Homework1/llm-homwork-01.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "149ab4f2-98af-4449-862d-8f011a1783c8",
   "metadata": {},
   "source": [
    "### Q1: Getting the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0b805d43-e4cd-4b21-9bc1-c0fee2001bd3",
   "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": 2,
   "id": "e7222d2b-1b1f-45c1-afc1-3f0fa5e20ce3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'text': \"The purpose of this document is to capture frequently asked technical questions\\nThe exact day and hour of the course will be 15th Jan 2024 at 17h00. The course will start with the first  “Office Hours'' live.1\\nSubscribe to course public Google Calendar (it works from Desktop only).\\nRegister before the course starts using this link.\\nJoin the course Telegram channel with announcements.\\nDon’t forget to register in DataTalks.Club's Slack and join the channel.\",\n",
       " 'section': 'General course-related questions',\n",
       " 'question': 'Course - When will the course start?',\n",
       " 'course': 'data-engineering-zoomcamp'}"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get the first index of the documents above\n",
    "documents[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "26b50ae0-adf2-4fa5-84bd-86289cefe6d2",
   "metadata": {},
   "source": [
    "### Q2: Indexing the data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6a8c466-2fb0-4c45-9cd3-863a86cabe0e",
   "metadata": {},
   "source": [
    "##### Index the data in the same way as was shown in the course videos. Make the course field a keyword and the rest should be text."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d063e7da-5100-4c54-a043-21c8fc581096",
   "metadata": {},
   "outputs": [],
   "source": [
    "#import Elastic search class\n",
    "from elasticsearch import Elasticsearch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "7a5e9950-f91d-4c54-9ad8-4c4e2199a100",
   "metadata": {},
   "outputs": [],
   "source": [
    "#estimator object of elastic search with port. ensure elastic search container is running\n",
    "es_client = Elasticsearch('http://localhost:9200')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4f660f6c-803a-4210-a6d0-bdbbdc35de9e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ObjectApiResponse({'name': '3f4bf6a5221a', 'cluster_name': 'docker-cluster', 'cluster_uuid': '3QpKe2FUSXWfFBxwj4YqHQ', '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": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#call elastic search method\n",
    "es_client.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "89e3d1d7-8fc8-425b-b679-1694098d01c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ObjectApiResponse({'acknowledged': True, 'shards_acknowledged': True, 'index': 'llm-questions'})"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create an index for elastic search engine\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 = \"llm-questions\"\n",
    "\n",
    "es_client.indices.create(index=index_name, body=index_settings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c40552cf-15fc-41ad-8841-4141b67f6a5b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# to track progress bar\n",
    "from tqdm.auto import tqdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "9253411b-11dd-4dd7-8d98-9b20adacd9d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3dddd0ffb5f541b78d816b834a0ebd4f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/948 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# insert all documents into elastic search\n",
    "for doc in tqdm(documents):\n",
    "    es_client.index(index=index_name, document=doc)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1d3f07d5-8e14-4b3b-8319-9971c769e100",
   "metadata": {},
   "source": [
    "### Q3: Searching"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "51d14516-3417-4ccf-af07-ce04c351c57e",
   "metadata": {},
   "source": [
    "##### Now let's search in our index.\n",
    "\n",
    "##### We will execute a query \"How do I execute a command in a running docker container?\".\n",
    "\n",
    "##### Use only question and text fields and give question a boost of 4, and use \"type\": \"best_fields\".\n",
    "\n",
    "##### What's the score for the top ranking result?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "9fdcd9cf-9892-4037-be77-8d7be1298fad",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = \"How do I execute a command in a running docker container?\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "44ad1eca-394b-4712-bbb6-80d6596fbb0c",
   "metadata": {},
   "outputs": [],
   "source": [
    "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",
    "            \"filter\": {\n",
    "                \"term\": {\n",
    "                    \"course\": \"data-engineering-zoomcamp\"\n",
    "                }\n",
    "            }\n",
    "        }\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b839eab9-0622-485c-98d5-947393bc3c5d",
   "metadata": {},
   "outputs": [],
   "source": [
    "#search query in the Elastic search engine\n",
