import os, uuid, subprocess, boto3, replicate
from typing import Dict, Any
from dotenv import load_dotenv
# from helpers_function.helpers import upload_to_r2

load_dotenv()

replicate_client = replicate.Client(api_token=os.getenv("REPLICATE_API_KEY"))

def video_to_audio(video_path: str) -> str:
    """Extract audio from video using ffmpeg and return audio filename."""
    audio_filename = f"{uuid.uuid4()}.mp3"
    command = [
        "ffmpeg", "-hide_banner", "-loglevel", "error",
        "-i", video_path, "-vn", "-acodec", "libmp3lame", "-y", audio_filename
    ]
    subprocess.run(command, check=True)
    return audio_filename

def extract_text_from_video(video_path: str, max_duration: int = 60) -> Dict[str, Any]:
    """
    Convert video speech to text using Replicate seamless model.
    Steps:
    1. Extract audio from video.
    2. Upload audio to R2.
    3. Run Replicate model.
    """

    audio_file = video_to_audio(video_path)


    # audio_url = upload_to_r2(audio_file, f"audio/{os.path.basename(audio_file)}")

    try:
        with open(audio_file, "rb") as f:
            # Call Replicate model
            result = replicate_client.run(
                "cjwbw/seamless_communication:668a4fec05a887143e5fe8d45df25ec4c794dd43169b9a11562309b2d45873b0",
                input={
                    "task_name": "S2ST (Speech to Speech translation)",
                    "input_audio": f,
                    "input_text_language": "None",
                    "max_input_audio_length": max_duration,
                    "target_language_text_only": "English",
                    "target_language_with_speech": "English",
                },
            )
    finally:
        try:
            os.remove(audio_file)
        except Exception:
            pass

    return result if result else {"error": "No output"}