vikramsoni2

import { defineStore } from 'pinia';

export const useUppyStore = defineStore({
  id: 'uppyStore',
  state: () => ({
    state: {}
  }),

  actions: {
    

vikramsoni2

from logging.config import ConvertingList, ConvertingDict, valid_ident
from logging.handlers import QueueHandler, QueueListener
from queue import Queue
import atexit
import logging


def _resolve_handlers(l):
    if not isinstance(l, ConvertingList):
        return l

vikramsoni2

<script setup>
const props = defineProps({
    progress: {
      type: Number,
      default: 0,
    },
})
</script>
<template>   
        <svg  viewBox="-6.25 -6.25 62.5 62.5" version="1.1" xmlns="http://www.w3.org/2000/svg" style="transform:rotate(-90deg)">

vikramsoni2

import os
import openai
import random

# Initialize OpenAI API
openai.api_key = os.getenv("OPENAI_API_KEY")  # Alternative: Use environment variable
if openai.api_key is None:
    raise Exception("No OpenAI API key found. Please set it as an environment variable or in main.py")

# Function to generate queries using OpenAI's ChatGPT

vikramsoni2

#pip install git+https://github.com/huggingface/transformers.git

import datetime
import sys
from transformers import pipeline
from transformers.pipelines.audio_utils import ffmpeg_microphone_live

pipe = pipeline("automatic-speech-recognition", model="openai/whisper-base", device=0)
sampling_rate = pipe.feature_extractor.sampling_rate

vikramsoni2

"BAX": {

        "Slide9Unwanted_0": "The topics of interest about the company's outlook and prospects discussed in the question-and-answer session include:",
        "Slide9Unwanted_1": "Some GPO contracts are coming up for renewal, with negotiations to reflect current costs that have increased in recent years.",
        "Slide9Unwanted_2": "Temporary price increases during recent periods will be rolling off.",
        "Slide9Unwanted_3": "Sequential improvement in bottom line will continue into 2024.",
        "Slide9Unwanted_4": "Expectations for 2024 growth are around market expectations, with mid to long term expectations of 4% to 5%.",
        "Slide9Unwanted_5": "New product launches from 2023 into 2024 in the pharmaceutical business.",
        "Slide9Unwanted_6": "Significant progress in the proposed spin-off of the Kidney Care segment into its own company, Vantive.",
        "Slide9Unwanted_7": "Significant operational efficiencies have been put in place, primarily in logistics and transportation an

vikramsoni2

import numpy as np
from pydantic import BaseModel
from utils.config import Config
from utils.models import ChatMessage
from tokenizers import Tokenizer
from typing import Dict, List, Optional, Union, Literal

DEFAULT_TOKEN_LIMIT_RATIO  = 0.75
DEFAULT_TOKENIZER = Tokenizer.from_pretrained(Config.LLAMA_MODEL)

vikramsoni2

"""QA Chatbot streaming using FastAPI, LangChain Expression Language , OpenAI, and Chroma.

Features
--------
- Persistent Chat Memory:
    Stores chat history in a local file.
- Persistent Vector Store:
    Stores document embeddings in a local vector store.
- Standalone Question Generation:
    Rephrases follow-up questions to standalone questions in their original language.

vikramsoni2

[Unit]
Description=WG-Easy Service
After=network.target

[Service]
ExecStart=/usr/bin/node /app/server.js
WorkingDirectory=/app
Restart=always
User=root
Group=nogroup

vikramsoni2

apt-get update && apt-get -y upgrade
apt-get install -y wireguard-tools dumb-init git

#Install NodeJS
curl -sL https://deb.nodesource.com/setup_16.x | bash -
apt-get update && apt-get -y upgrade
apt -y install nodejs

#Install WG Easy
git clone https://github.com/WeeJeWel/wg-easy WGEASY