Update app.py

app.py

@@ -1,95 +1,96 @@
-import gradio as gr
-from transformers import pipeline
-import fitz
-
-# Initialize summarization pipeline
-summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
-
-# Function to summarize text
-def summarize_text(text, model, max_length=1024):
-    # Split the input text into smaller chunks
-    chunks = [text[i:i+max_length] for i in range(0, len(text), max_length)]
-
-    # Summarize each chunk separately (You can use list comprehension)
-    summaries = []
-    for chunk in chunks:
-        summary = model(chunk, max_length=150, min_length=40, do_sample=False)[0]['summary_text']
-        summaries.append(summary)
-
-    # Concatenate the summaries into a single string
-    summary = ' '.join(summaries)
-
-    return summary
-
-# Function to read PDF and summarize
-def summarize_pdf(pdf_file, model):
-    with fitz.open(pdf_file.name) as doc:
-        text = ""
-        for page in doc:
-            text += page.get_text()
-    return summarize_text(text, model)
-
-def summarize(input_type, input_text, uploaded_file):
-    try:
-        if input_type == "Text":
-            summary = summarize_text(input_text, summarizer)
-        else:
-            summary = summarize_pdf(uploaded_file, summarizer)
-        return summary
-    except Exception as e:
-        return "There was a problem summarizing the text. Please try again later."
-
-# Define the footer
-footer = """
-<div style="text-align: center; margin-top: 20px;">
-    <a href="https://www.linkedin.com/in/pejman-ebrahimi-4a60151a7/" target="_blank">LinkedIn</a> |
-    <a href="https://github.com/arad1367" target="_blank">GitHub</a> |
-    <a href="https://arad1367.pythonanywhere.com/" target="_blank">Live demo of my PhD defense</a>
-    <br>
-    Made with 💖 by Pejman Ebrahimi
-</div>
-"""
-
-# Define the inputs and outputs
-inputs = [
-    gr.Radio(["Text", "PDF"], label="Input Type"),
-    gr.Textbox(lines=10, label="Enter Text to Summarize", visible=False),
-    gr.File(label="Upload PDF file", visible=False)
-]
-outputs = [
-    gr.Textbox(label="Summary"),
-    gr.HTML(footer)
-]
-
-# Define the submit button
-submit_btn = gr.Button("Submit")
-
-# Define the Gradio interface
-with gr.Blocks(theme='gradio/soft') as app:
-    gr.Markdown("# Text and PDF Summarization App")
-    gr.Markdown("Note: This model can handle a maximum of 1024 tokens. A token is a unit of text that the model can process at a time. When summarizing text, the input text is split into smaller chunks of up to 1024 tokens each, and each chunk is summarized separately. The summaries are then concatenated into a single summary.")
