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README.md

@@ -4,10 +4,10 @@ emoji: 🎴
 colorFrom: blue
 colorTo: purple
 sdk: gradio
-sdk_version: 6.5.1
+sdk_version: 4.0.0
 app_file: app.py
 pinned: false
-python_version: '3.10'
+python_version: "3.10"
 ---
 
 # Flashcard2Audio

app.py

@@ -239,16 +239,26 @@ def estimate_time(num_cards, has_existing_media=False, mode="Smart Fill (Preserv
         mins = int((seconds % 3600) / 60)
         return f"~{hours}h {mins}m" if mins > 0 else f"~{hours}h"
 
-def process_dataframe(df_full, search_term, extract_root, mode, progress=gr.Progress()):
+def process_dataframe(df_full, search_term, extract_root, mode, search_in, selected_tag, progress=gr.Progress()):
     if df_full is None or len(df_full) == 0:
         return None, "No data"
     
-    # Filter logic
+    # Start with full dataframe
+    df = df_full.copy()
+    
+    # Apply tag filter first
+    if selected_tag and selected_tag != "All":
+        df = df[df['Tags'].str.contains(selected_tag, na=False, case=False)]
+    
+    # Apply text search filter
     if search_term:
-        mask = df_full.astype(str).apply(lambda x: x.str.contains(search_term, case=False)).any(axis=1)
-        df = df_full[mask]
-    else:
-        df = df_full
+        if search_in == "Question Only":
+            mask = df['Question'].str.contains(search_term, case=False, na=False)
+        elif search_in == "Answer Only":
+            mask = df['Answer'].str.contains(search_term, case=False, na=False)
+        else:  # Both
+            mask = df.astype(str).apply(lambda x: x.str.contains(search_term, case=False, na=False)).any(axis=1)
+        df = df[mask]
 
     if len(df) == 0:
         return None, "No matching cards"
@@ -311,7 +321,7 @@ def process_dataframe(df_full, search_term, extract_root, mode, progress=gr.Prog
                     q_res, a_res = future.result()
                     
                     # --- Field Construction (Corrected) ---
-                    q_original = str(df.iloc[idx]['Question'])
+                    q_original = str(df.loc[idx, 'Question'])
                     q_field = q_original
                     
                     # Update Question
@@ -326,7 +336,7 @@ def process_dataframe(df_full, search_term, extract_root, mode, progress=gr.Prog
                         q_field = q_field.strip() + f"<br>[sound:{os.path.basename(q_mp3)}]"
                     
                     # Update Answer
-                    a_original = str(df.iloc[idx]['Answer'])
+                    a_original = str(df.loc[idx, 'Answer'])
                     a_field = a_original
                     
                     if a_res and a_res != "SKIP":
@@ -502,8 +512,8 @@ with gr.Blocks(title="Pocket TTS Anki") as app:
                      outputs=[preview_table, eta_box])
 
     btn.click(process_dataframe, 
-              inputs=[full_df_state, search_box, extract_root_state, mode_radio], 
+              inputs=[full_df_state, search_box, extract_root_state, mode_radio, search_field, tag_dropdown], 
               outputs=[dl, result_lbl])
 
 if __name__ == "__main__":
-    app.queue(max_size=2).launch(server_name="0.0.0.0", server_port=7860)
+    app.queue(max_size=2).launch(server_name="0.0.0.0", server_port=7860, ssr_mode=False)