Back to minimal working version

app.py

@@ -9,10 +9,10 @@ from sentence_transformers import SentenceTransformer
 model = SentenceTransformer('all-MiniLM-L6-v2')
 
 # Function to compute document embeddings and apply PCA
-def compute_pca(*inputs):
-    # Separate identifiers and texts
-    identifiers = inputs[::2]
-    texts = inputs[1::2]
+def compute_pca(id1, text1, id2, text2, id3, text3, id4, text4):
+    # Collect identifiers and texts into lists
+    identifiers = [id1, id2, id3, id4]
+    texts = [text1, text2, text3, text4]
     
     # Filter out any empty inputs
     valid_entries = [(id, text) for id, text in zip(identifiers, texts) if id and text]
@@ -40,46 +40,23 @@ def compute_pca(*inputs):
     fig = px.scatter(result_df, x='PC1', y='PC2', text='Identifier', title='PCA of Text Embeddings')
     return fig
 
-# Function to dynamically add new input pairs
-def add_new_input_boxes(identifiers, texts, n_boxes):
-    # Add new identifier and text input pairs
-    for i in range(n_boxes):
-        index = len(identifiers) + 1
-        identifiers.append(gr.Textbox(label=f"Identifier {index}", placeholder=f"Identifier {index}"))
-        texts.append(gr.Textbox(label=f"Text {index}", placeholder=f"Text {index}"))
-    return identifiers + texts
-
 # Gradio interface
 def text_editor_app():
     with gr.Blocks() as demo:
-        # Lists to hold identifier and text boxes separately
-        identifier_boxes = []
-        text_boxes = []
-        
-        # Function to initialize default input boxes
-        def initialize_default_boxes():
-            initial_values = [("Animal 1", "Cats"), ("Animal 2", "Dogs"), 
-                              ("Vehicle 1", "Planes"), ("Vehicle 2", "Boats")]
-            for index, (identifier, text) in enumerate(initial_values, 1):
-                identifier_boxes.append(gr.Textbox(label=f"Identifier {index}", value="", placeholder=identifier))
-                text_boxes.append(gr.Textbox(label=f"Text {index}", value=text, placeholder=f"Text {index}"))
-        
-        # Initialize with default boxes
-        initialize_default_boxes()
+        # Input boxes for four identifier-text pairs
+        with gr.Row():
+            id1 = gr.Textbox(label="Identifier 1")
+            text1 = gr.Textbox(label="Text 1")
+        with gr.Row():
+            id2 = gr.Textbox(label="Identifier 2")
+            text2 = gr.Textbox(label="Text 2")
+        with gr.Row():
+            id3 = gr.Textbox(label="Identifier 3")
+            text3 = gr.Textbox(label="Text 3")
+        with gr.Row():
+            id4 = gr.Textbox(label="Identifier 4")
+            text4 = gr.Textbox(label="Text 4")
         
-        # Counter to keep track of the number of components rendered so far
-        counter = 0
-        
-        # Column to hold all input boxes
-        with gr.Column() as input_container:
-            for identifier, text in zip(identifier_boxes, text_boxes):
-                identifier.render()
-                text.render()
-                counter += 1
-
-        # Button to add more text input pairs
-        add_button = gr.Button("Add Another Text")
-
         # Button to run the analysis
         analyze_button = gr.Button("Run Analysis")
 
@@ -87,23 +64,9 @@ def text_editor_app():
         output_plot = gr.Plot(label="PCA Visualization")
 
         # Run analysis when the button is clicked
-        analyze_button.click(fn=compute_pca, inputs=identifier_boxes + text_boxes, outputs=output_plot)
-
-        # Add new input boxes dynamically
-        def update_input_container():
-            # Create new input boxes and add them to the container
-            new_boxes = add_new_input_boxes(identifier_boxes, text_boxes, n_boxes=1)
-            return gr.Column(components=new_boxes)
-        
-        add_button.click(fn=update_input_container, inputs=[], outputs=input_container)
-
-        # Display the input fields and buttons
-        demo.append(input_container)
-        demo.append(add_button)
-        demo.append(analyze_button)
-        demo.append(output_plot)
-
+        analyze_button.click(fn=compute_pca, inputs=[id1, text1, id2, text2, id3, text3, id4, text4], outputs=output_plot)
+    
     return demo
 
 # Launch the app
-text_editor_app().launch()
+text_editor_app().launch()