Supports multiple Speech to Text providers

- Supports multiple STT providers: Groq, Google, Microsoft, and OpenAI
- Records audio with volume-based progress indication
- Handles error cases for missing API keys and audio devices
- Includes example usage in main block
- Depends on sounddevice, numpy, and provider-specific libraries
- Manages API keys through environment variables
- Converts audio format if file size exceeds limit

aider/voice.py

@@ -1,14 +1,15 @@
+
 import math
 import os
 import queue
 import tempfile
 import time
+import numpy as np
 import warnings
+from typing import Optional, Tuple, Union
 
 from prompt_toolkit.shortcuts import prompt
 
-from aider.llm import litellm
-
 from .dump import dump  # noqa: F401
 
 warnings.filterwarnings(
@@ -16,69 +17,132 @@ warnings.filterwarnings(
 )
 warnings.filterwarnings("ignore", category=SyntaxWarning)
 
-
-from pydub import AudioSegment  # noqa
-from pydub.exceptions import CouldntDecodeError, CouldntEncodeError  # noqa
+from pydub import AudioSegment
+from pydub.exceptions import CouldntDecodeError, CouldntEncodeError
 
 try:
     import soundfile as sf
 except (OSError, ModuleNotFoundError):
     sf = None
 
+try:
+    import google.cloud.speech as speech
+except (OSError, ModuleNotFoundError):
+    speech = None
+
+try:
+    import azure.cognitiveservices.speech as speech_sdk
+except (OSError, ModuleNotFoundError):
+    speech_sdk = None
+
+try:
+    import openai
+except (OSError, ModuleNotFoundError):
+    openai = None
+
+from groq import Groq  # Updated import
 
 class SoundDeviceError(Exception):
     pass
 
-
 class Voice:
-    max_rms = 0
-    min_rms = 1e5
-    pct = 0
+    """
+    A class to handle audio recording and transcription using sounddevice and various transcription services.
+    """
 
-    threshold = 0.15
+    def __init__(self, audio_format: str = "wav", device_name: Optional[str] = None, provider: str = "groq", api_key: Optional[str] = None):
+        """
+        Initialize the Voice class.
 
-    def __init__(self, audio_format="wav", device_name=None):
+        Args:
+            audio_format: The format of the output audio file. Supported formats: 'wav', 'mp3', 'webm'.
+            device_name: The name of the audio input device to use. If None, the default device is used.
+            provider: The transcription service provider. Supported providers: 'groq', 'google', 'microsoft', 'openai'.
+            api_key: Optional API key for the transcription service. If not provided, it will be retrieved from environment variables.
+
+        Raises:
+            SoundDeviceError: If sounddevice or soundfile is not available.
+            ValueError: If the audio_format is not supported or the device_name is not found.
+        """
         if sf is None:
-            raise SoundDeviceError
+            raise SoundDeviceError("soundfile is not available. Please install it.")
+
         try:
-            print("Initializing sound device...")
             import sounddevice as sd
-
             self.sd = sd
-
-            devices = sd.query_devices()
-
-            if device_name:
-                # Find the device with matching name
-                device_id = None
-                for i, device in enumerate(devices):
-                    if device_name in device["name"]:
-                        device_id = i
-                        break
-                if device_id is None:
-                    available_inputs = [d["name"] for d in devices if d["max_input_channels"] > 0]
-                    raise ValueError(
-                        f"Device '{device_name}' not found. Available input devices:"
-                        f" {available_inputs}"
-                    )
-
-                print(f"Using input device: {device_name} (ID: {device_id})")
-
-                self.device_id = device_id
-            else:
-                self.device_id = None
-
         except (OSError, ModuleNotFoundError):
-            raise SoundDeviceError
-        if audio_format not in ["wav", "mp3", "webm"]:
-            raise ValueError(f"Unsupported audio format: {audio_format}")
-        self.audio_format = audio_format
+            raise SoundDeviceError("sounddevice is not available. Please install it.")
 
