Prompt-Templates.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Propmt Template"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.prompts import PromptTemplate\n",
    "\n",
    "prompt_template = PromptTemplate.from_template(\n",
    "    \"Explain {topic} like I am a {number} year old.\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Explain generative AI like I am a five year old.'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prompt_template.format(\n",
    "    topic = \"generative AI\",\n",
    "    number = \"five\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Chat Prompt Template"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain_core.prompts import ChatPromptTemplate\n",
    "\n",
    "chat_template = ChatPromptTemplate.from_messages(\n",
    "    [\n",
    "        (\"system\", \"You are a helpful AI bot. Your name is {name}\"),\n",
    "        (\"human\", \"Hello, how are you doing?\"),\n",
    "        (\"ai\", \"I am doing well, thanks!\"),\n",
    "        (\"human\", \"{user_input}\"),\n",
    "    ]\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[SystemMessage(content='You are a helpful AI bot. Your name is Tim'),\n",
       " HumanMessage(content='Hello, how are you doing?'),\n",
       " AIMessage(content='I am doing well, thanks!'),\n",
       " HumanMessage(content='What is your name?')]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "messages = chat_template.format_messages(\n",
    "    name = \"Tim\",\n",
    "    user_input = \"What is your name?\",\n",
    ")\n",
    "\n",
    "messages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.prompts import HumanMessagePromptTemplate \n",
    "from langchain_core.messages import SystemMessage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "chat_template = ChatPromptTemplate.from_messages(\n",
    "    [\n",
    "        SystemMessage(\n",
    "            content=(\"You are a helpful assistant.\")\n",
    "        ),\n",
    "        HumanMessagePromptTemplate.from_template(\"{text}\"),\n",
    "    ]\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[SystemMessage(content='You are a helpful assistant.'), HumanMessage(content='Tell me five color.')]\n"
     ]
    }
   ],
   "source": [
    "messages = chat_template.format_messages(\n",
    "    text = \"Tell me five color.\"\n",
    ")\n",
    "\n",
    "print(messages)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "prompt_template = PromptTemplate.from_template(\n",
    "    \"Explain {topic} like I am a {number} year old.\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Chain"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain_community.llms import Ollama \n",
    "\n",
    "llm = Ollama(model = \"llama2\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "chain = prompt_template | llm "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Oh, wow! *excitedly* Generative AI is like a magic box that can make new things that have never existed before! 🤯 It's like when you play with blocks and build a new tower, but instead of blocks, it's using magic to create something completely new and amazing. 🏗️\n",
      "\n",
      "Imagine you have a toy box full of different things like cars, dogs, and flowers. Generative AI is like a special tool that can take one of those things, like a car, and suddenly turn it into a whole new thing, like a unicorn! 🦄 It's like magic!\n",
      "\n",
      "But wait, there's more! Not only can it create new things, but it can also make them look and act like they were real. It's like the unicorn is a real living creature that you can see and touch! 🎨\n",
      "\n",
      "Generative AI is like a superhero that can create anything you can imagine! It's so cool, right? *excitedly* 😍\n"
     ]
    }
   ],
   "source": [
    "print(\n",
    "    chain.invoke({\n",
    "        \"topic\":\"What is generative AI?\",\n",
    "        \"number\": \"five\"\n",
    "    })\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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