Spaces:
Sleeping
Sleeping
File size: 2,659 Bytes
357a027 c3c4685 357a027 f910e67 357a027 f910e67 357a027 7f00801 357a027 7f00801 357a027 f910e67 357a027 f910e67 357a027 f910e67 |
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 73 74 75 |
import streamlit as st
import tempfile
import os
from src.utils.ingest_text import create_vector_database
from src.utils.ingest_image import extract_and_store_images
from src.utils.text_qa import qa_bot
from src.utils.image_qa import query_and_print_results
import nest_asyncio
nest_asyncio.apply()
from dotenv import load_dotenv
load_dotenv()
def get_answer(query, chain):
try:
response = chain.invoke(query)
return response['result']
except Exception as e:
st.error(f"Error in get_answer: {e}")
return None
st.title("MULTIMODAL DOC QA")
uploaded_file = st.file_uploader("File upload", type="pdf")
if uploaded_file is not None:
# Save the uploaded file to a temporary location
temp_file_path = os.path.join("temp", uploaded_file.name)
os.makedirs("temp", exist_ok=True) # Ensure the temp directory exists
with open(temp_file_path, "wb") as f:
f.write(uploaded_file.getbuffer())
# Get the absolute path of the saved file
#temp_dir = tempfile.mkdtemp()
path = os.path.abspath(temp_file_path)
st.write(f"File saved to: {path}")
print(path)
st.write("Document uploaded successfully!")
if st.button("Start Processing"):
if uploaded_file is not None:
with st.spinner("Processing"):
try:
client = create_vector_database(path)
image_vdb = extract_and_store_images(path)
chain = qa_bot(client)
st.session_state['chain'] = chain # Store chain in session state
st.session_state['image_vdb'] = image_vdb # Store image_vdb in session state
st.success("Processing complete.")
except Exception as e:
st.error(f"Error during processing: {e}")
else:
st.error("Please upload a file before starting processing.")
if user_input := st.chat_input("User Input"):
if 'chain' in st.session_state and 'image_vdb' in st.session_state:
chain = st.session_state['chain']
image_vdb = st.session_state['image_vdb']
with st.chat_message("user"):
st.markdown(user_input)
with st.spinner("Generating Response..."):
response = get_answer(user_input, chain)
if response:
st.markdown(response)
try:
query_and_print_results(image_vdb, user_input)
except Exception as e:
st.error(f"Error querying image database: {e}")
else:
st.error("Failed to generate response.")
else:
st.error("Please start processing before entering user input.")
|