-    def callback(self, indata, frames, time, status):
-        """This is called (from a separate thread) for each audio block."""
+        if audio_format not in ["wav", "mp3", "webm"]:
+            raise ValueError(f"Unsupported audio format: {audio_format}. Supported formats: wav, mp3, webm.")
+
+        self.audio_format = audio_format
+        self.device_id = None
+        self.provider = provider
+        self.api_key = api_key
+
+        if device_name:
+            devices = self.sd.query_devices()
+            device_id = None
+            for i, device in enumerate(devices):
+                if device_name.lower() in device["name"].lower():
+                    device_id = i
+                    break
+            if device_id is None:
+                available_inputs = [d["name"] for d in devices if d["max_input_channels"] > 0]
+                raise ValueError(
+                    f"Device '{device_name}' not found. Available input devices: {available_inputs}"
+                )
+            self.device_id = device_id
+            print(f"Using input device: {device_name} (ID: {device_id})")
+
+        self._validate_provider()
+
+    def _validate_provider(self):
+        supported_providers = ['groq', 'google', 'microsoft', 'openai']
+        if self.provider not in supported_providers:
+            raise ValueError(f"Unsupported provider: {self.provider}. Supported providers: {supported_providers}")
+
+        if self.provider == 'google' and speech is None:
+            raise ValueError("google.cloud.speech is not available. Please install google-cloud-speech.")
+        
+        if self.provider == 'microsoft' and speech_sdk is None:
+            raise ValueError("azure.cognitiveservices.speech is not available. Please install azure-cognitive-services-speech.")
+
+        if self.provider == 'openai' and openai is None:
+            raise ValueError("openai is not available. Please install openai.")
+
+    def set_api_key(self):
+        if self.provider == 'groq':
+            self.api_key = os.getenv("GROQ_API_KEY")
+            if not self.api_key:
+                raise ValueError("Please set the GROQ_API_KEY environment variable.")
+        elif self.provider == 'google':
+            self.api_key = os.getenv("GOOGLE_API_KEY")
+            if not self.api_key:
+                raise ValueError("Please set the GOOGLE_API_KEY environment variable.")
+        elif self.provider == 'microsoft':
+            self.api_key = os.getenv("AZURE_SPEECH_KEY")
+            if not self.api_key:
+                raise ValueError("Please set the AZURE_SPEECH_KEY environment variable.")
+        elif self.provider == 'openai':
+            self.api_key = os.getenv("OPENAI_API_KEY")
+            if not self.api_key:
+                raise ValueError("Please set the OPENAI_API_KEY environment variable.")
+
+    def callback(self, indata: np.ndarray, frames: int, time: float, status: int) -> None:
+        """
+        Callback function for audio data processing.
+
+        Args:
+            indata: The audio data.
+            frames: The number of frames.
+            time: The time stamp.
+            status: The stream status.
+        """
         import numpy as np
 
-        rms = np.sqrt(np.mean(indata**2))
+        rms = np.sqrt(np.mean(indata ** 2))
         self.max_rms = max(self.max_rms, rms)
         self.min_rms = min(self.min_rms, rms)
 
@@ -90,7 +154,13 @@ class Voice:
 
         self.q.put(indata.copy())
 
-    def get_prompt(self):
+    def get_prompt(self) -> str:
+        """
+        Generate a progress prompt string.
+
+        Returns:
+            A formatted string showing recording status and progress bar.
+        """
         num = 10
         if math.isnan(self.pct) or self.pct < self.threshold:
             cnt = 0
@@ -101,19 +171,44 @@ class Voice:
         bar = bar[:num]
 
         dur = time.time() - self.start_time
-        return f"Recording, press ENTER when done... {dur:.1f}sec {bar}"
+        return f"Recording, press ENTER when done... {dur:.1f}s {bar}"
 
-    def record_and_transcribe(self, history=None, language=None):
+    def record_and_transcribe(self, history: Optional[list] = None, language: Optional[str] = None) -> Optional[str]:
+        """
+        Record audio and transcribe it.
+
+        Args:
+            history: Optional list of previous commands/transcripts for context.
+            language: Optional language code for transcription.
+
+        Returns:
+            The transcribed text or None if an error occurs.
+        """
         try:
             return self.raw_record_and_transcribe(history, language)
         except KeyboardInterrupt:
-            return
+            print("\nRecording stopped by user.")
+            return None
         except SoundDeviceError as e:
             print(f"Error: {e}")
             print("Please ensure you have a working audio input device connected and try again.")
-            return
+            return None
 
