
-    col1, col2, col3 = st.columns([0.25,1,0.25])
-    utils.new_line(2)
-
-    # Description
-    st.markdown("""Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt 
-    ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. 
-    Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident,""", unsafe_allow_html=True)
-    st.divider()
-
-    # Dataframe selection
-    st.markdown("<h2 align='center'> <b> Getting Started", unsafe_allow_html=True)
-    utils.new_line(1)
-    st.write("The first step is to upload your data. You can upload your data in three ways: **Upload File**, **Select from Ours**, and **Download URL**. In all ways the data should be a csv file and should not exceed 200 MB.")
-    utils.new_line(1)
-
-    # Uploading Way
-    uploading_way = st.session_state.uploading_way
-    col1, col2, col3 = st.columns(3,gap='large')
-
-    # Upload
-    def upload_click(): st.session_state.uploading_way = "upload"
-    col1.markdown("<h5 align='center'> Upload File", unsafe_allow_html=True)
-    col1.button("Upload File", key="upload_file", use_container_width=True, on_click=upload_click)
-
-    # Select    
-    def select_click(): st.session_state.uploading_way = "select"
-    col2.markdown("<h5 align='center'> Select from Ours", unsafe_allow_html=True)
-    col2.button("Select from Ours", key="select_from_ours", use_container_width=True, on_click=select_click)
-            
-    # URL
-    def url_click(): st.session_state.uploading_way = "url"
-    col3.markdown("<h5 align='center'> Download URL", unsafe_allow_html=True)
-    col3.button("Download URL", key="write_url", use_container_width=True, on_click=url_click)
-
-
-    # Upload
-    if uploading_way == "upload":
-        uploaded_file = st.file_uploader("Upload the Dataset", type="csv")
-        if uploaded_file:
-            pass
-    # Select
-    elif uploading_way == "select":
-                selected = st.selectbox("Select Dataset", ["Select", "Sample 1", "Sample 2", "Sample 3", "Sample 4"])
-                if selected == "Sample 1":
-                    pass
-                elif selected == "Sample 2":
-                    pass
-                elif selected == "Sample 3":
-                    pass
-                elif selected == "Sample 4":
-                    pass
-    # URL
-    elif uploading_way == "url":
-        url = st.text_input("Enter URL to download the dataset")
-        if url:
-            pass
-
-
-    utils.local_css("test.css")
-
-    utils.add_header('images/background2.png')

components/template2.py

@@ -1,80 +0,0 @@
-import streamlit as st
-import base64
-from components import utils
-
-def run():
-    with open('images/logo1.png', 'rb') as f:
-            data = f.read()
-    bin_str = base64.b64encode(data).decode()
-    st.markdown(f'<div class="header"> <figure><embed type="image/png" src="data:image/png;base64,{bin_str}" width="800px" height="200px"/></div>', unsafe_allow_html=True)
-
-    # Initial State
-    def initial_state():
-        if 'model' not in st.session_state:
-            st.session_state['model'] = False
-
-        if 'uploading_way' not in st.session_state:
-            st.session_state['uploading_way'] = None    
-
-    initial_state()
-
-    col1, col2, col3 = st.columns([0.25,1,0.25])
-    utils.new_line(2)
-
-    # Description
-    st.markdown("""Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt 
-    ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. 
-    Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident,""", unsafe_allow_html=True)
-    st.divider()
-
-
-    # Dataframe selection
-    st.markdown("<h2 align='center'> <b> Getting Started", unsafe_allow_html=True)
-    utils.new_line(1)
-    st.write("The first step is to upload your data. You can upload your data in three ways: **Upload File**, **Select from Ours**, and **Download URL**. In all ways the data should be a csv file and should not exceed 200 MB.")
-    utils.new_line(1)
-
-    # Uploading Way
-    uploading_way = st.session_state.uploading_way
-    col1, col2, col3 = st.columns(3,gap='large')
-
-    # Upload
-    def upload_click(): st.session_state.uploading_way = "upload"
-    col1.markdown("<h5 align='center'> Upload File", unsafe_allow_html=True)
-    col1.button("Upload File", key="upload_file", use_container_width=True, on_click=upload_click)
-
-    # Select    
-    def select_click(): st.session_state.uploading_way = "select"
-    col2.markdown("<h5 align='center'> Select from Ours", unsafe_allow_html=True)
-    col2.button("Select from Ours", key="select_from_ours", use_container_width=True, on_click=select_click)
-            
-    # URL
-    def url_click(): st.session_state.uploading_way = "url"
-    col3.markdown("<h5 align='center'> Download URL", unsafe_allow_html=True)
-    col3.button("Download URL", key="write_url", use_container_width=True, on_click=url_click)
-
-    # Upload
-    if uploading_way == "upload":
-        uploaded_file = st.file_uploader("Upload the Dataset", type="csv")
-        if uploaded_file:
-            pass
-    # Select
-    elif uploading_way == "select":
-                selected = st.selectbox("Select Dataset", ["Select", "Sample 1", "Sample 2", "Sample 3", "Sample 4"])
-                if selected == "Sample 1":
-                    pass
-                elif selected == "Sample 2":
-                    pass
-                elif selected == "Sample 3":
-                    pass
-                elif selected == "Sample 4":
-                    pass
-    # URL
-    elif uploading_way == "url":
-        url = st.text_input("Enter URL to download the dataset")
-        if url:
-            pass
-
-    utils.local_css("test.css")
-
-    utils.add_header('images/background3.png')

