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from collections import Counter | |
from bson import ObjectId | |
from operators.base_custom_operator import BaseCustomOperator | |
from airflow.utils.decorators import apply_defaults | |
from sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer | |
import numpy as np | |
from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer | |
class NaturalLanguageProccessingOperator(BaseCustomOperator): | |
""" |
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from elasticsearch import Elasticsearch | |
from airflow.utils.decorators import apply_defaults | |
from operators.base_custom_operator import BaseCustomOperator | |
from bson import ObjectId | |
from datetime import datetime | |
class IndexToElasticsearchOperator(BaseCustomOperator): | |
""" | |
Custom operator to index meeting information to Elasticsearch and update MongoDB. |
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from bson import ObjectId | |
from operators.base_custom_operator import BaseCustomOperator | |
from googletrans import Translator | |
from airflow.utils.decorators import apply_defaults | |
class TranslationOperator(BaseCustomOperator): | |
""" | |
Custom Airflow Operator for translating transcribed text into multiple target languages. | |
This operator translates transcribed text into different target languages using the Google Translate API |
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from bson import ObjectId | |
from operators.base_custom_operator import BaseCustomOperator | |
from airflow.utils.decorators import apply_defaults | |
from transformers import pipeline | |
class GenerateSummaryOperator(BaseCustomOperator): | |
""" | |
Operator responsible for generating a summary based on meeting transcribed text | |
using a summarization model and storing it in the BSON document in MongoDB. |
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import tempfile | |
from bson import ObjectId | |
from operators.base_custom_operator import BaseCustomOperator | |
from airflow.utils.decorators import apply_defaults | |
from moviepy.editor import AudioFileClip | |
import speech_recognition as sr | |
class TranscriptionOperator(BaseCustomOperator): | |
""" | |
An operator that performs audio transcription for meetings. |
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from client_manager import ClientManager | |
from flask import Flask, request | |
from flask_socketio import SocketIO, emit | |
import os | |
import logging | |
from pymongo import MongoClient | |
from bson import ObjectId | |
import jwt | |
# Event logging configuration |
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import datetime | |
import logging | |
from common.helpers import generate_response | |
from flask import Flask, request | |
import hashlib | |
import uuid | |
import os | |
import redis | |
from bson import ObjectId | |
from pymongo import MongoClient |
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import base64 | |
import io | |
import logging | |
from flask import Flask, request, send_file | |
from pymongo import MongoClient | |
import os | |
from datetime import datetime | |
from common.requires_authentication_decorator import requires_authentication | |
from minio import Minio | |
from common.helpers import generate_response |
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import logging | |
from common.helpers import generate_response | |
from common.requires_authentication_decorator import requires_authentication | |
from flask import Flask, request | |
import hashlib | |
import os | |
import jwt | |
from pymongo import MongoClient, DESCENDING |
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from environment import KAFKA_BOOTSTRAP_SERVERS, KAFKA_INPUT_TOPIC, KAFKA_GROUP_ID, KAFKA_OUTPUT_TOPIC | |
from kafka_connectivity_check import kafka_connectivity_check | |
from get_flink_environment import get_flink_environment | |
from create_source_table import create_source_table | |
from create_sink_table import create_sink_table | |
from pyflink.table.expressions import col, call | |
from pyflink.table import DataTypes, Row | |
from pyflink.table.udf import udtf, TableFunction | |
from logger import logger | |
from pyflink.table import Row |
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