Daniel4343
commited on
Commit
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Parent(s):
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Upload 8 files
Browse files- .gitattributes +1 -0
- files/Vorsorge und Verhalten bei Unwetter - Was tun bei Unwetter_ - BBK.pdf +3 -0
- landing.py +28 -0
- pages/__pycache__/table.cpython-311.pyc +0 -0
- pages/__pycache__/upload.cpython-311.pyc +0 -0
- pages/about.py +14 -0
- pages/bot.py +36 -0
- pages/table.py +88 -0
- pages/upload.py +32 -0
.gitattributes
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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files/Vorsorge[[:space:]]und[[:space:]]Verhalten[[:space:]]bei[[:space:]]Unwetter[[:space:]]-[[:space:]]Was[[:space:]]tun[[:space:]]bei[[:space:]]Unwetter_[[:space:]]-[[:space:]]BBK.pdf filter=lfs diff=lfs merge=lfs -text
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files/Vorsorge und Verhalten bei Unwetter - Was tun bei Unwetter_ - BBK.pdf
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version https://git-lfs.github.com/spec/v1
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oid sha256:76356872fafaa2ae3d092837fd41e363a4adde4e66a572ce900e88f2c0ebf868
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size 1447154
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landing.py
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import streamlit as st
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from transformers import pipeline
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import datetime
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import pandas as pd
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from pathlib import Path
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st.set_page_config(
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page_title="Startseite",
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layout="wide",
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initial_sidebar_state="expanded",
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)
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st.sidebar.markdown("# Startseite")
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# HEADER
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header = st.title("Dateiupload für Behörden und Organisationen mit Sicherheitsaufgaben")
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pages/__pycache__/table.cpython-311.pyc
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Binary file (4.09 kB). View file
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pages/__pycache__/upload.cpython-311.pyc
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Binary file (2.29 kB). View file
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pages/about.py
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import streamlit as st
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from transformers import pipeline
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import datetime
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import pandas as pd
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from pathlib import Path
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st.set_page_config(
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page_title="Impressum",
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layout="wide",
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initial_sidebar_state="expanded",
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)
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st.markdown("# Impressum")
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st.sidebar.markdown("# Impressum")
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pages/bot.py
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import streamlit as st
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from transformers import pipeline
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import datetime
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import pandas as pd
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from pathlib import Path
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# to-do import upload
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st.markdown("# Chatbot")
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st.sidebar.markdown("# Chatbot")
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uploaded_file = '' # PLACEHOLDER
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# Display file content
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file_content = uploaded_file.read()
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st.write("Dateiinhalt:")
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st.code(file_content)
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# User input for question
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user_question = st.text_input("Stellen Sie eine Frage zum hochgeladenen PDF:")
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# Perform Hugging Face task (e.g., question answering)
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if user_question:
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question_answering = pipeline(
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"question-answering",
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model="deepset/gelectra-base-germanquad-distilled",
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tokenizer="deepset/gelectra-base-germanquad-distilled"
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)
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# Get answer to the user's question
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answer = question_answering(question=user_question, context=file_content)
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# Display the answer to the user's question
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st.write(f"Antwort auf die Frage '{user_question}': {answer['answer']}")
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st.write("Confidence Score:", answer['score'])
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pages/table.py
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import streamlit as st
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from transformers import pipeline
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from datetime import datetime
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import pandas as pd
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from pathlib import Path
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import csv
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import os
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st.set_page_config(
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page_title="Hochgeladene Dokumente",
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layout="wide",
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initial_sidebar_state="expanded",
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)
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make_button_smaller = """
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<style>
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.stbutton {
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width: 20px;
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height: 19px;
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}
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</style>
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"""
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st.markdown(make_button_smaller, unsafe_allow_html=True)
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st.markdown("# Hochgeladene Dokumente")
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st.sidebar.markdown("# Hochgeladene Dokumente")
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field_names = ['Index', 'Titel', 'Hochladezeitpunkt']
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FILES = []
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def newIndex():
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lastIndex = len(FILES)
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newIndex = lastIndex + 1
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return newIndex
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def generate_files():
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folder = 'C:/Users/keckm/Documents/GitHub/Streamlit/files'
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files = os.listdir(folder)
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for file in files:
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file_path = Path(folder, file)
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index = newIndex()
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title = file
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upload_time = os.path.getctime(Path(folder, file))
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upload_time = datetime.fromtimestamp(upload_time).strftime("%d.%m.%Y - %H:%M:%S")
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if os.path.isfile(file_path):
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file_info = {
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"Index": index,
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"Titel": title,
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"Hochladezeitpunkt": upload_time
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}
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FILES.append(file_info)
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return FILES
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def delete_entry(key):
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folder = 'C:/Users/keckm/Documents/GitHub/Streamlit/files'
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file = FILES[key]['Titel']
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os.remove(Path(folder, file))
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FILES.pop(key)
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generate_files()
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def display_table():
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hide_table_row_index = """
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<style>
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thead tr th:first-child {display:none}
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tbody th {display:none}
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</style>
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"""
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# Inject CSS with Markdown
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st.markdown(hide_table_row_index, unsafe_allow_html=True)
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# Display a static table
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col1, col2 = st.columns([5, 1])
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with col1:
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table1 = pd.DataFrame.from_dict(generate_files())
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st.table(table1.style.format(subset=['Titel']))
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with col2:
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key = 0
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for entry in FILES:
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st.button('Löschen', on_click = delete_entry(key), key = key, use_container_width = True)
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key = key + 1
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display_table()
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pages/upload.py
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import streamlit as st
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from pathlib import Path
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from pages.table import generate_files
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st.set_page_config(
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page_title="Dokumentenupload",
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layout="wide",
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initial_sidebar_state="expanded",
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)
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st.markdown("# Dokumentenupload")
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st.sidebar.markdown("# Dokumentenupload")
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UPLOAD_FOLDER = 'C:/Users/keckm/Documents/GitHub/Streamlit/files' # Ordner für Dateiablage
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def save_file(uploaded_file):
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save_folder = UPLOAD_FOLDER
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save_path = Path(save_folder, uploaded_file.name)
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with open(save_path, mode = 'wb') as w:
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w.write(uploaded_file.getvalue())
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if save_path.exists():
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st.success(f'Dokument {uploaded_file.name} wurde erfolgreich auf den Server hochgeladen.')
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# file uploader
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with st.form('upload_form'):
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uploaded_file = st.file_uploader("Wählen Sie eine Datei aus.", type = [ ".pdf"])
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submit = st.form_submit_button(label='Hochladen')
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if uploaded_file:
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filename = uploaded_file.name
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save_file(uploaded_file)
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generate_files()
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