{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "c730c5b4",
   "metadata": {},
   "source": [
    "# SimpleSequentialChain\n",
    "In this series of chains, each individual chain has a single input and a single output, and the output of one step is used as input to the next."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f65a100b",
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install openai\n",
    "!pip install langchain"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "454013f3",
   "metadata": {},
   "outputs": [],
   "source": [
    "%env OPENAI_API_TYPE=azure\n",
    "%env OPENAI_API_VERSION=2022-12-01\n",
    "%env OPENAI_API_BASE=\n",
    "%env OPENAI_API_KEY="
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c8c0d462",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain import PromptTemplate, LLMChain\n",
    "from langchain.llms import AzureOpenAI\n",
    "azllm=AzureOpenAI(deployment_name=\"test-text-davinci\", model_name=\"text-davinci-003\", temperature=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "af343423",
   "metadata": {},
   "outputs": [],
   "source": [
    "# This is an LLMChain to write a synopsis given a title of a play.\n",
    "template = \"\"\"You are a playwright. Given the title of play, it is your job to write a synopsis for that title.\n",
    "\n",
    "Title: {title}\n",
    "Playwright: This is a synopsis for the above play:\"\"\"\n",
    "prompt_template = PromptTemplate(input_variables=[\"title\"], template=template)\n",
    "synopsis_chain = LLMChain(llm=azllm, prompt=prompt_template)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8dddc018",
   "metadata": {},
   "outputs": [],
   "source": [
    "# This is an LLMChain to write a review of a play given a synopsis.\n",
    "template = \"\"\"You are a play critic from the New York Times. Given the synopsis of play, it is your job to write a review for that play.\n",
    "\n",
    "Play Synopsis:\n",
    "{synopsis}\n",
    "Review from a New York Times play critic of the above play:\"\"\"\n",
    "prompt_template = PromptTemplate(input_variables=[\"synopsis\"], template=template)\n",
    "review_chain = LLMChain(llm=azllm, prompt=prompt_template)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "06767f4a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# This is the overall chain where we run these two chains in sequence.\n",
    "from langchain.chains import SimpleSequentialChain\n",
    "overall_chain = SimpleSequentialChain(chains=[synopsis_chain, review_chain], verbose=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c4e4a202",
   "metadata": {},
   "outputs": [],
   "source": [
    "review = overall_chain.run(\"Tragedy at sunset on the beach\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f1327102",
   "metadata": {},
   "outputs": [],
   "source": [
    "print(review)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b2119bbf",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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