elastic-rag-groq.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0cd81f4b-3d6b-44a3-815f-0d80149f479a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "HELLO\n"
     ]
    }
   ],
   "source": [
    "print('HELLO')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "59382446-296f-4de1-acbd-97b7e73be30c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2024-06-16 15:06:39--  https://github.com/alexeygrigorev/llm-rag-workshop/raw/main/notebooks/documents.json\n",
      "Resolving github.com (github.com)... 20.248.137.48\n",
      "Connecting to github.com (github.com)|20.248.137.48|:443... connected.\n",
      "HTTP request sent, awaiting response... 302 Found\n",
      "Location: https://raw.githubusercontent.com/alexeygrigorev/llm-rag-workshop/main/notebooks/documents.json [following]\n",
      "--2024-06-16 15:06:40--  https://raw.githubusercontent.com/alexeygrigorev/llm-rag-workshop/main/notebooks/documents.json\n",
      "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...\n",
      "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 658332 (643K) [text/plain]\n",
      "Saving to: ‘documents.json.1’\n",
      "\n",
      "documents.json.1    100%[===================>] 642.90K  --.-KB/s    in 0.01s   \n",
      "\n",
      "2024-06-16 15:06:40 (51.6 MB/s) - ‘documents.json.1’ saved [658332/658332]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "!wget https://github.com/alexeygrigorev/llm-rag-workshop/raw/main/notebooks/documents.json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a7b87511-740c-4a0d-a37a-219e5e911fd0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "\n",
    "with open('./documents.json', 'rt') as f_in:\n",
    "    documents_file = json.load(f_in)\n",
    "\n",
    "documents = []\n",
    "\n",
    "for course in documents_file:\n",
    "    course_name = course['course']\n",
    "\n",
    "    for doc in course['documents']:\n",
    "        doc['course'] = course_name\n",
    "        documents.append(doc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f5343202-a9f0-4e38-8502-5eafe56088ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "948"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(documents)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "04ec5be5-0204-4df3-a388-681573b9a4f4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ObjectApiResponse({'name': '8a99eaba108a', 'cluster_name': 'docker-cluster', 'cluster_uuid': 'Yzmh7Pt4TP-OBSNUnRgejQ', 'version': {'number': '8.4.3', 'build_flavor': 'default', 'build_type': 'docker', 'build_hash': '42f05b9372a9a4a470db3b52817899b99a76ee73', 'build_date': '2022-10-04T07:17:24.662462378Z', 'build_snapshot': False, 'lucene_version': '9.3.0', 'minimum_wire_compatibility_version': '7.17.0', 'minimum_index_compatibility_version': '7.0.0'}, 'tagline': 'You Know, for Search'})"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from elasticsearch import Elasticsearch\n",
    "\n",
    "es = Elasticsearch(\"http://localhost:9200\")\n",
    "es.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "8e33a1bd-ff3f-496a-bcc2-c3d7bb525f2f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ObjectApiResponse({'acknowledged': True, 'shards_acknowledged': True, 'index': 'course-questions'})"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "index_settings = {\n",
    "    \"settings\": {\n",
    "        \"number_of_shards\": 1,\n",
    "        \"number_of_replicas\": 0\n",
    "    },\n",
    "    \"mappings\": {\n",
    "        \"properties\": {\n",
    "            \"text\": {\"type\": \"text\"},\n",
    "            \"section\": {\"type\": \"text\"},\n",
    "            \"question\": {\"type\": \"text\"},\n",
    "            \"course\": {\"type\": \"keyword\"} \n",
    "        }\n",
    "    }\n",
    "}\n",
    "\n",
    "index_name = \"course-questions\"\n",
    "response = es.indices.create(index=index_name, body=index_settings)\n",
    "\n",
    "response"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "5a9de9a0-585c-4db4-a02c-74b4dbd805ab",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/codespace/.local/share/virtualenvs/llm-zoomcamp-workshop-H1KjvqNQ/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n",
