"""
Stage 7 — Audio Assembly
Stitches all TTS segments into a single continuous dubbed audio track.
Places each segment at the correct timestamp with silence padding.
"""

import logging
import subprocess
import json
from pathlib import Path
from typing import List, Dict

from config import TTS_CROSSFADE_MS

logger = logging.getLogger(__name__)


def assemble_dubbed_audio(
    segments: List[Dict],
    total_duration: float,
    output_dir: Path,
    progress_callback=None
) -> Path:
    """
    Create a full-length audio track by placing each TTS segment
    at its original timestamp position.

    Returns path to the assembled dubbed audio file.
    """
    output_path = output_dir / "dubbed_audio_full.wav"

    # Filter segments that have TTS audio
    valid_segments = [
        s for s in segments
        if s.get("tts_audio_path") and Path(s["tts_audio_path"]).exists()
    ]

    if not valid_segments:
        raise RuntimeError("No valid TTS segments to assemble.")

    logger.info(f"Assembling {len(valid_segments)} segments into {total_duration:.1f}s track")

    # Use ffmpeg filter_complex to place segments at correct timestamps
    # This is more reliable than pydub for long audio
    filter_parts = []
    inputs = []

    # First input: silence for the full duration
    inputs.extend([
        "-f", "lavfi",
        "-t", str(total_duration),
        "-i", f"anullsrc=r=24000:cl=mono"
    ])

    # Add each TTS segment as an input
    for idx, seg in enumerate(valid_segments):
        inputs.extend(["-i", seg["tts_audio_path"]])

    # Build filter: overlay each segment at its start time
    # [0] is the silence base, [1], [2], etc. are the TTS segments
    n_segs = len(valid_segments)

    if n_segs == 0:
        raise RuntimeError("No segments to assemble.")

    # For large numbers of segments, build the filter in stages
    # to avoid ffmpeg filter complexity limits
    if n_segs > 100:
        return _assemble_chunked(valid_segments, total_duration, output_dir, output_path, progress_callback)

    # Build adelay filter chain
    filter_parts = []
    mix_inputs = ["[base]"]

    # The silence base
    filter_parts.append("[0]aresample=24000[base]")

    for idx, seg in enumerate(valid_segments):
        input_idx = idx + 1  # +1 because [0] is silence
        delay_ms = int(seg["start"] * 1000)
        # Resample to 24kHz, apply delay
        filter_parts.append(
            f"[{input_idx}]aresample=24000,adelay={delay_ms}|{delay_ms}[s{idx}]"
        )
        mix_inputs.append(f"[s{idx}]")

    # Mix all together
    all_inputs = "".join(mix_inputs)
    filter_parts.append(
        f"{all_inputs}amix=inputs={n_segs + 1}:duration=longest:dropout_transition=0[out]"
    )

    filter_complex = ";".join(filter_parts)

    cmd = [
        "ffmpeg", "-y",
        *inputs,
        "-filter_complex", filter_complex,
        "-map", "[out]",
        "-acodec", "pcm_s16le",
        "-ar", "24000",
        "-ac", "1",
        str(output_path)
    ]

    logger.info("Running ffmpeg audio assembly...")
    result = subprocess.run(cmd, capture_output=True, text=True, timeout=600)

    if result.returncode != 0:
        logger.warning(f"FFmpeg filter_complex failed. Trying chunked assembly. Error: {result.stderr[:500]}")
        return _assemble_chunked(valid_segments, total_duration, output_dir, output_path, progress_callback)

    logger.info(f"Audio assembly complete: {output_path}")

    if progress_callback:
        progress_callback(100)

    return output_path


def _assemble_chunked(
    segments: List[Dict],
    total_duration: float,
    output_dir: Path,
    output_path: Path,
    progress_callback=None
) -> Path:
    """
    Fallback: assemble audio using pydub for better memory management.
    Processes in chunks for very long videos.
    """
    try:
        from pydub import AudioSegment
    except ImportError:
        raise RuntimeError("pydub not installed. Run: pip install pydub")

    logger.info("Using pydub chunked assembly (fallback)...")

    # Create silent base track
    total_ms = int(total_duration * 1000)
    base = AudioSegment.silent(duration=total_ms, frame_rate=24000)

    total_segs = len(segments)
    for idx, seg in enumerate(segments):
        try:
            tts_audio = AudioSegment.from_file(seg["tts_audio_path"])
            # Resample to 24kHz mono
            tts_audio = tts_audio.set_frame_rate(24000).set_channels(1)

            position_ms = int(seg["start"] * 1000)

            # Overlay at the correct position
            base = base.overlay(tts_audio, position=position_ms)

        except Exception as e:
            logger.warning(f"Failed to overlay segment {idx}: {e}")
            continue

        if progress_callback and idx % 50 == 0:
            progress_callback(int((idx + 1) / total_segs * 100))

    # Export
    base.export(str(output_path), format="wav")
    logger.info(f"Chunked assembly complete: {output_path}")
    return output_path