    "response = es_client.search(index=index_name, body=search_query)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "6b097b97-3958-4dfe-9eaf-a7865f72f0c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'_index': 'llm-questions',\n",
       "  '_id': 'ZoMqQ5ABxBO6zzbdV18m',\n",
       "  '_score': 75.54128,\n",
       "  '_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>',\n",
       "   'section': 'Module 1: Docker and Terraform',\n",
       "   'question': 'PGCLI - running in a Docker container',\n",
       "   'course': 'data-engineering-zoomcamp'}},\n",
       " {'_index': 'llm-questions',\n",
       "  '_id': 'hYMqQ5ABxBO6zzbdYWC5',\n",
       "  '_score': 43.922554,\n",
       "  '_source': {'text': 'You can check the version of your local spark using spark-submit --version. In the build.sh file of the Python folder, make sure that SPARK_VERSION matches your local version. Similarly, make sure the pyspark you pip installed also matches this version.',\n",
       "   'section': 'Module 6: streaming with kafka',\n",
       "   'question': 'How do I check compatibility of local and container Spark versions?',\n",
       "   'course': 'data-engineering-zoomcamp'}},\n",
       " {'_index': 'llm-questions',\n",
       "  '_id': 'AYMqQ5ABxBO6zzbdPl9U',\n",
       "  '_score': 38.684105,\n",
       "  '_source': {'text': \"There are 3 Zoom Camps in a year, as of 2024. However, they are for separate courses:\\nData-Engineering (Jan - Apr)\\nMLOps (May - Aug)\\nMachine Learning (Sep - Jan)\\nThere's only one Data-Engineering Zoomcamp “live” cohort per year, for the certification. Same as for the other Zoomcamps.\\nThey follow pretty much the same schedule for each cohort per zoomcamp. For Data-Engineering it is (generally) from Jan-Apr of the year. If you’re not interested in the Certificate, you can take any zoom camps at any time, at your own pace, out of sync with any “live” cohort.\",\n",
       "   'section': 'General course-related questions',\n",
       "   'question': 'Course - how many Zoomcamps in a year?',\n",
       "   'course': 'data-engineering-zoomcamp'}},\n",
       " {'_index': 'llm-questions',\n",
       "  '_id': 'NYMqQ5ABxBO6zzbdQF_d',\n",
       "  '_score': 38.33403,\n",
       "  '_source': {'text': \"It is recommended by the Docker do\\n[Windows 10 / 11 Home Edition] If you're running a Home Edition, you can still make it work with WSL2 (Windows Subsystem for Linux) by following the tutorial here\\nIf even after making sure your WSL2 (or Hyper-V) is set up accordingly, Docker remains stuck, you can try the option to Reset to Factory Defaults or do a fresh install.\",\n",
       "   'section': 'Module 1: Docker and Terraform',\n",
       "   'question': 'Should I run docker commands from the windows file system or a file system of a Linux distribution in WSL?',\n",
       "   'course': 'data-engineering-zoomcamp'}},\n",
       " {'_index': 'llm-questions',\n",
       "  '_id': 'B4MqQ5ABxBO6zzbdPl-T',\n",
       "  '_score': 35.94081,\n",
       "  '_source': {'text': \"No, you can only get a certificate if you finish the course with a “live” cohort. We don't award certificates for the self-paced mode. The reason is you need to peer-review capstone(s) after submitting a project. You can only peer-review projects at the time the course is running.\",\n",
       "   'section': 'General course-related questions',\n",
       "   'question': 'Certificate - Can I follow the course in a self-paced mode and get a certificate?',\n",
       "   'course': 'data-engineering-zoomcamp'}}]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "response['hits']['hits']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "8af2f43e-fdfc-4e02-be12-f3b3d6a1e48e",
   "metadata": {},
   "outputs": [],
   "source": [
    "result_doc = []\n",
    "\n",
    "for hit in response['hits']['hits']:\n",
    "    result_doc.append(hit)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "85d04fba-bf54-41c2-bdbd-7ac56649f1b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "75.54128"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# score of top ranking result\n",
    "result_doc[0]['_score']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c08daf3-ba7e-40cf-aee4-846351b835e7",
   "metadata": {},
   "source": [
    "### Q4: Filtering"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ad5e45b6-dfd6-49c3-904e-4b1c7e977ec9",
   "metadata": {},
   "source": [
    "##### Now let's only limit the questions to machine-learning-zoomcamp.\n",
    "\n",
    "##### Return 3 results. What's the 3rd question returned by the search engine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "69fcd3ac-76be-49a8-83f6-ac9022d9a846",
   "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": 16,
   "id": "f93eab99-c206-48ea-afdd-37420819d5b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "#search query in the Elastic search engine\n",
    "response = es_client.search(index=index_name, body=search_query)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "a6e6ba5f-4c84-4bd3-a44f-285a18993430",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'_index': 'llm-questions',\n",
       "  '_id': 'WIMqQ5ABxBO6zzbdaGHj',\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': 'llm-questions',\n",
       "  '_id': 'd4MqQ5ABxBO6zzbdaWHQ',\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': 'llm-questions',\n",