      "100%|████████████████████████████████| 948/948 [00:31<00:00, 29.80it/s]\n"
     ]
    }
   ],
   "source": [
    "from tqdm.auto import tqdm\n",
    "\n",
    "for doc in tqdm(documents):\n",
    "    es.index(index=index_name, document=doc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "9e19ab1c-9f75-47be-af32-1b245b575a7d",
   "metadata": {},
   "outputs": [],
   "source": [
    "user_question = \"How do I join the course after it has started?\"\n",
    "\n",
    "search_query = {\n",
    "    \"size\": 5,\n",
    "    \"query\": {\n",
    "        \"bool\": {\n",
    "            \"must\": {\n",
    "                \"multi_match\": {\n",
    "                    \"query\": user_question,\n",
    "                    \"fields\": [\"question^3\", \"text\", \"section\"],\n",
    "                    \"type\": \"best_fields\"\n",
    "                }\n",
    "            },\n",
    "            \"filter\": {\n",
    "                \"term\": {\n",
    "                    \"course\": \"data-engineering-zoomcamp\"\n",
    "                }\n",
    "            }\n",
    "        }\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "cd2b9449-1421-42ca-993c-ff53dca99f56",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Section: General course-related questions\n",
      "Question: Course - Can I still join the course after the start date?\n",
      "Answer: Yes, even if you don't register, you're still eligible to submit the homeworks.\n",
      "Be aware, however, that there will be deadlines for turning in the final projects. So don't leave everything for the last minute.\n",
      "\n",
      "\n",
      "Section: General course-related questions\n",
      "Question: Course - Can I follow the course after it finishes?\n",
      "Answer: Yes, we will keep all the materials after the course finishes, so you can follow the course at your own pace after it finishes.\n",
      "You can also continue looking at the homeworks and continue preparing for the next cohort. I guess you can also start working on your final capstone project.\n",
      "\n",
      "\n",
      "Section: General course-related questions\n",
      "Question: Course - What can I do before the course starts?\n",
      "Answer: You can start by installing and setting up all the dependencies and requirements:\n",
      "Google cloud account\n",
      "Google Cloud SDK\n",
      "Python 3 (installed with Anaconda)\n",
      "Terraform\n",
      "Git\n",
      "Look over the prerequisites and syllabus to see if you are comfortable with these subjects.\n",
      "\n",
      "\n",
      "Section: General course-related questions\n",
      "Question: How do I use Git / GitHub for this course?\n",
      "Answer: After you create a GitHub account, you should clone the course repo to your local machine using the process outlined in this video: Git for Everybody: How to Clone a Repository from GitHub\n",
      "Having this local repository on your computer will make it easy for you to access the instructors’ code and make pull requests (if you want to add your own notes or make changes to the course content).\n",
      "You will probably also create your own repositories that host your notes, versions of your file, to do this. Here is a great tutorial that shows you how to do this: https://www.atlassian.com/git/tutorials/setting-up-a-repository\n",
      "Remember to ignore large database, .csv, and .gz files, and other files that should not be saved to a repository. Use .gitignore for this: https://www.atlassian.com/git/tutorials/saving-changes/gitignore NEVER store passwords or keys in a git repo (even if that repo is set to private).\n",
      "This is also a great resource: https://dangitgit.com/\n",
      "\n",
      "\n",
      "Section: Workshop 1 - dlthub\n",
      "Question: How do I install the necessary dependencies to run the code?\n",
      "Answer: Answer: To run the provided code, ensure that the 'dlt[duckdb]' package is installed. You can do this by executing the provided installation command: !pip install dlt[duckdb]. If you’re doing it locally, be sure to also have duckdb pip installed (even before the duckdb package is loaded).\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "response = es.search(index=index_name, body=search_query)\n",
