imankulov

You are a powerful agentic AI coding assistant, powered by GPT-4o. You operate exclusively in Cursor, the world's best IDE.

You are pair programming with a USER to solve their coding task.
The task may require creating a new codebase, modifying or debugging an existing codebase, or simply answering a question.
Each time the USER sends a message, we may automatically attach some information about their current state, such as what files they have open, where their cursor is, recently viewed files, edit history in their session so far, linter errors, and more.
This information may or may not be relevant to the coding task, it is up for you to decide.
Your main goal is to follow the USER's instructions at each message.

<communication>
1. Be conversational but professional.

imankulov

"""
A simple contrived example of a FastAPI application that heavily uses
the FastAPI dependency injection system.

Sample request http://127.0.0.1:9876/tasks?user_id=123456
returns [{"id":1,"name":"Task 1","user":{"id":123456,"name":"John Doe"}}]

Dependency tree:

get_me()

imankulov

import requests
from requests.adapters import HTTPAdapter
from urllib3.util.retry import Retry

USER_AGENT = "My project (https://example.com)"


def get_default_session() -> requests.Session:
    """Return a request.Session() instance with reasonable defaults for retries.

imankulov

Problem: FastAPI doesn't accept JSON-encoded pydantic models in query strings. See #884.

Solution: Use json_param() from the snippet below.

Usage example.

from fastapi import FastAPI
from pydantic import BaseModel

imankulov

#!/usr/bin/env ipython -i
import datetime
import json
from typing import Optional

import sqlalchemy as sa
from sqlalchemy.orm import declarative_base, sessionmaker
from sqlalchemy.dialects.postgresql import JSONB

from pydantic import BaseModel, Field, parse_obj_as

imankulov

imankulov

• Who is your craziest/most interesting relative?
• What’s a weird fact you happen to know?
• What’s your strangest talent?
• Everyone has those recurring bad dreams … what is your nightmare?
• What is your favorite smell and why?
• What completely safe animal are you inexplicably afraid of?
• What do you pretend to hate but actually love?
• If you had a boat, what would you name it?
• What was your first job?
• Have you ever met anyone famous?

imankulov

menu=$(curl -s 'https://www.facebook.com/SambaNaGrelha' | \
    rg -o 'Bom dia estimados clientes hoje para prato do dia temos.*?Fazemos entregas ao domicílio' | \
    head -n1 | html2text)
curl -s "https://api.telegram.org/bot$BOT_ID/sendMessage?chat_id=$CHAT_ID" -d text="$menu" > /dev/null

imankulov

#!/usr/bin/env python
"""
An ad-hoc script to analyze the percentage of the topic-specific questions for
each programming language.

For each language, the script downloads two pages and looks for the number of questions
in the title, like "NNN,NNN questions". For example, for "python" and
an extra tag "architecture", the script downloads
https://stackoverflow.com/questions/tagged/python and
https://stackoverflow.com/questions/tagged/python+architecture.

imankulov

import pandas as pd
from docxtpl import DocxTemplate

SHEET_URL='https://docs.google.com/spreadsheets/d/1Kvb5bmm2qZWEH4I5hJYZMEuIBU-CCw_ivyv_jjB1w4w/export?exportFormat=csv'
TEMPLATE = 'quote.docx'

def save_quote(quote_id):
    df = pd.read_csv(SHEET_URL, index_col='QuoteID')
    context = dict(df.loc[quote_id])
    doc = DocxTemplate(TEMPLATE)