Update app.py

app.py

@@ -61,8 +61,6 @@ def fetch_and_display_content(url):
 
     # Add detected language to metadata
     metadata["Detected Language"] = detected_lang.upper()
-    #return cleaned_text, detected_lang, gr.update(visible=True), gr.update(visible=True)
-    #return cleaned_text, metadata, gr.update(visible=True), gr.update(visible=True), gr.update(visible=True)
     return cleaned_text, metadata, detected_lang, gr.update(visible=True), gr.update(visible=True), gr.update(visible=True), gr.update(visible=True)
 
 ### 2️⃣ Cleaning Function
@@ -168,7 +166,9 @@ def extract_entities_with_stanza(text, chunk_size=1000):
         doc = nlp(chunk)
         for ent in doc.ents:
             entities.append({"text": ent.text, "type": ent.type})
-
+			
+    formatted_entities = "\n".join([f"{i+1}: {ent['text']} --> {ent['type']}" for i, ent in enumerate(entities)])
+    return formatted_entities
     return entities
 
 ### 4️⃣ TTS Functionality (KokoroTTS)
@@ -252,11 +252,11 @@ with gr.Blocks() as demo:
     url_input = gr.Textbox(label="Enter URL", placeholder="https://example.com/article")
     
     voice_selection = gr.Dropdown(AVAILABLE_VOICES, label="Select Voice", value="af_bella")
-
-    process_text_button = gr.Button("Fetch Text & Detect Language")
-    process_summary_button = gr.Button("Summarize Text", visible=False)
-    process_audio_button = gr.Button("Generate Audio", visible=False)
-    process_ner_button = gr.Button("Extract Entities", visible=True)  # ✅ New button for NER
+    with gr.Row():
+        process_text_button = gr.Button("Fetch Text & Detect Language",scale = 1)
+        process_summary_button = gr.Button("Summarize Text", visible=False,scale = 1)
+        process_audio_button = gr.Button("Generate Audio", visible=False,scale = 1)
+        process_ner_button = gr.Button("Extract Entities", visible=False,scale = 1)  # ✅ New button for NER
 
     # Layout: Two adjacent columns (Text and Metadata)
     with gr.Row():
@@ -264,19 +264,17 @@ with gr.Blocks() as demo:
         metadata_output = gr.JSON(label="Article Metadata", visible=False)  # Displays metadata
 
     
-    #extracted_text = gr.Markdown(label="Extracted Content")
-   
     detected_lang = gr.Textbox(label="Detected Language", visible=False)
     summary_output = gr.Textbox(label="Summary", visible=True, interactive=False)
     full_audio_output = gr.Audio(label="Generated Audio", visible=True)
-    ner_output = gr.JSON(label="Extracted Entities", visible=True)  # ✅ New output for NER
+    ner_output = gr.Textbox(label="Extracted Entities", visible=False, interactive=False)  # ✅ New output for NER
 
     # Step 1: Fetch Text & Detect Language First
     process_text_button.click(
         fetch_and_display_content, 
         inputs=[url_input], 
         
-        outputs=[extracted_text, metadata_output, detected_lang, process_summary_button, process_audio_button, extracted_text, metadata_output]
+        outputs=[extracted_text, metadata_output, detected_lang, process_summary_button, process_audio_button,process_ner_button, extracted_text, metadata_output]
     )
     
     process_summary_button.click(hierarchical_summarization, inputs=[extracted_text], outputs=[summary_output])
@@ -284,9 +282,6 @@ with gr.Blocks() as demo:
     # Step 2: Generate Audio After Text & Language Are Displayed
     process_audio_button.click(
         generate_audio_kokoro, 
-        #inputs=[extracted_text, detected_language], 
-        #inputs=[extracted_text, metadata_output, voice_selection],
-        #inputs=[extracted_text, metadata_output["Detected Language"], voice_selection], 
         inputs=[extracted_text, detected_lang, voice_selection],
         outputs=[full_audio_output]
     )
@@ -297,6 +292,4 @@ with gr.Blocks() as demo:
         outputs=[ner_output]
     )
 
-    #process_button.click(process_url, inputs=[url_input], outputs=[extracted_text, detected_language, full_audio_output])
-
 demo.launch()