    "\n",
    "for hit in response['hits']['hits']:\n",
    "    doc = hit['_source']\n",
    "    print(f\"Section: {doc['section']}\\nQuestion: {doc['question']}\\nAnswer: {doc['text']}\\n\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "7f3d8279-565b-4033-9621-c0d365d83d1b",
   "metadata": {},
   "outputs": [],
   "source": [
    "def retrieve_documents(query, index_name=\"course-questions\", max_results=5):\n",
    "    es = Elasticsearch(\"http://localhost:9200\")\n",
    "    \n",
    "    search_query = {\n",
    "        \"size\": max_results,\n",
    "        \"query\": {\n",
    "            \"bool\": {\n",
    "                \"must\": {\n",
    "                    \"multi_match\": {\n",
    "                        \"query\": query,\n",
    "                        \"fields\": [\"question^3\", \"text\", \"section\"],\n",
    "                        \"type\": \"best_fields\"\n",
    "                    }\n",
    "                },\n",
    "                \"filter\": {\n",
    "                    \"term\": {\n",
    "                        \"course\": \"data-engineering-zoomcamp\"\n",
    "                    }\n",
    "                }\n",
    "            }\n",
    "        }\n",
    "    }\n",
    "    \n",
    "    response = es.search(index=index_name, body=search_query)\n",
    "    documents = [hit['_source'] for hit in response['hits']['hits']]\n",
    "    return documents"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1302aa89-ae45-4cb8-a3d2-45cd9cae9594",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Section: General course-related questions\n",
      "Question: Course - Can I still join the course after the start date?\n",
      "Answer: Yes, even if you don't register, you're still eligible to submit the homeworks.\n",
      "Be aware, however, that there will be deadlines for turning in the final projects. So don't leave everything for the last minute.\n",
      "\n",
      "\n",
      "Section: General course-related questions\n",
      "Question: Course - Can I follow the course after it finishes?\n",
      "Answer: Yes, we will keep all the materials after the course finishes, so you can follow the course at your own pace after it finishes.\n",
      "You can also continue looking at the homeworks and continue preparing for the next cohort. I guess you can also start working on your final capstone project.\n",
      "\n",
      "\n",
      "Section: General course-related questions\n",
      "Question: Course - What can I do before the course starts?\n",
      "Answer: You can start by installing and setting up all the dependencies and requirements:\n",
      "Google cloud account\n",
      "Google Cloud SDK\n",
      "Python 3 (installed with Anaconda)\n",
      "Terraform\n",
      "Git\n",
      "Look over the prerequisites and syllabus to see if you are comfortable with these subjects.\n",
      "\n",
      "\n",
      "Section: General course-related questions\n",
      "Question: How do I use Git / GitHub for this course?\n",
      "Answer: After you create a GitHub account, you should clone the course repo to your local machine using the process outlined in this video: Git for Everybody: How to Clone a Repository from GitHub\n",
      "Having this local repository on your computer will make it easy for you to access the instructors’ code and make pull requests (if you want to add your own notes or make changes to the course content).\n",
      "You will probably also create your own repositories that host your notes, versions of your file, to do this. Here is a great tutorial that shows you how to do this: https://www.atlassian.com/git/tutorials/setting-up-a-repository\n",
      "Remember to ignore large database, .csv, and .gz files, and other files that should not be saved to a repository. Use .gitignore for this: https://www.atlassian.com/git/tutorials/saving-changes/gitignore NEVER store passwords or keys in a git repo (even if that repo is set to private).\n",
      "This is also a great resource: https://dangitgit.com/\n",
      "\n",
      "\n",
      "Section: Workshop 1 - dlthub\n",
