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import streamlit as st
from transformers import pipeline
import datetime
import pandas as pd
from pathlib import Path
# to-do import upload
st.markdown("# Chatbot")
st.sidebar.markdown("# Chatbot")
uploaded_file = '' # PLACEHOLDER
# Display file content
file_content = uploaded_file.read()
st.write("Dateiinhalt:")
st.code(file_content)
# User input for question
user_question = st.text_input("Stellen Sie eine Frage zum hochgeladenen PDF:")
# Perform Hugging Face task (e.g., question answering)
if user_question:
question_answering = pipeline(
"question-answering",
model="deepset/gelectra-base-germanquad-distilled",
tokenizer="deepset/gelectra-base-germanquad-distilled"
)
# Get answer to the user's question
answer = question_answering(question=user_question, context=file_content)
# Display the answer to the user's question
st.write(f"Antwort auf die Frage '{user_question}': {answer['answer']}")
st.write("Confidence Score:", answer['score']) |