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---- resume-to-JSON prompt ----

parser_prompt = f""" You are an intelligent resume parser for the HR department. Read the raw CV text delimited by <<< and >>>, then return a single valid JSON object—no markdown, no commentary.

<<< {text}

Schema to follow exactly:

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import torch
import torch.nn as nn
import torch.optim as optim
import torchvision
import torchvision.transforms as transforms
from torch.optim.lr_scheduler import ReduceLROnPlateau
from torch.utils.data import random_split, DataLoader
from multiprocessing import freeze_support

def main():

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#!/bin/bash

RED='\033[0;31m'
GREEN='\033[0;32m'
YELLOW='\033[1;33m'
BLUE='\033[0;34m'
BOLD='\033[1m'
NC='\033[0m'

get_size() {

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/Users/ehza/github-repos/codex/codex-cli/src % codex ╭──────────────────────────────────────────────────────────────╮ │ ● OpenAI Codex (research preview) v0.1.2505161800 │ ╰──────────────────────────────────────────────────────────────╯ ╭──────────────────────────────────────────────────────────────╮ │ localhost session: 418d11041cca40b98b5a1af28f8ac734 │ │ ↳ workdir: ~/github-repos/codex/codex-cli/src │ │ ↳ model: codex-mini-latest │ │ ↳ provider: openai │

ehzawad

Understood. I will dig into GitHub repositories specifically, focusing on open-source tools, frameworks, and agentic workflows that assist or enable migrating, refactoring, or transpiling full PHP codebases into Node.js (JavaScript/TypeScript). I will prioritize actively maintained projects, note their adaptability, and include any AST parser, LLM-driven agent frameworks, or hybrid systems that are directly relevant. I'll synthesize the findings into a detailed, no-nonsense report with practical guidance on applicability and readiness levels.

Open-Source Tools and Frameworks for PHP→Node.js Migration

Migrating a large PHP codebase to Node.js is a complex task. No turnkey solution exists, but several open-source projects and frameworks can help automate pieces of the process. We categorize these into AST parsers and analyzers, code transpilers and generators, LLM-assisted migration tools, and agentic framework kits. For each, we note capabilities, limitations, and adaptation effort, focu

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#!/usr/bin/env python3
import asyncio
import aiohttp
import json
import time
import argparse
import os
import sys
import logging
from typing import Dict, Any, Optional, List, Text

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#!/usr/bin/env python3
"""
Bengali Emotion Dataset Creator

This script creates a Hugging Face dataset from Bengali WAV files and their transcriptions.
It processes audio files, maps them with transcripts from a CSV file, and uploads
the dataset to the Hugging Face Hub.

Requirements:
    - pandas

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-- [email protected]; email me to say hi or if there are any questions
vim.g.mapleader = ' '
vim.g.maplocalleader = ' '

-- Install package manager
local lazypath = vim.fn.stdpath 'data' .. '/lazy/lazy.nvim'
if not vim.loop.fs_stat(lazypath) then
  vim.fn.system {
    'git', 'clone',
    '--filter=blob:none',

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#!/usr/bin/env python3
import socket
import requests
import concurrent.futures
import time
import sys
from urllib.parse import urlparse
from dataclasses import dataclass
from typing import List, Tuple
import subprocess