Env_QA_System.ipynb

{
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      "metadata": {
        "id": "MqUPQvC2vf9C"
      },
      "source": [
        "# Environmental Issues QA System\n",
        "\n",
        "Prototype of a Question-Answering (QA) system for learning about environmental issues.  \n",
        "\n",
        "The system queries a set of environment-related Wikipedia articles for relevant passages, then uses a fine-tuned language model to produce a list of possible answers. The articles were downloaded in a separate notebook, based on the index page below. Modified from the Haystack Pipeline tutorial, see the original below for more detailed comments. Author: ekohrt.\n",
        "\n",
        "[Original Tutorial Source](https://colab.research.google.com/github/deepset-ai/haystack/blob/main/tutorials/Tutorial1_Basic_QA_Pipeline.ipynb)\n",
        "\n",
        "[Wikipedia Index of Environmental Articles](https://en.wikipedia.org/wiki/Index_of_environmental_articles)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "collapsed": false,
        "id": "188TNAxOvf9J"
      },
      "source": [
        "### Prepare environment\n",
        "\n",
        "#### Colab: Enable the GPU runtime\n",
        "Make sure you enable the GPU runtime to experience decent speed in this tutorial.\n",
        "**Runtime -> Change Runtime type -> Hardware accelerator -> GPU**\n",
        "\n",
        "<img src=\"https://raw.githubusercontent.com/deepset-ai/haystack/main/docs/img/colab_gpu_runtime.jpg\">"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "id": "LH3hg9revf9L"
      },
      "outputs": [],
      "source": [
        "%%capture\n",
        "# Install the latest release of Haystack\n",
        "! pip install farm-haystack\n",
        "\n",
        "# Install the latest main of Haystack\n",
        "!pip install --upgrade pip\n",
        "!pip install git+https://github.com/deepset-ai/haystack.git#egg=farm-haystack[colab]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "outputs": [],
      "source": [
        "from haystack.utils import clean_wiki_text, convert_files_to_docs, print_answers\n",
        "from haystack.nodes import FARMReader, TransformersReader"
      ],
      "metadata": {
        "pycharm": {
          "name": "#%%\n"
        },
        "id": "LwdDsVnQvf9N"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2VVS7QL-vf9O"
      },
      "source": [
        "## Document Store\n",
        "\n",
        "Haystack finds answers to queries within the documents stored in a `DocumentStore`. The current implementations of `DocumentStore` include `ElasticsearchDocumentStore`, `FAISSDocumentStore`,  `SQLDocumentStore`, and `InMemoryDocumentStore`.\n",
        "\n",
        "### Start an Elasticsearch server\n",
        "Manually download and execute Elasticsearch from source."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "id": "Np9C1cdnvf9R"
      },
      "outputs": [],
      "source": [
        "# In Colab / No Docker environments: Start Elasticsearch from source\n",
        "! wget https://artifacts.elastic.co/downloads/elasticsearch/elasticsearch-7.9.2-linux-x86_64.tar.gz -q\n",
        "! tar -xzf elasticsearch-7.9.2-linux-x86_64.tar.gz\n",
        "! chown -R daemon:daemon elasticsearch-7.9.2\n",
        "\n",
        "import os\n",
        "from subprocess import Popen, PIPE, STDOUT\n",
        "\n",
        "es_server = Popen(\n",
        "    [\"elasticsearch-7.9.2/bin/elasticsearch\"], stdout=PIPE, stderr=STDOUT, preexec_fn=lambda: os.setuid(1)  # as daemon\n",
        ")\n",
        "# wait until ES has started\n",
        "! sleep 30"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "pycharm": {
          "name": "#%%\n"
        },
        "id": "izA8L4Mtvf9S"
      },
      "outputs": [],
      "source": [
        "# Connect to Elasticsearch\n",
        "\n",
        "from haystack.document_stores import ElasticsearchDocumentStore\n",
        "\n",
        "document_store = ElasticsearchDocumentStore(host=\"localhost\", username=\"\", password=\"\", index=\"document\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "pycharm": {
          "name": "#%% md\n"
        },
        "id": "n9nKeSJzvf9T"
      },
      "source": [
        "## Loading Documents and Preprocessing"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "pycharm": {
          "name": "#%%\n"
        },
        "outputId": "3199c390-9316-43a8-f17e-f30109043e20",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Te_Kc1QFP7BC"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n",
            "<Document: id=f5f3761d5bfc109259df472f757b14d0, content='\n",
            "== Environmental issues with conventional burials ==\n",
            "Each year, 22 500 cemeteries across the United ...'>\n"
          ]
        }
      ],
      "source": [
        "# Fetch documents to query (collection of 1397 Wikipedia articles about environmental issues)\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')\n",
        "doc_dir = \"/content/drive/MyDrive/Colab Notebooks/Wiki_Env_Articles/\"\n",
        "\n",
        "# Convert files to dicts\n",
        "docs = convert_files_to_docs(dir_path=doc_dir, clean_func=clean_wiki_text, split_paragraphs=True)\n",
        "\n",
        "# look at en example entry:\n",