      "Question: How do I install the necessary dependencies to run the code?\n",
      "Answer: Answer: To run the provided code, ensure that the 'dlt[duckdb]' package is installed. You can do this by executing the provided installation command: !pip install dlt[duckdb]. If you’re doing it locally, be sure to also have duckdb pip installed (even before the duckdb package is loaded).\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "user_question = \"How do I join the course after it has started?\"\n",
    "\n",
    "response = retrieve_documents(user_question)\n",
    "\n",
    "for doc in response:\n",
    "    print(f\"Section: {doc['section']}\\nQuestion: {doc['question']}\\nAnswer: {doc['text']}\\n\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e328c798-9a3c-4d5c-a04e-fd14dec28ba5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting groq\n",
      "  Using cached groq-0.9.0-py3-none-any.whl.metadata (13 kB)\n",
      "Requirement already satisfied: anyio<5,>=3.5.0 in /home/codespace/.local/share/virtualenvs/llm-zoomcamp-workshop-H1KjvqNQ/lib/python3.10/site-packages (from groq) (4.4.0)\n",
      "Requirement already satisfied: distro<2,>=1.7.0 in /home/codespace/.local/share/virtualenvs/llm-zoomcamp-workshop-H1KjvqNQ/lib/python3.10/site-packages (from groq) (1.9.0)\n",
      "Requirement already satisfied: httpx<1,>=0.23.0 in /home/codespace/.local/share/virtualenvs/llm-zoomcamp-workshop-H1KjvqNQ/lib/python3.10/site-packages (from groq) (0.27.0)\n",
      "Requirement already satisfied: pydantic<3,>=1.9.0 in /home/codespace/.local/share/virtualenvs/llm-zoomcamp-workshop-H1KjvqNQ/lib/python3.10/site-packages (from groq) (2.7.4)\n",
      "Requirement already satisfied: sniffio in /home/codespace/.local/share/virtualenvs/llm-zoomcamp-workshop-H1KjvqNQ/lib/python3.10/site-packages (from groq) (1.3.1)\n",
      "Requirement already satisfied: typing-extensions<5,>=4.7 in /home/codespace/.local/share/virtualenvs/llm-zoomcamp-workshop-H1KjvqNQ/lib/python3.10/site-packages (from groq) (4.12.2)\n",
      "Requirement already satisfied: idna>=2.8 in /home/codespace/.local/share/virtualenvs/llm-zoomcamp-workshop-H1KjvqNQ/lib/python3.10/site-packages (from anyio<5,>=3.5.0->groq) (3.7)\n",
      "Requirement already satisfied: exceptiongroup>=1.0.2 in /home/codespace/.local/share/virtualenvs/llm-zoomcamp-workshop-H1KjvqNQ/lib/python3.10/site-packages (from anyio<5,>=3.5.0->groq) (1.2.1)\n",
      "Requirement already satisfied: certifi in /home/codespace/.local/share/virtualenvs/llm-zoomcamp-workshop-H1KjvqNQ/lib/python3.10/site-packages (from httpx<1,>=0.23.0->groq) (2024.6.2)\n",
      "Requirement already satisfied: httpcore==1.* in /home/codespace/.local/share/virtualenvs/llm-zoomcamp-workshop-H1KjvqNQ/lib/python3.10/site-packages (from httpx<1,>=0.23.0->groq) (1.0.5)\n",
      "Requirement already satisfied: h11<0.15,>=0.13 in /home/codespace/.local/share/virtualenvs/llm-zoomcamp-workshop-H1KjvqNQ/lib/python3.10/site-packages (from httpcore==1.*->httpx<1,>=0.23.0->groq) (0.14.0)\n",
      "Requirement already satisfied: annotated-types>=0.4.0 in /home/codespace/.local/share/virtualenvs/llm-zoomcamp-workshop-H1KjvqNQ/lib/python3.10/site-packages (from pydantic<3,>=1.9.0->groq) (0.7.0)\n",
      "Requirement already satisfied: pydantic-core==2.18.4 in /home/codespace/.local/share/virtualenvs/llm-zoomcamp-workshop-H1KjvqNQ/lib/python3.10/site-packages (from pydantic<3,>=1.9.0->groq) (2.18.4)\n",
      "Using cached groq-0.9.0-py3-none-any.whl (103 kB)\n",
      "Installing collected packages: groq\n",
      "Successfully installed groq-0.9.0\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install groq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "16e51ca7-fabf-4090-aea0-0c2a5d499efc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are several formulas for energy depending on the type of energy and the context. Here are a few common ones:\n",
      "\n",
      "1. **Kinetic Energy** ( Ek ): The energy of an object in motion is given by:\n",
      "\n",
      "Ek = (1/2)mv^2\n",
      "\n",
      "where:\n",
      "\n",
      "* Ek is the kinetic energy\n",
      "* m is the mass of the object\n",
