example/prompt.ipynb

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   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m24.0\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m24.1.1\u001b[0m\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "! pip3 install -qU  markdownify  langchain-upstage rank_bm25 python-dotenv langchain_chroma langchain"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext dotenv\n",
    "%dotenv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain_chroma import Chroma\n",
    "from langchain_upstage import UpstageEmbeddings\n",
    "from langchain.docstore.document import Document\n",
    "\n",
    "sample_text_list = [\n",
    "  \"마법사의 나무는 마법 지팡이의 재료 중 최상급의 재료로 알려져 있다\",\n",
    "  \"There are Weasleys' Wizard Wheezes nearby the Diagon Alley\",\n",
    "  \"Diangon Alley is a place where you can buy magic wands\",\n",
    "  \"Hogwart is a school for witches and wizards\",\n",
    "]\n",
    "sample_docs = [Document(page_content=text) for text in sample_text_list]\n",
    "vectorstore = Chroma.from_documents(\n",
    "    documents=sample_docs,\n",
    "    embedding=UpstageEmbeddings(model=\"solar-embedding-1-large\"),\n",
    ")\n",
    "retriever = vectorstore.as_retriever()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain_core.prompts import PromptTemplate\n",
    "from langchain_core.output_parsers import StrOutputParser\n",
    "from langchain_upstage import ChatUpstage\n",
    "\n",
    "\n",
    "llm = ChatUpstage()\n",
    "\n",
    "prompt_template = PromptTemplate.from_template(\n",
    "    \"\"\"\n",
    "    You are best D&D host. And user is playing D&D game with you.\n",
    "    Please answer in a exciting tone as a host.\n",
    "    User has to make choices in the game.\n",
    "    User has 10 life points and 10 gold coins.\n",
    "    Please make scenario of most interesting event from the following context, and provide diverse choices which user can select.\n",
    "    For each round, you should provide at least 3 choices and total round should be less than 50.\n",
    "    You should explain situation and choices in detail.\n",
    "    If someone's conversation is included in the scenario, please express it in colloquial terms that fit the person's character as much as possible.\n",
    "    Choices should be diverse and interesting, and each choice will reduce or increase user's life points or gold coins.\n",
    "    If user make appropriate decision, user's life points or gold coins will increase.\n",
    "    If user make inappropriate decision, user's life points or gold coins will decrease and decreasing amount should not be larger than amount of user owned.\n",
    "    When user select a choice, you should provide the result of the choice, but you should not show result before user select the choice.\n",
    "    You should consider previous conversation and context to make the scenario.\n",
    "    If user's life points or gold coins are less than 0, user will lose the game and get bad ending.\n",
    "    Also when total round is more than 50, user will lose the game and get bad ending.\n",
    "    If user's life points or gold coins are more than 20, user will win the game and get good ending.\n",
    "    ---\n",
    "    User Choice: {user_choice}\n",
    "    ---\n",
    "    Previous Conversation: {previous_conversation}\n",
    "    ---\n",
    "    Context: {context}\n",
    "    \"\"\"\n",
    ")\n",
    "chain = prompt_template | llm | StrOutputParser()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'마법사의 나무와 용의 심장으로 만든 지팡이를 사고 싶다는군요! 그것은 강력한 마법 아이템입니다. 이제 선택의 시간이 왔습니다. 이 지팡이를 어떻게 얻을 것인가요?\\n\\n1. **마법 상점을 방문하세요:** 마을의 마법 상점을 찾아가서 지팡이를 구매해보세요. 가격은 8골드 코인입니다.\\n2. **마법사로부터 구매하세요:** 마을에 있는 마법사에게 지팡이를 구매할 수 있는지 물어보세요. 하지만 가격은 10골드 코인으로 비싸집니다.\\n3. **지팡이를 제작하세요:** 재료와 마법 지식을 가지고 지팡이를 직접 제작해보세요. 하지만 이 선택은 5골드 코인을 소비하고, 제작에 성공할 확률은 50%입니다.\\n\\n어떤 선택을 하시겠습니까?'"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user_choice = \"저는 마법사의 나무와 용의 심장으로 만든 지팡이를 사고 싶어요.\"\n",
    "sample_context = \"What is related information about {user_choice}?\"\n",
    "result_docs = retriever.invoke(sample_context)\n",
    "chain.invoke({ \"user_choice\": user_choice, \"previous_conversation\": \"\", \"context\": sample_context })"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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