Add application file

app.py

@@ -271,142 +271,7 @@ def generate_results_dataframe(results):
     dfs["statistics"] = pd.DataFrame(data, columns=["Metric", "Value"])
     
     return dfs
-
-with gr.Blocks(title="Text Similarity Detector") as demo:
-    gr.Markdown("# 🔍 Text Similarity Detector with Image Extraction")
-    gr.Markdown("""
-    This tool analyzes the similarity between texts extracted from an image and reference key texts.
-    It can identify:
-    - Direct similar texts
-    - Key text fragments within the texts
-    - Text combinations that match key texts
-    """)
-
-    with gr.Tabs() as tabs:
-        with gr.TabItem("Image Analysis"):
-            with gr.Row():
-                with gr.Column(scale=1):  # Column for inputs on the left
-                    input_image = gr.Image(label="Upload an image to extract text", type="pil", height=600)
-                    key_texts_image = gr.Textbox(
-                            label="Key Texts for Comparison",
-                            placeholder="Paste your key texts here (one per line)",
-                            lines=5
-                        )
-                    # with gr.Row():
-                    #     key_texts_image = gr.Textbox(
-                    #         label="Key Texts for Comparison",
-                    #         placeholder="Paste your key texts here (one per line)",
-                    #         lines=5
-                    #     )
-
-                    #     min_similarity_per_key_image = gr.Textbox(
-                    #         label="Minimum Similarity for Each Key Text (%)",
-                    #         placeholder="Enter one value per line, matching the key texts",
-                    #         lines=5
-                    #     )
-
-                    with gr.Row():
-                        similarity_threshold_image = gr.Slider(
-                            label="Similarity Threshold (%)",
-                            minimum=50,
-                            maximum=100,
-                            value=70,
-                            step=1
-                        )
-                        fragment_threshold_image = gr.Slider(
-                            label="Fragment Similarity Threshold (%)",
-                            minimum=50,
-                            maximum=100,
-                            value=70,
-                            step=1
-                        )
-
-                    analyze_image_btn = gr.Button("Analyze Image", variant="primary")
-                
-                with gr.Column(scale=1):  # Column for outputs on the right
-                    gpu_available = gr.Checkbox(label="Used GPU")
-                    extracted_texts = gr.Textbox(label="Extracted Texts from the Image", lines=5)
-                    html_output = gr.HTML(label="Similarity Report")
-                    with gr.Tabs():
-                        with gr.TabItem("Statistics"):
-                            statistics_output = gr.Dataframe(label="Statistics")
-                        with gr.TabItem("Direct Similarity"):
-                            similar_texts_output = gr.Dataframe(label="Direct Similar Texts")
-                        with gr.TabItem("Fragments"):
-                            fragments_output = gr.Dataframe(label="Texts with Fragments")
-                        with gr.TabItem("Combined"):
-                            combined_output = gr.Dataframe(label="Combined Texts")
-
-        with gr.TabItem("Manual Analysis"):
-            with gr.Row():
-                with gr.Column(scale=1):  # Column for inputs on the left
-                    input_texts = gr.Textbox(
-                        label="List of Texts for Analysis",
-                        placeholder="Paste your list of texts here (one per line)",
-                        lines=10
-                    )
-                    key_texts_input = gr.Textbox(
-                            label="Key Texts for Comparison",
-                            placeholder="Paste your key texts here (one per line)",
-                            lines=5
-                        )
-                    # with gr.Row():
-                    #     key_texts_input = gr.Textbox(
-                    #         label="Key Texts for Comparison",
-                    #         placeholder="Paste your key texts here (one per line)",
-                    #         lines=5
-                    #     )
-
-                    #     min_similarity_per_key_input = gr.Textbox(
-                    #         label="Minimum Similarity for Each Key Text (%)",
-                    #         placeholder="Enter one value per line, matching the key texts",
-                    #         lines=5
-                    #     )
-                                    
-                    with gr.Row():
-                        similarity_threshold = gr.Slider(
-                            label="Similarity Threshold (%)",
-                            minimum=50,
-                            maximum=100,
-                            value=70,
-                            step=1
-                        )
-                        fragment_threshold = gr.Slider(
-                            label="Fragment Similarity Threshold (%)",
-                            minimum=50,
-                            maximum=100,
-                            value=70,
-                            step=1
-                        )
-
-                    analyze_btn = gr.Button("Analyze Image", variant="primary")
-
-                with gr.Column(scale=1):  # Column for outputs on the right
-                    html_output_manual = gr.HTML(label="Manual Similarity Report")
-                    with gr.Tabs():
-                        with gr.TabItem("Statistics"):
-                            statistics_output_manual = gr.Dataframe(label="Statistics")
-                        with gr.TabItem("Direct Similarity"):
-                            similar_texts_output_manual = gr.Dataframe(label="Direct Similar Texts")
-                        with gr.TabItem("Fragments"):
-                            fragments_output_manual = gr.Dataframe(label="Texts with Fragments")
-                        with gr.TabItem("Combined"):
-                            combined_output_manual = gr.Dataframe(label="Combined Texts")
-
-    # Connect the image processing function to the button
-    analyze_image_btn.click(
-        process_image,
-        inputs=[input_image, key_texts_image, similarity_threshold_image, fragment_threshold_image],
-        outputs=[html_output, statistics_output, similar_texts_output, fragments_output, combined_output, extracted_texts, gpu_available]
-    )
-
-    # Connect the manual text processing function to the button
-    analyze_btn.click(
-        process_manual_input,
-        inputs=[input_texts, key_texts_input, similarity_threshold, fragment_threshold],
-        outputs=[html_output_manual, statistics_output_manual, similar_texts_output_manual, fragments_output_manual, combined_output_manual]
-    )
-
+    
 #app = gr.mount_gradio_app(app, demo, path="/")
 
 @app.get("/api")