01_intro/homework1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "e86b6474-aab4-422a-ae11-e7b0596e538f",
   "metadata": {},
   "source": [
    "## Q1. Running Elastic"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1d74905a-5cfa-4ca3-a7ce-26904cc3f118",
   "metadata": {},
   "source": [
    "What's the version.build_hash value?"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a5a4d491-4e98-4253-a653-17d686c847a5",
   "metadata": {},
   "source": [
    " 42f05b9372a9a4a470db3b52817899b99a76ee73 "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d60b07b-a2fa-4b0e-b5ea-5a7b4bfee086",
   "metadata": {},
   "source": [
    "## Q2. Indexing the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "609a8cca-97c5-44b5-9bf6-f76e6f8c9268",
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests \n",
    "\n",
    "docs_url = 'https://github.com/DataTalksClub/llm-zoomcamp/blob/main/01-intro/documents.json?raw=1'\n",
    "docs_response = requests.get(docs_url)\n",
    "documents_raw = docs_response.json()\n",
    "\n",
    "documents = []\n",
    "\n",
    "for course in documents_raw:\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": 6,
   "id": "5ecc2af6-2513-421c-b168-625056d06c71",
   "metadata": {},
   "outputs": [],
   "source": [
    "from elasticsearch import Elasticsearch\n",
    "\n",
    "\n",
    "es_client = Elasticsearch('http://localhost:9200')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "57fc6a78-bf35-49ad-b71a-f9faf7503006",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ObjectApiResponse({'acknowledged': True, 'shards_acknowledged': True, 'index': 'course-questions'})"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create index\n",
    "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",
    "es_client.indices.create(index=index_name, body=index_settings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "fa4de442-3e2d-44f0-b4f6-30aa19a6f22b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2634612b84594ad88d13aba698bdbef4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/948 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from tqdm.auto import tqdm\n",
    "for doc in tqdm(documents):\n",
    "    es_client.index(index=index_name, document=doc)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d956c70-ee42-4286-b4b9-5925d35cd5f3",
   "metadata": {},
   "source": [
    "### Which function do you use for adding your data to elastic?\n",
    "insert\n",
    "index\n",
    "put\n",
    "add"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "152bb0ba-2e9d-458a-846b-58d515d438b8",
   "metadata": {},
   "source": [
    "### index"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a008d9be-12d1-47b9-9795-43f41f0fa24b",
   "metadata": {},
   "source": [
    "# Q3. Searching"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a7360575-80f6-4771-8c37-08cda693635b",
   "metadata": {},
   "outputs": [],
   "source": [
    "def elastic_search(query):\n",
    "    search_query = {\n",
    "        \"size\": 5,\n",
    "        \"query\": {\n",
    "            \"bool\": {\n",
    "                \"must\": {\n",
    "                    \"multi_match\": {\n",
    "                        \"query\": query,\n",
    "                        \"fields\": [\"question^4\", \"text\"],\n",
    "                        \"type\": \"best_fields\"\n",
    "                    }\n",
    "                }\n",
    "            }\n",
    "        }\n",
    "    }\n",
    "\n",
    "    response = es_client.search(index = index_name, body=search_query)\n",
    "    \n",
    "    result_docs = []\n",
    "    \n",
    "    for hit in response ['hits']['hits']:\n",
    "        result_docs.append(hit['_score'])\n",
    "    \n",
    "    \n",
    "    return result_docs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "97daf9fe-39de-4615-a6b3-8ba8f22fc5f9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[84.050095, 75.54128, 72.08518, 51.04628, 49.938507]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "query = \"How do I execute a command in a running docker container?\"\n",
    "elastic_search(query)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc768472-3f61-4a1b-b7e7-fd121b2222bc",
   "metadata": {},
   "source": [
    "#84.05"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a23b28ee-4e91-4b54-a992-dc8e021b6b43",
   "metadata": {},
   "source": [
    "# Q4. Filtering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "903c5c4d-85b3-4900-bc28-fd6cf49b5c2a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'How do I copy files from a different folder into docker container’s working directory?'"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "search_query = {\n",
    "    \"size\": 3,\n",
    "    \"query\": {\n",
    "        \"bool\": {\n",
    "            \"must\": {\n",
    "                \"multi_match\": {\n",
    "                    \"query\": query,\n",
    "                    \"fields\": [\"question^4\", \"text\", \"section\"],\n",
    "                    \"type\": \"best_fields\"\n",
    "                }\n",
    "            },\n",
    "            \"filter\": {\n",
    "                \"term\": {\n",
    "                    \"course\": \"machine-learning-zoomcamp\"\n",
    "                }\n",
