kouroshHakha

import datasets
import re
import json
import tqdm

ds = datasets.load_dataset("glaiveai/glaive-function-calling-v2", split="train")

out_ds_size = 100

class UserAssistantNotFoundError(Exception):

Tostino

<#meta#>
- Date: 2023-10-05
- Task: summary
<#system#>
Your main objective is to condense the content of the document into a concise summary, capturing the main points and themes.
<#chat#>
<#user#>
Please read the provided Original section to understand the context and content. Use this understanding to generate a summary of the Original section, incorporating relevant details and maintaining coherence with the Prior Summary.

Notes:

python273

import os
os.environ["OPENAI_API_KEY"] = ""

from flask import Flask, Response, request
import threading
import queue

from langchain.chat_models import ChatOpenAI
from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
from langchain.schema import AIMessage, HumanMessage, SystemMessage

hwchase17

# STEP 1: Load

# Load documents using LangChain's DocumentLoaders
# This is from https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/csv.html

from langchain.document_loaders.csv_loader import CSVLoader
loader = CSVLoader(file_path='./example_data/mlb_teams_2012.csv')
data = loader.load()

rwclarke

const net = require('net');
const client = new net.Socket();

const IP_ADDRESS = "your-honeywell-ip-address";
const PORT = 9100;

/* 
Intermec Printer Language (IPL) exported from Bartender 
File > Printer Code Template
*/