00_Chapter 0. Getting Started-Tutorial How-To.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# **Chapter 0. Getting Started-Tutorial How-To**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You need to run this initial notebook first to ensure that the necessary requirements and environment variables are set up for all notebooks in this cookbook. In this section, we will introduce Solar, a large language model (LLM) developed by Upstage. This notebook covers the basics of setting up Solar, understanding its core components, and running a simple \"Hello, World!\" example to demonstrate its basic functionality."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **Table of Contents**\n",
    "- Use `Ctrl + F` (Windows) or `Cmd + F` (Mac) to locate specific sections by title."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- **Setting** \n",
    "\n",
    "    - UPSTAGE_API_KEY  \n",
    "\n",
    "    - How to run Solar Pro  \n",
    "\n",
    "\n",
    "- **Alternative Options for the Task**  \n",
    "\n",
    "    - Request the API with the Example Code"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **Setting**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **UPSTAGE_API_KEY**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To obtain your Upstage API key, follow these steps:\n",
    "\n",
    "1. Visit the Upstage AI console at [https://console.upstage.ai](https://console.upstage.ai/).\n",
    "2. Sign up for an account if you don't already have one.\n",
    "3. Log in to your account.\n",
    "4. Navigate to the API Key section.\n",
    "5. Generate your API Key.\n",
    "6. Copy the key and save it securely."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **How to run Solar Pro**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Install the required dependencies by running the following command(`Shift(or Cmd) + Enter`):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture\n",
    "!pip install openai pickleshare langchain-upstage llama_index.llms.upstage llama_index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Stored 'UPSTAGE_API_KEY' (str)\n"
     ]
    }
   ],
   "source": [
    "import pickleshare\n",
    "import os\n",
    "from dotenv import load_dotenv\n",
    "load_dotenv()\n",
    "\n",
    "UPSTAGE_API_KEY = os.getenv(\"UPSTAGE_API_KEY\")\n",
    "\n",
    "# To load the UPSTAGE_API_KEY as a variable across all notebooks in this cookbook.\n",
    "%store UPSTAGE_API_KEY "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello! I'm just a computer program, so I don't have feelings, but I'm functioning perfectly. How can I assist you today? \n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Python\n",
    "from openai import OpenAI\n",
    "\n",
    "client = OpenAI(\n",
    "    api_key = UPSTAGE_API_KEY,\n",
    "    base_url = \"https://api.upstage.ai/v1/solar\",\n",
    ")\n",
    "\n",
    "response = client.chat.completions.create(\n",
    "    model= 'solar-pro',\n",
    "    messages= [\n",
    "        {\n",
    "            \"role\": \"user\",\n",
    "            \"content\": \"Hi, how are you?\"\n",
    "        }\n",
    "    ]\n",
    ")\n",
    "\n",
    "print(response.choices[0].message.content, '\\n\\n')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **Alternative Options for the Task**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Request the API with the Example Code**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello! I'm just a computer program, so I don't have feelings, but I'm functioning perfectly and ready to assist you. How can I help you today? \n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# LangChain\n",
    "from langchain_upstage import ChatUpstage\n",
    "\n",
    "client = ChatUpstage(api_key=UPSTAGE_API_KEY, model=\"solar-pro\")\n",
    "\n",
    "response = client.invoke(\"Hi, how are you?\")\n",
    "print(response.content, '\\n\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello! I'm just a computer program, so I don't have feelings, but I'm functioning perfectly. How can I assist you today? \n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# LlamaIndex\n",
    "from llama_index.llms.upstage import Upstage\n",
    "from llama_index.core.llms import ChatMessage\n",
    "\n",
    "client = Upstage(api_key=UPSTAGE_API_KEY, model=\"solar-pro\")\n",
    "\n",
    "message = []\n",
    "message.append(ChatMessage(role=\"user\", content=\"Hi, how are you?\"))\n",
    "\n",
    "response = client.chat(messages=message)\n",