        "print(docs[42])\n",
        "\n",
        "# Now, let's write the dicts containing documents to our DB.\n",
        "document_store.write_documents(docs)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "S5yF2WSDvf9U"
      },
      "source": [
        "## Initialize Retriever, Reader & Pipeline\n",
        "\n",
        "### Retriever\n",
        "\n",
        "Retrievers help narrow down the scope for the Reader to smaller units of text where a given question could be answered.  \n",
        "We use Elasticsearch's default BM25 algorithm.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "id": "2h-uN28fvf9U"
      },
      "outputs": [],
      "source": [
        "from haystack.nodes import BM25Retriever\n",
        "\n",
        "retriever = BM25Retriever(document_store=document_store)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "S3-tgzgAvf9V"
      },
      "source": [
        "### Reader\n",
        "\n",
        "A Reader scans the texts returned by retrievers in detail and extracts the k best answers. \n",
        "\n",
        "#### FARMReader"
      ]
    },
    {
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              "model_id": "72b4cf6cc986428a8f4189588d78ba81"
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      ],
      "source": [
        "# Load a  local model or any of the QA models on Hugging Face's model hub (https://huggingface.co/models)\n",
        "reader = FARMReader(model_name_or_path=\"deepset/roberta-base-squad2\", use_gpu=True)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SCwBugNLvf9X"
      },
      "source": [
        "### Pipeline\n",
        "\n",
        "With a Haystack `Pipeline` you can stick together your building blocks to a search pipeline.\n",
        "Under the hood, `Pipelines` are Directed Acyclic Graphs (DAGs) that you can easily customize for your own use cases.\n",
        "To speed things up, Haystack also comes with a few predefined Pipelines. One of them is the `ExtractiveQAPipeline` that combines a retriever and a reader to answer our questions.\n",
        "You can learn more about `Pipelines` in the [docs](https://haystack.deepset.ai/docs/latest/pipelinesmd)."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 48,
      "metadata": {
        "pycharm": {
          "is_executing": false
        },
        "id": "WJCPWHSQvf9X"
      },
      "outputs": [],
      "source": [
        "from haystack.pipelines import ExtractiveQAPipeline\n",
        "\n",
        "pipe = ExtractiveQAPipeline(reader, retriever)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CKHmHFdGvf9X"
      },
      "source": [
        "## Example Questions"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 93,
      "metadata": {
        "pycharm": {
          "is_executing": false
        },
        "id": "34QgLU3tvf9Y"
      },
      "outputs": [],
      "source": [
        "# You can configure how many candidates the Reader and Retriever shall return\n",
        "from IPython.utils import io\n",
        "\n",
        "# The higher top_k_retriever, the better (but also the slower) your answers.\n",
        "def ask(query):\n",
        "  with io.capture_output() as captured: # suppress console output\n",
        "    prediction = pipe.run(\n",
        "        query=query, params={\"Retriever\": {\"top_k\": 50}, \"Reader\": {\"top_k\": 3}}\n",
        "    )\n",
        "  return prediction"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 54,
      "metadata": {
        "pycharm": {
          "is_executing": false,
          "name": "#%%\n"
        },
        "id": "sKPhczSnvf9Z",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9cdbc4b3-b7d9-4896-f9b0-85b0304931a7"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Query: What is the main cause of deforestation in the amazon?\n",
            "Answers:\n",
            "[   {   'answer': 'cattle ranching',\n",
            "        'context': 's. Some 80% of the deforestation of the Amazon can be '\n",
            "                   'attributed to cattle ranching, as Brazil is the largest '\n",
            "                   'exporter of beef in the world. The Amazo'},\n",
            "    {   'answer': 'Consumption and production of beef',\n",
            "        'context': 'lion hectares of virgin tropical forest was lost in 2018. '\n",
            "                   'Consumption and production of beef is the primary driver '\n",
            "                   'of deforestation in the Amazon, wit'},\n",
            "    {   'answer': 'Agricultural expansion',\n",
            "        'context': 'lobally due to increasing stocks in temperate and boreal '\n",
            "                   'forest.Agricultural expansion continues to be the main '\n",
            "                   'driver of deforestation and forest fra'}]\n"
          ]
        }
      ],
      "source": [
        "# Correct: cattle ranching\n",
        "prediction = ask(\"What is the main cause of deforestation in the amazon?\")\n",
        "print_answers(prediction, details=\"minimum\")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Incorrect: Qatar\n",
        "prediction = ask(\"What country has the highest per capita carbon emissions?\")\n",
