Update app.py

app.py

@@ -1,48 +1,48 @@
-import streamlit as st
-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):
-    response = chain.invoke(query)
-    return response['result']
-
-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
-    with open(uploaded_file.name, "wb") as f:
-        f.write(uploaded_file.getbuffer())
-
-    # Get the absolute path of the saved file
-    path = os.path.abspath(uploaded_file.name)
-    st.write(f"File saved to: {path}")
-    print(path)
-
-st.write("Document uploaded successfuly!")
-
-
-if st.button("Start Processing"):
-    with st.spinner("Processing"):
-        client = create_vector_database(path)
-        image_vdb = extract_and_store_images(path)
-    chain = qa_bot(client) 
-
-
-    if user_input := st.chat_input("User Input"):
-        with st.chat_message("user"):
-            st.markdown(user_input)
-
-        with st.spinner("Generating Response..."):
-            response = get_answer(chain,user_input)
-            answer = response['result']
-            st.markdown(answer)
-            query_and_print_results(image_vdb,user_input)
+import streamlit as st
+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):
+    response = chain.invoke(query)
+    return response['result']
+
+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
+    with open(uploaded_file.name, "wb") as f:
+        f.write(uploaded_file.getbuffer())
+
+    # Get the absolute path of the saved file
+    path = os.path.abspath(uploaded_file.name)
+    st.write(f"File saved to: {path}")
+    print(path)
+
+st.write("Document uploaded successfuly!")
+
+
+if st.button("Start Processing"):
+    with st.spinner("Processing"):
+        client = create_vector_database(path)
+        image_vdb = extract_and_store_images(path)
+    chain = qa_bot(client) 
+
+
+if user_input := st.chat_input("User Input"):
+    with st.chat_message("user"):
+        st.markdown(user_input)
+
+    with st.spinner("Generating Response..."):
+        response = get_answer(chain,user_input)
+        answer = response['result']
+        st.markdown(answer)
+        query_and_print_results(image_vdb,user_input)