Update backend/main.py

backend/main.py

@@ -1,368 +1,348 @@
-# 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
-# # sys.path.append('/Users/benolojo/DCU/CA4/ca400_FinalYearProject/2024-ca400-olojob2-majdap2/src/backend/')
-
-# 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.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
-# #----------------------------------
-# # base seamless imports
-# # --------------------------------- 
-# 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']
-
-# # Set transformers cache
-# # os.environ['HF_HOME'] = './.cache/'
-# # os.environ['SENTENCE_TRANSFORMERS_HOME'] = './.cache'
-
-# # 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)
+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
+# sys.path.append('/Users/benolojo/DCU/CA4/ca400_FinalYearProject/2024-ca400-olojob2-majdap2/src/backend/')
+
+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.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
+#----------------------------------
+# base seamless imports
+# --------------------------------- 
+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']
+
+# Set transformers cache
+# os.environ['HF_HOME'] = './.cache/'
+# os.environ['SENTENCE_TRANSFORMERS_HOME'] = './.cache'
+
+# 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
+    yield
+
+    # shutdown logic
+    print("Closing MongoDB Connection...")
+    app.mongodb_client.close()
 
-#     # shutdown logic
-#     print("Closing MongoDB Connection...")
-#     app.mongodb_client.close()
+app = FastAPI(lifespan=lifespan, logger=gunicorn_logger)
 
-# 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=["*"],
+)
 
-# # 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
 
-# app.include_router(api_router) # include routers for user, calls and transcripts operations
+DEBUG = True
 
-# DEBUG = True
+ESCAPE_HATCH_SERVER_LOCK_RELEASE_NAME = "remove_server_lock"
 
-# ESCAPE_HATCH_SERVER_LOCK_RELEASE_NAME = "remove_server_lock"
+TARGET_SAMPLING_RATE = 16000
+MAX_BYTES_BUFFER = 480_000
 
-# TARGET_SAMPLING_RATE = 16000
-# MAX_BYTES_BUFFER = 480_000
+print("")
+print("")
+print("=" * 20 + " ⭐️ Starting Server... ⭐️ " + "=" * 20)
 
-# print("")
-# print("")
-# print("=" * 20 + " ⭐️ Starting Server... ⭐️ " + "=" * 20)
+###############################################
+# Configure socketio server
+###############################################
 
-# ###############################################
-# # 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", force_download=True)
+#cache_dir="/.cache"
+
+# PM - hardcoding temporarily as my GPU doesnt have enough vram
+# model = SeamlessM4Tv2Model.from_pretrained("facebook/seamless-m4t-v2-large").to("cpu")
+model = SeamlessM4Tv2Model.from_pretrained("facebook/seamless-m4t-v2-large", force_download=True).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"]
+    return app.database["call_test"]
+
+
+@app.get("/test/", response_description="Welcome User")
+def test():
+
+    return {"message": "Welcome to InterpreTalk!"}
+
+
+@app.post("/test_post/", response_description="List more test call records")
+def test_post():
+    request_data = {
+        "call_id": "TESTID000001"
+    }
+
+    result = create_calls(get_collection_calls(), request_data)
+
+    # return {"message": "Welcome to InterpreTalk!"}
+    return result
+
+@app.put("/test_put/", response_description="List test call records")
+def test_put():
+
+    # result = list_calls(get_collection_calls(), 100)
+    # result = send_captions("TEST", "TEST", "TEST", "oUjUxTYTQFVVjEarIcZ0")
+    result = send_captions("TEST", "TEST", "TEST", "TESTID000001")
+
+    print(result)
+    return result
+
+
+async def send_translated_text(client_id, original_text, translated_text, room_id):
+    print('SEND_TRANSLATED_TEXT IS WOKRING IN FASTAPI BACKEND...')
+    print(rooms)
+    print(clients)
+
+    data = {
+        "author": 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}")
+    # sid = socketid, client_id = client specific ID ,always the same for same user
+    clients[sid] = Client(sid, client_id)
+    gunicorn_logger.warning(f"Client connected: {sid}")
+    gunicorn_logger.warning(clients)
+
+@sio.on("disconnect")
+async def disconnect(sid): # BO - also pass call id as parameter for updating MongoDB
+    gunicorn_logger.debug(f"📤 [event: disconnected] sid={sid}")
+    clients.pop(sid, None)
+    # BO -> Update Call record with call duration, key terms
+
+@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)
 
