added the paiwan model and db

app.py

@@ -1,35 +1,207 @@
+import gradio as gr
+import torch
+import librosa
+from transformers import Wav2Vec2Processor, AutoModelForCTC
+import zipfile
 import os
-import json
 import firebase_admin
-from firebase_admin import credentials, firestore
-import gradio as gr
-
-# Fetch Firebase credentials from Hugging Face Secrets (environment variable)
-firebase_creds = os.environ.get('firebase_creds')
-
-if not firebase_creds:
-    raise ValueError("❌ ERROR: The environment variable 'firebase_creds' is NOT set. Please set it in Hugging Face Secrets.")
-
-# Convert the JSON string back into a dictionary
-firebase_config = json.loads(firebase_creds)
+from firebase_admin import credentials, firestore, storage
+from datetime import datetime, timedelta
+import json
+import tempfile
+import uuid
 
-# Initialize Firebase with credentials
+# LOCAL INITIALIZATION - ONLY USE ON YOUR OWN DEVICE 
+'''
+os.chdir(os.path.dirname(os.path.abspath(__file__)))
+cred = credentials.Certificate("serviceAccountKey.json")
+'''
+# Deployed Initialization
+firebase_config = json.loads(os.environ.get('firebase_creds'))
 cred = credentials.Certificate(firebase_config)
-firebase_admin.initialize_app(cred)
+
+firebase_admin.initialize_app(cred, {
+    "storageBucket": "amis-asr-corrections-dem-8cf3d.firebasestorage.app"
+})
 db = firestore.client()
+bucket = storage.bucket()
 
-print("✅ Firebase initialized successfully!")
+# Load the ASR model and processor
+MODEL_NAME = "eleferrand/XLSR_paiwan"
+processor = Wav2Vec2Processor.from_pretrained(MODEL_NAME)
+model = AutoModelForCTC.from_pretrained(MODEL_NAME)
 
-# Gradio app setup
 def transcribe(audio_file):
-    # Replace with actual transcription logic
-    return "Transcription here"
+    try:
+        audio, rate = librosa.load(audio_file, sr=16000)
+        input_values = processor(audio, sampling_rate=16000, return_tensors="pt").input_values
+
+        with torch.no_grad():
+            logits = model(input_values).logits
+        predicted_ids = torch.argmax(logits, dim=-1)
+        transcription = processor.batch_decode(predicted_ids)[0]
+        return transcription
+    except Exception as e:
+        return f"處理文件錯誤: {e}"
+
+def transcribe_both(audio_file):
+    start_time = datetime.now()
+    transcription = transcribe(audio_file)
+    return transcription, transcription
+
+def store_correction(original_transcription, corrected_transcription, audio_file, age, native_speaker):
+    try:
+        audio_metadata = {}
+        audio_file_url = None
+        
+        # If an audio file is provided, upload it to Firebase Storage
+        if audio_file and os.path.exists(audio_file):
+            audio, sr = librosa.load(audio_file, sr=44100)
+            duration = librosa.get_duration(y=audio, sr=sr)
+            file_size = os.path.getsize(audio_file)
+            audio_metadata = {'duration': duration, 'file_size': file_size}
+            
+            # Generate a unique identifier for the audio file
+            unique_id = str(uuid.uuid4())
+            destination_path = f"audio/paiwan/{unique_id}.wav"
+            
+            # Create a blob and upload the file
+            blob = bucket.blob(destination_path)
+            blob.upload_from_filename(audio_file)
+            
+            # Generate a signed download URL valid for 1 hour (adjust expiration as needed)
+            audio_file_url = blob.generate_signed_url(expiration=timedelta(hours=1))
+        
+        combined_data = {
+            'transcription_info': {
+                'original_text': original_transcription,
+                'corrected_text': corrected_transcription,
+                'language': "paiwan",
+            },
+            'audio_data': {
+                'audio_metadata': audio_metadata,
+                'audio_file_url': audio_file_url,
+            },
+            'user_info': {
+                'native_paiwan_speaker': native_speaker,
+                'age': age
+            },
+            'timestamp': datetime.now().isoformat(),
+            'model_name': "eleferrand/XLSR_paiwan"
+        }
+        # Save data to a collection for that language 
+        db.collection('paiwan_transcriptions').add(combined_data)
+        return "校正保存成功! (Correction saved successfully!)"
+    except Exception as e:
+        return f"保存失败: {e} (Error saving correction: {e})"
+
+def prepare_download(audio_file, original_transcription, corrected_transcription):
+    if audio_file is None:
+        return None
+
+    tmp_zip = tempfile.NamedTemporaryFile(delete=False, suffix=".zip")
+    tmp_zip.close()
+    with zipfile.ZipFile(tmp_zip.name, "w") as zf:
+        if os.path.exists(audio_file):
+            zf.write(audio_file, arcname="audio.wav")
+        
+        orig_txt = "original_transcription.txt"
+        with open(orig_txt, "w", encoding="utf-8") as f:
+            f.write(original_transcription)
+        zf.write(orig_txt, arcname="original_transcription.txt")
+        os.remove(orig_txt)
 