-    def raw_record_and_transcribe(self, history, language):
+    def raw_record_and_transcribe(self, history: Optional[list], language: Optional[str]) -> Optional[str]:
+        """
+        Raw method to record and transcribe audio without exception handling.
+
+        Args:
+            history: Optional list of previous commands/transcripts for context.
+            language: Optional language code for transcription.
+
+        Returns:
+            The transcribed text or None if an error occurs.
+        """
+        self.max_rms = 0
+        self.min_rms = 1e5
+        self.pct = 0
+        self.threshold = 0.15
         self.q = queue.Queue()
 
         temp_wav = tempfile.mktemp(suffix=".wav")
@@ -121,7 +216,7 @@ class Voice:
         try:
             sample_rate = int(self.sd.query_devices(self.device_id, "input")["default_samplerate"])
         except (TypeError, ValueError):
-            sample_rate = 16000  # fallback to 16kHz if unable to query device
+            sample_rate = 16000  # Fallback to 16kHz
         except self.sd.PortAudioError:
             raise SoundDeviceError(
                 "No audio input device detected. Please check your audio settings and try again."
@@ -132,56 +227,177 @@ class Voice:
         try:
             with self.sd.InputStream(
                 samplerate=sample_rate, channels=1, callback=self.callback, device=self.device_id
-            ):
+            ) as stream:
                 prompt(self.get_prompt, refresh_interval=0.1)
         except self.sd.PortAudioError as err:
             raise SoundDeviceError(f"Error accessing audio input device: {err}")
 
-        with sf.SoundFile(temp_wav, mode="x", samplerate=sample_rate, channels=1) as file:
-            while not self.q.empty():
-                file.write(self.q.get())
+        # Write recorded data to file
+        try:
+            with sf.SoundFile(temp_wav, mode="x", samplerate=sample_rate, channels=1) as file:
+                while not self.q.empty():
+                    file.write(self.q.get())
+        except Exception as e:
+            print(f"Error writing audio data: {e}")
+            return None
 
+        # Convert audio format if necessary
         use_audio_format = self.audio_format
+        filename = temp_wav
 
         # Check file size and offer to convert to mp3 if too large
         file_size = os.path.getsize(temp_wav)
         if file_size > 24.9 * 1024 * 1024 and self.audio_format == "wav":
-            print("\nWarning: {temp_wav} is too large, switching to mp3 format.")
+            print("\nWarning: The WAV file is too large, switching to MP3 format.")
             use_audio_format = "mp3"
 
-        filename = temp_wav
-        if use_audio_format != "wav":
             try:
                 new_filename = tempfile.mktemp(suffix=f".{use_audio_format}")
                 audio = AudioSegment.from_wav(temp_wav)
                 audio.export(new_filename, format=use_audio_format)
                 os.remove(temp_wav)
                 filename = new_filename
-            except (CouldntDecodeError, CouldntEncodeError) as e:
-                print(f"Error converting audio: {e}")
-            except (OSError, FileNotFoundError) as e:
-                print(f"File system error during conversion: {e}")
             except Exception as e:
-                print(f"Unexpected error during audio conversion: {e}")
+                print(f"Error converting audio: {e}")
+                use_audio_format = "wav"
+                filename = temp_wav
 
-        with open(filename, "rb") as fh:
-            try:
-                transcript = litellm.transcription(
-                    model="whisper-1", file=fh, prompt=history, language=language
+        # Set API key based on provider
+        self.set_api_key()
+
+        # Transcribe audio using the selected provider
+        if self.provider == 'groq':
+            return self._transcribe_groq(filename, language)
+        elif self.provider == 'google':
+            return self._transcribe_google(filename, language)
+        elif self.provider == 'microsoft':
+            return self._transcribe_microsoft(filename, language)
+        elif self.provider == 'openai':
+            return self._transcribe_openai(filename, language)
+        else:
+            raise ValueError(f"Unsupported provider: {self.provider}")
+
+    def _transcribe_groq(self, filename: str, language: Optional[str] = None) -> Optional[str]:
+        """
+        Transcribe audio using Groq's Whisper model.
+
+        Args:
+            filename: Path to the audio file.
+            language: Optional language code for transcription.
+
+        Returns:
+            The transcribed text or None if an error occurs.
+        """
+        try:
+            client = Groq(api_key=self.api_key)
+            with open(filename, "rb") as audio_file:
+                transcript = client.audio.transcriptions.create(
+                    file=(os.path.basename(filename), audio_file.read()),
+                    model="distil-whisper-large-v3-en"
                 )
-            except Exception as err:
-                print(f"Unable to transcribe {filename}: {err}")
-                return
+                return transcript.text
+        except Exception as e:
+            print(f"Unable to transcribe audio using Groq: {e}")
+            return None
 
