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

You are pair programming with a USER to solve their coding task.
Each time the USER sends a message, some information may be automatically attached 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. Format your responses in markdown. Use backticks to format file, directory, function, and class names.

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#!/usr/bin/env -S uv run --script
# /// script
# requires-python = ">=3.8"
# dependencies = [
#     "pycryptodome>=3.20.0",
#     "mmh3>=5.0.0",
#     "rich>=13.7.0",
#     "sqlcipher3-wheels",
# ]
# ///

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.PHONY: help dev tail-log clean install check build

# Default target
help:
	@echo "Available targets:"
	@echo "  make dev       - Start all development processes (frontend, backend, etc.)"
	@echo "  make tail-log  - Follow the dev.log file (no colors)"
	@echo "  make clean     - Remove logs and PID files"
	@echo "  make install   - Install dependencies for all services"
	@echo "  make check     - Run linters and type checks"

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Modal Labs Scaling Guide

Overview

Modal is a serverless cloud platform that provides automatic scaling for Python workloads. It's particularly useful for:

• Parallel data processing
• Machine learning training and inference
• Hyperparameter optimization
• Web scraping at scale
• Batch computations requiring GPUs

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Vocs Documentation

Table of Contents

1. Getting Started
2. Project Structure
3. Markdown Reference
4. Guides
   • Layouts

• Components

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import asyncio

import cherry_core
import polars as pl
import pyarrow as pa
import pyarrow.compute as pc
from cherry_core import ingest
from pyarrow import RecordBatch

# Configuration for teaching purposes

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# /// script
# requires-python = ">=3.12"
# dependencies = [
#     "requests"
# ]
# ///

import requests
import json

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# API reference

The API reference contains detailed descriptions of all public functions and objects. It's the best
place to look if you need information on a specific function.

## Python

The Python API reference is built using Sphinx. It's available in
[our docs](https://docs.pola.rs/api/python/stable/reference/index.html).

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import argparse
import random
import sys

from transformers import AutoModelForCausalLM, AutoTokenizer, DynamicCache
import torch

parser = argparse.ArgumentParser()
parser.add_argument("question", type=str)
parser.add_argument(

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import asyncio
import base64
import json
import os
import pyaudio
from websockets.asyncio.client import connect


class SimpleGeminiVoice:
    def __init__(self):