import gradio as gr
from transformers import pipeline
import soundfile as sf
import librosa
import numpy as np
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware

# --- تعريف النموذج ودالة المعالجة (لا تغيير هنا) ---
MODEL_ID = "svu22/arabic_model"

# --- تم حذف قسم الأمثلة بالكامل لأنه كان يسبب خطأ في بدء التشغيل ---

try:
    pipe = pipeline("automatic-speech-recognition", model=MODEL_ID)
    print("Pipeline loaded successfully!")
except Exception as e:
    print(f"Error loading pipeline: {e}")
    pipe = None

def transcribe_audio(audio_input):
    if pipe is None:
        return "Error: Model pipeline could not be loaded. Please check the logs."
    if audio_input is None:
        return "Please upload an audio file."

    filepath = audio_input
    try:
        audio_array, sampling_rate = sf.read(filepath)
        if audio_array.ndim > 1:
            audio_array = audio_array.mean(axis=1)
        if sampling_rate != 16000:
            audio_array = librosa.resample(y=audio_array, orig_sr=sampling_rate, target_sr=16000)
        
        result = pipe(audio_array.copy())
        transcription = result["text"]
        return transcription
    except Exception as e:
        print(f"An error occurred during transcription: {e}")
        return f"An error occurred: {str(e)}"

# =============================================================================
# [لا تغيير هنا] - بناء الواجهة باستخدام gr.Blocks
# =============================================================================
with gr.Blocks() as interface:
    gr.Markdown("## Automatic Speech Recognition for Arabic")
    gr.Markdown("This is a demo for the fine-tuned Wav2Vec2 model for Arabic ASR. Upload an audio file or record your voice to see the transcription.")
    
    with gr.Row():
        audio_input = gr.Audio(sources=["upload", "microphone"], type="filepath", label="Audio File")
        transcribed_text = gr.Textbox(label="Result", interactive=False)

    submit_btn = gr.Button("Transcribe")

    submit_btn.click(
        fn=transcribe_audio,
        inputs=audio_input,
        outputs=transcribed_text,
        api_name="predict"
    )
    
    # --- تم حذف gr.Examples من هنا أيضاً ---

# =============================================================================
# [لا تغيير هنا] - إضافة إعدادات CORS باستخدام FastAPI
# =============================================================================
app = FastAPI()

app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

app = gr.mount_gradio_app(app, interface, path="/")