Correcting title

app.py

@@ -51,16 +51,16 @@ def process_inputs(smiles: str, file_obj):
         df_out.to_csv("embeddings.csv", index=False)
         return json.dumps(vec), gr.update(value="embeddings.csv", visible=True)
     except Exception as e:
-        return f"Error generating embedding: {e}", gr.update(visible=False)
+        return f"Error extracting embedding: {e}", gr.update(visible=False)
 
 # 4) Build the Gradio Blocks interface
 with gr.Blocks() as demo:
     gr.Markdown(
         """
-        # SMI-TED Embedding Generator  
+        # SMI-TED-Embeddings-Extraction
         **Single mode:** paste a SMILES string in the left box.  
         **Batch mode:** upload a CSV file where each row has a SMILES in the first column.  
-        In both cases, an `embeddings.csv` file will be generated for download, with the first column as SMILES and the embedding values in the following columns.
+        In both cases, an `embeddings.csv` file will be extracted for download, with the first column as SMILES and the embedding values in the following columns.
         """
     )
 
@@ -68,7 +68,7 @@ with gr.Blocks() as demo:
         smiles_in = gr.Textbox(label="SMILES (single mode)", placeholder="e.g. CCO")
         file_in   = gr.File(label="SMILES CSV (batch mode)", file_types=[".csv"])
 
-    generate_btn = gr.Button("Generate Embeddings")
+    generate_btn = gr.Button("Extract Embeddings")
 
     with gr.Row():
         output_msg   = gr.Textbox(label="Message / Embedding (JSON)", interactive=False, lines=2)