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import io | |
import os | |
import streamlit as st | |
import tempfile | |
from scripts import generate_metadata, ingest, MODEL_NAME | |
st.title('DocVerifyRAG') | |
st.write('Anomaly detection for BIM document metadata') | |
uploaded_file = st.file_uploader("Choose a PDF file", type=["pdf","txt"]) | |
if uploaded_file is not None: | |
try: | |
with tempfile.NamedTemporaryFile(delete=False, suffix=os.path.splitext(uploaded_file.name)[1]) as tmp: | |
tmp.write(uploaded_file.read()) | |
file_path = tmp.name | |
st.write(f'Created temporary file {file_path}') | |
docs = ingest(file_path) | |
st.write('## Querying Together.ai API') | |
metadata = generate_metadata(docs) | |
st.write(f'## Metadata Generated by {MODEL_NAME}') | |
st.write(metadata) | |
# Clean up the temporary file | |
os.remove(file_path) | |
except Exception as e: | |
st.error(f'Error: {e}') |