from langchain_core.tools import tool
import os
import whisper

@tool
def transcribe_audio(file_path: str) -> str:
    """
    Transcribes an audio file using OpenAI Whisper and returns the transcribed text.

    Args:
        file_path (str): Path to the audio file.
    """
    if not os.path.exists(file_path):
        return f"Error: Audio file {file_path} not found."

    try:
        # Attempt transcription with Whisper
        # Using "base" model for a balance of speed and accuracy.
        # Other models: "tiny", "small", "medium", "large", "large-v2", "large-v3"
        # Consider making the model choice configurable if needed.
        model = whisper.load_model("base") 
        result = model.transcribe(file_path, fp16=False) # fp16=False can improve compatibility/stability on some systems
        transcription = result["text"]

        if transcription.strip(): # Check if transcription is not empty or just whitespace
            return f"Audio transcription: {transcription}"
        else:
            return "Audio transcribed, but no text was detected."
            
    except Exception as e_whisper:
        # Catching a general exception, but more specific ones can be added
        # (e.g., for model loading errors, unsupported file formats by Whisper)
        return f"Error during audio transcription: {str(e_whisper)}"