-    with gr.Row():
-        input_type = gr.Radio(["Text", "PDF"], label="Input Type")
-    with gr.Row():
-        input_text = gr.Textbox(lines=10, label="Enter Text to Summarize", visible=False)
-        uploaded_file = gr.File(label="Upload PDF file", visible=False)
-    with gr.Row():
-        submit_btn = gr.Button("Submit")
-    with gr.Row():
-        summary = gr.Textbox(label="Summary")
-    with gr.Row():
-        footer = gr.HTML(footer)
-
-    # Define the change event handler for the input type radio buttons
-    def input_type_change(input_type):
-        if input_type == "Text":
-            return {input_text: gr.Textbox(visible=True), uploaded_file: gr.File(visible=False)}
-        else:
-            return {input_text: gr.Textbox(visible=False), uploaded_file: gr.File(visible=True)}
-    input_type.change(fn=input_type_change, inputs=[input_type], outputs=[input_text, uploaded_file])
-
-    # Define the click event handler for the submit button
-    submit_btn.click(fn=summarize, inputs=[input_type, input_text, uploaded_file], outputs=[summary])
-
-# Launch the Gradio interface
-app.launch('share=True')
+import gradio as gr
+from transformers import pipeline
+import fitz
+
+# Initialize summarization pipeline
+summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+
+# Function to summarize text
+def summarize_text(text, model, max_length=1024):
+    # Split the input text into smaller chunks
+    chunks = [text[i:i+max_length] for i in range(0, len(text), max_length)]
+
+    # Summarize each chunk separately (You can use list comprehension)
+    summaries = []
+    for chunk in chunks:
+        summary = model(chunk, max_length=150, min_length=40, do_sample=False)[0]['summary_text']
+        summaries.append(summary)
+
+    # Concatenate the summaries into a single string
+    summary = ' '.join(summaries)
+
+    return summary
+
+# Function to read PDF and summarize
+def summarize_pdf(pdf_file, model):
+    with fitz.open(pdf_file.name) as doc:
+        text = ""
+        for page in doc:
+            text += page.get_text()
+    return summarize_text(text, model)
+
+def summarize(input_type, input_text, uploaded_file):
+    try:
+        if input_type == "Text":
+            summary = summarize_text(input_text, summarizer)
+        else:
+            summary = summarize_pdf(uploaded_file, summarizer)
+        return summary
+    except Exception as e:
+        return "There was a problem summarizing the text. Please try again later."
+
+# Define the footer
+footer = """
+<div style="text-align: center; margin-top: 20px;">
+    <a href="https://www.linkedin.com/in/pejman-ebrahimi-4a60151a7/" target="_blank">LinkedIn</a> |
+    <a href="https://github.com/arad1367" target="_blank">GitHub</a> |
+    <a href="https://arad1367.pythonanywhere.com/" target="_blank">Live demo of my PhD defense</a>
+    <br>
+    Made with 💖 by Pejman Ebrahimi
+</div>
+"""
+
+# Define the inputs and outputs
+inputs = [
+    gr.Radio(["Text", "PDF"], label="Input Type"),
+    gr.Textbox(lines=10, label="Enter Text to Summarize", visible=False),
+    gr.File(label="Upload PDF file", visible=False)
+]
+outputs = [
+    gr.Textbox(label="Summary"),
+    gr.HTML(footer)
+]
+
+# Define the submit button
+submit_btn = gr.Button("Submit")
+
+# Define the Gradio interface
+with gr.Blocks(theme='gradio/soft') as app:
+    gr.Markdown("# Text and PDF Summarization App")
+    gr.Markdown("Note: This model can handle a maximum of 1024 tokens. A token is a unit of text that the model can process at a time. When summarizing text, the input text is split into smaller chunks of up to 1024 tokens each, and each chunk is summarized separately. The summaries are then concatenated into a single summary.")
+    with gr.Row():
+        input_type = gr.Radio(["Text", "PDF"], label="Input Type")
+    with gr.Row():
+        input_text = gr.Textbox(lines=10, label="Enter Text to Summarize", visible=False)
+        uploaded_file = gr.File(label="Upload PDF file", visible=False)
+    with gr.Row():
+        submit_btn = gr.Button("Submit")
+    with gr.Row():
+        summary = gr.Textbox(label="Summary")
+    with gr.Row():
+        footer = gr.HTML(footer)
+
+    # Define the change event handler for the input type radio buttons
+    def input_type_change(input_type):
+        if input_type == "Text":
+            return {input_text: gr.Textbox(visible=True), uploaded_file: gr.File(visible=False)}
+        else:
+            return {input_text: gr.Textbox(visible=False), uploaded_file: gr.File(visible=True)}
+    input_type.change(fn=input_type_change, inputs=[input_type], outputs=[input_text, uploaded_file])
+
+    # Define the click event handler for the submit button
+    submit_btn.click(fn=summarize, inputs=[input_type, input_text, uploaded_file], outputs=[summary])
+
+# Launch the Gradio interface
+if __name__ == "__main__":
+    app.launch()