{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Question Answering with Langchain, Tair and OpenAI\n",
    "This notebook presents how to implement a Question Answering system with Langchain, Tair as a knowledge based and OpenAI embeddings. If you are not familiar with Tair, it’s better to check out the [Getting_started_with_Tair_and_OpenAI.ipynb](Getting_started_with_Tair_and_OpenAI.ipynb) notebook.\n",
    "\n",
    "This notebook presents an end-to-end process of:\n",
    "- Calculating the embeddings with OpenAI API.\n",
    "- Storing the embeddings in an Tair instance to build a knowledge base.\n",
    "- Converting raw text query to an embedding with OpenAI API.\n",
    "- Using Tair to perform the nearest neighbour search in the created collection to find some context.\n",
    "- Asking LLM to find the answer in a given context.\n",
    "\n",
    "All the steps will be simplified to calling some corresponding Langchain methods."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Prerequisites\n",
    "For the purposes of this exercise we need to prepare a couple of things:\n",
    "[Tair cloud instance](https://www.alibabacloud.com/help/en/tair/latest/what-is-tair).\n",
    "[Langchain](https://github.com/hwchase17/langchain) as a framework.\n",
    "An OpenAI API key."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Install requirements\n",
    "This notebook requires the following Python packages: `openai`, `tiktoken`, `langchain` and `tair`.\n",
    "- `openai` provides convenient access to the OpenAI API.\n",
    "- `tiktoken` is a fast BPE tokeniser for use with OpenAI's models.\n",
    "- `langchain` helps us to build applications with LLM more easily.\n",
    "- `tair` library is used to interact with the tair vector database."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-06T10:21:40.843630Z",
     "start_time": "2023-05-06T10:21:38.796769Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Looking in indexes: http://sg.mirrors.cloud.aliyuncs.com/pypi/simple/\n",
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      "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "! pip install openai tiktoken langchain tair "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prepare your OpenAI API key\n",
    "The OpenAI API key is used for vectorization of the documents and queries.\n",
    "\n",
    "If you don't have an OpenAI API key, you can get one from [https://platform.openai.com/account/api-keys ).\n",
    "\n",
    "Once you get your key, please add it by getpass."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-06T10:21:40.974668Z",
     "start_time": "2023-05-06T10:21:40.845980Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Input your OpenAI API key:········\n"
     ]
    }
   ],
   "source": [
    "import getpass\n",
    "\n",
    "openai_api_key = getpass.getpass(\"Input your OpenAI API key:\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prepare your Tair URL\n",
    "To build the Tair connection, you need to have `TAIR_URL`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-06T10:21:41.574807Z",
     "start_time": "2023-05-06T10:21:40.976664Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Input your tair url:········\n"
     ]
    }
   ],
   "source": [
    "# The format of url: redis://[[username]:[password]]@localhost:6379/0\n",
    "TAIR_URL = getpass.getpass(\"Input your tair url:\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load data\n",
    "In this section we are going to load the data containing some natural questions and answers to them. All the data will be used to create a Langchain application with Tair being the knowledge base."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100% [..............................................................................] 95372 / 95372"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'answers (2).json'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import wget\n",
    "\n",
    "# All the examples come from https://ai.google.com/research/NaturalQuestions\n",
    "# This is a sample of the training set that we download and extract for some\n",
    "# further processing.\n",
    "wget.download(\"https://storage.googleapis.com/dataset-natural-questions/questions.json\")\n",
    "wget.download(\"https://storage.googleapis.com/dataset-natural-questions/answers.json\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "\n",
