corrections save annotations

annotations_export.csv

@@ -0,0 +1 @@
+user_id,gender,audio_file,score

app.py

@@ -1,3 +1,4 @@
+from huggingface_hub import HfApi
 import gradio as gr
 import pandas as pd
 import os
@@ -9,6 +10,7 @@ from huggingface_hub import login
 # CONFIGURATION
 # ============================
 
+LOCAL_CSV = "annotations.csv"
 AUDIO_FOLDER = "audio_files"
 audio_files = sorted(os.listdir(AUDIO_FOLDER))
 
@@ -18,8 +20,8 @@ ADMIN_PASSWORD_HASH = "eb32da077dfaf326cd6f73e0716b628da6427aa318a2d0b9fafa9ef31
 # HF DATASET CONFIGURATION
 # ============================
 
-HF_DATASET_NAME = "MeysamSh/Annotate_Samples"  # replace with your HF dataset
-HF_TOKEN = os.environ.get("HF_TOKEN")  # store your token as a secret in Spaces
+HF_DATASET_NAME = "PaulineDV/TTS_annotations_data"  # replace with your HF dataset
+HF_TOKEN = os.environ.get("MyJulySecretToken")  # store your token as a secret in Spaces
 login(HF_TOKEN)
 
 # ============================
@@ -39,6 +41,31 @@ def load_hf_dataset():
 
 def submit_annotation_hf(user_id, gender, score, audio_file):
     """Append annotation to HF Dataset."""
+    row = pd.DataFrame([{
+        "user_id": user_id,
+        "gender": gender,
+        "audio_file": audio_file,
+        "score": score
+    }])
+    
+    if os.path.exists(LOCAL_CSV):
+        df = pd.read_csv(LOCAL_CSV)
+        df = pd.concat([df, row], ignore_index = True)
+    else:
+        df = row
+
+    df.to_csv(LOCAL_CSV, index = False)
+
+    api = HfApi()
+
+    api.upload_file(
+        path_or_fileobj=LOCAL_CSV,
+        path_in_repo="annotations.csv",
+        repo_id="HF_DATASET_NAME",
+        repo_type="dataset"
+    )
+
+    """
     ds = load_hf_dataset()
     new_row = pd.DataFrame([{
         "user_id": user_id,
@@ -49,6 +76,7 @@ def submit_annotation_hf(user_id, gender, score, audio_file):
     ds_new = Dataset.from_pandas(new_row)
     ds_combined = concatenate_datasets([ds, ds_new])
     ds_combined.push_to_hub(HF_DATASET_NAME)
+    """
 
 def load_next_audio(state):
     if state is None: