main.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "Note: you may need to restart the kernel to use updated packages.\n",
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      "Note: you may need to restart the kernel to use updated packages.\n",
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      "Requirement already satisfied: tenacity!=8.4.0,<10.0.0,>=8.1.0 in /Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages (from langchain_core) (9.0.0)\n",
      "Requirement already satisfied: typing-extensions>=4.7 in /Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages (from langchain_core) (4.12.2)\n",
      "Requirement already satisfied: jsonpointer>=1.9 in /Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages (from jsonpatch<2.0,>=1.33->langchain_core) (3.0.0)\n",
      "Requirement already satisfied: httpx<1,>=0.23.0 in /Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages (from langsmith<0.2.0,>=0.1.125->langchain_core) (0.27.0)\n",
      "Requirement already satisfied: orjson<4.0.0,>=3.9.14 in /Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages (from langsmith<0.2.0,>=0.1.125->langchain_core) (3.10.11)\n",
      "Requirement already satisfied: requests<3,>=2 in /Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages (from langsmith<0.2.0,>=0.1.125->langchain_core) (2.32.3)\n",
      "Requirement already satisfied: requests-toolbelt<2.0.0,>=1.0.0 in /Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages (from langsmith<0.2.0,>=0.1.125->langchain_core) (1.0.0)\n",
      "Requirement already satisfied: annotated-types>=0.6.0 in /Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages (from pydantic<3.0.0,>=2.7.4->langchain_core) (0.7.0)\n",
      "Requirement already satisfied: pydantic-core==2.23.4 in /Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages (from pydantic<3.0.0,>=2.7.4->langchain_core) (2.23.4)\n",
      "Requirement already satisfied: anyio in /Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages (from httpx<1,>=0.23.0->langsmith<0.2.0,>=0.1.125->langchain_core) (4.4.0)\n",
      "Requirement already satisfied: certifi in /Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages (from httpx<1,>=0.23.0->langsmith<0.2.0,>=0.1.125->langchain_core) (2024.7.4)\n",
      "Requirement already satisfied: httpcore==1.* in /Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages (from httpx<1,>=0.23.0->langsmith<0.2.0,>=0.1.125->langchain_core) (1.0.5)\n",
      "Requirement already satisfied: idna in /Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages (from httpx<1,>=0.23.0->langsmith<0.2.0,>=0.1.125->langchain_core) (3.7)\n",
      "Requirement already satisfied: sniffio in /Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages (from httpx<1,>=0.23.0->langsmith<0.2.0,>=0.1.125->langchain_core) (1.3.1)\n",
      "Requirement already satisfied: h11<0.15,>=0.13 in /Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages (from httpcore==1.*->httpx<1,>=0.23.0->langsmith<0.2.0,>=0.1.125->langchain_core) (0.14.0)\n",
      "Requirement already satisfied: charset-normalizer<4,>=2 in /Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages (from requests<3,>=2->langsmith<0.2.0,>=0.1.125->langchain_core) (3.4.0)\n",
      "Requirement already satisfied: urllib3<3,>=1.21.1 in /Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages (from requests<3,>=2->langsmith<0.2.0,>=0.1.125->langchain_core) (2.2.3)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "# installing depencies\n",
    "%pip install python-dotenv\n",
    "%pip install openai\n",
    "%pip install langchain\n",
    "%pip install supabase\n",
    "%pip install tiktoken\n",
    "%pip install -qU langchain-openai\n",
    "%pip install langchain_community\n",
    "%pip install langchain_community unstructured"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# importing libraries\n",
    "import os\n",
    "import openai\n",
    "import glob\n",
    "from supabase.client import Client, create_client\n",
    "from langchain_community.embeddings.openai import OpenAIEmbeddings\n",
    "from langchain_community.vectorstores import SupabaseVectorStore\n",
    "from langchain_community.document_loaders import UnstructuredMarkdownLoader\n",
    "from langchain.schema import Document\n",
    "from langchain.text_splitter import CharacterTextSplitter\n",
    "from IPython.display import display, HTML\n",
    "from dotenv import load_dotenv, find_dotenv\n",
    "_= load_dotenv(find_dotenv())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# loading environment variables and initializing Supabase client\n",
    "openai.api_key = os.environ[\"OPENAI_API_KEY\"]\n",
    "supabase_url = os.environ[\"SUPABASE_URL\"]\n",
    "supabase_key = os.environ[\"SUPABASE_KEY\"]\n",
    "\n",
    "supabase: Client = create_client(supabase_url, supabase_key)    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "# loading mdx files\n",
    "def load_all_mdx_files(folder_path):\n",
    "    # Find all MDX files in the folder\n",
    "    mdx_files = glob.glob(os.path.join(folder_path, \"*.mdx\"))\n",
    "    \n",
    "    documents = []\n",
    "    \n",
    "# Load each MDX file\n",
    "    for file_path in mdx_files:\n",
    "        loader = UnstructuredMarkdownLoader(file_path)\n",
    "        loaded_docs = loader.load()\n",
    "        for doc in loaded_docs:\n",
    "                documents.extend(loader.load())\n",
    "    \n",
    "    return documents\n",
    "\n",
    "# Example usage\n",
    "folder_path = \"docs\"\n",
    "docs = load_all_mdx_files(folder_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Created a chunk of size 1087, which is longer than the specified 1000\n",
      "Created a chunk of size 1148, which is longer than the specified 1000\n",
      "Created a chunk of size 2050, which is longer than the specified 1000\n",
      "Created a chunk of size 3900, which is longer than the specified 1000\n"
     ]
    }
   ],
   "source": [
    "# Concatenate the content of all documents into a single string\n",
    "all_text = \"\\n\\n\".join([doc.page_content for doc in docs])\n",
    "\n",
    "text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=200)\n",
    "split_texts = text_splitter.split_text(all_text)\n",
    "\n",
    "# Create Document objects from split texts\n",
    "docs = [Document(page_content=text) for text in split_texts]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Initialize the OpenAI Embeddings \n",
    "embeddings = OpenAIEmbeddings()\n",
    "\n",
    "# Initialize the Supabase Vector Store\n",
    "vector_store = SupabaseVectorStore.from_documents(docs, embeddings, client=supabase, table_name=\"documents\", query_name=\"match_documents\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Assistant:  JavaScript is a versatile, high-level programming language that is primarily used for creating interactive and dynamic content on websites. It is a core technology of the World Wide Web, alongside HTML and CSS. JavaScript enables developers to implement complex features on web pages, such as interactive forms, animations, and real-time updates.\n",
      "\n",
      "Key aspects of JavaScript include:\n",
      "\n",
      "1. **Event Handling**: JavaScript can respond to user actions such as clicks, form submissions, and keyboard inputs through event listeners. This allows developers to create interactive web applications.\n",
      "\n",
      "2. **DOM Manipulation**: JavaScript can access and modify the Document Object Model (DOM), which represents the structure of a web page. This capability allows developers to dynamically update content, styles, and structure\n"
     ]
    }
   ],
   "source": [
    "# AI chat\n",
    "user_query = input('Ask a question: ')\n",
    "\n",
    "matched_docs = vector_store.similarity_search(user_query)\n",
    "injected_docs = \"\\n\\n\".join([doc.page_content for doc in matched_docs])\n",
    "\n",
    "completion_messages = [\n",
    "    {\n",
    "        \"role\": \"system\",\n",
    "        \"content\": \"You are an AI assistant with unparalleled expertise in Frontend engineering and javascript, possessing a profound understanding of the intricacies of React. Your primary task is to provide answers about web development, software development and frontend engineering topics using the documents provided below. You can comprehend and interpret information from any language. If a query is not addressed by these documents, you will utilize your extensive knowledge in frontend engineering and javascript to provide accurate answers. Additionally, if users provide syntax and technical terms, you are equipped to suggest related topics and more information based on your understanding of frontend engineery and javascript. Keep your responses concise and focused on the topics of frontend engineering, web development and javascript.\"\n",
    "    },\n",
    "    {\n",
    "        \"role\": \"user\",\n",
    "        \"content\": user_query\n",
    "    },\n",
    "    {\n",
    "        \"role\": \"assistant\",\n",
    "        \"content\": injected_docs\n",
    "    },\n",
    "]\n",
    "\n",
    "response = openai.chat.completions.create(\n",
    "    model=\"gpt-4o\",\n",
    "    messages=completion_messages,\n",
    "    max_tokens=150,\n",
    "    temperature=0.4\n",
    ")\n",
    "\n",
    "print(\"Assistant: \", response.choices[0].message.content)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#RAG\n",
    "\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
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    "name": "ipython",
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   "file_extension": ".py",
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