       "  '_id': 'eIMqQ5ABxBO6zzbdaWHX',\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": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "response['hits']['hits']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "a66d8361-12e6-47c9-8779-d62b7be7b852",
   "metadata": {},
   "outputs": [],
   "source": [
    "result_doc = []\n",
    "\n",
    "for hit in response['hits']['hits']:\n",
    "    result_doc.append(hit)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "89ce8568-2a65-4261-b50f-682fb1d3fb3b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'How do I copy files from a different folder into docker container’s working directory?'"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# What's the 3rd question returned by the search engine\n",
    "result_doc[2]['_source']['question']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35c85ab4-c6cb-442a-ae84-33049cc8d39b",
   "metadata": {},
   "source": [
    "### Q5: Building a prompt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "11c9c2f2-3975-4057-bbf3-3f6cbdf5b13b",
   "metadata": {},
   "source": [
    "##### Now we're ready to build a prompt to send to an LLM.\n",
    "\n",
    "##### 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",
    "##### What's the length of the resulting prompt? (use the len function)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "d8cd3f39-0727-4eb0-8049-77a36f4aa045",
   "metadata": {},
   "outputs": [],
   "source": [
    "context_template = \"\"\"\n",
    "Q: {question}\n",
    "A: {text}\n",
    "\"\"\".strip()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "188f2dd5-60d1-4178-a890-b4efa52226bd",
   "metadata": {},
   "outputs": [],
   "source": [
    "question = 'How do I copy files from a different folder into docker container’s working directory?'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "0488c3ac-a099-45ed-9845-25898577b402",
   "metadata": {},
   "outputs": [],
   "source": [
    "# putting the above in a function:\n",
    "\n",
    "def elastic_search(query):\n",
    "    search_query = {\n",
    "        \"size\": 3,\n",
    "        \"query\": {\n",
    "            \"bool\": {\n",
    "                \"must\": {\n",
    "                    \"multi_match\": {\n",
    "                        \"query\": question,\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",
    "    }\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",
    "    return result_docs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "60327fac-3811-4113-a8ea-711278b0717d",
   "metadata": {},
   "outputs": [],
   "source": [
    "search_results = elastic_search(question)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d3386706-4436-4acc-aa6c-10ea285cf564",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'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'},\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': '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'}]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "search_results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "35ca66c1-f06b-48fc-8368-4e7bb1e6b6d1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# prompt function\n",
    "def build_prompt(query, search_results):\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\"question: {doc['question']}\\nanswer: {doc['text']}\\n\\n\"\n",
    "    \n",
    "    prompt = prompt_template.format(question=question, context=context).strip()\n",
    "    return prompt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "0012ef8f-4a9e-4907-8b6a-f581a3bea3bd",
   "metadata": {},
   "outputs": [],
   "source": [
    "# combining all functions \n",
    "search_results = elastic_search(question)\n",
    "prompt = build_prompt(question, search_results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "5296901c-dcab-4220-8e51-bd9102843a6e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1528"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(prompt)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fd99a6f0-e7b0-4377-96a9-1c5c75ed1616",
   "metadata": {},
   "source": [
    "### Q6: Tokens"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "763b73e6-ad91-42fe-85c7-48cbe96fc2c1",
   "metadata": {},
   "source": [
    "##### Let's calculate the number of tokens in our query with tiktoken:\n",
    "\n",
    "##### Use the encode function. How many tokens does our prompt have?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "39b10951-81c3-4f06-a4ec-ac363d6d993d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import tiktoken"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "8f837598-bf24-42f9-9ebc-d00b1bc9715c",
   "metadata": {},
   "outputs": [],
   "source": [
    "encoding = tiktoken.encoding_for_model(\"gpt-4o\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "b77dda1c-ba4b-463f-8748-1277a8db5355",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "328"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(encoding.encode(text=prompt))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "164926f8-de8d-4da7-becc-ab941fa75d42",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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