Create app.py

app.py

@@ -0,0 +1,53 @@
+import gradio as gr
+imprt functions
+
+demo=gr.Blocks()
+
+with demo:    
+    gr.Image("logo_credit_agricole_CIB_0.jpg")
+    gr.Markdown("## Important Sentences Recognizer")
+    gr.Markdown("This project aims to retrieve critical sentences related with some important words in a document.")
+#gr.Interface(fn=reading_file, inputs=gr.File(),  outputs="text")
+    with gr.Box():
+        with gr.Row():
+            file=gr.File()
+            with gr.Column():
+                b1=gr.Button("Reading file",variant="primary")
+                t1=gr.Textbox(label="Result")
+        
+                b2=gr.Button("Filtering")
+                t2=gr.Textbox(label="Result")
+   
+    gr.Markdown("Now we run ctrl+f method.")
+    with gr.Box():
+        checkbox1=gr.CheckboxGroup(words, label="Select desired words")
+        b4=gr.Button("Run analysis")
+        t4=gr.Textbox(label="Result")
+
+    gr.Markdown("But first we need to choose how to parse the text.")
+    with gr.Box():
+        t=gr.Textbox(label="Write: sentences or paragraphs or lines or words", value="sentences")
+        #radio1=gr.Radio(["lines", "sentences", "paragraphs"], label="Parse by", value="sentences", interactive=True),
+        b3=gr.Button("Split text")
+        t3=gr.Textbox(label="Result")
+
+
+    gr.Markdown("Using previous the previous result, we run now the NLP analysis.")
+    with gr.Box():
+        
+        gr.Markdown("Now we will proceed with the analysis.")
+        dropdown1=gr.Dropdown(choices=["all-MiniLM-L6-v2","multi-qa-mpnet-base-dot-v1","msmarco-distilbert-base-v4"], label="Model")
+        slider1=gr.Slider(1,100,10, label="Top k", interactive=True, step=1)
+        dropdown2=gr.Dropdown(choices=["cosine similarity","dot product"], label="Similarity function")
+        b5=gr.Button("Run analysis", variant="primary")
+
+
+    gr.Markdown
+    df1= gr.Dataframe(row_count = (1, "dynamic"), col_count=(2, "fixed"), label="Important sentences", headers=["Expression", "Score"], overflow_row_behaviour="paginate")
+
+    b1.click(reading_file, inputs=file, outputs=t1)
+    b2.click(filtering, inputs=t1, outputs=t2)
+    b3.click(splitting, inputs=[t, t2], outputs=t3)
+    b4.click(ctrlf,[checkbox1, t2], t4)
+    b5.click(fn=total, inputs=[t2, t4,t, dropdown1, slider1, dropdown2], outputs=df1)           
+demo.launch(share=True)