    "with open(\"questions.json\", \"r\") as fp:\n",
    "    questions = json.load(fp)\n",
    "\n",
    "with open(\"answers.json\", \"r\") as fp:\n",
    "    answers = json.load(fp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "when is the last episode of season 8 of the walking dead\n"
     ]
    }
   ],
   "source": [
    "print(questions[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No . overall No. in season Title Directed by Written by Original air date U.S. viewers ( millions ) 100 `` Mercy '' Greg Nicotero Scott M. Gimple October 22 , 2017 ( 2017 - 10 - 22 ) 11.44 Rick , Maggie , and Ezekiel rally their communities together to take down Negan . Gregory attempts to have the Hilltop residents side with Negan , but they all firmly stand behind Maggie . The group attacks the Sanctuary , taking down its fences and flooding the compound with walkers . With the Sanctuary defaced , everyone leaves except Gabriel , who reluctantly stays to save Gregory , but is left behind when Gregory abandons him . Surrounded by walkers , Gabriel hides in a trailer , where he is trapped inside with Negan . 101 `` The Damned '' Rosemary Rodriguez Matthew Negrete & Channing Powell October 29 , 2017 ( 2017 - 10 - 29 ) 8.92 Rick 's forces split into separate parties to attack several of the Saviors ' outposts , during which many members of the group are killed ; Eric is critically injured and rushed away by Aaron . Jesus stops Tara and Morgan from executing a group of surrendered Saviors . While clearing an outpost with Daryl , Rick is confronted and held at gunpoint by Morales , a survivor he met in the initial Atlanta camp , who is now with the Saviors . 102 `` Monsters '' Greg Nicotero Matthew Negrete & Channing Powell November 5 , 2017 ( 2017 - 11 - 05 ) 8.52 Daryl finds Morales threatening Rick and kills him ; the duo then pursue a group of Saviors who are transporting weapons to another outpost . Gregory returns to Hilltop , and after a heated argument , Maggie ultimately allows him back in the community . Eric dies from his injuries , leaving Aaron distraught . Despite Tara and Morgan 's objections , Jesus leads the group of surrendered Saviors to Hilltop . Ezekiel 's group attacks another Savior compound , during which several Kingdommers are shot while protecting Ezekiel . 103 `` Some Guy '' Dan Liu David Leslie Johnson November 12 , 2017 ( 2017 - 11 - 12 ) 8.69 Ezekiel 's group is overwhelmed by the Saviors , who kill all of them except for Ezekiel himself and Jerry . Carol clears the inside of the compound , killing all but two Saviors , who almost escape but are eventually caught by Rick and Daryl . En route to the Kingdom , Ezekiel , Jerry , and Carol are surrounded by walkers , but Shiva sacrifices herself to save them . The trio returns to the Kingdom , where Ezekiel 's confidence in himself as a leader has diminished . 104 5 `` The Big Scary U '' Michael E. Satrazemis Story by : Scott M. Gimple & David Leslie Johnson & Angela Kang Teleplay by : David Leslie Johnson & Angela Kang November 19 , 2017 ( 2017 - 11 - 19 ) 7.85 After confessing their sins to each other , Gabriel and Negan manage to escape from the trailer . Simon and the other lieutenants grow suspicious of each other , knowing that Rick 's forces must have inside information . The workers in the Sanctuary become increasingly frustrated with their living conditions , and a riot nearly ensues , until Negan returns and restores order . Gabriel is locked in a cell , where Eugene discovers him sick and suffering . Meanwhile , Rick and Daryl argue over how to take out the Saviors , leading Daryl to abandon Rick . 105 6 `` The King , the Widow , and Rick '' John Polson Angela Kang & Corey Reed November 26 , 2017 ( 2017 - 11 - 26 ) 8.28 Rick visits Jadis in hopes of convincing her to turn against Negan ; Jadis refuses , and locks Rick in a shipping container . Carl encounters Siddiq in the woods and recruits him to Alexandria . Daryl and Tara plot to deviate from Rick 's plans by destroying the Sanctuary . Ezekiel isolates himself at the Kingdom , where Carol tries to encourage him to be the leader his people need . Maggie has the group of captured Saviors placed in a holding area and forces Gregory to join them as punishment for betraying Hilltop . 