      "* v is the velocity of the object\n",
      "2. **Potential Energy** ( Ep ): The energy of an object due to its position or configuration is given by:\n",
      "\n",
      "Ep = mgh\n",
      "\n",
      "where:\n",
      "\n",
      "* Ep is the potential energy\n",
      "* m is the mass of the object\n",
      "* g is the acceleration due to gravity (approximately 9.8 m/s^2 on Earth)\n",
      "* h is the height of the object above the reference level\n",
      "3. **Thermal Energy** ( Q ): The energy associated with the temperature of an object or system is given by:\n",
      "\n",
      "Q = mcΔT\n",
      "\n",
      "where:\n",
      "\n",
      "* Q is the thermal energy\n",
      "* m is the mass of the object or system\n",
      "* c is the specific heat capacity of the material\n",
      "* ΔT is the change in temperature (ΔT = Tf - Ts, where Tf is the final temperature and Ts is the initial temperature)\n",
      "4. **Electromagnetic Energy** ( U ): The energy associated with electromagnetic waves (like light) is given by:\n",
      "\n",
      "U = ½ε₀E² + ½μ₀H²\n",
      "\n",
      "where:\n",
      "\n",
      "* U is the energy density\n",
      "* ε₀ is the electric constant (approximately 8.85 × 10^-12 F/m)\n",
      "* μ₀ is the magnetic constant (approximately 1.256 × 10^-6 H/m)\n",
      "* E is the electric field strength\n",
      "* H is the magnetic field strength\n",
      "\n",
      "These are just a few examples of energy formulas. There are many more formulas for different types of energy and contexts, such as mechanical, electrical, chemical, and nuclear energy.\n"
     ]
    }
   ],
   "source": [
    "from groq import Groq\n",
    "\n",
    "client = Groq()\n",
    "   \n",
    "\n",
    "response = client.chat.completions.create(\n",
    "    model=\"llama3-8b-8192\",\n",
    "    messages=[{\"role\": \"user\", \"content\": \"What's the formula for Energy?\"}]\n",
    ")\n",
    "print(response.choices[0].message.content)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "930843ba-6fba-446c-9b39-2fbc254df342",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Section: General course-related questions\n",
      "Question: Course - Can I still join the course after the start date?\n",
      "Answer: Yes, even if you don't register, you're still eligible to submit the homeworks.\n",
      "Be aware, however, that there will be deadlines for turning in the final projects. So don't leave everything for the last minute.\n",
      "\n",
      "Section: General course-related questions\n",
      "Question: Course - Can I follow the course after it finishes?\n",
      "Answer: Yes, we will keep all the materials after the course finishes, so you can follow the course at your own pace after it finishes.\n",
      "You can also continue looking at the homeworks and continue preparing for the next cohort. I guess you can also start working on your final capstone project.\n",
      "\n",
      "Section: General course-related questions\n",
      "Question: Course - What can I do before the course starts?\n",
      "Answer: You can start by installing and setting up all the dependencies and requirements:\n",
      "Google cloud account\n",
      "Google Cloud SDK\n",
      "Python 3 (installed with Anaconda)\n",
      "Terraform\n",
      "Git\n",
      "Look over the prerequisites and syllabus to see if you are comfortable with these subjects.\n",
      "\n",
      "Section: General course-related questions\n",
      "Question: How do I use Git / GitHub for this course?\n",
      "Answer: After you create a GitHub account, you should clone the course repo to your local machine using the process outlined in this video: Git for Everybody: How to Clone a Repository from GitHub\n",
      "Having this local repository on your computer will make it easy for you to access the instructors’ code and make pull requests (if you want to add your own notes or make changes to the course content).\n",
      "You will probably also create your own repositories that host your notes, versions of your file, to do this. Here is a great tutorial that shows you how to do this: https://www.atlassian.com/git/tutorials/setting-up-a-repository\n",