-        if filename != temp_wav:
-            os.remove(filename)
+    def _transcribe_google(self, filename: str, language: Optional[str] = None) -> Optional[str]:
+        """
+        Transcribe audio using Google Cloud Speech-to-Text.
 
-        text = transcript.text
-        return text
+        Args:
+            filename: Path to the audio file.
+            language: Optional language code for transcription.
 
+        Returns:
+            The transcribed text or None if an error occurs.
+        """
+        if language is None:
+            language = "en-US"
+
+        try:
+            client = speech.SpeechClient()
+            with open(filename, "rb") as audio_file:
+                audio = speech.RecognitionAudio(content=audio_file.read())
+                config = speech.RecognitionConfig(
+                    encoding=speech.RecognitionConfig.AudioEncoding.LINEAR16,
+                    language_code=language,
+                )
+                response = client.recognize(config, audio)
+                return " ".join([result.alternatives[0].transcript for result in response.results])
+        except Exception as e:
+            print(f"Unable to transcribe audio using Google: {e}")
+            return None
+
+    def _transcribe_microsoft(self, filename: str, language: Optional[str] = None) -> Optional[str]:
+        """
+        Transcribe audio using Microsoft Azure Speech Services.
+
+        Args:
+            filename: Path to the audio file.
+            language: Optional language code for transcription.
+
+        Returns:
+            The transcribed text or None if an error occurs.
+        """
+        if language is None:
+            language = "en-US"
+
+        try:
+            speech_config = speech_sdk.SpeechConfig(subscription=self.api_key, region="global")
+            audio_config = speech_sdk.AudioConfig(filename=filename)
+            speech_recognizer = speech_sdk.SpeechRecognizer(speech_config, audio_config=audio_config)
+            
+            result = speech_recognizer.recognize_once()
+            return result.text
+        except Exception as e:
+            print(f"Unable to transcribe audio using Microsoft: {e}")
+            return None
+
+    def _transcribe_openai(self, filename: str, language: Optional[str] = None) -> Optional[str]:
+        """
+        Transcribe audio using OpenAI Whisper model.
+
+        Args:
+            filename: Path to the audio file.
+            language: Optional language code for transcription.
+
+        Returns:
+            The transcribed text or None if an error occurs.
+        """
+        try:
+            client = openai.OpenAI(api_key=self.api_key)
+            with open(filename, "rb") as audio_file:
+                response = client.audio.transcriptions.create(
+                    "whisper-1",
+                    file=audio_file.read()
+                )
+                return response.text
+        except Exception as e:
+            print(f"Unable to transcribe audio using OpenAI: {e}")
+            return None
 
 if __name__ == "__main__":
-    api_key = os.getenv("OPENAI_API_KEY")
-    if not api_key:
-        raise ValueError("Please set the OPENAI_API_KEY environment variable.")
-    print(Voice().record_and_transcribe())
+    # Example usage with different providers
+    voice_groq = Voice(provider='groq')
+    transcript_groq = voice_groq.record_and_transcribe()
+    if transcript_groq:
+        print("\nTranscript (Groq):")
+        print(transcript_groq)
+
+    voice_google = Voice(provider='google')
+    transcript_google = voice_google.record_and_transcribe()
+    if transcript_google:
+        print("\nTranscript (Google):")
+        print(transcript_google)
+
+    voice_microsoft = Voice(provider='microsoft')
+    transcript_microsoft = voice_microsoft.record_and_transcribe()
+    if transcript_microsoft:
+        print("\nTranscript (Microsoft):")
+        print(transcript_microsoft)
+
+    voice_openai = Voice(provider='openai')
+    transcript_openai = voice_openai.record_and_transcribe()
+    if transcript_openai:
+        print("\nTranscript (OpenAI):")
+        print(transcript_openai)