conceptofmind

def topological_sort_nx(files):
    graphs = nx.DiGraph()
    for file in files:
        graphs.add_node(file)

    for fileA in files:
        for fileB in files:
            if has_dependency(fileA, fileB):
                graphs.add_edge(fileB, fileA)

conceptofmind

# coding=utf-8
# Copyright 2022 EleutherAI and the HuggingFace Inc. team. All rights reserved.
#
# This code is based on EleutherAI's GPT-NeoX library and the GPT-NeoX
# and OPT implementations in this library. It has been modified from its
# original forms to accommodate minor architectural differences compared
# to GPT-NeoX and OPT used by the Meta AI team that trained the model.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.

conceptofmind

import torch
from datasets import load_dataset
import argparse
import os
import math
import time
import random
import wandb
from huggingface_hub import HfApi, HfFolder
from huggingface_hub.utils._errors import HfHubHTTPError

conceptofmind

import re
from my_secret_keys import api_key, cse_id
from googleapiclient.discovery import build
from fuzzywuzzy import fuzz
from playwright.sync_api import sync_playwright

# get the google search api result

def google_search(input_query: str, api_key: str, cse_id: str):
    num_results = 3

conceptofmind

import torch
from datasets import load_dataset
import argparse
import os
import math
from itertools import chain
from datetime import timedelta
from torch.utils.data import DataLoader
from accelerate import Accelerator
from accelerate.utils import (DummyOptim, DummyScheduler,

conceptofmind

import re
import nltk
import ftfy
import multiprocessing
from datasets import load_dataset
from langdetect import detect_langs
from nltk.tokenize import sent_tokenize, word_tokenize

nltk.download("punkt")

conceptofmind

[
  {
    "generated_text": " the trainz frorum. A little bit more patience to iron out little critters and cracks by the N3V crew. they have a mountain of routes [Retrieval( \"Glad Roy\")] from me to get ready so give them credit and energy to get things done the soonest and well.\n",
    "index": 32,
    "Retrieval": [
      "Thanks Roy. yes when you purchase my routes it will show you what to dowload for eg.",
      "Thanks a million Roy! You are a wonderful and patient support.",
      "Roy you're awesome! I just finished installing \"Rogers Pass\" and I am in shock at how beautiful the route looks in TS12."
    ],
    "Generated": "\n the trainz frorum. A little bit more patience to iron out little critters and cracks by the N3V crew. they have a mountain of routes [Retrieval( \"Glad Roy\")] from me to get ready so give them credit and energy to get things done the soonest and well.\n",

conceptofmind

import os
import pandas as pd
from tqdm import tqdm
from IPython.display import display 
from langchain.llms import OpenAI
from langchain.prompts import PromptTemplate, FewShotPromptTemplate
from langchain.chains import LLMChain
from utils import evaluate, ColBERTv2
from langchain.agents import initialize_agent, Tool, ZeroShotAgent, ConversationalAgent, AgentExecutor
from langchain import GoogleSearchAPIWrapper

conceptofmind

import torch
from torch import nn
import torch.nn.functional as F

import math

from einops import rearrange

def exists(val):
    return val is not None

conceptofmind

import gzip
import hashlib
import json
import multiprocessing
import os
import shutil
import time
import re
from pathlib import Path