    "            }\n",
    "        }\n",
    "    }\n",
    "}\n",
    "\n",
    "response = es_client.search(index = index_name, body=search_query)\n",
    "\n",
    "result_docs = []\n",
    "\n",
    "for hit in response ['hits']['hits']:\n",
    "    result_docs.append(hit['_source'])\n",
    "\n",
    "\n",
    "result_docs[2]['question']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "16eea001-c7ca-4554-b92a-3e5a0946805b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'text': 'Launch the container image in interactive mode and overriding the entrypoint, so that it starts a bash command.\\ndocker run -it --entrypoint bash <image>\\nIf the container is already running, execute a command in the specific container:\\ndocker ps (find the container-id)\\ndocker exec -it <container-id> bash\\n(Marcos MJD)',\n",
       "  'section': '5. Deploying Machine Learning Models',\n",
       "  'question': 'How do I debug a docker container?',\n",
       "  'course': 'machine-learning-zoomcamp'},\n",
       " {'text': \"You can copy files from your local machine into a Docker container using the docker cp command. Here's how to do it:\\nTo copy a file or directory from your local machine into a running Docker container, you can use the `docker cp command`. The basic syntax is as follows:\\ndocker cp /path/to/local/file_or_directory container_id:/path/in/container\\nHrithik Kumar Advani\",\n",
       "  'section': '5. Deploying Machine Learning Models',\n",
       "  'question': 'How do I copy files from my local machine to docker container?',\n",
       "  'course': 'machine-learning-zoomcamp'},\n",
       " {'text': 'You can copy files from your local machine into a Docker container using the docker cp command. Here\\'s how to do it:\\nIn the Dockerfile, you can provide the folder containing the files that you want to copy over. The basic syntax is as follows:\\nCOPY [\"src/predict.py\", \"models/xgb_model.bin\", \"./\"]\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGopakumar Gopinathan',\n",
       "  'section': '5. Deploying Machine Learning Models',\n",
       "  'question': 'How do I copy files from a different folder into docker container’s working directory?',\n",
       "  'course': 'machine-learning-zoomcamp'}]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result_docs"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ed0100c-5e16-405e-abca-eedebaab8817",
   "metadata": {},
   "source": [
    "# Q5. Building a prompt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "89256a24-c642-406e-af27-369218fae95a",
   "metadata": {},
   "source": [
    "Take the records returned from Elasticsearch in Q4 and use this template to build the context. Separate context entries by two linebreaks (\\n\\n)\n",
    "\n",
    "context_template = \"\"\"\n",
    "Q: {question}\n",
    "A: {text}\n",
    "\"\"\".strip()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "2127349c-a1a6-4bc1-8c82-de172e05eb2f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from openai import OpenAI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "dfff6c73-3a4c-424d-9c45-839330ec84c7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Q: How do I debug a docker container?\n",
      "A: Launch the container image in interactive mode and overriding the entrypoint, so that it starts a bash command.\n",
      "docker run -it --entrypoint bash <image>\n",
      "If the container is already running, execute a command in the specific container:\n",
      "docker ps (find the container-id)\n",
      "docker exec -it <container-id> bash\n",
      "(Marcos MJD)\n",
      "\n",
      "Q: How do I copy files from my local machine to docker container?\n",
      "A: You can copy files from your local machine into a Docker container using the docker cp command. Here's how to do it:\n",
      "To copy a file or directory from your local machine into a running Docker container, you can use the `docker cp command`. The basic syntax is as follows:\n",
      "docker cp /path/to/local/file_or_directory container_id:/path/in/container\n",
      "Hrithik Kumar Advani\n",
      "\n",
      "Q: How do I copy files from a different folder into docker container’s working directory?\n",
      "A: You can copy files from your local machine into a Docker container using the docker cp command. Here's how to do it:\n",
      "In the Dockerfile, you can provide the folder containing the files that you want to copy over. The basic syntax is as follows:\n",
      "COPY [\"src/predict.py\", \"models/xgb_model.bin\", \"./\"]\t\t\t\t\t\t\t\t\t\t\tGopakumar Gopinathan\n"
     ]
    }
   ],
   "source": [
    "context_template = \"\"\"\n",
    "Q: {question}\n",
    "A: {text}\n",
    "\"\"\".strip()\n",
    "\n",
    "# Build the context string\n",
    "context_entries = [context_template.format(question=doc[\"question\"], text=doc[\"text\"]) for doc in result_docs]\n",
    "context = \"\\n\\n\".join(context_entries)\n",
    "\n",
    "print(context)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "31511a8a-d8af-43d9-b809-09bd4e0a62e8",
   "metadata": {},
   "outputs": [],
   "source": [
    "def build_prompt(query, search_results):\n",
    "    context_template = \"\"\"\n",
    "Q: {question}\n",
