bkw777

# minimal example just for reference, not pointful by itself
# binary-safe read/write file without cp/cat/dd etc, pure bash, no subshell
 while LANG=C IFS= read -d '' -r -n 1 x ;do printf '%c' "$x" ;done <bin1 >bin2

kickingvegas

cc/org-table-to-sqlite

Org Babel code block to import an Org table into an in-memory SQLite DB to enable SQL queries on aforementioned table.

Parameters

• table : Org table object The Org table object is referenced via the #+NAME value assigned to the table. The table must have a header row identifying each column. This name value must be a SQL-legal name.
• table-name : string Name of table in string form. It must be identical to the name of the table parameter above.

thistleknot

import openai
import os
import sqlite3
import numpy as np
from sklearn.neighbors import NearestNeighbors
from sentence_transformers import SentenceTransformer
from datasets import load_dataset
import pandas as pd
from gptcache import cache
#from gptcache.adapter import openai

dgicloud

import requests
from requests.exceptions import RequestException
import json

#pegando lista de proxy via api
def proxy_scrap():
    url = "https://api.proxyscrape.com/v2/?request=displayproxies&protocol=socks5&timeout=10000&country=all&ssl=yes&anonymity=all"
    payload={}
    headers = {}
    response = requests.request("GET", url, headers=headers, data=payload)

wesslen

import os
import json
import typer

app = typer.Typer()

def process_scripts(input_prompts_file: str, scripts_folder: str, output_file: str):
    output_data = []

    # Read input prompts from the .jsonl file

CGamesPlay

greencamp20552

import os
import openai

def init_api():
 with open(".env") as env:
     for line in env:
       key, value = line.strip().split("=")
       os.environ[key] = value

openai.api_key = os.environ.get("API_KEY")

MokoSan

from langchain.document_loaders import YoutubeLoader
from langchain.indexes import VectorstoreIndexCreator
loader = YoutubeLoader.from_youtube_url("https://www.youtube.com/watch?v=2v6TpRE82Ps", add_video_info=False)
index = VectorstoreIndexCreator().from_loaders([loader])
query = "What are some top spots to visit in Montepulciano?"
index.query(query)

mohameddhaoui

import re
import uuid
from datetime import datetime
from typing import List, Optional

from pydantic import UUID4, BaseModel, EmailStr, StrictStr, validator
from sqlmodel import Boolean, Column, DateTime, Field, SQLModel


class TimestampsMixin(BaseModel):

hwchase17

from langchain.chat_models import ChatOpenAI
from pydantic import BaseModel, Field
from langchain.document_loaders import UnstructuredURLLoader
from langchain.chains.openai_functions import create_extraction_chain_pydantic

class LLMItem(BaseModel):
    title: str = Field(description="The simple and concise title of the product")
    description: str = Field(description="The description of the product")

def main():