minmal example with a server client architecture

src/voice_client/tts_client.py

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+import requests
+import numpy as np
+import soundfile as sf
+
+from voice_models.request_models import SynthesizeRequest
+
+
+API_URL = "http://127.0.0.1:8099/synthesize/"
+
+def request_synthesis(request_data: SynthesizeRequest):
+    response = requests.post(API_URL, json=request_data.model_dump())
+
+    if response.status_code == 200:
+        response_data = response.json()
+        
+        if request_data.return_lc3:
+            # Save LC3 audio as binary file
+            lc3_bytes = bytes.fromhex(response_data["audio_lc3"])
+            return lc3_bytes
+        
+        else:
+            # Convert hex-encoded PCM bytes back to numpy array and save as WAV
+            audio_bytes = bytes.fromhex(response_data["audio_pcm"])
+            audio_array = np.frombuffer(audio_bytes, dtype=np.float32)
+            return audio_array
+    
+    else:
+        print(f"Error: {response.status_code}, {response.text}")
+
+if __name__ == "__main__":
+
+    target_rate=16000
+
+    # Example request
+    request_data = SynthesizeRequest(
+        text="Hello, this is a test.",
+        target_sample_rate=target_rate,
+        framework="piper",
+        model="de_DE-kerstin-low",
+        return_lc3=False  # Set to True to receive LC3 compressed output
+    )
+
+    audio = request_synthesis(request_data)
+    sf.write('hello.wav', audio, target_rate)