Spaces:
Runtime error
Runtime error
Update app.py
Browse files
app.py
CHANGED
|
@@ -1,4 +1,5 @@
|
|
| 1 |
import streamlit as st
|
|
|
|
| 2 |
from PyPDF2 import PdfReader
|
| 3 |
from langchain.text_splitter import RecursiveCharacterTextSplitter
|
| 4 |
from langchain_groq import ChatGroq
|
|
@@ -71,38 +72,41 @@ def main():
|
|
| 71 |
st.markdown("<h1 style='font-size:20px;'>ChatBot by Muhammad Huzaifa</h1>", unsafe_allow_html=True)
|
| 72 |
api_key = st.secrets["inference_api_key"]
|
| 73 |
|
|
|
|
|
|
|
| 74 |
# Sidebar column for file upload
|
| 75 |
with st.sidebar:
|
| 76 |
st.header("Chat with PDF")
|
| 77 |
-
pdf_docs = st.file_uploader("Upload your PDF Files", accept_multiple_files=True, type=["pdf"])
|
| 78 |
|
| 79 |
# Main column for displaying extracted text and user interaction
|
| 80 |
col1, col2 = st.columns([1, 2])
|
| 81 |
-
|
| 82 |
-
if pdf_docs:
|
| 83 |
with col1:
|
| 84 |
if st.button("Submit"):
|
| 85 |
with st.spinner("Processing..."):
|
| 86 |
-
raw_text = get_pdf_text(pdf_docs)
|
| 87 |
-
text_chunks = get_text_chunks(raw_text)
|
| 88 |
get_vector_store(text_chunks, api_key)
|
| 89 |
st.success("Processing Complete")
|
| 90 |
-
|
|
|
|
| 91 |
# Check if PDF documents are uploaded and processing is complete
|
| 92 |
-
if pdf_docs and raw_text:
|
| 93 |
with col1:
|
| 94 |
user_question = st.text_input("Ask a question from the Docs")
|
| 95 |
if user_question:
|
| 96 |
user_input(user_question, api_key)
|
| 97 |
|
| 98 |
# Display extracted text if available
|
| 99 |
-
if raw_text is not None:
|
| 100 |
with col2:
|
| 101 |
st.subheader("Extracted Text from PDF:")
|
| 102 |
-
st.text(raw_text)
|
| 103 |
|
| 104 |
# Show message if no PDF documents are uploaded
|
| 105 |
-
if not pdf_docs:
|
| 106 |
with col1:
|
| 107 |
st.write("Please upload a document first to proceed.")
|
| 108 |
|
|
|
|
| 1 |
import streamlit as st
|
| 2 |
+
from streamlit.state.session_state import SessionState
|
| 3 |
from PyPDF2 import PdfReader
|
| 4 |
from langchain.text_splitter import RecursiveCharacterTextSplitter
|
| 5 |
from langchain_groq import ChatGroq
|
|
|
|
| 72 |
st.markdown("<h1 style='font-size:20px;'>ChatBot by Muhammad Huzaifa</h1>", unsafe_allow_html=True)
|
| 73 |
api_key = st.secrets["inference_api_key"]
|
| 74 |
|
| 75 |
+
session_state = SessionState.get(pdf_docs=None, raw_text=None, processing_complete=False)
|
| 76 |
+
|
| 77 |
# Sidebar column for file upload
|
| 78 |
with st.sidebar:
|
| 79 |
st.header("Chat with PDF")
|
| 80 |
+
session_state.pdf_docs = st.file_uploader("Upload your PDF Files", accept_multiple_files=True, type=["pdf"])
|
| 81 |
|
| 82 |
# Main column for displaying extracted text and user interaction
|
| 83 |
col1, col2 = st.columns([1, 2])
|
| 84 |
+
|
| 85 |
+
if session_state.pdf_docs:
|
| 86 |
with col1:
|
| 87 |
if st.button("Submit"):
|
| 88 |
with st.spinner("Processing..."):
|
| 89 |
+
session_state.raw_text = get_pdf_text(session_state.pdf_docs)
|
| 90 |
+
text_chunks = get_text_chunks(session_state.raw_text)
|
| 91 |
get_vector_store(text_chunks, api_key)
|
| 92 |
st.success("Processing Complete")
|
| 93 |
+
session_state.processing_complete = True
|
| 94 |
+
|
| 95 |
# Check if PDF documents are uploaded and processing is complete
|
| 96 |
+
if session_state.pdf_docs and session_state.raw_text and session_state.processing_complete:
|
| 97 |
with col1:
|
| 98 |
user_question = st.text_input("Ask a question from the Docs")
|
| 99 |
if user_question:
|
| 100 |
user_input(user_question, api_key)
|
| 101 |
|
| 102 |
# Display extracted text if available
|
| 103 |
+
if session_state.raw_text is not None:
|
| 104 |
with col2:
|
| 105 |
st.subheader("Extracted Text from PDF:")
|
| 106 |
+
st.text(session_state.raw_text)
|
| 107 |
|
| 108 |
# Show message if no PDF documents are uploaded
|
| 109 |
+
if not session_state.pdf_docs:
|
| 110 |
with col1:
|
| 111 |
st.write("Please upload a document first to proceed.")
|
| 112 |
|