components/template3.py

@@ -1,57 +0,0 @@
-import streamlit as st
-import os
-from components import utils
-
-def run():
-    # Connect to OpenAI GPT-3, fetch API key from Streamlit secrets
-    #openai.api_key = os.getenv("OPENAI_API_KEY")
-    # Design move app further up and remove top padding
-    st.markdown('''<style>.css-1egvi7u {margin-top: -4rem;}</style>''',
-        unsafe_allow_html=True)
-    # Design change hyperlink href link color
-    st.markdown('''<style>.css-znku1x a {color: #9d03fc;}</style>''',
-        unsafe_allow_html=True)  # darkmode
-    st.markdown('''<style>.css-znku1x a {color: #9d03fc;}</style>''',
-        unsafe_allow_html=True)  # lightmode
-    # Design change height of text input fields headers
-    st.markdown('''<style>.css-qrbaxs {min-height: 0.0rem;}</style>''',
-        unsafe_allow_html=True)
-    # Design change spinner color to primary color
-    st.markdown('''<style>.stSpinner > div > div {border-top-color: #9d03fc;}</style>''',
-        unsafe_allow_html=True)
-    # Design change min height of text input box
-    st.markdown('''<style>.css-15tx938{min-height: 0.0rem;}</style>''',
-        unsafe_allow_html=True)
-    # Design hide top header line
-    #hide_decoration_bar_style = '''<style>header {visibility: hidden;}</style>'''
-    #st.markdown(hide_decoration_bar_style, unsafe_allow_html=True)
-    # Design hide "made with streamlit" footer menu area
-    #hide_streamlit_footer = """<style>#MainMenu {visibility: hidden;}
-    #                        footer {visibility: hidden;}</style>"""
-    #st.markdown(hide_streamlit_footer, unsafe_allow_html=True)
-
-    st.image('images/logo2.png')  # TITLE and Creator information
-    st.markdown("""Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt 
-    ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. 
-    Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident,""", unsafe_allow_html=True)
-   
-    st.write('\n')  # add spacing
-
-    st.subheader('\nGetting Started\n')
-    with st.expander("Dataset Upload", expanded=False):
-        uploaded_file = st.file_uploader('File uploader', type=["csv", "txt", "json"])
-        if uploaded_file:
-            pass
-        else:
-            st.info("Please upload a file to get started.", icon='⚠')
-
-    with st.expander("Select from ours", expanded=False):
-        selected = st.selectbox("Select Dataset", ["Select", "Sample 1", "Sample 2", "Sample 3", "Sample 4"])
-        if selected == "Sample 1":
-            pass
-        elif selected == "Sample 2":
-            pass
-        elif selected == "Sample 3":
-            pass
-        elif selected == "Sample 4":
-            pass

