Spaces:
Paused
Paused
File size: 12,085 Bytes
9680844 175d877 9680844 175d877 9680844 e6f7c33 9680844 175d877 9680844 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 |
from operator import itemgetter
import os
from datetime import datetime
import uvicorn
from typing import Any, Optional, Tuple, Dict, TypedDict
from urllib import parse
from uuid import uuid4
import logging
from fastapi.logger import logger as fastapi_logger
import sys
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from fastapi import APIRouter, Body, Request, status
from pymongo import MongoClient
from dotenv import dotenv_values
from routes import router as api_router
from contextlib import asynccontextmanager
import requests
from typing import List
from datetime import date
from mongodb.operations.calls import *
from mongodb.operations.users import *
from mongodb.models.calls import UserCall, UpdateCall
# from mongodb.endpoints.calls import *
from transformers import AutoProcessor, SeamlessM4Tv2Model
# from seamless_communication.inference import Translator
from Client import Client
import numpy as np
import torch
import socketio
# Configure logger
gunicorn_error_logger = logging.getLogger("gunicorn.error")
gunicorn_logger = logging.getLogger("gunicorn")
uvicorn_access_logger = logging.getLogger("uvicorn.access")
gunicorn_error_logger.propagate = True
gunicorn_logger.propagate = True
uvicorn_access_logger.propagate = True
uvicorn_access_logger.handlers = gunicorn_error_logger.handlers
fastapi_logger.handlers = gunicorn_error_logger.handlers
# sio is the main socket.io entrypoint
sio = socketio.AsyncServer(
async_mode="asgi",
cors_allowed_origins="*",
logger=gunicorn_logger,
engineio_logger=gunicorn_logger,
)
# sio.logger.setLevel(logging.DEBUG)
socketio_app = socketio.ASGIApp(sio)
# app.mount("/", socketio_app)
config = dotenv_values(".env")
# Read connection string from environment vars
# uri = os.environ['MONGODB_URI']
# Read connection string from .env file
uri = config['MONGODB_URI']
# MongoDB Connection Lifespan Events
@asynccontextmanager
async def lifespan(app: FastAPI):
# startup logic
app.mongodb_client = MongoClient(uri)
app.database = app.mongodb_client['IT-Cluster1'] #connect to interpretalk primary db
try:
app.mongodb_client.admin.command('ping')
print("MongoDB Connection Established...")
except Exception as e:
print(e)
yield
# shutdown logic
print("Closing MongoDB Connection...")
app.mongodb_client.close()
app = FastAPI(lifespan=lifespan, logger=gunicorn_logger)
# New CORS funcitonality
app.add_middleware(
CORSMiddleware,
allow_origins=["*"], # configured node app port
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
app.include_router(api_router) # include routers for user, calls and transcripts operations
DEBUG = True
ESCAPE_HATCH_SERVER_LOCK_RELEASE_NAME = "remove_server_lock"
TARGET_SAMPLING_RATE = 16000
MAX_BYTES_BUFFER = 960_000
print("")
print("")
print("=" * 18 + " Interpretalk is starting... " + "=" * 18)
###############################################
# Configure socketio server
###############################################
# TODO PM - change this to the actual path
# seamless remnant code
CLIENT_BUILD_PATH = "../streaming-react-app/dist/"
static_files = {
"/": CLIENT_BUILD_PATH,
"/assets/seamless-db6a2555.svg": {
"filename": CLIENT_BUILD_PATH + "assets/seamless-db6a2555.svg",
"content_type": "image/svg+xml",
