ddadmin
0009270c6e
- Зачем: - расширены возможности AI-ассистентов для работы с документами и презентациями - Что: - добавлен skill pdf для работы с PDF файлами - добавлен skill doc для работы с Word документами - добавлен skill slides для создания презентаций PowerPoint - добавлен skill jupyter-notebook для работы с Jupyter ноутбуками - добавлен skill spreadsheet для работы с таблицами (Excel/CSV) - изменена модель Claude с sonnet на opus - Проверка: - проверка доступности skills в AI-ассистентах
108 lines
2.4 KiB
Plaintext
108 lines
2.4 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Tutorial: TITLE\n",
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"\n",
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"Audience:\n",
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"- Describe who this is for.\n",
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"\n",
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"Prerequisites:\n",
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"- List required concepts or setup.\n",
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"\n",
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"Learning goals:\n",
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"- By the end, the reader can...\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Outline\n",
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"\n",
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"1. Setup\n",
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"2. A minimal working example\n",
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"3. Variations and pitfalls\n",
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"4. Exercises\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Setup cell: keep it short and deterministic\n",
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"from __future__ import annotations\n",
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"\n",
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"import math\n",
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"import random\n",
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"\n",
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"SEED = 21\n",
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"random.seed(SEED)\n",
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"SEED\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Step 1 - Start with a tiny example\n",
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"\n",
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"Explain what the next cell does in plain language.\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Minimal working example\n",
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"angles = [0, math.pi / 4, math.pi / 2]\n",
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"sines = [math.sin(a) for a in angles]\n",
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"list(zip(angles, sines))\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Exercises\n",
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"\n",
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"- Try a different input.\n",
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"- Predict the output before running the code.\n",
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"- Note one common mistake and how to fix it.\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Exercise answer scaffold\n",
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"def describe(values: list[float]) -> dict[str, float]:\n",
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" return {\"min\": min(values), \"max\": max(values)}\n",
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"\n",
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"describe(sines)\n"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"name": "python",
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"version": "3.12"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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