components/template4.py

@@ -1,70 +0,0 @@
-import streamlit as st
-from components import utils
-
-def run():
-    st.markdown("# 🫀 Life Pulse AI")
-    # Initial State
-    def initial_state():
-        if 'model' not in st.session_state:
-            st.session_state['model'] = False
-
-        if 'uploading_way' not in st.session_state:
-            st.session_state['uploading_way'] = None    
-
-    initial_state()
-
-    col1, col2, col3 = st.columns([0.25,1,0.25])
-
-    # Description
-    st.markdown("""Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt 
-    ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. 
-    Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident,""", unsafe_allow_html=True)
-    st.divider()
-
-
-    # Dataframe selection
-    st.markdown("<h2 align='center'> <b> Getting Started", unsafe_allow_html=True)
-    utils.new_line(1)
-    st.write("The first step is to upload your data. You can upload your data in three ways: **Upload File**, **Select from Ours**, and **Download URL**. In all ways the data should be a csv file and should not exceed 200 MB.")
-    utils.new_line(1)
-
-    # Uploading Way
-    uploading_way = st.session_state.uploading_way
-    col1, col2, col3 = st.columns(3,gap='large')
-
-    # Upload
-    def upload_click(): st.session_state.uploading_way = "upload"
-    col1.markdown("<h5 align='center'> Upload File", unsafe_allow_html=True)
-    col1.button("Upload File", key="upload_file", use_container_width=True, on_click=upload_click)
-
-    # Select    
-    def select_click(): st.session_state.uploading_way = "select"
-    col2.markdown("<h5 align='center'> Select from Ours", unsafe_allow_html=True)
-    col2.button("Select from Ours", key="select_from_ours", use_container_width=True, on_click=select_click)
-            
-    # URL
-    def url_click(): st.session_state.uploading_way = "url"
-    col3.markdown("<h5 align='center'> Download URL", unsafe_allow_html=True)
-    col3.button("Download URL", key="write_url", use_container_width=True, on_click=url_click)
-
-    # Upload
-    if uploading_way == "upload":
-        uploaded_file = st.file_uploader("Upload the Dataset", type="csv")
-        if uploaded_file:
-            pass
-    # Select
-    elif uploading_way == "select":
-                selected = st.selectbox("Select Dataset", ["Select", "Sample 1", "Sample 2", "Sample 3", "Sample 4"])
-                if selected == "Sample 1":
-                    pass
-                elif selected == "Sample 2":
-                    pass
-                elif selected == "Sample 3":
-                    pass
-                elif selected == "Sample 4":
-                    pass
-    # URL
-    elif uploading_way == "url":
-        url = st.text_input("Enter URL to download the dataset")
-        if url:
-            pass

components/template5.py

@@ -1,50 +0,0 @@
-import streamlit as st
-
-def run():
-    st.markdown("# 🫀 Life Pulse AI")
-    st.markdown("---")
-    st.markdown("""Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt 
-    ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. 
-    Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident,""", unsafe_allow_html=True)
-    st.divider()
-    gallery_tab, upload_tab, url_tab = st.tabs(["Samples", "Upload", "Download URL"])
-    with gallery_tab:
-        options = ["Sample 1", "Sample 2", "Sample 3", "Sample 4"]
-        file_name = st.selectbox("Select Dataset", 
-                                options=options, index=options.index("Sample 1"))
-        #file = gallery_dict[file_name]
-
-        if st.session_state.get("file_uploader") is not None:
-            st.warning("To use the Gallery, remove the uploaded image first.")
-        if st.session_state.get("dataset_url") not in ["", None]:
-            st.warning("To use the Gallery, remove the image URL first.")
-
-        #img = Image.open(file)
-
-    with upload_tab:
-        file = st.file_uploader("Upload Dataset", key="file_uploader")
-        if file is not None:
-            try:
-                pass
-            except:
-                st.error("The file you uploaded does not seem to be a valid dataset. Try uploading a CSV or txt file.")
-        if st.session_state.get("image_url") not in ["", None]:
-            st.warning("To use the file uploader, remove the URL first.")
-
-    with url_tab:
-        url_text = st.empty()
-        
-        # FIXME: the button is a bit buggy, but it's worth fixing this later
-
-        # url_reset = st.button("Clear URL", key="url_reset")
-        # if url_reset and "image_url" in st.session_state:
-        #     st.session_state["image_url"] = ""
-        #     st.write(st.session_state["image_url"])
-
-        url = url_text.text_input("Enter URL to download the dataset", key="dataset_url")
-        
-        if url!="":
-            try:
-                pass
-            except:
-                st.error("The URL does not seem to be valid.")