    "A: {text}\n",
    "\"\"\".strip() \n",
    "    \n",
    "    prompt_template = \"\"\"\n",
    "You're a course teaching assistant. Answer the QUESTION based on the CONTEXT from the FAQ database.\n",
    "Use only the facts from the CONTEXT when answering the QUESTION.\n",
    "\n",
    "QUESTION: {question}\n",
    "\n",
    "CONTEXT:\n",
    "{context}\n",
    "\"\"\".strip()\n",
    "\n",
    "    context = \"\"\n",
    "    \n",
    "    for doc in search_results:\n",
    "        context = context + f\"{context_template.format(question=doc['question'], text=doc['text'])}\\n\\n\"\n",
    "    \n",
    "    prompt = prompt_template.format(question=query, context=context).strip()\n",
    "    return prompt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "f75a2ad7-c9df-458c-a612-6a864977d667",
   "metadata": {},
   "outputs": [],
   "source": [
    "prompt = build_prompt(query, result_docs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "70e22c17-c786-415d-b26f-c781841a40c4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "You're a course teaching assistant. Answer the QUESTION based on the CONTEXT from the FAQ database.\n",
      "Use only the facts from the CONTEXT when answering the QUESTION.\n",
      "\n",
      "QUESTION: How do I execute a command in a running docker container?\n",
      "\n",
      "CONTEXT:\n",
      "Q: How do I debug a docker container?\n",
      "A: Launch the container image in interactive mode and overriding the entrypoint, so that it starts a bash command.\n",
      "docker run -it --entrypoint bash <image>\n",
      "If the container is already running, execute a command in the specific container:\n",
      "docker ps (find the container-id)\n",
      "docker exec -it <container-id> bash\n",
      "(Marcos MJD)\n",
      "\n",
      "Q: How do I copy files from my local machine to docker container?\n",
      "A: You can copy files from your local machine into a Docker container using the docker cp command. Here's how to do it:\n",
      "To copy a file or directory from your local machine into a running Docker container, you can use the `docker cp command`. The basic syntax is as follows:\n",
      "docker cp /path/to/local/file_or_directory container_id:/path/in/container\n",
      "Hrithik Kumar Advani\n",
      "\n",
      "Q: How do I copy files from a different folder into docker container’s working directory?\n",
      "A: You can copy files from your local machine into a Docker container using the docker cp command. Here's how to do it:\n",
      "In the Dockerfile, you can provide the folder containing the files that you want to copy over. The basic syntax is as follows:\n",
      "COPY [\"src/predict.py\", \"models/xgb_model.bin\", \"./\"]\t\t\t\t\t\t\t\t\t\t\tGopakumar Gopinathan\n"
     ]
    }
   ],
   "source": [
    "print(prompt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "910a8b74-1617-4194-9881-080743917a92",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1462"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(prompt)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3139ccd1-e767-47f4-8047-e919822852e5",
   "metadata": {},
   "source": [
    "# Q6. Tokens"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "d16cd29e-3b7d-4964-b921-3313a9566b0a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: tiktoken in /usr/local/python/3.10.13/lib/python3.10/site-packages (0.7.0)\n",
      "Requirement already satisfied: regex>=2022.1.18 in /usr/local/python/3.10.13/lib/python3.10/site-packages (from tiktoken) (2024.5.15)\n",
      "Requirement already satisfied: requests>=2.26.0 in /home/codespace/.local/lib/python3.10/site-packages (from tiktoken) (2.32.3)\n",
      "Requirement already satisfied: charset-normalizer<4,>=2 in /home/codespace/.local/lib/python3.10/site-packages (from requests>=2.26.0->tiktoken) (3.3.2)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /home/codespace/.local/lib/python3.10/site-packages (from requests>=2.26.0->tiktoken) (3.7)\n",
      "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/python/3.10.13/lib/python3.10/site-packages (from requests>=2.26.0->tiktoken) (2.0.7)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /home/codespace/.local/lib/python3.10/site-packages (from requests>=2.26.0->tiktoken) (2024.2.2)\n",
      "\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;49mpython3 -m pip install --upgrade pip\u001b[0m\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install tiktoken"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "eb340576-b64a-40fb-bbc4-d1e96cef71ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "import tiktoken"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "e3a0fce7-e155-4454-8905-d28757fcc959",
   "metadata": {},
   "outputs": [],
   "source": [
    "encoding = tiktoken.encoding_for_model(\"gpt-4o\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "4c845516-de9c-432d-81b9-1f3929d9c576",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "322"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(encoding.encode(prompt))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9806525f-d229-4b2b-8b6d-7968cad227e3",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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