Update app.py

app.py

@@ -30,18 +30,22 @@ DATA_FILENAME = "ASRLive.csv"
 DATA_FILE = os.path.join("data", DATA_FILENAME)
 HF_TOKEN = os.environ.get("HF_TOKEN")
 
-try:
-    hf_hub_download(
-        repo_id=DATASET_REPO_ID,
-        filename=DATA_FILENAME,
-        cache_dir=DATA_DIRNAME,
-        force_filename=DATA_FILENAME
+PersistToDataset = False
+#PersistToDataset = True  # uncomment to save inference output to ASRLive.csv dataset
+
+if PersistToDataset:
+    try:
+        hf_hub_download(
+            repo_id=DATASET_REPO_ID,
+            filename=DATA_FILENAME,
+            cache_dir=DATA_DIRNAME,
+            force_filename=DATA_FILENAME
+        )
+    except:
+        print("file not found")
+    repo = Repository(
+        local_dir="data", clone_from=DATASET_REPO_URL, use_auth_token=HF_TOKEN
     )
-except:
-    print("file not found")
-repo = Repository(
-    local_dir="data", clone_from=DATASET_REPO_URL, use_auth_token=HF_TOKEN
-)
            
 def store_message(name: str, message: str):
     if name and message:
@@ -106,8 +110,12 @@ def transcribe(audio, state = ""):
         if type(transcriptions) == tuple and len(transcriptions) == 2:
             transcriptions = transcriptions[0]
         transcriptions = transcriptions[0]
-    ret = store_message(transcriptions, state) # Save to dataset - uncomment to store into a dataset - hint you will need your HF_TOKEN
-    state = state + transcriptions + " " + ret
+        
+    if PersistToDataset:
+        ret = store_message(transcriptions, state) # Save to dataset - uncomment to store into a dataset - hint you will need your HF_TOKEN
+        state = state + transcriptions + " " + ret
+    else:
+        state = state + transcriptions
     return state, state
 
 gr.Interface(