01 - intro/Week 1 - Homework.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "dbfd18b7-064a-4f28-a81a-af302512f7fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "078b2584-3691-4883-8eba-f157f694280c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: requests in /home/codespace/.local/lib/python3.10/site-packages (2.32.3)\n",
      "Requirement already satisfied: charset-normalizer<4,>=2 in /home/codespace/.local/lib/python3.10/site-packages (from requests) (3.3.2)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /home/codespace/.local/lib/python3.10/site-packages (from requests) (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) (2.0.7)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /home/codespace/.local/lib/python3.10/site-packages (from requests) (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\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"
     ]
    }
   ],
   "source": [
    "!pip install requests"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5f27b560-8adc-4cf2-9c12-7b54cad8daea",
   "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": 4,
   "id": "9b254215-fd0d-4854-8d7e-633017838c03",
   "metadata": {},
   "outputs": [],
   "source": [
    "from elasticsearch import Elasticsearch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e74a26f6-1509-484d-966e-37f5050db98d",
   "metadata": {},
   "outputs": [],
   "source": [
    "es_client = Elasticsearch('http://localhost:9200')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f778f178-b7d5-45d9-85a3-3f5bc5320384",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ObjectApiResponse({'name': '1c1469dd8db9', 'cluster_name': 'docker-cluster', 'cluster_uuid': '95fbJix7S4CexGPFRTGYYw', '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": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "es_client.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "212d4cf2-5397-41a2-b0d6-2d87d6ec8160",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ObjectApiResponse({'acknowledged': True, 'shards_acknowledged': True, 'index': 'homework_responses4'})"
      ]
     },
     "execution_count": 9,
     "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",
    "            \"question\": {\"type\": \"text\"},\n",
    "            \"section\": {\"type\": \"text\"},\n",
    "            \"course\": {\"type\": \"keyword\"} \n",
    "        }\n",
    "    }\n",
    "}   \n",
    "\n",
    "index_name = \"homework_responses4\"\n",
    "\n",
    "es_client.indices.create(index=index_name, body=index_settings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "25d57ad6-e282-49c3-a816-f26ec15f416c",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/python/3.10.13/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"
     ]
    }
   ],
   "source": [
    "from tqdm.auto import tqdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "12edf8bf-bfc4-4f3f-acbb-569d69b84fc3",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 948/948 [00:23<00:00, 39.91it/s]\n"
     ]
    }
   ],
   "source": [
    "for doc in tqdm(documents):\n",
    "    es_client.index(index=index_name, document=doc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "7c6889ab-e28e-434e-add1-ea8d293c0c0b",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = 'How do I execute a command in a running docker container?'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "7fc3cede-401f-4a37-aed2-139ae6be5eea",
   "metadata": {},
   "outputs": [],
   "source": [
    "search_query = {\n",
    "    \"size\": 3,\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",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "d4611f93-0279-41b4-a7a2-125fcdada778",
   "metadata": {},
   "outputs": [],
   "source": [
    "response = es_client.search(index=index_name, body=search_query)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "533b81fa-7276-4e04-b227-a1df3842bb17",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ObjectApiResponse({'took': 105, 'timed_out': False, '_shards': {'total': 1, 'successful': 1, 'skipped': 0, 'failed': 0}, 'hits': {'total': {'value': 865, 'relation': 'eq'}, 'max_score': 84.050095, 'hits': [{'_index': 'homework_responses4', '_id': 'h1f5SpABrtCsKLdlQEwQ', '_score': 84.050095, '_source': {'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)', 'section': '5. Deploying Machine Learning Models', 'question': 'How do I debug a docker container?', 'course': 'machine-learning-zoomcamp'}}, {'_index': 'homework_responses4', '_id': 'lVf5SpABrtCsKLdlD0od', '_score': 75.54128, '_source': {'text': 'In case running pgcli  locally causes issues or you do not want to install it locally you can use it running in a Docker container instead.\\nBelow the usage with values used in the videos of the course for:\\nnetwork name (docker network)\\npostgres related variables for pgcli\\nHostname\\nUsername\\nPort\\nDatabase name\\n$ docker run -it --rm --network pg-network ai2ys/dockerized-pgcli:4.0.1\\n175dd47cda07:/# pgcli -h pg-database -U root -p 5432 -d ny_taxi\\nPassword for root:\\nServer: PostgreSQL 16.1 (Debian 16.1-1.pgdg120+1)\\nVersion: 4.0.1\\nHome: http://pgcli.com\\nroot@pg-database:ny_taxi> \\\\dt\\n+--------+------------------+-------+-------+\\n| Schema | Name             | Type  | Owner |\\n|--------+------------------+-------+-------|\\n| public | yellow_taxi_data | table | root  |\\n+--------+------------------+-------+-------+\\nSELECT 1\\nTime: 0.009s\\nroot@pg-database:ny_taxi>', 'section': 'Module 1: Docker and Terraform', 'question': 'PGCLI - running in a Docker container', 'course': 'data-engineering-zoomcamp'}}, {'_index': 'homework_responses4', '_id': 'tlf5SpABrtCsKLdlXU0M', '_score': 72.08518, '_source': {'text': 'If you are trying to run Flask gunicorn & MLFlow server from the same container, defining both in Dockerfile with CMD will only run MLFlow & not Flask.