},
}
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
processor = AutoProcessor.from_pretrained("facebook/seamless-m4t-v2-large")
# PM - hardcoding temporarily as my GPU doesnt have enough vram
model = SeamlessM4Tv2Model.from_pretrained("facebook/seamless-m4t-v2-large").to(device)
bytes_data = bytearray()
model_name = "seamlessM4T_v2_large"
vocoder_name = "vocoder_v2" if model_name == "seamlessM4T_v2_large" else "vocoder_36langs"
clients = {}
rooms = {}
def get_collection_users():
return app.database["user_records"]
def get_collection_calls():
return app.database["call_records"]
@app.get("/home/", response_description="Welcome User")
def test():
return {"message": "Welcome to InterpreTalk!"}
async def send_translated_text(client_id, username, original_text, translated_text, room_id):
# print(rooms) # Debugging
# print(clients) # Debugging
data = {
"author_id": str(client_id),
"author_username": str(client_id),
"original_text": str(original_text),
"translated_text": str(translated_text),
"timestamp": str(datetime.now())
}
gunicorn_logger.info("SENDING TRANSLATED TEXT TO CLIENT")
await sio.emit("translated_text", data, room=room_id)
gunicorn_logger.info("SUCCESSFULLY SEND AUDIO TO FRONTEND")
@sio.on("connect")
async def connect(sid, environ):
print(f"📥 [event: connected] sid={sid}")
query_params = dict(parse.parse_qsl(environ["QUERY_STRING"]))
client_id = query_params.get("client_id")
gunicorn_logger.info(f"📥 [event: connected] sid={sid}, client_id={client_id}")
# get username to Client Object from DB
username = find_name_from_id(get_collection_users(), username)
# sid = socketid, client_id = client specific ID ,always the same for same user
clients[sid] = Client(sid, client_id, username)
print(clients[sid].username)
gunicorn_logger.warning(f"Client connected: {sid}")
gunicorn_logger.warning(clients)
@sio.on("disconnect")
async def disconnect(sid):
gunicorn_logger.debug(f"📤 [event: disconnected] sid={sid}")
call_id = clients[sid].call_id
user_id = clients[sid].client_id
target_language = clients[sid].target_language
clients.pop(sid, None)
# Perform Key Term Extraction and summarisation
try:
# Get combined caption field for call record based on call_id
key_terms = term_extraction(get_collection_calls(), call_id, user_id, target_language)
# Perform summarisation based on target language
summary_result = summarise(get_collection_calls(), call_id, user_id, target_language)
except:
gunicorn_logger.error(f"📤 [event: term_extraction/summarisation request error] sid={sid}, call={call_id}")
@sio.on("target_language")
async def target_language(sid, target_lang):
gunicorn_logger.info(f"📥 [event: target_language] sid={sid}, target_lang={target_lang}")
clients[sid].target_language = target_lang
@sio.on("call_user")
async def call_user(sid, call_id):
clients[sid].call_id = call_id
gunicorn_logger.info(f"CALL {sid}: entering room {call_id}")
rooms[call_id] = rooms.get(call_id, [])
if sid not in rooms[call_id] and len(rooms[call_id]) < 2:
rooms[call_id].append(sid)
sio.enter_room(sid, call_id)
else:
gunicorn_logger.info(f"CALL {sid}: room {call_id} is full")
# await sio.emit("room_full", room=call_id, to=sid)
# BO - Get call id from dictionary created during socketio connection
client_id = clients[sid].client_id
gunicorn_logger.warning(f"NOW TRYING TO CREATE DB RECORD FOR Caller with ID: {client_id} for call: {call_id}")
