Update app.py

app.py

@@ -1,54 +1,57 @@
-import gradio as gr
-from main import main
-
-def rexplore_summarizer(corpus):
-    response = main(corpus)
-    return response, response['summary'], response['mindmap']
-
-def clear_everything(text_corpus, raw_data, summary, mindmap):
-    return None, None, None, None
-
-theme = gr.themes.Soft(
-    primary_hue="purple",
-    secondary_hue="cyan",
-    neutral_hue="slate",
-    font=[
-        gr.themes.GoogleFont('Syne'), 
-        gr.themes.GoogleFont('Poppins'), 
-        gr.themes.GoogleFont('Poppins'), 
-        gr.themes.GoogleFont('Poppins')
-    ],
-)
-
-with gr.Blocks(theme=theme, title="ReXplore Summarizer", fill_height=True) as app:
-    gr.HTML(
-        value ='''
-        <h1 style="text-align: center;">ReXplore Summarizer <p style="text-align: center;">Designed and Developed by <a href='https://raannakasturi.eu.org' target="_blank" rel="nofollow noreferrer external">Nayan Kasturi</a></p> </h1>
-        <p style="text-align: center;">This app uses a hybrid approach to summarize PDF documents based on CPU as well as GPU.</p>
-        <p style="text-align: center;">The app uses traditional methodologies such as TextRank, LSA, Luhn algorithms as well as large language model (LLM) to generate summaries as well as mindmaps.</p>
-        <p style="text-align: center;">The summarization process can take some time depending on the size of the text corpus and the complexity of the content.</p>
-        ''')
-    with gr.Row():
-        with gr.Column():
-            text_corpus = gr.TextArea(label="Text Corpus", placeholder="Paste the text corpus here", lines=5)
-            with gr.Row():
-                clear_btn = gr.Button(value="Clear", variant='stop')
-                summarize_btn = gr.Button(value="Summarize", variant='primary')
-        raw_data = gr.TextArea(label="Raw Data", placeholder="The generated raw data will be displayed here", lines=7, interactive=False, show_copy_button=True)
-    with gr.Row():
-        summary = gr.TextArea(label="Summary", placeholder="The generated summary will be displayed here", lines=7, interactive=False, show_copy_button=True)
-        mindmap = gr.TextArea(label="Mindmap", placeholder="The generated mindmap will be displayed here", lines=7, interactive=False, show_copy_button=True)
-
-    summarize_btn.click(
-        rexplore_summarizer,
-        inputs=[text_corpus],
-        outputs=[raw_data, summary, mindmap],
-        concurrency_limit=1,
-        scroll_to_output=True,
-        show_api=True,
-        api_name="rexplore_summarizer",
-        show_progress="full",
-    )
-    clear_btn.click(clear_everything, inputs=[text_corpus, raw_data, summary, mindmap], outputs=[text_corpus, raw_data, summary, mindmap], show_api=False)
-
-app.queue(default_concurrency_limit=1).launch(show_api=True)
+import gradio as gr
+from main import main
+import nltk
+
+def rexplore_summarizer(corpus):
+    response = main(corpus)
+    return response, response['summary'], response['mindmap']
+
+def clear_everything(text_corpus, raw_data, summary, mindmap):
+    return None, None, None, None
+
+theme = gr.themes.Soft(
+    primary_hue="purple",
+    secondary_hue="cyan",
+    neutral_hue="slate",
+    font=[
+        gr.themes.GoogleFont('Syne'), 
+        gr.themes.GoogleFont('Poppins'), 
+        gr.themes.GoogleFont('Poppins'), 
+        gr.themes.GoogleFont('Poppins')
+    ],
+)
+
+with gr.Blocks(theme=theme, title="ReXplore Summarizer", fill_height=True) as app:
+    gr.HTML(
+        value ='''
+        <h1 style="text-align: center;">ReXplore Summarizer <p style="text-align: center;">Designed and Developed by <a href='https://raannakasturi.eu.org' target="_blank" rel="nofollow noreferrer external">Nayan Kasturi</a></p> </h1>
+        <p style="text-align: center;">This app uses a hybrid approach to summarize PDF documents based on CPU as well as GPU.</p>
+        <p style="text-align: center;">The app uses traditional methodologies such as TextRank, LSA, Luhn algorithms as well as large language model (LLM) to generate summaries as well as mindmaps.</p>
+        <p style="text-align: center;">The summarization process can take some time depending on the size of the text corpus and the complexity of the content.</p>
+        ''')
+    with gr.Row():
+        with gr.Column():
+            text_corpus = gr.TextArea(label="Text Corpus", placeholder="Paste the text corpus here", lines=5)
+            with gr.Row():
+                clear_btn = gr.Button(value="Clear", variant='stop')
+                summarize_btn = gr.Button(value="Summarize", variant='primary')
+        raw_data = gr.TextArea(label="Raw Data", placeholder="The generated raw data will be displayed here", lines=7, interactive=False, show_copy_button=True)
+    with gr.Row():
+        summary = gr.TextArea(label="Summary", placeholder="The generated summary will be displayed here", lines=7, interactive=False, show_copy_button=True)
+        mindmap = gr.TextArea(label="Mindmap", placeholder="The generated mindmap will be displayed here", lines=7, interactive=False, show_copy_button=True)
+
+    summarize_btn.click(
+        rexplore_summarizer,
+        inputs=[text_corpus],
+        outputs=[raw_data, summary, mindmap],
+        concurrency_limit=1,
+        scroll_to_output=True,
+        show_api=True,
+        api_name="rexplore_summarizer",
+        show_progress="full",
+    )
+    clear_btn.click(clear_everything, inputs=[text_corpus, raw_data, summary, mindmap], outputs=[text_corpus, raw_data, summary, mindmap], show_api=False)
+
+nltk.download('punkt')
+nltk.download('punkt_tab')
+app.queue(default_concurrency_limit=1).launch(show_api=True)