\\nSolution: Create separate shell script with server run commands, for eg:\\n> \\tscript1.sh\\n#!/bin/bash\\ngunicorn --bind=0.0.0.0:9696 predict:app\\nAnother script with e.g. MLFlow server:\\n>\\tscript2.sh\\n#!/bin/bash\\nmlflow server -h 0.0.0.0 -p 5000 --backend-store-uri=sqlite:///mlflow.db --default-artifact-root=g3://zc-bucket/mlruns/\\nCreate a wrapper script to run above 2 scripts:\\n>\\twrapper_script.sh\\n#!/bin/bash\\n# Start the first process\\n./script1.sh &\\n# Start the second process\\n./script2.sh &\\n# Wait for any process to exit\\nwait -n\\n# Exit with status of process that exited first\\nexit $?\\nGive executable permissions to all scripts:\\nchmod +x *.sh\\nNow we can define last line of Dockerfile as:\\n> \\tDockerfile\\nCMD ./wrapper_script.sh\\nDont forget to expose all ports defined by services!', 'section': 'Module 4: Deployment', 'question': 'Running multiple services in a Docker container', 'course': 'mlops-zoomcamp'}}]}})"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "response"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90e6690e-b827-41c7-8d67-17a97fbc33b9",
   "metadata": {},
   "source": [
    "# Q4: Filtering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "e4366657-791a-43c3-8514-bc0d557bc16c",
   "metadata": {},
   "outputs": [],
   "source": [
    "search_query = {\n",
    "    \"size\": 3,\n",
    "    \"query\": {\n",
    "        \"bool\": {\n",
    "            \"must\": {\n",
    "                \"multi_match\": {\n",
    "                    \"query\": query,\n",
    "                    \"fields\": [\"question^4\", \"text\"],\n",
    "                    \"type\": \"best_fields\"\n",
    "                }\n",
    "            },\n",
    "            \"filter\": {\n",
    "                \"term\": {\n",
    "                    \"course\": \"machine-learning-zoomcamp\"\n",
    "                }\n",
    "            }\n",
    "        }\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "6a220497-9d9f-4e50-914a-f97cb539ed6d",
   "metadata": {},
   "outputs": [],
   "source": [
    "search_results = es_client.search(index=index_name, body=search_query)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "44fdc786-d793-439c-9644-014280194115",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ObjectApiResponse({'took': 25, 'timed_out': False, '_shards': {'total': 1, 'successful': 1, 'skipped': 0, 'failed': 0}, 'hits': {'total': {'value': 345, 'relation': 'eq'}, 'max_score': 84.050095, 'hits': [{'_index': 'homework_responses4', '_id': 'h1f5SpABrtCsKLdlQEwQ', '_score': 84.050095, '_source': {'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)', 'section': '5. Deploying Machine Learning Models', 'question': 'How do I debug a docker container?', 'course': 'machine-learning-zoomcamp'}}, {'_index': 'homework_responses4', '_id': 'plf5SpABrtCsKLdlQ0we', '_score': 51.04628, '_source': {'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\", 'section': '5. Deploying Machine Learning Models', 'question': 'How do I copy files from my local machine to docker container?', 'course': 'machine-learning-zoomcamp'}}, {'_index': 'homework_responses4', '_id': 'p1f5SpABrtCsKLdlQ0w1', '_score': 49.938507, '_source': {'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', 'section': '5. Deploying Machine Learning Models', 'question': 'How do I copy files from a different folder into docker container’s working directory?', 'course': 'machine-learning-zoomcamp'}}]}})"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "search_results"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94c7c446-fbc2-4d7e-a414-2b5de1328644",
   "metadata": {},
   "source": [
    "# Q5: Tempalates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "dd52821d-71d7-43b2-a6a0-390865dcbf0e",
   "metadata": {},
   "outputs": [],
   "source": [
    "context_template = \"\"\"\n",
    "Q: {question}\n",
    "A: {text}\n",
    "\"\"\".strip()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "26aa0b05-84d6-419d-b8ce-494dc18bc774",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'_index': 'homework_responses4',\n",
       "  '_id': 'h1f5SpABrtCsKLdlQEwQ',\n",
       "  '_score': 84.050095,\n",
       "  '_source': {'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",
       " {'_index': 'homework_responses4',\n",
       "  '_id': 'plf5SpABrtCsKLdlQ0we',\n",
       "  '_score': 51.04628,\n",
       "  '_source': {'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",
       " {'_index': 'homework_responses4',\n",
       "  '_id': 'p1f5SpABrtCsKLdlQ0w1',\n",
       "  '_score': 49.938507,\n",
       "  '_source': {'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": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "search_results['hits']['hits']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "4d86f24d-b4b7-48ba-bc51-6cc26142d9f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "result_docs = []\n",
