app.py

app.py

@@ -1,54 +1,25 @@
 import torch
 import gradio as gr
+# Use a pipeline as a high-level helper
 from transformers import pipeline
 
 # Initialize the summarization pipeline
 pipe = pipeline("summarization", model="Falconsai/text_summarization")
 
-# Store chat history as a list of tuples [(user_input, summary), ...]
-chat_history = []
-
 # Define the summarize function
-def summarize(input_text, clear_history=False):
-    global chat_history
-
-    # Clear history if requested
-    if clear_history:
-        chat_history = []
-        return chat_history
-
-    # Generate the summary
-    output = pipe(input_text)
-    summary = output[0]['summary_text']
-
-    # Append the user's input and the summary to chat history
-    chat_history.append(("User", input_text))
-    chat_history.append(("Summarizer", summary))
-
-    # Return the updated chat history
-    return chat_history
+def summarize(input):
+    output = pipe(input)
+    return output[0]['summary_text']
 
 # Define the Gradio interface
-with gr.Blocks() as interface:
-    # Title and description
-    gr.Markdown("# ChatGPT-like Text Summarizer")
-    gr.Markdown("Enter a long piece of text, and the summarizer will provide a concise summary. History will appear like a chat interface.")
-    
-    # Input section
-    with gr.Row():
-        input_text = gr.Textbox(lines=10, placeholder="Enter text to summarize here...", label="Input Text")
-        clear_history_btn = gr.Button("Clear History")
-
-    # Chatbot-style output
-    chatbot = gr.Chatbot(label="History", type="messages")
-
-    # Submit button for summarization
-    submit_button = gr.Button("Summarize")
-
-    # Functionality for buttons
-    submit_button.click(summarize, inputs=[input_text, gr.State(False)], outputs=chatbot)
-    clear_history_btn.click(summarize, inputs=["", gr.State(True)], outputs=chatbot)
+iface = gr.Interface(
+    fn=summarize,
+    inputs=gr.Textbox(lines=12, placeholder="Enter text to summarize here..."),
+    outputs="text",
+    title="Text Summarizer",
+    description="Enter a long piece of text, and the summarizer will provide a concise summary."
+)
 
 # Launch the interface
 if __name__ == "__main__":
-    interface.launch()
+    iface.launch()