inference_cli.py

# --- START OF FILE inference_cli.py ---

import argparse
import shutil
import soundfile as sf
import os # For path manipulation if needed
import sys # To potentially add app.py directory to path

# Try to import app.py - assumes it's in the same directory or Python path
try:
    # If app.py is not directly importable, you might need to add its directory to the path
    # Example: sys.path.append(os.path.dirname(os.path.abspath(__file__))) # Add current dir
    import app
    from app import infer # Import the main inference function
except ImportError as e:
    print(f"Error: Could not import 'app.py'. Make sure it's in the Python path.")
    print(f"Details: {e}")
    sys.exit(1)
except Exception as e:
    print(f"An unexpected error occurred during 'app.py' import: {e}")
    sys.exit(1)


def main():
    parser = argparse.ArgumentParser(description="F5 TTS - Simplified CLI Interface using app.py")

    # --- Input Arguments ---
    parser.add_argument("--ref_audio", required=True, help="Path to the reference audio file (wav, mp3, etc.)")
    parser.add_argument("--ref_text", default="", help="Reference text. If empty, audio transcription will be performed by app.py's infer function.")
    parser.add_argument("--gen_text", required=True, help="Text to generate")

    # --- Model & Generation Parameters ---
    # Note: app.py seems hardcoded to load the "Multi" model at the top level.
    # This argument might not change the loaded model unless app.py's infer logic uses it internally.
    parser.add_argument("--exp_name", default="Multi", help="Experiment name / model selection (default: Multi - effectiveness depends on app.py)")
    parser.add_argument("--language", default="en-us", help="Synthesized language code (e.g., en-us, pl, de) (default: en-us)")
    parser.add_argument("--ref_language", default="en-us", help="Reference language code (e.g., en-us, pl, de) (default: en-us)")
    parser.add_argument("--speed", type=float, default=1.0, help="Audio speed factor (default: 1.0)")

    # --- Postprocessing ---
    parser.add_argument("--remove_silence", action="store_true", help="Remove silence from the output audio (uses app.py logic)")
    parser.add_argument("--cross_fade_duration", type=float, default=0.15, help="Cross-fade duration between batches (s)")

    # --- Output Arguments ---
    parser.add_argument("--output_audio", default="output.wav", help="Path to save the output WAV file")
    parser.add_argument("--output_spectrogram", default="spectrogram.png", help="Path to save the spectrogram image (PNG)")

    args = parser.parse_args()

    print("--- Configuration ---")
    print(f"Reference Audio: {args.ref_audio}")
    print(f"Reference Text: '{args.ref_text if args.ref_text else '<Automatic Transcription>'}'")
    print(f"Generation Text: '{args.gen_text[:100]}...'")
    print(f"Model (exp_name): {args.exp_name}")
    print(f"Synth Language: {args.language}")
    print(f"Ref Language: {args.ref_language}")
    print(f"Speed: {args.speed}")
    print(f"Remove Silence: {args.remove_silence}")
    print(f"Cross-Fade: {args.cross_fade_duration}s")
    print(f"Output Audio: {args.output_audio}")
    print(f"Output Spectrogram: {args.output_spectrogram}")
    print("--------------------")

    # --- Set Global Variables in app.py ---
    # The 'infer' function in app.py relies on these globals being set.
    try:
        print(f"Setting language in app module to: {args.language}")
        app.language = args.language
        print(f"Setting ref_language in app module to: {args.ref_language}")
        app.ref_language = args.ref_language
        print(f"Setting speed in app module to: {args.speed}")
        app.speed = args.speed
    except AttributeError as e:
        print(f"Error: Could not set global variable in 'app.py'. Does it exist? Details: {e}")
        sys.exit(1)

    # --- Run Inference ---
    print("\nStarting inference process (will load models if not already loaded)...")
    try:
        # Call the infer function directly from the imported app module
        (sr, audio_data), temp_spectrogram_path = infer(
            ref_audio_orig=args.ref_audio,
            ref_text=args.ref_text,
            gen_text=args.gen_text,
            exp_name=args.exp_name,
            remove_silence=args.remove_silence,
            cross_fade_duration=args.cross_fade_duration
            # Note: language, ref_language, speed are used globally within app.py's functions
        )
        print("Inference completed.")

    except Exception as e:
        print(f"\nError during inference: {e}")
        import traceback
        traceback.print_exc() # Print detailed traceback
        sys.exit(1)

    # --- Save Outputs ---
    try:
        # Save audio
        print(f"Saving audio to: {args.output_audio}")
        # Ensure directory exists
        os.makedirs(os.path.dirname(os.path.abspath(args.output_audio)) or '.', exist_ok=True)
        # Ensure data is float32 for soundfile
        if audio_data.dtype != "float32":
             audio_data = audio_data.astype("float32")
        sf.write(args.output_audio, audio_data, sr)

        # Copy spectrogram from the temporary path returned by infer
        print(f"Copying spectrogram from {temp_spectrogram_path} to: {args.output_spectrogram}")
        # Ensure directory exists
        os.makedirs(os.path.dirname(os.path.abspath(args.output_spectrogram)) or '.', exist_ok=True)
        shutil.copy(temp_spectrogram_path, args.output_spectrogram)

        print("\n--- Success ---")
        print(f"Audio saved in: {args.output_audio}")
        print(f"Spectrogram saved in: {args.output_spectrogram}")
        print("---------------")

    except Exception as e:
        print(f"\nError saving output files: {e}")
        sys.exit(1)

    # Optional: Clean up the temporary spectrogram file if needed,
    # but NamedTemporaryFile usually handles this if delete=True was used in app.py
    # try:
    #     if os.path.exists(temp_spectrogram_path):
    #         os.remove(temp_spectrogram_path)
    # except Exception as e:
    #     print(f"Warning: Could not clean up temporary spectrogram file {temp_spectrogram_path}: {e}")

if __name__ == "__main__":
    main()

# --- END OF FILE inference_cli.py ---