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import streamlit as st
from streamlit_chat import message
import os
from utils import (
parse_docx,
parse_pdf,
parse_txt,
parse_csv,
search_docs,
embed_docs,
text_to_docs,
get_answer,
get_sources,
wrap_text_in_html,
)
from openai.error import OpenAIError
def clear_submit():
st.session_state["submit"] = False
def set_openai_api_key(api_key: str):
st.session_state["OPENAI_API_KEY"] = api_key
st.markdown('<h1>Chat with your Files </h1>', unsafe_allow_html=True)
st.markdown('<h3>Developed with LangChain and OpenAI Embeddings </h3>', unsafe_allow_html=True)
# Sidebar
index = None
doc = None
with st.sidebar:
user_secret = st.text_input(
"OpenAI API Key",
type="password",
placeholder="Paste your OpenAI API key here (sk-...)",
help="You can get your API key from https://platform.openai.com/account/api-keys.",
value=st.session_state.get("OPENAI_API_KEY", ""),
)
if user_secret:
set_openai_api_key(user_secret)
uploaded_file = st.file_uploader(
"Upload a pdf, docx, or txt file",
type=["pdf", "docx", "txt", "csv", "pptx", "js", "py", "json", "html", "css", "md"],
help="Scanned documents are not supported yet!",
on_change=clear_submit,
)
if uploaded_file is not None:
if uploaded_file.name.endswith(".pdf"):
doc = parse_pdf(uploaded_file)
elif uploaded_file.name.endswith(".docx"):
doc = parse_docx(uploaded_file)
elif uploaded_file.name.endswith(".csv"):
doc = parse_csv(uploaded_file)
elif uploaded_file.name.endswith(".txt"):
doc = parse_txt(uploaded_file)
else:
doc = parse_any(uploaded_file)
# st.error("File type not supported")
# doc = None
text = text_to_docs(doc)
st.write(text)
try:
with st.spinner("Indexing document..."):
index = embed_docs(text)
st.session_state["api_key_configured"] = True
except OpenAIError as e:
st.error(e._message)
tab1, tab2 = st.tabs(["Chat with the File", "About the Application"])
with tab1:
# st.write('To obtain an API Key you must create an OpenAI account at the following link: https://openai.com/api/')
if 'generated' not in st.session_state:
st.session_state['generated'] = []
if 'past' not in st.session_state:
st.session_state['past'] = []
def get_text():
if user_secret:
st.header("Ask me something about the document:")
input_text = st.text_area("You:", on_change=clear_submit)
return input_text
user_input = get_text()
button = st.button("Submit")
if button or st.session_state.get("submit"):
if not user_input:
st.error("Please enter a question!")
else:
st.session_state["submit"] = True
sources = search_docs(index, user_input)
try:
answer = get_answer(sources, user_input)
st.session_state.past.append(user_input)
st.session_state.generated.append(answer["output_text"].split("SOURCES: ")[0])
except OpenAIError as e:
st.error(e._message)
if st.session_state['generated']:
for i in range(len(st.session_state['generated'])-1, -1, -1):
message(st.session_state["generated"][i], key=str(i))
message(st.session_state['past'][i], is_user=True, key=str(i) + '_user')
with tab2:
st.write('About the Application')
st.write('Chat with Files enables user to extract all the information from a file. User can obtain the transcription, the embedding of each segment and also ask questions to the file through a chat.')
st.write('Features include- ')
st.write('1. Reading any pdf, docx, txt or csv file')
st.write('2. Embedding texts segments with Langchain and OpenAI')
st.write('3. Chatting with the file using streamlit-chat and LangChain QA with source and GPT model')
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