    "\n",
    "for hit in search_results['hits']['hits']:\n",
    "    result_docs.append(hit['_source'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "6eb20949-26d3-4823-94be-f87c1e12877c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ObjectApiResponse({'took': 25, 'timed_out': False, '_shards': {'total': 1, 'successful': 1, 'skipped': 0, 'failed': 0}, 'hits': {'total': {'value': 345, 'relation': 'eq'}, 'max_score': 84.050095, 'hits': [{'_index': 'homework_responses4', '_id': 'h1f5SpABrtCsKLdlQEwQ', '_score': 84.050095, '_source': {'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)', 'section': '5. Deploying Machine Learning Models', 'question': 'How do I debug a docker container?', 'course': 'machine-learning-zoomcamp'}}, {'_index': 'homework_responses4', '_id': 'plf5SpABrtCsKLdlQ0we', '_score': 51.04628, '_source': {'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\", 'section': '5. Deploying Machine Learning Models', 'question': 'How do I copy files from my local machine to docker container?', 'course': 'machine-learning-zoomcamp'}}, {'_index': 'homework_responses4', '_id': 'p1f5SpABrtCsKLdlQ0w1', '_score': 49.938507, '_source': {'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', 'section': '5. Deploying Machine Learning Models', 'question': 'How do I copy files from a different folder into docker container’s working directory?', 'course': 'machine-learning-zoomcamp'}}]}})"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "search_results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "ed1d8fbc-aa28-442c-9bf8-751ffbcd8e74",
   "metadata": {},
   "outputs": [],
   "source": [
    "context = \"\"\n",
    "\n",
    "# for doc in search_results:\n",
    "#         context = context + context_template.format(question={doc['question']}, text={doc['text']}) + \"\\n\\n\"\n",
    "\n",
    "for doc in search_results['hits']['hits']:\n",
    "    question = doc['_source']['question']\n",
    "    text = doc['_source']['text']\n",
    "    context += context_template.format(question=question, text=text) + \"\\n\\n\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "7b8f758a-882b-4e60-9b9f-621b0aa80a47",
   "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",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(context)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "fac30833-4fdc-4d2c-9277-22ec2f441ba8",
   "metadata": {},
   "outputs": [],
   "source": [
    "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: {context}\n",
    "\"\"\".strip()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "0b56da09-51f9-4a3f-a9aa-49352b5669ef",
   "metadata": {},
   "outputs": [],
   "source": [
    "prompt = prompt_template.format(question=query, context=context).strip()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "3d3ba514-6022-4899-9d3b-1968a3afe7dd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'You\\'re a course teaching assistant. Answer the QUESTION based on the CONTEXT from the FAQ database.\\nUse only the facts from the CONTEXT when answering the QUESTION.\\n\\nQUESTION: How do I execute a command in a running docker container?\\n\\nCONTEXT: Q: How do I debug a docker container?\\nA: 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\\nQ: How do I copy files from my local machine to docker container?\\nA: 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\\nQ: How do I copy files from a different folder into docker container’s working directory?\\nA: 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'"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prompt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "f038841a-6858-412c-a58a-fac751db50a9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1462"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(prompt)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "43fe99af-6282-42d6-bdd7-a7bc6d227a96",
   "metadata": {},
   "source": [
    "## Q6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "247e045c-872e-4de5-8b48-8dcba013367d",
   "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\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": 31,
   "id": "a66b005a-640a-4caa-a3b9-9f9c62d54e62",
   "metadata": {},
   "outputs": [],
   "source": [
    "import tiktoken\n",
    "\n",
    "encoding = tiktoken.encoding_for_model(\"gpt-4o\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "94df63e2-d231-4636-8c39-0ada7258b595",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<Encoding 'o200k_base'>\n"
     ]
    }
   ],
   "source": [
    "print(encoding)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "13694254-76ad-4153-ae0c-66ab28638298",
   "metadata": {},
   "outputs": [],
   "source": [
    "encoded_prompt = encoding.encode(prompt)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "0981e009-f100-4add-9bb8-85fced13100e",
   "metadata": {},
   "outputs": [],
   "source": [
    "num_tokens = len(encoded_prompt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "5bff740f-ec49-4e1b-a897-ed2b795d0f5a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "322"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_tokens"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fddb8fc9-6102-4761-bc9e-097fe8af2618",
   "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": "3.10.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}