import os
import requests
import json
import time
import subprocess
import gradio as gr
import uuid
from dotenv import load_dotenv

# Load environment variables
load_dotenv()

# API Keys
A_KEY = os.getenv("A_KEY")
B_KEY = os.getenv("B_KEY")

# URLs
API_URL = os.getenv("API_URL")
UPLOAD_URL = os.getenv("UPLOAD_URL")

def get_voices():
    url = "https://api.elevenlabs.io/v1/voices"
    headers = {
        "Accept": "application/json",
        "xi-api-key": A_KEY
    }
    
    response = requests.get(url, headers=headers)
    if response.status_code != 200:
        return []
    return [(voice['name'], voice['voice_id']) for voice in response.json().get('voices', [])]

def get_video_models():
    return [f for f in os.listdir("models") if f.endswith((".mp4", ".avi", ".mov"))]

def text_to_speech(voice_id, text, session_id):
    url = f"https://api.elevenlabs.io/v1/text-to-speech/{voice_id}"
    
    headers = {
        "Accept": "audio/mpeg",
        "Content-Type": "application/json",
        "xi-api-key": A_KEY
    }
    
    data = {
        "text": text,
        "model_id": "eleven_turbo_v2_5",
        "voice_settings": {
            "stability": 0.5,
            "similarity_boost": 0.5
        }
    }
    
    response = requests.post(url, json=data, headers=headers)
    if response.status_code != 200:
        return None
    
    # Save temporary audio file with session ID
    audio_file_path = f'temp_voice_{session_id}.mp3'
    with open(audio_file_path, 'wb') as audio_file:
        audio_file.write(response.content)
    return audio_file_path

def upload_file(file_path):
    with open(file_path, 'rb') as file:
        files = {'fileToUpload': (os.path.basename(file_path), file)}
        data = {'reqtype': 'fileupload'}
        response = requests.post(UPLOAD_URL, files=files, data=data)
    
    if response.status_code == 200:
        return response.text.strip()
    return None

def lipsync_api_call(video_url, audio_url):
    headers = {
        "Content-Type": "application/json",
        "x-api-key": B_KEY
    }
    
    data = {
        "audioUrl": audio_url,
        "videoUrl": video_url,
        "maxCredits": 1000,
        "model": "sync-1.6.0",
        "synergize": True,
        "pads": [0, 5, 0, 0],
        "synergizerStrength": 1
    }
    
    response = requests.post(API_URL, headers=headers, data=json.dumps(data))
    return response.json()

def check_job_status(job_id):
    headers = {"x-api-key": B_KEY}
    max_attempts = 30  # Limit the number of attempts
    
    for _ in range(max_attempts):
        response = requests.get(f"{API_URL}/{job_id}", headers=headers)
        data = response.json()
        
        if data["status"] == "COMPLETED":
            return data["videoUrl"]
        elif data["status"] == "FAILED":
            return None
        
        time.sleep(10)
    return None

def combine_audio_video(video_path, audio_path, output_path):
    cmd = [
        'ffmpeg', '-i', video_path, '-i', audio_path,
        '-map', '0:v', '-map', '1:a',
        '-c:v', 'copy', '-c:a', 'aac',
        '-shortest', '-y', output_path
    ]
    subprocess.run(cmd, check=True)

def process_video(voice, model, text, progress=gr.Progress()):
    session_id = str(uuid.uuid4())  # Generate a unique session ID
    progress(0, desc="Generating speech...")
    audio_path = text_to_speech(voice, text, session_id)
    if not audio_path:
        return None, "Failed to generate speech audio."
    
    progress(0.2, desc="Processing video...")
    video_path = os.path.join("models", model)
    
    try:
        progress(0.3, desc="Uploading files...")
        video_url = upload_file(video_path)
        audio_url = upload_file(audio_path)
        
        if not video_url or not audio_url:
            raise Exception("Failed to upload files")
        
        progress(0.4, desc="Initiating lipsync...")
        job_data = lipsync_api_call(video_url, audio_url)
        
        if "error" in job_data or "message" in job_data:
            raise Exception(job_data.get("error", job_data.get("message", "Unknown error")))
        
        job_id = job_data["id"]
        
        progress(0.5, desc="Processing lipsync...")
        result_url = check_job_status(job_id)
        
        if result_url:
            progress(0.9, desc="Downloading result...")
            response = requests.get(result_url)
            output_path = f"output_{session_id}.mp4"
            with open(output_path, "wb") as f:
                f.write(response.content)
            progress(1.0, desc="Complete!")
            return output_path, "Lipsync completed successfully!"
        else:
            raise Exception("Lipsync processing failed or timed out")
            
    except Exception as e:
        progress(0.8, desc="Falling back to simple combination...")
        try:
            output_path = f"output_{session_id}.mp4"
            combine_audio_video(video_path, audio_path, output_path)
            progress(1.0, desc="Complete!")
            return output_path, f"Used fallback method. Original error: {str(e)}"
        except Exception as fallback_error:
            return None, f"All methods failed. Error: {str(fallback_error)}"
    finally:
        # Cleanup
        if os.path.exists(audio_path):
            os.remove(audio_path)

def create_interface():
    voices = get_voices()
    models = get_video_models()
    
    with gr.Blocks() as app:
        gr.Markdown("# JSON Train")
        with gr.Row():
            with gr.Column():
                voice_dropdown = gr.Dropdown(choices=[v[0] for v in voices], label="Select", value=voices[0][0] if voices else None)
                model_dropdown = gr.Dropdown(choices=models, label="Select", value=models[0] if models else None)
                text_input = gr.Textbox(label="json", lines=3)
                generate_btn = gr.Button("Generate Video")
            with gr.Column():
                video_output = gr.Video(label="Generated Video")
                status_output = gr.Textbox(label="Status", interactive=False)
        
        def on_generate(voice_name, model_name, text):
            voice_id = next((v[1] for v in voices if v[0] == voice_name), None)
            if not voice_id:
                return None, "Invalid voice selected."
            return process_video(voice_id, model_name, text)
        
        generate_btn.click(
            fn=on_generate,
            inputs=[voice_dropdown, model_dropdown, text_input],
            outputs=[video_output, status_output]
        )
    
    return app

if __name__ == "__main__":
    app = create_interface()
    app.launch()