components/template7.py

@@ -1,24 +0,0 @@
-import streamlit as st
-
-
-def run():
-    # Title
-    st.title("🫀 Life Pulse AI")
-
-    # Question
-    question = "Do you have datasets (e.g., ECG heartbeat categorization) to upload for analysis?"
-    choice = st.selectbox(question, ("Yes", "No, but I want to demo the software"))
-
-    if choice == "Yes":
-        # Display upload option
-        uploaded_file = st.file_uploader("Upload your document:", type=["txt", "pdf", "docx"])
-        if uploaded_file is not None:
-            st.success("Document uploaded successfully!")
-            # Perform analysis on the uploaded document here
-    else:
-        # Display analysis type selection
-        if st.button("Perform Analysis"):
-            # Perform the selected analysis here
-            st.info(f"Performing {analysis_type} analysis...")
-
-    # Optionally, you can add more instructions or information here

components/template8.py

@@ -1,81 +0,0 @@
-import streamlit as st
-import base64
-from components import utils
-
-def run():
-    with open('images/logo2.png', 'rb') as f:
-            data = f.read()
-    bin_str = base64.b64encode(data).decode()
-    st.markdown(f'<div class="header"> <figure><embed type="image/png" src="data:image/png;base64,{bin_str}" width="800px" height="200px"/></div>', unsafe_allow_html=True)
-
-    # Initial State
-    def initial_state():
-        if 'model' not in st.session_state:
-            st.session_state['model'] = False
-
-        if 'uploading_way' not in st.session_state:
-            st.session_state['uploading_way'] = None    
-
-    initial_state()
-
-    col1, col2, col3 = st.columns([0.25,1,0.25])
-    utils.new_line(2)
-
-    # Description
-    st.markdown("""Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt 
-    ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. 
-    Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident,""", unsafe_allow_html=True)
-    st.divider()
-
-    # Dataframe selection
-    st.markdown("<h2 align='center'> <b> Getting Started", unsafe_allow_html=True)
-    utils.new_line(1)
-    st.write("The first step is to upload your data. You can upload your data in three ways: **Upload File**, **Select from Ours**, and **Download URL**. In all ways the data should be a csv file and should not exceed 200 MB.")
-    utils.new_line(1)
-
-    # Uploading Way
-    uploading_way = st.session_state.uploading_way
-    col1, col2, col3 = st.columns(3,gap='large')
-
-    # Upload
-    def upload_click(): st.session_state.uploading_way = "upload"
-    col1.markdown("<h5 align='center'> Upload File", unsafe_allow_html=True)
-    col1.button("Upload File", key="upload_file", use_container_width=True, on_click=upload_click)
-
-    # Select    
-    def select_click(): st.session_state.uploading_way = "select"
-    col2.markdown("<h5 align='center'> Select from Ours", unsafe_allow_html=True)
-    col2.button("Select from Ours", key="select_from_ours", use_container_width=True, on_click=select_click)
-            
-    # URL
-    def url_click(): st.session_state.uploading_way = "url"
-    col3.markdown("<h5 align='center'> Download URL", unsafe_allow_html=True)
-    col3.button("Download URL", key="write_url", use_container_width=True, on_click=url_click)
-
-
-    # Upload
-    if uploading_way == "upload":
-        uploaded_file = st.file_uploader("Upload the Dataset", type="csv")
-        if uploaded_file:
-            pass
-    # Select
-    elif uploading_way == "select":
-                selected = st.selectbox("Select Dataset", ["Select", "Sample 1", "Sample 2", "Sample 3", "Sample 4"])
-                if selected == "Sample 1":
-                    pass
-                elif selected == "Sample 2":
-                    pass
-                elif selected == "Sample 3":
-                    pass
-                elif selected == "Sample 4":
-                    pass
-    # URL
-    elif uploading_way == "url":
-        url = st.text_input("Enter URL to download the dataset")
-        if url:
-            pass
-
-
-    utils.local_css("test2.css")
-
-    utils.add_header('images/background2.png')