    "print(response.message.content, '\\n\\n')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Upstage LangChain integrations**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "| API | Description | Import | Example Usage |\n",
    "| :---: | :---: | :---: | :---: |\n",
    "|  Chat | Build assistants using Solar Mini Chat | `from langchain_upstage import ChatUpstage` | [Go](https://python.langchain.com/v0.2/docs/integrations/chat/upstage/) |\n",
    "| Text Embedding | Embed strings to vectors | `from langchain_upstage import UpstageEmbeddings` | [Go](https://python.langchain.com/v0.2/docs/integrations/text_embedding/upstage/) |\n",
    "| Groundedness Check | Verify groundedness of assistant's response | `from langchain_upstage import UpstageGroundednessCheck` | [Go](https://python.langchain.com/v0.2/docs/integrations/tools/upstage_groundedness_check/) |\n",
    "| Layout Analysis | Serialize documents with tables and figures | `from langchain_upstage import UpstageLayoutAnalysisLoader` | [Go](https://python.langchain.com/v0.2/docs/integrations/document_loaders/upstage/) |\n",
    "\n",
    "See [documentations](https://python.langchain.com/v0.2/docs/integrations/providers/upstage/) for more details about the features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "content='Hello! How can I assist you today?' additional_kwargs={'refusal': None} response_metadata={'token_usage': {'completion_tokens': 10, 'prompt_tokens': 13, 'total_tokens': 23, 'completion_tokens_details': None, 'prompt_tokens_details': None}, 'model_name': 'solar-mini-240612', 'system_fingerprint': None, 'finish_reason': 'stop', 'logprobs': None} id='run-a64bfe7c-65c5-4188-a3f0-3b13778906cb-0' usage_metadata={'input_tokens': 13, 'output_tokens': 10, 'total_tokens': 23, 'input_token_details': {}, 'output_token_details': {}} \n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Quick hello Langchain Upstage\n",
    "# Make sure you have the langchain-upstage package installed\n",
    "# Make sure UPSTAGE_API_KEY is set in the environment variables\n",
    "import os\n",
    "from langchain_upstage import ChatUpstage\n",
    "\n",
    "os.environ[\"UPSTAGE_API_KEY\"] = UPSTAGE_API_KEY\n",
    "\n",
    "llm = ChatUpstage(model=\"solar-1-mini-chat\")\n",
    "print(llm.invoke(\"Hello Mini!\"), '\\n\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "content='こんにちは！ 今日はどのようなご用件でしょうか？' additional_kwargs={'refusal': None} response_metadata={'token_usage': {'completion_tokens': 10, 'prompt_tokens': 15, 'total_tokens': 25, 'completion_tokens_details': None, 'prompt_tokens_details': None}, 'model_name': 'solar-mini-ja-240612', 'system_fingerprint': None, 'finish_reason': 'stop', 'logprobs': None} id='run-84880253-e21e-4e60-86c6-3ec4d2de4e8e-0' usage_metadata={'input_tokens': 15, 'output_tokens': 10, 'total_tokens': 25, 'input_token_details': {}, 'output_token_details': {}} \n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from langchain_upstage import ChatUpstage\n",
    "\n",
    "llm = ChatUpstage(model=\"solar-1-mini-chat-ja\")\n",
    "print(llm.invoke(\"こんにちは、ソーラー！\"), '\\n\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "grounded \n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Solar Groundedness Check\n",
    "from langchain_upstage import UpstageGroundednessCheck\n",
    "\n",
    "groundedness_check = UpstageGroundednessCheck()\n",
    "\n",
    "context = \"Solar is a language model that can generate human-like text. It is developed by Upstage.\"\n",
    "print(groundedness_check.invoke(\n",
    "    {\"context\": context, \"answer\": \"Solar is created by Upstage.\"}\n",
    "), '\\n\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "notGrounded \n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(groundedness_check.invoke({\"context\": context, \"answer\": \"Solar is created by OpenAI.\"}), '\\n\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
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       "  -0.025848388671875,\n",
       "  ...]]"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from langchain_upstage import UpstageEmbeddings\n",
    "\n",
    "embeddings_model = UpstageEmbeddings(model=\"solar-embedding-1-large\")\n",
    "embeddings_model.embed_documents(\n",
    "    [\n",
    "        \"What is the best season to visit Korea?\",\n",
    "    ]\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Next: [Chapter 1. Basic Prompt Structure](./01_Chapter%201.%20Basic%20Prompt%20Structure.ipynb)*"
   ]
  }
 ],
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