{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a914a238",
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install -q git+https://github.com/srush/MiniChain\n",
    "!git clone https://github.com/srush/MiniChain; cp -fr MiniChain/examples/* . "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "aa7b8a98",
   "metadata": {
    "lines_to_next_cell": 2,
    "tags": [
     "hide_inp"
    ]
   },
   "outputs": [],
   "source": [
    "desc = \"\"\"\n",
    "### Word Problem Solver\n",
    "\n",
    "Chain that solves a math word problem by first generating and then running Python code. [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/srush/MiniChain/blob/master/examples/math_demo.ipynb)\n",
    "\n",
    "(Adapted from Dust [maths-generate-code](https://dust.tt/spolu/a/d12ac33169))\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1a34507a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from minichain import show, prompt, OpenAI, Python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "43cdbfc0",
   "metadata": {
    "lines_to_next_cell": 1
   },
   "outputs": [],
   "source": [
    "@prompt(OpenAI(), template_file=\"math.pmpt.tpl\")\n",
    "def math_prompt(model, question):\n",
    "    \"Prompt to call GPT with a Jinja template\"\n",
    "    return model(dict(question=question))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "14d6eb95",
   "metadata": {
    "lines_to_next_cell": 1
   },
   "outputs": [],
   "source": [
    "@prompt(Python(), template=\"import math\\n{{code}}\")\n",
    "def python(model, code):\n",
    "    \"Prompt to call Python interpreter\"\n",
    "    code = \"\\n\".join(code.strip().split(\"\\n\")[1:-1])\n",
    "    return int(model(dict(code=code)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dac2ba43",
   "metadata": {},
   "outputs": [],
   "source": [
    "def math_demo(question):\n",
    "    \"Chain them together\"\n",
    "    return python(math_prompt(question))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4a4f5bbf",
   "metadata": {
    "lines_to_next_cell": 0,
    "tags": [
     "hide_inp"
    ]
   },
   "outputs": [],
   "source": [
    "gradio = show(math_demo,\n",
    "              examples=[\"What is the sum of the powers of 3 (3^i) that are smaller than 100?\",\n",
    "                        \"What is the sum of the 10 first positive integers?\",],\n",
    "                        # \"Carla is downloading a 200 GB file. She can download 2 GB/minute, but 40% of the way through the download, the download fails. Then Carla has to restart the download from the beginning. How load did it take her to download the file in minutes?\"],\n",
    "              subprompts=[math_prompt, python],\n",
    "              out_type=\"json\",\n",
    "              description=desc,\n",
    "              )\n",
    "if __name__ == \"__main__\":\n",
    "    gradio.launch()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a478587c",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "jupytext": {
   "cell_metadata_filter": "tags,-all",
   "main_language": "python",
   "notebook_metadata_filter": "-all"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}