        "print_answers(prediction, details=\"minimum\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FSw8yJu8WiFc",
        "outputId": "382e3522-a7dd-4294-b819-d09af8ba3255"
      },
      "execution_count": 68,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Query: What country has the highest per capita carbon emissions?\n",
            "Answers:\n",
            "[   {   'answer': 'U.S.',\n",
            "        'context': 'mitter at 1.8 Tonnes of CO2e respectively, compared with '\n",
            "                   'for example the U.S. at position of the 14th largest per '\n",
            "                   'capita CO2e emitter at 22.9 Tonnes o'},\n",
            "    {   'answer': 'Denmark',\n",
            "        'context': '\\n'\n",
            "                   '=== Denmark ===\\n'\n",
            "                   'As of 2002, the standard carbon tax rate since 1996 '\n",
            "                   'amounted to 100 kr. per tonne of CO2, equivalent to '\n",
            "                   'approximately €13 or US$18. T'},\n",
            "    {   'answer': 'Japan ===\\nAlthough Japan',\n",
            "        'context': '\\n'\n",
            "                   '=== Japan ===\\n'\n",
            "                   'Although Japan does not tax carbon emissions directly, '\n",
            "                   'since 2012 the country has levied a \"Tax for Climate '\n",
            "                   'Change Mitigation\" on petro'}]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Incorrect: U.S. \n",
        "prediction = ask(\"What country has produced the highest cumulative carbon emissions?\")\n",
        "print_answers(prediction, details=\"minimum\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9CyCBBdGosHa",
        "outputId": "f2cb3e5d-b0de-4984-cda6-763c478c7d8b"
      },
      "execution_count": 77,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Query: What country has produced the highest cumulative carbon emissions?\n",
            "Answers:\n",
            "[   {   'answer': 'Japan',\n",
            "        'context': '\\n'\n",
            "                   '=== Japan ===\\n'\n",
            "                   'Although Japan does not tax carbon emissions directly, '\n",
            "                   'since 2012 the country has levied a \"Tax for Climate '\n",
            "                   'Change Mitigation\" on petro'},\n",
            "    {   'answer': 'Norway',\n",
            "        'context': '(about US$1.3 billion in 2010 dollars).\\n'\n",
            "                   \"According to IEA's 2005 Review, Norway's CO2 tax is its \"\n",
            "                   'most important climate policy instrument, and covers a'},\n",
            "    {   'answer': 'Tokyo',\n",
            "        'context': 'n trading scheme launched in April 2010 covers the top '\n",
            "                   '1,400 emitters in Tokyo, and is enforced and overseen by '\n",
            "                   'the Tokyo Metropolitan Government. Pha'}]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Incorrect: China (weird though, since the context of the first answer actually is about China)\n",
        "prediction = ask(\"What country currently has the highest total carbon emissions?\")\n",
        "print_answers(prediction, details=\"minimum\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cDF71sFGpSNP",
        "outputId": "b714368e-da3c-4f82-c138-787ac50f57bb"
      },
      "execution_count": 96,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Query: What country currently has the highest total carbon emissions?\n",
            "Answers:\n",
            "[   {   'answer': 'India',\n",
            "        'context': ' carbon dioxide than the next two biggest countries '\n",
            "                   'combined (U.S.A. and India). Total carbon dioxide '\n",
            "                   'emissions were projected to increase until 2030.'},\n",
            "    {   'answer': 'United States',\n",
            "        'context': 'he UK, and accounts for about 27% of total emissions, and '\n",
            "                   '33% in the United States.  Of the total greenhouse gas '\n",
            "                   'emissions from transport, over 85% ar'},\n",
            "    {   'answer': 'Japan',\n",
            "        'context': '\\n'\n",
            "                   '=== Japan ===\\n'\n",
            "                   'Although Japan does not tax carbon emissions directly, '\n",
            "                   'since 2012 the country has levied a \"Tax for Climate '\n",
            "                   'Change Mitigation\" on petro'}]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Correct: 1978\n",
        "prediction = ask(\"when were CFCs banned in the US?\")\n",
        "print_answers(prediction, details=\"minimum\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SA1BS4MKkKhG",
        "outputId": "ce67a76e-7798-46e6-b93b-3787e4ff43ed"
      },
      "execution_count": 65,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Query: when were CFCs banned in the US?\n",
            "Answers:\n",
            "[   {   'answer': '1978',\n",
            "        'context': '\\n'\n",
            "                   '==== Regulation and DuPont ====\\n'\n",