106 7 `` Time for After '' Larry Teng Matthew Negrete & Corey Reed December 3 , 2017 ( 2017 - 12 - 03 ) 7.47 After learning of Dwight 's association with Rick 's group , Eugene affirms his loyalty to Negan and outlines a plan to get rid of the walkers surrounding the Sanctuary . With help from Morgan and Tara , Daryl drives a truck through the Sanctuary 's walls , flooding its interior with walkers , killing many Saviors . Rick finally convinces Jadis and the Scavengers to align with him , and they plan to force the Saviors to surrender . However , when they arrive at the Sanctuary , Rick is horrified to see the breached walls and no sign of the walker herd . 107 8 `` How It 's Gotta Be '' Michael E. Satrazemis David Leslie Johnson & Angela Kang December 10 , 2017 ( 2017 - 12 - 10 ) 7.89 Eugene 's plan allows the Saviors to escape , and separately , the Saviors waylay the Alexandria , Hilltop , and Kingdom forces . The Scavengers abandon Rick , after which he returns to Alexandria . Ezekiel ensures that the Kingdom residents are able to escape before locking himself in the community with the Saviors . Eugene aids Gabriel and Doctor Carson in escaping the Sanctuary in order to ease his conscience . Negan attacks Alexandria , but Carl devises a plan to allow the Alexandria residents to escape into the sewers . Carl reveals he was bitten by a walker while escorting Siddiq to Alexandria . 108 9 `` Honor '' Greg Nicotero Matthew Negrete & Channing Powell February 25 , 2018 ( 2018 - 02 - 25 ) 8.28 After the Saviors leave Alexandria , the survivors make for the Hilltop while Rick and Michonne stay behind to say their final goodbyes to a dying Carl , who pleads with Rick to build a better future alongside the Saviors before killing himself . In the Kingdom , Morgan and Carol launch a rescue mission for Ezekiel . Although they are successful and retake the Kingdom , the Saviors ' lieutenant Gavin is killed by Benjamin 's vengeful brother Henry . 109 10 `` The Lost and the Plunderers '' TBA TBA March 4 , 2018 ( 2018 - 03 - 04 ) TBD 110 11 `` Dead or Alive Or '' TBA TBA March 11 , 2018 ( 2018 - 03 - 11 ) TBD 111 12 `` The Key '' TBA TBA March 18 , 2018 ( 2018 - 03 - 18 ) TBD\n"
     ]
    }
   ],
   "source": [
    "print(answers[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Chain definition\n",
    "\n",
    "Langchain is already integrated with Tair and performs all the indexing for given list of documents. In our case we are going to store the set of answers we have."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.vectorstores import Tair\n",
    "from langchain.embeddings import OpenAIEmbeddings\n",
    "from langchain import VectorDBQA, OpenAI\n",
    "\n",
    "embeddings = OpenAIEmbeddings(openai_api_key=openai_api_key)\n",
    "doc_store = Tair.from_texts(\n",
    "    texts=answers, embedding=embeddings, tair_url=TAIR_URL,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "At this stage all the possible answers are already stored in Tair, so we can define the whole QA chain."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/root/anaconda3/envs/notebook/lib/python3.10/site-packages/langchain/chains/retrieval_qa/base.py:251: UserWarning: `VectorDBQA` is deprecated - please use `from langchain.chains import RetrievalQA`\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "llm = OpenAI(openai_api_key=openai_api_key)\n",
    "qa = VectorDBQA.from_chain_type(\n",
    "    llm=llm,\n",
    "    chain_type=\"stuff\",\n",
    "    vectorstore=doc_store,\n",
    "    return_source_documents=False,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Search data\n",
    "\n",
    "Once the data is put into Tair we can start asking some questions. A question will be automatically vectorized by OpenAI model, and the created vector will be used to find some possibly matching answers in Tair. Once retrieved, the most similar answers will be incorporated into the prompt sent to OpenAI Large Language Model.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "import random\n",
    "\n",
    "random.seed(52)\n",
    "selected_questions = random.choices(questions, k=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "> where do frankenstein and the monster first meet\n",
      " Frankenstein and the monster first meet in the mountains.\n",
      "\n",
      "> who are the actors in fast and furious\n",
