elastic_rag_hw.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hello\n"
     ]
    }
   ],
   "source": [
    "print(\"hello\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "zsh:1: no matches found: https://github.com/DataTalksClub/llm-zoomcamp/blob/main/01-intro/documents.json?raw=1\n"
     ]
    }
   ],
   "source": [
    "!wget https://github.com/DataTalksClub/llm-zoomcamp/blob/main/01-intro/documents.json?raw=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from dotenv import load_dotenv, find_dotenv\n",
    "\n",
    "_ = load_dotenv(find_dotenv())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ObjectApiResponse({'name': '8266a155d12c', 'cluster_name': 'docker-cluster', 'cluster_uuid': 'DBRFEOrbROmbfb-M2w0Vbg', '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": [
    "from elasticsearch import Elasticsearch\n",
    "\n",
    "es = Elasticsearch(\"http://localhost:9200\")\n",
    "es.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ObjectApiResponse({'acknowledged': True, 'shards_acknowledged': True, 'index': 'course-questions'})"
      ]
     },
     "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",
    "            \"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": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2acca69d4299459e8fe7c85aed5fbd5e",
       "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",
    "\n",
    "for doc in tqdm(documents):\n",
    "    es.index(index=index_name, document=doc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "user_question = \"How do I execute a command in a running docker container?\"\n",
    "\n",
    "search_query = {\n",
    "    \"size\": 5,\n",
    "    \"query\": {\n",
    "        \"bool\": {\n",
    "            \"must\": {\n",
    "                \"multi_match\": {\n",
    "                    \"query\": user_question,\n",
    "                    \"fields\": [\"question^4\", \"text\"],\n",
    "                    \"type\": \"best_fields\"\n",
    "                }\n",
    "            }\n",
    "        }\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Section: 5. Deploying Machine Learning Models\n",
      "Question: How do I debug a docker container?\n",
      "Answer: Launch the container image in interactive mode and overridin...\n",
      "\n",
      "The score is: 84.050095 \n",
      "\n",
      "\n",
      "Section: Module 1: Docker and Terraform\n",
      "Question: PGCLI - running in a Docker container\n",
      "Answer: In case running pgcli  locally causes issues or you do not w...\n",
      "\n",
      "The score is: 75.54128 \n",
      "\n",
      "\n",
      "Section: Module 4: Deployment\n",
      "Question: Running multiple services in a Docker container\n",
      "Answer: If you are trying to run Flask gunicorn & MLFlow server from...\n",
      "\n",
      "The score is: 72.08518 \n",
      "\n",
      "\n",
      "Section: 5. Deploying Machine Learning Models\n",
      "Question: How do I copy files from my local machine to docker container?\n",
      "Answer: You can copy files from your local machine into a Docker con...\n",
      "\n",
      "The score is: 51.04628 \n",
      "\n",
      "\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",
      "Answer: You can copy files from your local machine into a Docker con...\n",
      "\n",
      "The score is: 49.938507 \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']}\")\n",
    "    print(f\"Question: {doc['question']}\")\n",
    "    print(f\"Answer: {doc['text'][:60]}...\\n\")\n",
    "    score = hit[\"_score\"]\n",
    "    print(f\"The score is: {score} \\n\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "user_question = \"How do I execute a command in a running docker container?\"\n",
    "\n",
    "search_query = {\n",
    "    \"size\": 5,\n",
    "    \"query\": {\n",
    "        \"bool\": {\n",
    "            \"must\": {\n",
    "                \"multi_match\": {\n",
    "                    \"query\": user_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",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Section: 5. Deploying Machine Learning Models\n",
      "Question: How do I debug a docker container?\n",
      "Answer: Launch the container image in interactive mode and overridin...\n",
      "\n",
      "The score is: 84.050095 \n",
      "\n",
      "\n",
      "Section: 5. Deploying Machine Learning Models\n",
      "Question: How do I copy files from my local machine to docker container?\n",
      "Answer: You can copy files from your local machine into a Docker con...\n",
      "\n",
      "The score is: 51.04628 \n",
      "\n",
      "\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",
      "Answer: You can copy files from your local machine into a Docker con...\n",
      "\n",
      "The score is: 49.938507 \n",
      "\n",
      "\n",
      "Section: 5. Deploying Machine Learning Models\n",
      "Question: The input device is not a TTY when running docker in interactive mode (Running Docker on Windows in GitBash)\n",
      "Answer: $ docker exec -it 1e5a1b663052 bash\n",
      "the input device is not ...\n",
      "\n",
      "The score is: 45.275463 \n",
      "\n",
      "\n",
      "Section: 5. Deploying Machine Learning Models\n",
