Update app.py

app.py

@@ -24,13 +24,6 @@ with gr.Blocks() as demo:
         """
         # CHATGPT-PAPER-READER
         """)
-     with open("./logo.png", "rb") as f:
-        image_data = f.read()
-        image_base64 = base64.b64encode(image_data).decode("utf-8")
-    
-    gr.HTML(vlaue= f"""<h2 style="background-image: linear-gradient(to right, #3A5FCD, #87CEFA); -webkit-background-clip: text;-webkit-text-fill-color: transparent; text-align: center;">Fashion Aggregator</h2>""")
-    gr.HTML(value= f"""<div style="display: flex; align-items: center; justify-content: center; flex-direction: column;"><p style="font-size: 18px; color: #4AAAFF; text-align: center;">Discover your perfect apparel effortlessly. Simply describe what you're looking for!</p><div style="display: flex; align-items: center; margin-bottom: 0px;"><img src='data:image/jpeg;base64,{image_base64}' width='50' height='30' style="margin-right: 5px;"/><p style="font-size: 14px; color: #555;">Disclaimer: The purpose of this application is solely for demonstration. 1001epochs does not claim ownership for the results. Contact: contact@1001epochs.co.uk for full solution.</p></div></div>""")
-    with gr.Tab("Upload PDF File"):
         pdf_input = gr.File(label="PDF File")
         api_input = gr.Textbox(label="OpenAI API Key")
         result = gr.Textbox(label="PDF Summary")
@@ -41,11 +34,7 @@ with gr.Blocks() as demo:
         ask_button = gr.Button("Ask")
     with gr.Accordion("About this project"):
         gr.Markdown(
-            """## CHATGPT-PAPER-READER📝 
-            This repository provides a simple interface that utilizes the gpt-3.5-turbo 
-            model to read academic papers in PDF format locally. You can use it to help you summarize papers, 
-            create presentation slides, or simply fulfill tasks assigned by your supervisor.\n 
-            [Github](https://github.com/talkingwallace/ChatGPT-Paper-Reader)""")
+            """ Simply upload your document and let our model read it within seconds!""")
 
     app = GUI()
     upload_button.click(fn=app.analyse, inputs=[api_input, pdf_input], outputs=result)