      " The actors in Fast & Furious are Vin Diesel ( Dominic Toretto ), Paul Walker ( Brian O'Conner ), Michelle Rodriguez ( Letty Ortiz ), Jordana Brewster ( Mia Toretto ), Tyrese Gibson ( Roman Pearce ), Ludacris ( Tej Parker ), Lucas Black ( Sean Boswell ), Sung Kang ( Han Lue ), Gal Gadot ( Gisele Yashar ), and Dwayne Johnson ( Luke Hobbs ).\n",
      "\n",
      "> properties of red black tree in data structure\n",
      " The properties of a red-black tree in data structure are that each node is either red or black, the root is black, if a node is red then both its children must be black, and every path from a given node to any of its descendant NIL nodes contains the same number of black nodes.\n",
      "\n",
      "> who designed the national coat of arms of south africa\n",
      " Iaan Bekker\n",
      "\n",
      "> caravaggio's death of the virgin pamela askew\n",
      " I don't know.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import time\n",
    "for question in selected_questions:\n",
    "    print(\">\", question)\n",
    "    print(qa.run(question), end=\"\\n\\n\")\n",
    "    # wait 20seconds because of the rate limit\n",
    "    time.sleep(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Custom prompt templates\n",
    "\n",
    "The `stuff` chain type in Langchain uses a specific prompt with question and context documents incorporated. This is what the default prompt looks like:\n",
    "\n",
    "```text\n",
    "Use the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer.\n",
    "{context}\n",
    "Question: {question}\n",
    "Helpful Answer:\n",
    "```\n",
    "\n",
    "We can, however, provide our prompt template and change the behaviour of the OpenAI LLM, while still using the `stuff` chain type. It is important to keep `{context}` and `{question}` as placeholders.\n",
    "\n",
    "#### Experimenting with custom prompts\n",
    "\n",
    "We can try using a different prompt template, so the model:\n",
    "1. Responds with a single-sentence answer if it knows it.\n",
    "2. Suggests a random song title if it doesn't know the answer to our question."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.prompts import PromptTemplate\n",
    "custom_prompt = \"\"\"\n",
    "Use the following pieces of context to answer the question at the end. Please provide\n",
    "a short single-sentence summary answer only. If you don't know the answer or if it's\n",
    "not present in given context, don't try to make up an answer, but suggest me a random\n",
    "unrelated song title I could listen to.\n",
    "Context: {context}\n",
    "Question: {question}\n",
    "Helpful Answer:\n",
    "\"\"\"\n",
    "\n",
    "custom_prompt_template = PromptTemplate(\n",
    "    template=custom_prompt, input_variables=[\"context\", \"question\"]\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "custom_qa = VectorDBQA.from_chain_type(\n",
    "    llm=llm,\n",
    "    chain_type=\"stuff\",\n",
    "    vectorstore=doc_store,\n",
    "    return_source_documents=False,\n",
    "    chain_type_kwargs={\"prompt\": custom_prompt_template},\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "> what was uncle jesse's original last name on full house\n",
      "Uncle Jesse's original last name on Full House was Cochran.\n",
      "\n",
      "> when did the volcano erupt in indonesia 2018\n",
      "The given context does not mention any volcanic eruption in Indonesia in 2018. Suggested song title: \"The Heat Is On\" by Glenn Frey.\n",
      "\n",
      "> what does a dualist way of thinking mean\n",
      "Dualism means the belief that there is a distinction between the mind and the body, and that the mind is a non-extended, non-physical substance.\n",
      "\n",
      "> the first civil service commission in india was set up on the basis of recommendation of\n",
      "The first Civil Service Commission in India was not set up on the basis of the recommendation of the Election Commission of India's Model Code of Conduct.\n",
      "\n",
      "> how old do you have to be to get a tattoo in utah\n",
      "You must be at least 18 years old to get a tattoo in Utah.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "random.seed(41)\n",
    "for question in random.choices(questions, k=5):\n",
    "    print(\">\", question)\n",
    "    print(custom_qa.run(question), end=\"\\n\\n\")\n",
    "    # wait 20seconds because of the rate limit\n",
    "    time.sleep(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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