      "Question: How to fix error after running the Docker run command\n",
      "Answer: Solution\n",
      "This error was because there was another instance o...\n",
      "\n",
      "The score is: 45.255775 \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']}\")\n",
    "    print(f\"Question: {doc['question']}\")\n",
    "    print(f\"Answer: {doc['text'][:60]}...\\n\")\n",
    "    score = hit[\"_score\"]\n",
    "    print(f\"The score is: {score} \\n\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "It depends on the policies of the course and the instructor. You should reach out to the instructor or course administrator to see if it is possible to join the course late. They may be able to provide you with a syllabus, catch-up materials, or make accommodations for you to join the class. It never hurts to ask!\n"
     ]
    }
   ],
   "source": [
    "from openai import OpenAI\n",
    "\n",
    "client = OpenAI(\n",
    "    api_key = os.environ.get(\"OPENAI_API_KEY\")\n",
    ")\n",
    "\n",
    "response = client.chat.completions.create(\n",
    "    model=\"gpt-3.5-turbo\",\n",
    "    messages=[{\"role\": \"user\", \"content\": \"The course already started. Can I still join?\"}]\n",
    ")\n",
    "print(response.choices[0].message.content)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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\": 3,\n",
    "        \"query\": {\n",
    "            \"bool\": {\n",
    "                \"must\": {\n",
    "                    \"multi_match\": {\n",
    "                        \"query\": user_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.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": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Question: How do I debug a docker container?\n",
      "Answer: Launch the container image in interactive mode and overridin...\n",
      "\n",
      "Question: How do I copy files from my local machine to docker container?\n",
      "Answer: You can copy files from your local machine into a Docker con...\n",
      "\n",
      "Question: How do I copy files from a different folder into docker container’s working directory?\n",
      "Answer: You can copy files from your local machine into a Docker con...\n",
      "\n"
     ]
    }
   ],
   "source": [
    "user_question = \"How do I execute a command in a running docker container?\"\n",
    "\n",
    "response = retrieve_documents(user_question)\n",
    "\n",
    "for doc in response:\n",
    "    print(f\"Question: {doc['question']}\")\n",
    "    print(f\"Answer: {doc['text'][:60]}...\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "context_template = \"\"\"\n",
    "Q: {question}\n",
    "A: {text}\n",
    "\\n\\n\n",
    "\"\"\".strip()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "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_docs = retrieve_documents(user_question)\n",
    "\n",
    "context_result = \"\"\n",
    "\n",
    "for doc in context_docs:\n",
    "    doc_str = context_template.format(**doc)\n",
    "    context_result += (\"\\n\\n\" + doc_str)\n",
    "\n",
    "context = context_result.strip()\n",
    "print(context)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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: {user_question}\n",
    "\n",
    "CONTEXT:\n",
    "{context}\n",
    "\"\"\".strip()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "def build_context(documents):\n",
    "    context_result = \"\"\n",
    "    \n",
    "    for doc in documents:\n",
    "        doc_str = context_template.format(**doc)\n",
    "        context_result += (\"\\n\\n\" + doc_str)\n",
    "    \n",
    "    return context_result.strip()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "def build_prompt(user_question, documents):\n",
    "    context = build_context(documents)\n",
    "    prompt = prompt_template.format(\n",
    "        user_question=user_question,\n",
    "        context=context\n",
    "    )\n",
    "    return prompt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "def ask_openai(prompt, model=\"gpt-4o\"):\n",
    "    response = client.chat.completions.create(\n",
    "        model=model,\n",
    "        messages=[{\"role\": \"user\", \"content\": prompt}]\n",
    "    )\n",
    "    answer = response.choices[0].message.content\n",
    "    return answer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "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": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1462\n"
     ]
    }
   ],
   "source": [
    "user_question = \"How do I execute a command in a running docker container?\"\n",
    "prompt_res = build_prompt(user_question, retrieve_documents(user_question))\n",
    "print(len(prompt_res))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tiktoken\n",
    "encoding = tiktoken.encoding_for_model(\"gpt-4o\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "tokens = encoding.encode(prompt_res)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of tokens: 322\n"
     ]
    }
   ],
   "source": [
    "print(f\"Number of tokens: {len(tokens)}\")"
   ]
  }
 ],
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   "display_name": "anaconda3",
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