-# Define Gradio Interface
+        corr_txt = "corrected_transcription.txt"
+        with open(corr_txt, "w", encoding="utf-8") as f:
+            f.write(corrected_transcription)
+        zf.write(corr_txt, arcname="corrected_transcription.txt")
+        os.remove(corr_txt)
+    return tmp_zip.name
+
+def toggle_language(switch):
+    """Switch UI text between English and Traditional Chinese"""
+    if switch:
+        return (
+            "阿美語轉錄與修正系統", 
+            "步驟 1：音訊上傳與轉錄",
+            "步驟 2：審閱與編輯轉錄",
+            "步驟 3：使用者資訊",
+            "步驟 4：儲存與下載",
+            "音訊輸入", "轉錄音訊",
+            "原始轉錄", "更正轉錄",
+            "年齡", "以阿美語為母語？",
+            "儲存更正", "儲存狀態",
+            "下載 ZIP 檔案"
+        )
+    else:
+        return (
+            "Amis ASR Transcription & Correction System", 
+            "Step 1: Audio Upload & Transcription",
+            "Step 2: Review & Edit Transcription",
+            "Step 3: User Information",
+            "Step 4: Save & Download",
+            "Audio Input", "Transcribe Audio",
+            "Original Transcription", "Corrected Transcription",
+            "Age", "Native Paiwan Speaker?",
+            "Save Correction", "Save Status",
+            "Download ZIP File"
+        )
+
+# Interface
 with gr.Blocks() as demo:
-    audio_input = gr.Audio(source="upload", type="filepath", label="Upload Audio")
-    output = gr.Textbox(label="Transcription")
+    lang_switch = gr.Checkbox(label="切換到繁體中文 (Switch to Traditional Chinese)")
+    
+    title = gr.Markdown("Paiwan ASR Transcription & Correction System")
+    step1 = gr.Markdown("Step 1: Audio Upload & Transcription")
+    
+    with gr.Row():
+        audio_input = gr.Audio(sources=["upload", "microphone"], type="filepath", label="Audio Input")
+    
+    step2 = gr.Markdown("Step 2: Review & Edit Transcription")
+    with gr.Row():
+        transcribe_button = gr.Button("Transcribe Audio")
+    
+    original_text = gr.Textbox(label="Original Transcription", interactive=False, lines=5)
+    corrected_text = gr.Textbox(label="Corrected Transcription", interactive=True, lines=5)
+
+    step3 = gr.Markdown("Step 3: User Information")
+    with gr.Row():
+        age_input = gr.Slider(minimum=0, maximum=100, step=1, label="Age", value=25)
+        native_speaker_input = gr.Checkbox(label="Native Paiwan Speaker?", value=True)
+
+    step4 = gr.Markdown("Step 4: Save & Download")
+    with gr.Row():
+        save_button = gr.Button("Save Correction")
+        save_status = gr.Textbox(label="Save Status", interactive=False)
     
-    audio_input.change(transcribe, inputs=audio_input, outputs=output)
+    with gr.Row():
+        download_button = gr.Button("Download ZIP File")
+        download_output = gr.File()
+
+    lang_switch.change(
+        toggle_language, 
+        inputs=lang_switch, 
+        outputs=[title, step1, step2, step3, step4, audio_input, transcribe_button,
+                 original_text, corrected_text, age_input, native_speaker_input,
+                 save_button, save_status, download_button]
+    )
+
+    transcribe_button.click(
+        transcribe_both, 
+        inputs=audio_input, 
+        outputs=[original_text, corrected_text]
+    )
+
+    save_button.click(
+        store_correction, 
+        inputs=[original_text, corrected_text, audio_input, age_input, native_speaker_input], 
+        outputs=save_status
+    )
+
+    download_button.click(
+        prepare_download, 
+        inputs=[audio_input, original_text, corrected_text], 
+        outputs=download_output
+    )
 
-demo.launch()
+demo.launch()