2good4hisowngood

# Define file types by category
$documentExtensions = @('.doc', '.docx', '.odt', '.rtf', '.txt', '.pdf', '.pages', '.xls', '.xlsx', '.ods', '.csv', '.ppt', '.pptx', '.odp', '.key', '.one', '.enex')
$photoExtensions = @('.jpg', '.jpeg', '.png', '.gif', '.bmp', '.tif', '.tiff', '.raw', '.cr2', '.nef', '.orf', '.sr2')
$videoExtensions = @('.mp4', '.mov', '.avi', '.wmv', '.mkv', '.flv', '.mpeg', '.mpg', '.hevc', '.h265', '.m2ts', '.vob')
$musicExtensions = @('.mp3', '.wav', '.aac', '.flac', '.ogg', '.m4a', '.wma', '.ape', '.alac')

# Combine all extensions for easier processing
$allExtensions = $documentExtensions + $photoExtensions + $videoExtensions + $musicExtensions

# Define directories to exclude

2good4hisowngood

# BabyAGI User Guide
# This notebook demonstrates how to implement BabyAGI by Yohei Nakajima. BabyAGI is an AI agent that can generate and pretend to execute tasks based on a given objective.
# This guide will help you understand the components to create your own recursive agents.
# Although BabyAGI uses specific vectorstores/model providers (Pinecone, OpenAI), one of the benefits of implementing it with LangChain is that you can easily swap those out for different options. In this implementation we use a FAISS vectorstore (because it runs locally and is free).

import os, langchain, faiss
from collections import deque
from typing import Dict, List, Optional, Any
from langchain import PromptTemplate, LLMChain
from langchain.callbacks.manager import CallbackManager

2good4hisowngood

2good4hisowngood

kind: Deployment
apiVersion: apps/v1
metadata:
  name: nfs-client-provisioner
spec:
  selector:
    matchLabels:
      app: nfs-client-provisioner
  replicas: 1
  strategy: