.envrc_template

export OPENAI_API_KEY=sk-HS1XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

hleb-exampl.jpg

hlebushek.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "5aa4abd6-3ed3-410f-9f7b-01aaf209586c",
   "metadata": {},
   "source": [
    "Сначала надо установить всякое\n",
    "\n",
    "```\n",
    "pip install langchain pypdf chromadb tiktoken\n",
    "```\n",
    "\n",
    "хромадб это база для эмбеддингов, тиктокен режет на токены, остальное понятно"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "86cbf32c-2711-4321-815d-9772527ef58d",
   "metadata": {},
   "source": [
    "сначала может пригодится сплиттер чтобы резать текст на чанки когда текст длинный"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "62763214-8e0e-4fbc-bf6e-30040d702e36",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.text_splitter import CharacterTextSplitter\n",
    "\n",
    "splitter = CharacterTextSplitter(\n",
    "    separator='\\n',\n",
    "    chunk_size=512,\n",
    "    chunk_overlap=64,\n",
    "    length_function=len,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "dd9a5e2c-dd14-45d3-9e06-33bca00a6c7a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.document_loaders import PyPDFLoader"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "b4b90d84-35a1-4b40-ad69-6504500eba22",
   "metadata": {},
   "outputs": [],
   "source": [
    "pdfs = []\n",
    "for path in (\"./pashka.pdf\", \"./tuesday.pdf\"):\n",
    "    loader = PyPDFLoader(path)\n",
    "    pdf = loader.load()\n",
    "    pdfs.extend(splitter.split_documents(pdf))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "b3ce6128-abe8-44f5-aba9-24e098b56f52",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Document(page_content='Pashka is a parrot with a green tail.\\nHe is rather smart and his favorite food is rice cracker with pickles', metadata={'source': './pashka.pdf', 'page': 0}),\n",
       " Document(page_content='On tuesday Pashka went missing but then we found him under the bed', metadata={'source': './tuesday.pdf', 'page': 0})]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pdfs   # тут их могло бы быть много"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "840a228f-b586-4dab-8306-f2ef35c8409f",
   "metadata": {},
   "source": [
    "теперь общаемся с учётом дока\n",
    "\n",
    "делаем эмбеддинги. для этого в env долженг быть ключик `OPENAI_API_KEY`, но если что код ниже ругнётся если его нет не переживай"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "2c82af46-12df-4d70-a215-5eb9e8358357",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "assert 'OPENAI_API_KEY' in os.environ, 'если ты это проигноришь дальше дело не пойдёт'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "d3841730-8072-4d2d-80ff-6ad385365e29",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.embeddings import OpenAIEmbeddings\n",
    "from langchain.vectorstores import Chroma\n",
    "from langchain.chains import RetrievalQA\n",
    "\n",
    "embeddings = OpenAIEmbeddings()\n",
    "db = Chroma.from_documents(pdfs, embeddings, persist_directory='/tmp/db')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c73ad7b-bd65-4460-8006-72c26ee5c637",
   "metadata": {},
   "source": [
    "теперь когда есть база и эмбеддинги надо сделать ретривер"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "a167118d-67a0-4072-9366-eeaea891a93a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.llms import OpenAI\n",
    "my_retriever = db.as_retriever()\n",
    "qa = RetrievalQA.from_chain_type(llm=OpenAI(), chain_type='stuff', retriever=my_retriever)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "39aa50ba-419c-4ee6-a8e9-4ce7f622495a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "' On Tuesday Pashka was under the bed and his tail was green.'"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "query = 'Какого цвета во вторник был ховст у Пашки? И где он был?'\n",
    "qa.run(query)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c1916557-a7f9-4812-acd0-4a2a4f2ac0cf",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}

pashka.pdf

tuesday.pdf