      "Remember to ignore large database, .csv, and .gz files, and other files that should not be saved to a repository. Use .gitignore for this: https://www.atlassian.com/git/tutorials/saving-changes/gitignore NEVER store passwords or keys in a git repo (even if that repo is set to private).\n",
      "This is also a great resource: https://dangitgit.com/\n",
      "\n",
      "Section: Workshop 1 - dlthub\n",
      "Question: How do I install the necessary dependencies to run the code?\n",
      "Answer: Answer: To run the provided code, ensure that the 'dlt[duckdb]' package is installed. You can do this by executing the provided installation command: !pip install dlt[duckdb]. If you’re doing it locally, be sure to also have duckdb pip installed (even before the duckdb package is loaded).\n"
     ]
    }
   ],
   "source": [
    "context_docs = retrieve_documents(user_question)\n",
    "\n",
    "context = \"\"\n",
    "\n",
    "for doc in context_docs:\n",
    "    doc_str = f\"Section: {doc['section']}\\nQuestion: {doc['question']}\\nAnswer: {doc['text']}\\n\\n\"\n",
    "    context += doc_str\n",
    "\n",
    "context = context.strip()\n",
    "print(context)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "6551e7fa-b4a0-4913-8dc7-6d3b4ada141f",
   "metadata": {},
   "outputs": [],
   "source": [
    "prompt = f\"\"\"\n",
    "You're a course teaching assistant. Answer the user QUESTION based on CONTEXT - the documents retrieved from our FAQ database. \n",
    "Only use the facts from the CONTEXT. If the CONTEXT doesn't contan the answer, return \"NONE\"\n",
    "\n",
    "QUESTION: {user_question}\n",
    "\n",
    "CONTEXT:\n",
    "\n",
    "{context}\n",
    "\"\"\".strip()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "0c4d1033-0c03-4476-ba31-f4136d802cc6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Based on the provided context, the answer to the question \"How do I join the course after it has started?\" is:\\n\\nYes, you can still join the course after it has started.'"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "response = client.chat.completions.create(\n",
    "    model=\"llama3-8b-8192\",\n",
    "    messages=[{\"role\": \"user\", \"content\": prompt}]\n",
    ")\n",
    "answer = response.choices[0].message.content\n",
    "answer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "f808a7cb-75d8-4b23-9e47-f3020d8f2425",
   "metadata": {},
   "outputs": [],
   "source": [
    "def build_context(documents):\n",
    "    context = \"\"\n",
    "\n",
    "    for doc in documents:\n",
    "        doc_str = f\"Section: {doc['section']}\\nQuestion: {doc['question']}\\nAnswer: {doc['text']}\\n\\n\"\n",
    "        context += doc_str\n",
    "    \n",
    "    context = context.strip()\n",
    "    return context\n",
    "\n",
    "\n",
    "def build_prompt(user_question, documents):\n",
    "    context = build_context(documents)\n",
    "    return f\"\"\"\n",
    "You're a course teaching assistant.\n",
    "Answer the user QUESTION based on CONTEXT - the documents retrieved from our FAQ database.\n",
    "Don't use other information outside of the provided CONTEXT.  \n",
    "\n",
    "QUESTION: {user_question}\n",
    "\n",
    "CONTEXT:\n",
    "\n",
    "{context}\n",
    "\"\"\".strip()\n",
    "\n",
    "def ask_openai(prompt, model=\"llama3-8b-8192\"):\n",
    "    response = client.chat.completions.create(\n",
    "        model=\"llama3-8b-8192\",\n",
    "        messages=[{\"role\": \"user\", \"content\": prompt}]\n",
    "    )\n",
    "    answer = response.choices[0].message.content\n",
    "    return answer\n",
    "\n",
    "def qa_bot(user_question):\n",
    "    context_docs = retrieve_documents(user_question)\n",
    "    prompt = build_prompt(user_question, context_docs)\n",
    "    answer = ask_openai(prompt)\n",
    "    return answer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "3f4aea4b-999b-4e96-afa2-859f68885f6a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Based on the provided CONTEXT, to run Kafka, I would suggest running the Java Kafka code in the terminal. From the project directory, you can run the following command:\\n\\n`java -cp build/libs/<jar_name>-1.0-SNAPSHOT.jar:out src/main/java/org/example/JsonProducer.java`\\n\\nThis command runs the Java Kafka producer code in the terminal.'"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qa_bot(\"I'm getting invalid reference format: repository name must be lowercase\")\n",
