send wav files

.gitignore

@@ -169,3 +169,6 @@ cython_debug/
 _.aifs
 software/output_audio.wav
 .DS_Store
+
+node_modules/
+.expo/

software/source/server/server.py

@@ -21,8 +21,7 @@ from ..utils.accumulator import Accumulator
 from .utils.logs import setup_logging
 from .utils.logs import logger
 import base64
-from google.cloud import storage
-
+import shutil
 from ..utils.print_markdown import print_markdown
 
 os.environ["STT_RUNNER"] = "server"
@@ -394,31 +393,31 @@ def stream_tts(sentence):
 
     with open(audio_file, "rb") as f:
         audio_bytes = f.read()
-
-    storage_client = storage.Client(project="react-native-421323")
-    bucket = storage_client.bucket("01-audio")
-    blob = bucket.blob(f"{datetime.datetime.now().strftime('%Y%m%d%H%M%S%f')}.wav")
-    generation_match_precondition = 0
-
-    blob.upload_from_filename(
-        audio_file, if_generation_match=generation_match_precondition
-    )
-    print(
-        f"Audio file {audio_file} uploaded to {datetime.datetime.now().strftime('%Y%m%d%H%M%S%f')}.wav"
-    )
+    desktop_path = os.path.join(os.path.expanduser('~'), 'Desktop')
+    desktop_audio_file = os.path.join(desktop_path, os.path.basename(audio_file))
+    shutil.copy(audio_file, desktop_audio_file)
+    print(f"Audio file saved to Desktop: {desktop_audio_file}")
+    # storage_client = storage.Client(project="react-native-421323")
+    # bucket = storage_client.bucket("01-audio")
+    # blob = bucket.blob(f"{datetime.datetime.now().strftime('%Y%m%d%H%M%S%f')}.wav")
+    # generation_match_precondition = 0
+
+    # blob.upload_from_filename(
+    #     audio_file, if_generation_match=generation_match_precondition
+    # )
+    # print(
+    #     f"Audio file {audio_file} uploaded to {datetime.datetime.now().strftime('%Y%m%d%H%M%S%f')}.wav"
+    # )
 
     os.remove(audio_file)
 
-    file_type = "bytes.raw"
-    chunk_size = 1024
-
-    # Stream the audio
-    yield {"role": "assistant", "type": "audio", "format": file_type, "start": True}
-    for i in range(0, len(audio_bytes), chunk_size):
-        chunk = audio_bytes[i : i + chunk_size]
-        yield chunk
-    yield {"role": "assistant", "type": "audio", "format": file_type, "end": True}
+    file_type = "audio/wav"
+    # Read the entire WAV file
+    with open(audio_file, "rb") as f:
+        audio_bytes = f.read()
 
+    # Stream the audio as a single message
+    yield {"role": "assistant", "type": "audio", "format": file_type, "content": base64.b64encode(audio_bytes).decode('utf-8'), "start": True, "end": True}
 
 from uvicorn import Config, Server
 import os

software/source/server/services/tts/openai/tts.py

@@ -36,9 +36,9 @@ class Tts:
             response.stream_to_file(temp_file.name)
 
             # TODO: hack to format audio correctly for device
-            outfile = tempfile.gettempdir() + "/" + "raw.dat"
+            outfile = tempfile.gettempdir() + "/" + "output.wav"
             ffmpeg.input(temp_file.name).output(
-                outfile, f="s16le", ar="16000", ac="1", loglevel="panic"
+                outfile, f="wav", ar="16000", ac="1", loglevel="panic"
             ).run()
 
             return outfile

software/source/server/tunnel.py

@@ -100,7 +100,7 @@ def create_tunnel(
         # If ngrok is installed, start it on the specified port
         # process = subprocess.Popen(f'ngrok http {server_port} --log=stdout', shell=True, stdout=subprocess.PIPE)
         process = subprocess.Popen(
-            f"ngrok http {server_port} --scheme http,https --domain=sterling-snail-conversely.ngrok-free.app --log=stdout",
+            f"ngrok http {server_port} --scheme http,https  --log=stdout",
             shell=True,
             stdout=subprocess.PIPE,
         )