Update app.py

app.py

@@ -9,15 +9,18 @@ from sentence_transformers import SentenceTransformer
 model = SentenceTransformer('all-MiniLM-L6-v2')
 
 # Function to compute document embeddings and apply PCA
-def compute_pca(dataframe):
-    # Drop empty rows and extract identifiers and texts
-    dataframe = dataframe.dropna()
-    identifiers = dataframe['Identifier'].tolist()
-    texts = dataframe['Text'].tolist()
+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]
     
-    # Check if there's data to process
-    if len(texts) == 0:
-        return gr.Plot.update(value=None, label="No data to process. Please fill in the table.")
+    # Filter out any empty inputs
+    valid_entries = [(id, text) for id, text in zip(identifiers, texts) if id and text]
+    if not valid_entries:
+        return gr.Plot.update(value=None, label="No data to process. Please fill in the boxes.")
+    
+    # Unzip identifiers and texts
+    identifiers, texts = zip(*valid_entries)
     
     # Generate embeddings
     embeddings = model.encode(texts)
@@ -40,30 +43,28 @@ def compute_pca(dataframe):
 # Gradio interface
 def text_editor_app():
     with gr.Blocks() as demo:
-        # Editable DataFrame with 4 initial rows
-        data_table = gr.Dataframe(headers=["Identifier", "Text"], value=[["", ""] for _ in range(4)], 
-                                  interactive=True, wrap=True, label="Enter Identifiers and Texts")
-
+        # 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")
+        
         # Button to run the analysis
         analyze_button = gr.Button("Run Analysis")
 
         # Output plot
         output_plot = gr.Plot(label="PCA Visualization")
 
-        # Add rows dynamically as the table is filled
-        def add_rows(data):
-            # Check if all current rows are filled
-            if data["Identifier"].isnull().sum() == 0 and data["Text"].isnull().sum() == 0:
-                # Add an empty row
-                new_row = pd.DataFrame({"Identifier": [""], "Text": [""]})
-                return pd.concat([data, new_row], ignore_index=True)
-            return data
-
-        # Update table as rows are filled
-        data_table.change(fn=add_rows, inputs=data_table, outputs=data_table)
-
         # Run analysis when the button is clicked
-        analyze_button.click(fn=compute_pca, inputs=data_table, outputs=output_plot)
+        analyze_button.click(fn=compute_pca, inputs=[id1, text1, id2, text2, id3, text3, id4, text4], outputs=output_plot)
     
     return demo