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import gradio as gr | |
from langchain.embeddings.openai import OpenAIEmbeddings | |
from langchain.text_splitter import CharacterTextSplitter | |
from langchain.vectorstores import Chroma | |
from langchain.chains import ConversationalRetrievalChain | |
from langchain.chat_models import ChatOpenAI | |
from langchain.document_loaders import PyPDFLoader | |
import os | |
import fitz | |
from PIL import Image | |
import streamlit as st | |
# # Global variables | |
# COUNT, N = 0, 0 | |
# chat_history = [] | |
# chain = None # Initialize chain as None | |
# # Function to set the OpenAI API key | |
# def set_apikey(api_key): | |
# os.environ['OPENAI_API_KEY'] = api_key | |
# return disable_box # Update the disable_box | |
# # Function to enable the API key input box | |
# def enable_api_box(): | |
# return enable_box # Update the enable_box | |
# # Function to add text to the chat history | |
# def add_text(history, text): | |
# if not text: | |
# raise gr.Error('Enter text') | |
# history = history + [(text, '')] | |
# return history | |
# # Function to process the PDF file and create a conversation chain | |
# def process_file(file): | |
# global chain # Access the global 'chain' variable | |
# if 'OPENAI_API_KEY' not in os.environ: | |
# raise gr.Error('Upload your OpenAI API key') | |
# loader = PyPDFLoader(file.name) | |
# documents = loader.load() | |
# embeddings = OpenAIEmbeddings() | |
# pdfsearch = Chroma.from_documents(documents, embeddings) | |
# chain = ConversationalRetrievalChain.from_llm(ChatOpenAI(temperature=0.3), | |
# retriever=pdfsearch.as_retriever(search_kwargs={"k": 1}), | |
# return_source_documents=True) | |
# return chain | |
# # Function to generate a response based on the chat history and query | |
def generate_response(history, query, btn): | |
global COUNT, N, chat_history, chain | |
if not btn: | |
raise gr.Error(message='Upload a PDF') | |
if COUNT == 0: | |
chain = process_file(btn) | |
COUNT += 1 | |
result = chain({"question": query, 'chat_history': chat_history}, return_only_outputs=True) | |
chat_history += [(query, result["answer"])] | |
N = list(result['source_documents'][0])[1][1]['page'] | |
for char in result['answer']: | |
history[-1][-1] += char # Update the last response | |
yield history, '' | |
# # Function to render a specific page of a PDF file as an image | |
# def render_file(file): | |
# global N | |
# doc = fitz.open(file.name) | |
# page = doc[N] | |
# pix = page.get_pixmap(matrix=fitz.Matrix(300/72, 300/72)) | |
# image = Image.frombytes('RGB', [pix.width, pix.height], pix.samples) | |
# return image | |
# # Gradio application setup | |
# # with gr.Blocks() as demo: | |
# # with gr.Column(): | |
# # gr.Markdown(""" | |
# # <style> | |
# # .image-container { height: 680px; } | |
# # </style> | |
# # """) | |
# # with gr.Row(): | |
# # enable_box = gr.Textbox(placeholder='Enter OpenAI API key', | |
# # show_label=False, interactive=True) | |
# # disable_box = gr.Textbox(value='OpenAI API key is Set', interactive=False) | |
# # change_api_key = gr.Button('Change Key') | |
# # with gr.Row(): | |
# # chatbot = gr.Chatbot(value=[], elem_id='chatbot') | |
# # show_img = gr.Image(label='Upload PDF') | |
# # # Set up event handlers | |
# # # Event handler for submitting the OpenAI API key | |
# # enable_box.submit(fn=set_apikey, inputs=[enable_box], outputs=[disable_box]) | |
# # # Event handler for changing the API key | |
# # change_api_key.click(fn=enable_api_box, outputs=[enable_box]) | |
# def render_first(pdf_file): | |
# # ... Logic to process the PDF | |
# # ... Generate the first image | |
# return image | |
# with gr.Blocks() as demo: | |
# with gr.Column(): | |
# gr.Markdown(""" | |
# <style> | |
# .image-container { height: 680px; } | |
# </style> | |
# """) | |
# with gr.Row(): | |
# enable_box = gr.Textbox(placeholder='Enter OpenAI API key', | |
# show_label=False, interactive=True) | |
# disable_box = gr.Textbox(value='OpenAI API key is Set', interactive=False) | |
# change_api_key = gr.Button('Change Key') | |
# with gr.Row(): | |
# chatbot = gr.Chatbot(value=[], elem_id='chatbot') | |
# show_img = gr.Image(label='Upload PDF') | |
# pdf_upload = gr.UploadButton("π Upload a PDF", file_types=[".pdf"]) # Added | |
# # Event handlers | |
# enable_box.submit(fn=set_apikey, inputs=[enable_box], outputs=[disable_box]) | |
# change_api_key.click(fn=enable_api_box, outputs=[enable_box]) | |
# pdf_upload.upload(fn=render_first, inputs=[pdf_upload], outputs=[show_img]) # Corrected | |
# txt = gr.Textbox(label="Enter your query", placeholder="Ask a question...") # Add Textbox | |
# submit_btn = gr.Button('Submit') # Added the Submit button | |
# submit_btn.click( | |
# fn=add_text, | |
# inputs=[chatbot, txt], # Assuming 'txt' is your textbox for query input | |
# outputs=[chatbot], | |
# queue=False | |
# ).success( | |
# fn=generate_response, | |
# inputs=[chatbot, txt, pdf_upload], # Changed from 'btn' | |
# outputs=[chatbot, txt] | |
# ).success( | |
# fn=render_file, | |
# inputs=[pdf_upload], # Changed from 'btn' | |
# outputs=[show_img] | |
# ) | |
# demo.launch(server_port=7861) | |
def add_text(history, text): | |
if not text: | |
raise gr.Error('Enter text') | |
history = history + [(text, '')] | |
return history | |
def render_first(pdf_file): | |
# ... Logic to process the PDF (extract text, create summary, etc.) | |
# ... Generate a simple image as a placeholder | |
image = Image.new('RGB', (600, 400), color = 'white') # Example | |
return image | |
st.title("PDF-Powered Chatbot") # Add a title | |
# Gradio interface with Streamlit containers | |
with st.container(): | |
gr.Markdown(""" | |
<style> | |
.image-container { height: 680px; } | |
</style> | |
""") | |
with gr.Row(): | |
enable_box = gr.Textbox(placeholder='Enter OpenAI API key', | |
show_label=False, interactive=True) | |
disable_box = gr.Textbox(value='OpenAI API key is Set', interactive=False) | |
change_api_key = gr.Button('Change Key') | |
with gr.Row(): | |
chatbot = gr.Chatbot(value=[], elem_id='chatbot') | |
show_img = gr.Image(label='Upload PDF') | |
pdf_upload = gr.UploadButton("π Upload a PDF", file_types=[".pdf"]) | |
# Event handlers (same as before) | |
# ... your event handlers ... | |
# If you only want a Gradio interface, launch Gradio | |
if __name__ == "__main__": | |
gr.Interface( | |
[render_first, add_text, generate_response, render_file], | |
[pdf_upload, chatbot, txt, pdf_upload, pdf_upload], | |
[show_img, chatbot, txt, show_img], | |
title="PDF-Powered Chatbot", | |
).launch() |