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from concurrent import futures
import torch
from models import build_model
from collections import deque
import grpc
import text_to_speech_pb2
import text_to_speech_pb2_grpc
from chat_database import save_chat_entry
import fastAPI
from providers.audio_provider import get_audio_bytes, dummy_bytes, generate_audio_from_chunks
from providers.llm_provider import getResponseWithRAG, getResponse
device = 'cuda' if torch.cuda.is_available() else 'cpu'
MODEL = build_model('kokoro-v0_19.pth', device)
VOICE_NAME = [
'af',
'af_bella', 'af_sarah', 'am_adam', 'am_michael',
'bf_emma', 'bf_isabella', 'bm_george', 'bm_lewis',
'af_nicole', 'af_sky',
][0]
VOICEPACK = torch.load(
f'voices/{VOICE_NAME}.pt', weights_only=True).to(device)
class TextToSpeechServicer(text_to_speech_pb2_grpc.TextToSpeechServiceServicer):
def ProcessText(self, request_iterator , context):
try:
global VOICEPACK
print("Received new request")
parameters = {
"processing_active": False,
"queue": deque(),
"file_number": 0,
"session_id": "",
"interrupt_seq": 0,
"temperature": 1,
"activeVoice": "af",
"maxTokens": 500,
}
for request in request_iterator:
field = request.WhichOneof('request_data')
if field == 'metadata':
meta = request.metadata
print("Metadata received:")
print(" session_id:", meta.session_id)
print(" silenceDuration:", meta.silenceDuration)
print(" threshold:", meta.threshold)
print(" temperature:", meta.temperature)
print(" activeVoice:", meta.activeVoice)
print(" maxTokens:", meta.maxTokens)
print("Metadata : ", request.metadata)
if meta.session_id:
parameters["session_id"] = meta.session_id
if meta.temperature:
parameters["temperature"] = meta.temperature
if meta.maxTokens:
parameters["maxTokens"] = meta.maxTokens
if meta.activeVoice:
parameters["activeVoice"] = meta.activeVoice
VOICEPACK = torch.load(
f'voices/{parameters["activeVoice"]}.pt', weights_only=True).to(device)
continue
elif field == 'text':
text = request.text
if not text:
continue
# yield text_to_speech_pb2.ProcessTextResponse(
# buffer=dummy_bytes(),
# session_id=parameters["session_id"],
# sequence_id="0",
# transcript="",
# )
# intent = check_for_rag(
# text, parameters["session_id"])
# print("Intent : ", intent.intent)
# print("Intent : ", intent.rag)
save_chat_entry(parameters["session_id"], "user", text)
parameters["queue"].clear()
yield text_to_speech_pb2.ProcessTextResponse(
buffer=dummy_bytes(),
session_id=parameters["session_id"],
sequence_id="-2",
transcript=text,
)
final_response = ""
complete_response = ""
response = getResponse(text, parameters["session_id"])
for chunk in response:
msg = chunk.choices[0].delta.content
if msg:
final_response += msg
complete_response += msg
if final_response.endswith(('.', '!', '?')):
parameters["file_number"] += 1
parameters["queue"].append(
(final_response, parameters["file_number"]))
final_response = ""
if not parameters["processing_active"]:
yield from self.process_queue(parameters)
if final_response:
parameters["file_number"] += 1
parameters["queue"].append(
(final_response, parameters["file_number"]))
if not parameters["processing_active"]:
yield from self.process_queue(parameters)
if ("Let me check" in complete_response):
final_response = ""
complete_response = ""
response = getResponseWithRAG(
text, parameters["session_id"])
for chunk in response:
msg = chunk.choices[0].delta.content
if msg:
final_response += msg
complete_response += msg
if final_response.endswith(('.', '!', '?')):
parameters["file_number"] += 1
parameters["queue"].append(
(final_response, parameters["file_number"]))
final_response = ""
if not parameters["processing_active"]:
yield from self.process_queue(parameters)
if final_response:
parameters["file_number"] += 1
parameters["queue"].append(
(final_response, parameters["file_number"]))
if not parameters["processing_active"]:
yield from self.process_queue(parameters)
elif field == 'status':
transcript = request.status.transcript
played_seq = request.status.played_seq
interrupt_seq = request.status.interrupt_seq
parameters["interrupt_seq"] = interrupt_seq
save_chat_entry(
parameters["session_id"], "assistant", transcript)
continue
else:
continue
except Exception as e:
print("Error in ProcessText:", e)
def process_queue(self, parameters):
global VOICEPACK
try:
while True:
if not parameters["queue"]:
parameters["processing_active"] = False
break
parameters["processing_active"] = True
sentence, file_number = parameters["queue"].popleft()
if file_number <= int(parameters["interrupt_seq"]):
continue
combined_audio = generate_audio_from_chunks(
sentence, MODEL, VOICEPACK, VOICE_NAME)
audio_bytes = get_audio_bytes(combined_audio)
# filename = save_audio_to_file(combined_audio, file_number)
yield text_to_speech_pb2.ProcessTextResponse(
buffer=audio_bytes,
session_id=parameters["session_id"],
sequence_id=str(file_number),
transcript=sentence,
)
except Exception as e:
parameters["processing_active"] = False
print("Error in process_queue:", e)
def serve():
print("Starting gRPC server...")
server = grpc.server(futures.ThreadPoolExecutor(max_workers=1))
text_to_speech_pb2_grpc.add_TextToSpeechServiceServicer_to_server(
TextToSpeechServicer(), server)
server.add_insecure_port('[::]:8081')
server.start()
print("gRPC server is running on port 8081")
server.wait_for_termination()
if __name__ == "__main__":
serve()
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