Update app.py

app.py

@@ -1,11 +1,10 @@
+import streamlit as st
 import urllib.request
 import fitz
 import re
 import numpy as np
 import tensorflow_hub as hub
 import openai
-import gradio as gr
-import os
 from sklearn.neighbors import NearestNeighbors
 
 def download_pdf(url, output_path):
@@ -122,62 +121,37 @@ def generate_answer(question,openAI_key):
     answer = generate_text(openAI_key, prompt,"text-davinci-003")
     return answer
 
-def question_answer(url, file, question,openAI_key):
-    if openAI_key.strip()=='':
-        return '[ERROR]: Please enter you Open AI Key. Get your key here : https://platform.openai.com/account/api-keys'
-    if url.strip() == '' and file == None:
-        return '[ERROR]: Both URL and PDF is empty. Provide atleast one.'
-    
-    if url.strip() != '' and file != None:
-        return '[ERROR]: Both URL and PDF is provided. Please provide only one (eiter URL or PDF).'
+recommender = SemanticSearch()
+
+st.title('PDF GPT')
+
+description = """ PDF GPT allows you to chat with your PDF file using Universal Sentence Encoder and Open AI. It gives hallucination free response than other tools as the embeddings are better than OpenAI. The returned response can even cite the page number in square brackets([]) where the information is located, adding credibility to the responses and helping to locate pertinent information quickly."""
+
+st.markdown(description)
 
-    if url.strip() != '':
+openAI_key = st.text_input('Enter your OpenAI API key here')
+url = st.text_input('Enter PDF URL here')
+file = st.file_uploader('Upload your PDF/ Research Paper / Book here', type=['pdf'])
+question = st.text_input('Enter your question here')
+
+if st.button('Submit'):
+    if openAI_key.strip()=='':
+        st.error('Please enter you Open AI Key. Get your key here : https://platform.openai.com/account/api-keys')
+    elif url.strip() == '' and file == None:
+        st.error('Both URL and PDF is empty. Provide atleast one.')
+    elif url.strip() != '' and file != None:
+        st.error('Both URL and PDF is provided. Please provide only one (eiter URL or PDF).')
+    elif url.strip() != '':
         glob_url = url
         download_pdf(glob_url, 'corpus.pdf')
         load_recommender('corpus.pdf')
-
+    elif question.strip() == '':
+        st.error('Question field is empty')
     else:
         old_file_name = file.name
         file_name = file.name
         file_name = file_name[:-12] + file_name[-4:]
         os.rename(old_file_name, file_name)
         load_recommender(file_name)
-
-    if question.strip() == '':
-        return '[ERROR]: Question field is empty'
-
-    return generate_answer(question,openAI_key)
-
-recommender = SemanticSearch()
-
-title = 'PDF GPT'
-description = """ PDF GPT allows you to chat with your PDF file using Universal Sentence Encoder and Open AI. It gives hallucination free response than other tools as the embeddings are better than OpenAI. The returned response can even cite the page number in square brackets([]) where the information is located, adding credibility to the responses and helping to locate pertinent information quickly."""
-
-openAI_key=gr.Textbox(label='Enter your OpenAI API key here')
-
-with gr.Blocks() as demo:
-
-    gr.Markdown(f'<center><h1>{title}</h1></center>')
-    gr.Markdown(description)
-
-    with gr.Row():
-        
-        with gr.Group():
-            gr.Markdown(f'<p style="text-align:center">Get your Open AI API key <a href="https://platform.openai.com/account/api-keys">here</a></p>')
-            url = gr.Textbox(label='Enter PDF URL here')
-            gr.Markdown("<center><h4>OR<h4></center>")
-            file = gr.File(label='Upload your PDF/ Research Paper / Book here', file_types=['.pdf'])
-            question = gr.Textbox(label='Enter your question here')
-            btn = gr.Button(value='Submit')
-            btn.style(full_width=True)
-
-        with gr.Group():
-            answer = gr.Textbox(label='The answer to your question is :')
-
-        btn.click(question_answer, inputs=[url, file, question,openAI_key], outputs=[answer])
-
-    with gr.Sidebar():
-        gr.Interface(inputs=openAI_key)
-
-#openai.api_key = os.getenv('Your_Key_Here') 
-demo.launch()
+        answer = generate_answer(question,openAI_key)
+        st.text_area('The answer to your question is :', value=answer, height=200)