-# # 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", force_download=True)
-# #cache_dir="/.cache"
-
-# # PM - hardcoding temporarily as my GPU doesnt have enough vram
-# # model = SeamlessM4Tv2Model.from_pretrained("facebook/seamless-m4t-v2-large").to("cpu")
-# # model = SeamlessM4Tv2Model.from_pretrained("facebook/seamless-m4t-v2-large", force_download=True).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 = {}
-
-# import torch
-# from transformers import pipeline
-# translator = pipeline("automatic-speech-recognition",
-#                       "facebook/seamless-m4t-v2-large",
-#                       torch_dtype=torch.float32,
-#                       device="cpu")
-
-# converter = pipeline("translation",
-#                       "facebook/seamless-m4t-v2-large",
-#                       torch_dtype=torch.float32,
-#                       device="cpu")
-
-
-# def get_collection_users():
-#     return app.database["user_records"]
-
-# def get_collection_calls():
-#     # return app.database["call_records"]
-#     return app.database["call_test"]
-
-
-# @app.get("/test/", response_description="Welcome User")
-# def test():
-
-#     return {"message": "Welcome to InterpreTalk!"}
-
-
-# @app.post("/test_post/", response_description="List more test call records")
-# def test_post():
-#     request_data = {
-#         "call_id": "TESTID000001"
-#     }
-
-#     result = create_calls(get_collection_calls(), request_data)
-
-#     # return {"message": "Welcome to InterpreTalk!"}
-#     return result
-
-# @app.put("/test_put/", response_description="List test call records")
-# def test_put():
-
-#     # result = list_calls(get_collection_calls(), 100)
-#     # result = send_captions("TEST", "TEST", "TEST", "oUjUxTYTQFVVjEarIcZ0")
-#     result = send_captions("TEST", "TEST", "TEST", "TESTID000001")
-
-#     print(result)
-#     return result
-
-
-# async def send_translated_text(client_id, original_text, translated_text, room_id):
-#     print('SEND_TRANSLATED_TEXT IS WOKRING IN FASTAPI BACKEND...')
-#     print(rooms)
-#     print(clients)
-
-#     data = {
-#         "author": 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}")
-#     # sid = socketid, client_id = client specific ID ,always the same for same user
-#     clients[sid] = Client(sid, client_id)
-#     gunicorn_logger.warning(f"Client connected: {sid}")
-#     gunicorn_logger.warning(clients)
-
-# @sio.on("disconnect")
-# async def disconnect(sid): # BO - also pass call id as parameter for updating MongoDB
-#     gunicorn_logger.debug(f"📤 [event: disconnected] sid={sid}")
-#     clients.pop(sid, None)
-#     # BO -> Update Call record with call duration, key terms
-
-# @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
+    # # 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
+    # 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
+    # # 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
-#             vad_result, resampled_audio = clients[sid].resample_and_write_to_file()
-#             # 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")
-#                 # 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)
-#                 asr_text = translator(resampled_audio, generate_kwargs={"tgt_lang": src_lang})['text']
-#                 print(f"ASR TEXT = {asr_text}")
-#                 # ASR TEXT => ORIGINAL TEXT
-
-#                 # t2t_tokens = processor(text=asr_text, src_lang=src_lang, tgt_lang=tgt_lang, return_tensors="pt")
-#                 # print(f"FIRST TYPE = {type(output_tokens)}, SECOND TYPE = {type(t2t_tokens)}")
-#                 # 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)
-#                 translated_text = converter(asr_text, src_lang=src_lang, tgt_lang=tgt_lang)
-#                 print(f"TRANSLATED TEXT = {translated_text}")
-
-#                 # BO -> send translated_text to mongodb as caption record update based on call_id
-#                 # send_captions(clients[sid].client_id, asr_text, translated_text, call_id)
+@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
+            vad_result, resampled_audio = clients[sid].resample_and_write_to_file()
+            # 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")
+                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
+
+                t2t_tokens = processor(text=asr_text, src_lang=src_lang, tgt_lang=tgt_lang, return_tensors="pt")
+                print(f"FIRST TYPE = {type(output_tokens)}, SECOND TYPE = {type(t2t_tokens)}")
+                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}")
+
+                # BO -> send translated_text to mongodb as caption record update based on call_id
+                # send_captions(clients[sid].client_id, asr_text, translated_text, call_id)
                 
-#                 # TRANSLATED TEXT
-#                 # PM - text_output is a list with 1 string
-#                 await send_translated_text(clients[sid].client_id, asr_text, translated_text, call_id)
+                # TRANSLATED TEXT
+                # PM - text_output is a list with 1 string
+                await send_translated_text(clients[sid].client_id, asr_text, translated_text, call_id)
 
-#                 # # BO -> send translated_text to mongodb as caption record update based on call_id
-#                 # send_captions(clients[sid].client_id, asr_text, translated_text, call_id)
+                # # BO -> send translated_text to mongodb as caption record update based on call_id
+                # send_captions(clients[sid].client_id, asr_text, translated_text, call_id)
 
-#     except Exception as e:
-#         gunicorn_logger.error(f"Error in incoming_audio: {e.with_traceback()}")
+    except Exception as e:
+        gunicorn_logger.error(f"Error in incoming_audio: {e.with_traceback()}")
     
-# def send_captions(client_id, 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": str(client_id),
-#         "original_text": str(original_text),
-#         "translated_text": str(translated_text),
-#         "timestamp": str(datetime.now())
-#     }
-
-#     response =  update_captions(get_collection_calls(), 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="debug")
-
-# # Running in Docker Container
-# if __name__ != "__main__":
-#     fastapi_logger.setLevel(gunicorn_logger.level)
-# else:
-#     fastapi_logger.setLevel(logging.DEBUG)
-
-from huggingface_hub import scan_cache_dir
-
-hf_cache_info = scan_cache_dir()
-
-print(hf_cache_info)
+def send_captions(client_id, 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": str(client_id),
+        "original_text": str(original_text),
+        "translated_text": str(translated_text),
+        "timestamp": str(datetime.now())
+    }
+
+    response =  update_captions(get_collection_calls(), call_id, data)
+    return response
+
+app.mount("/", socketio_app)
+
+if __name__ == '__main__':
+    uvicorn.run("main:app", host='127.0.0.1', port=8080, log_level="info")
+
+# Running in Docker Container
+if __name__ != "__main__":
+    fastapi_logger.setLevel(gunicorn_logger.level)
+else:
+    fastapi_logger.setLevel(logging.DEBUG)