# BO -> Create Call Record with Caller and call_id field (None for callee, duration, terms..)
request_data = {
"call_id": str(call_id),
"caller_id": str(client_id),
"creation_date": str(datetime.now())
}
response = create_calls(get_collection_calls(), request_data)
print(response) # BO - print created db call record
@sio.on("audio_config")
async def audio_config(sid, sample_rate):
clients[sid].original_sr = sample_rate
@sio.on("answer_call")
async def answer_call(sid, call_id):
clients[sid].call_id = call_id
gunicorn_logger.info(f"ANSWER {sid}: entering room {call_id}")
rooms[call_id] = rooms.get(call_id, [])
if sid not in rooms[call_id] and len(rooms[call_id]) < 2:
rooms[call_id].append(sid)
sio.enter_room(sid, call_id)
else:
gunicorn_logger.info(f"ANSWER {sid}: room {call_id} is full")
# await sio.emit("room_full", room=call_id, to=sid)
# BO - Get call id from dictionary created during socketio connection
client_id = clients[sid].client_id
# BO -> Update Call Record with Callee field based on call_id
gunicorn_logger.warning(f"NOW UPDATING MongoDB RECORD FOR Caller with ID: {client_id} for call: {call_id}")
# BO -> Create Call Record with callee_id field (None for callee, duration, terms..)
request_data = {
"callee_id": client_id
}
response = update_calls(get_collection_calls(), call_id, request_data)
print(response) # BO - print created db call record
@sio.on("incoming_audio")
async def incoming_audio(sid, data, call_id):
try:
clients[sid].add_bytes(data)
if clients[sid].get_length() >= MAX_BYTES_BUFFER:
gunicorn_logger.info('Buffer full, now outputting...')
output_path = clients[sid].output_path
resampled_audio = clients[sid].resample_and_clear()
vad_result = clients[sid].vad_analyse(resampled_audio)
# source lang is speakers tgt language 😃
src_lang = clients[sid].target_language
if vad_result:
gunicorn_logger.info('Speech detected, now processing audio.....')
tgt_sid = next(id for id in rooms[call_id] if id != sid)
tgt_lang = clients[tgt_sid].target_language
# following example from https://github.com/facebookresearch/seamless_communication/blob/main/docs/m4t/README.md#transformers-usage
output_tokens = processor(audios=resampled_audio, src_lang=src_lang, return_tensors="pt", sampling_rate=TARGET_SAMPLING_RATE).to(device)
model_output = model.generate(**output_tokens, tgt_lang=src_lang, generate_speech=False)[0].tolist()[0]
asr_text = processor.decode(model_output, skip_special_tokens=True)
print(f"ASR TEXT = {asr_text}")
# ASR TEXT => ORIGINAL TEXT
if src_lang != tgt_lang:
t2t_tokens = processor(text=asr_text, src_lang=src_lang, tgt_lang=tgt_lang, return_tensors="pt").to(device)
translated_data = model.generate(**t2t_tokens, tgt_lang=tgt_lang, generate_speech=False)[0].tolist()[0]
translated_text = processor.decode(translated_data, skip_special_tokens=True)
print(f"TRANSLATED TEXT = {translated_text}")
else:
# PM - both users have same language selected, no need to translate
translated_text = asr_text
# PM - text_output is a list with 1 string
await send_translated_text(clients[sid].client_id, clients[sid].username, asr_text, translated_text, call_id)
# BO -> send translated_text to mongodb as caption record update based on call_id
await send_captions(clients[sid].client_id, clients[sid].username, asr_text, translated_text, call_id)
except Exception as e:
gunicorn_logger.error(f"Error in incoming_audio: {e.with_traceback()}")
async def send_captions(client_id, username, original_text, translated_text, call_id):
# BO -> Update Call Record with Callee field based on call_id
print(f"Now updating Caption field in call record for Caller with ID: {client_id} for call: {call_id}")
data = {
"author_id": str(client_id),
"author_username": str(username),
"original_text": str(original_text),
"translated_text": str(translated_text),
"timestamp": str(datetime.now())
}
response = update_captions(get_collection_calls(), get_collection_users(), call_id, data)
return response
app.mount("/", socketio_app)
if __name__ == '__main__':
uvicorn.run("main:app", host='0.0.0.0', port=7860, log_level="info")
# Running in Docker Container
if __name__ != "__main__":
fastapi_logger.setLevel(gunicorn_logger.level)
else:
fastapi_logger.setLevel(logging.DEBUG)
|