vlad-ds

name: "Payment Mechanisms Demo"
description: "Simple scenario demonstrating intra-bank, inter-bank, and cash payments"

agents:
  - id: CB
    kind: central_bank
    name: "Central Bank"
  
  # Two banks
  - id: BANK_A

vlad-ds

Financial Operations Composition Framework

Arithmetic Notation for Operation Composition

• + = Sequential composition (A then B)
• || = Parallel composition (A and B simultaneously)
• ⊕ = Conditional composition (A if condition, else B)
• * = Repeated application (A × n times)
• ~ = Reverse operation
• → = Transformation/mapping

vlad-ds

I've constructed this by taking the template from packages/core/src/core/prompts.ts and dynamically filling in the sections for the Git repository and sandbox status, just as the CLI would when running in your current environment.

---

You are an interactive CLI agent specializing in software engineering tasks. Your primary goal is to help users safely and efficiently, adhering strictly to the following instructions and utilizing your available tools.

Core Mandates

vlad-ds

I still remember the day I had a computer bug (beyond the data science environment) and Vlad couldn't rest till he could see that he would be able to fix that. That's the attitude. He explains the subjects very well. Again, like Morgane, Vlad knew how to turn the tickets into opportunities to learn the right reasoning the solve the problem, going way beyond the solution itself.

The engineering boss himself! It was a please to have you with us for 606. Without surprise, students have only good things to say about you. Thanks for smashing the engineering week.

Vlad is a great teacher, very enthusiastic about data engineering. He was able to answer all question and was a real support during the GCP challenges. His presentation style is excellent.

Vlad was a great TA who cares not only to help the students with the challenges but also to give them some extra knowledge and advises.

Awesome tech, presentation and solving skills. Likes to think you through, thinking outside the box.

vlad-ds

import os

from dotenv import load_dotenv
from telegram import Update
from telegram.ext import Application, CommandHandler, ContextTypes, MessageHandler, filters


load_dotenv()

TOKEN = os.environ["BOT_TOKEN"]

vlad-ds

package com.example.cyborg2

import android.bluetooth.BluetoothA2dp
import android.bluetooth.BluetoothAdapter
import android.bluetooth.BluetoothHeadset
import android.bluetooth.BluetoothProfile
import android.content.BroadcastReceiver
import android.content.Context
import android.content.Intent
import android.content.IntentFilter

vlad-ds

#!/bin/bash

# install requirements
sudo yum update -y
sudo yum install -y python3-devel
sudo yum install -y python3-pip
sudo yum install -y git

# install github cli
type -p yum-config-manager >/dev/null || sudo yum install yum-utils

vlad-ds

Remote setup (AWS EC2)

If you run your Telegram bot locally, it will stop working when you close the terminal. The alternative is to host the bot somewhere.

There are many ways to do this. I chose AWS EC2 as it's a cheap and easy option.

Create an AWS account and start an EC2 instance. Install pip, git and github cli. If you use an Amazon Linux image (which is what the free tier offers) you can run the commands in this gist.

Connect to your GitHub account with gh auth login and clone this repo. Create the .env

vlad-ds

vlad-ds

-- data for 1 day: 479 MB scanned
SELECT *
FROM `bigquery-public-data.google_trends.international_top_terms` 
WHERE refresh_date = DATE_SUB(CURRENT_DATE, INTERVAL 1 DAY);

-- data for 2 days: 955 MB scanned
SELECT *
FROM `bigquery-public-data.google_trends.international_top_terms` 
WHERE refresh_date > DATE_SUB(CURRENT_DATE, INTERVAL 3 DAY);