Update app.py

app.py

@@ -1,4 +1,124 @@
-from transformers.tools.base import launch_gradio_demo
+import gradio as gr
+import warnings
+
+# Suppress warnings
+warnings.filterwarnings("ignore")
+
+# Import our NER Tool
 from ner_tool import NamedEntityRecognitionTool
 
-launch_gradio_demo(NamedEntityRecognitionTool)
+# Initialize the NER Tool
+ner_tool = NamedEntityRecognitionTool()
+
+# Function to analyze text using our tool
+def analyze_text(text, model, aggregation, min_score):
+    try:
+        result = ner_tool(
+            text=text,
+            model=model,
+            aggregation=aggregation,
+            min_score=float(min_score)
+        )
+        return result
+    except Exception as e:
+        return f"Error analyzing text: {str(e)}"
+
+# Sample texts for quick testing
+sample_texts = {
+    "Business News": """Apple Inc. CEO Tim Cook announced yesterday that the company will invest $5 billion
+in new AI research centers across the United States and Europe. The first center will 
+open in San Francisco by December 2025, followed by additional facilities in New York, 
+London, and Berlin. This initiative, called 'Project Horizon', aims to compete with 
+Microsoft and Google in the rapidly growing artificial intelligence market.""",
+    
+    "Political News": """The United Nations Security Council met in New York on Monday to discuss 
+the ongoing conflict in Eastern Europe. Representatives from the United States, 
+Russia, China, and the European Union presented their positions. Secretary-General 
+António Guterres urged all parties to return to diplomatic negotiations by July 15th.""",
+    
+    "Sports News": """Manchester United defeated Liverpool 3-2 in yesterday's Premier League match 
+at Old Trafford. Marcus Rashford scored two goals, while Mohamed Salah managed to score 
+for Liverpool. The victory puts Manchester United in second place in the league standings, 
+just behind Manchester City.""",
+    
+    "Academic Text": """According to researchers at Stanford University and MIT, the latest advancements 
+in quantum computing could revolutionize cryptography within the next decade. The paper, 
+published in the Journal of Computational Physics, suggests that Shor's algorithm implemented 
+on quantum systems with just 100 qubits could potentially break RSA encryption."""
+}
+
+# Create Gradio interface
+with gr.Blocks(title="Named Entity Recognition Tool") as demo:
+    gr.Markdown("# 🔍 Named Entity Recognition Tool")
+    gr.Markdown("Identify and analyze named entities in text using different models and display formats.")
+    
+    with gr.Row():
+        with gr.Column():
+            # Input section
+            text_input = gr.Textbox(
+                label="Text to Analyze", 
+                placeholder="Enter text to analyze for named entities...",
+                lines=10
+            )
+            
+            # Sample texts dropdown
+            sample_dropdown = gr.Dropdown(
+                choices=list(sample_texts.keys()),
+                label="Or Select a Sample Text"
+            )
+            
+            # Configuration options
+            with gr.Row():
+                with gr.Column():
+                    model_dropdown = gr.Dropdown(
+                        choices=list(ner_tool.available_models.keys()),
+                        value="dslim/bert-base-NER",
+                        label="NER Model"
+                    )
+                    
+                    aggregation_dropdown = gr.Dropdown(
+                        choices=["simple", "grouped", "detailed"],
+                        value="grouped",
+                        label="Display Format"
+                    )
+                    
+                with gr.Column():
+                    min_score_slider = gr.Slider(
+                        minimum=0.1, 
+                        maximum=1.0, 
+                        value=0.8, 
+                        step=0.05,
+                        label="Minimum Confidence Score"
+                    )
+                    
+            analyze_button = gr.Button("Analyze Text")
+        
+        with gr.Column():
+            # Output section
+            result_output = gr.Textbox(label="Analysis Results", lines=20)
+            
+            # Model info
+            gr.Markdown("### Available Models:")
+            model_info = gr.HTML(
+                "".join([f"<p><strong>{k}</strong>: {v}</p>" for k, v in ner_tool.available_models.items()])
+            )
+    
+    # Set up event handlers
+    def load_sample(sample_name):
+        return sample_texts.get(sample_name, "")
+    
+    sample_dropdown.change(
+        load_sample,
+        inputs=sample_dropdown,
+        outputs=text_input
+    )
+    
+    analyze_button.click(
+        analyze_text,
+        inputs=[text_input, model_dropdown, aggregation_dropdown, min_score_slider],
+        outputs=result_output
+    )
+
+# Launch the app
+if __name__ == "__main__":
+    demo.launch()