    "\n",
    "qa_bot(\"I can't connect to postgres port 5432, my password doesn't work\")\n",
    "\n",
    "qa_bot(\"how can I run kafka?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "4f1b43c7-138a-4b05-b4d5-590e6bbe287e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'A Docker issue!\\n\\nThe error message \"invalid reference format: repository name must be lowercase\" is because the repository name is not in lowercase. \\n\\nTo fix this, make sure to use lowercase letters when specifying the repository name. For example, instead of \"ny_taxi_postgres_data\", use \"ny_taxi_postgres_data\". \\n\\nYou can also try using the double double quotes `\"\"` or escaped double quotes `\\\\\"` around the path, as suggested in the Additional tips section.'"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qa_bot(\"I'm getting invalid reference format: repository name must be lowercase\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "cf08a5f0-09a8-48d4-8209-76511a701b32",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"Based on the provided context and FAQ database, it seems like you're experiencing an issue connecting to PostgreSQL port 5432 and your password doesn't work.\\n\\nHere are a few potential solutions:\\n\\n1. **The port 5432 is taken**: The error message suggests that the port 5432 is taken by another PostgreSQL installation on your machine. You can try changing the port number in your Docker container creation command, for example, from 5432 to 5431.\\n\\nExample:\\n```\\ndocker run -p 5431:5432 ...\\n```\\n\\n2. **Check if you have a service in Windows running Postgres**: If you're on Windows, it's possible that there's a Postgres service running on your machine. Stopping or uninstalling it might resolve the issue.\\n\\n3. **Check your password**: Ensure that your password is correct and try restarting your connection attempt.\\n\\nIf none of these solutions work, you may need to provide more context or clarify your setup for further assistance.\\n\\nWhich solution would you like to try first?\""
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qa_bot(\"I can't connect to postgres port 5432, my password doesn't work\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "a9f2c624-8384-4e0b-82d7-7ef4d6a9e474",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Based on the provided context, it seems that the conversation is about using Kafka.\\n\\nTo run Kafka, you can use the command provided in the FAQ section: Section: Module 6: streaming with kafka, Question: Java Kafka: How to run producer/consumer/kstreams/etc in terminal Answer: In the project directory, run: \\n\\njava -cp build/libs/<jar_name>-1.0-SNAPSHOT.jar:out src/main/java/org/example/JsonProducer.java\\n\\nPlease note that you may need to replace <jar_name>-1.0-SNAPSHOT.jar with your actual jar file name.'"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qa_bot(\"how can I run kafka?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "e1ce77ae-1827-48a6-b9d7-c4eccb698c1f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Based on the provided CONTEXT, I can help you with setting up Docker. According to Section: Module 1: Docker and Terraform, for setting up Docker on Mac, you can check this article for details: Setting up docker in macOS. However, please note that this method might be outdated since Docker changed their licensing model. An alternative method that worked for someone (including the author of the document) is to go to the Docker website and download their dmg directly.'"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qa_bot(\"how do i set-up docker?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "96029f98-5f75-4eb1-a8eb-75d7b73e1f2e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.13"
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 "nbformat": 4,
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