            "                   'In 1978 the United States banned the use of CFCs such as '\n",
            "                   'Freon in aerosol cans, the beginning of a long series of '\n",
            "                   'reg'},\n",
            "    {   'answer': '1978',\n",
            "        'context': 'tates, Canada and Norway banned the use of CFCs in aerosol '\n",
            "                   'spray cans in 1978. Early estimates were that, if CFC '\n",
            "                   'production continued at 1977 levels, '},\n",
            "    {   'answer': '1978',\n",
            "        'context': 'ire in 1979. The United States banned the use of CFCs in '\n",
            "                   'aerosol cans in 1978. The European Community rejected '\n",
            "                   'proposals to ban CFCs in aerosol sprays'}]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Correct: Montreal protocol\n",
        "prediction = ask(\"what treaty fixed the ozone layer?\")\n",
        "print_answers(prediction, details=\"minimum\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gubQw4Gopgx8",
        "outputId": "2285abfc-cfff-4d42-bc45-bfbad3433e97"
      },
      "execution_count": 81,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Query: what treaty fixed the ozone layer?\n",
            "Answers:\n",
            "[   {   'answer': 'Montreal Protocol',\n",
            "        'context': 'y for the Preservation of the Ozone Layer, or \"World Ozone '\n",
            "                   'Day\". The designation commerates the signing of the '\n",
            "                   'Montreal Protocol on that date in 1987.'},\n",
            "    {   'answer': 'Montreal Protocol',\n",
            "        'context': 'was the Chief U.S. Negotiator at the meetings that '\n",
            "                   'resulted in the Montreal Protocol.)\\n'\n",
            "                   'Chasek, P. S.; Downie, David L.; Brown, J. W. (2013). '\n",
            "                   'Global En'},\n",
            "    {   'answer': 'Montreal Protocol',\n",
            "        'context': 'was the Chief U.S. Negotiator at the meetings that '\n",
            "                   'resulted in the Montreal Protocol.)\\n'\n",
            "                   'Chasek, Pamela S., David L. Downie, and Janet Welsh Brown '\n",
            "                   '(2013'}]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 2nd guess is correct: 194\n",
        "prediction = ask(\"how many countries signed the paris agreement?\")\n",
        "print_answers(prediction, details=\"minimum\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vWDzDrwrj2o9",
        "outputId": "2b64bcdf-afcd-4d91-896c-3e7689525387"
      },
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Query: how many countries signed the paris agreement?\n",
            "Answers:\n",
            "[   {   'answer': '82',\n",
            "        'context': 'es, Samoa, St. Lucia and Switzerland. At the end of the '\n",
            "                   'signature period, 82 countries and the European Community '\n",
            "                   'had signed. Ratification (which is r'},\n",
            "    {   'answer': '194',\n",
            "        'context': 't developing countries must be financially supported. As '\n",
            "                   'of October 2021, 194 states and the European Union have '\n",
            "                   'signed the treaty and 191 states and '},\n",
            "    {   'answer': '175',\n",
            "        'context': 'ificant climate accord in the history of the climate '\n",
            "                   'movement. On Earth Day 2016, world leaders from 175 '\n",
            "                   'nations broke a record by doing exactly that.'}]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Correct, kind of: an international treaty on climate change\n",
        "prediction = ask(\"What is the paris agreement?\")\n",
        "print_answers(prediction, details=\"minimum\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6l611_SUkm4D",
        "outputId": "4f547a98-0848-42ac-9aa8-877616e61996"
      },
      "execution_count": 69,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Query: What is the paris agreement?\n",
            "Answers:\n",
            "[   {   'answer': 'climate change mitigation responsibilities',\n",
            "        'context': 'such as CO2 emissions reductions of 55% by 2030 by the EU, '\n",
            "                   'climate change mitigation responsibilities of the Paris '\n",
            "                   'Agreement and EU air quality rules.'},\n",
            "    {   'answer': 'to reduce emission',\n",
            "        'context': ' of climate change, not only did Nigeria sign the Paris '\n",
            "                   'agreement to reduce emission, in its national climate '\n",
            "                   'pledge, the Nigerian government has prom'},\n",
            "    {   'answer': 'climate change goals – such as the Paris Agreement on '\n",
            "                  'Climate Change',\n",
            "        'context': 'States. This means that in order to meet climate change '\n",
            "                   'goals – such as the Paris Agreement on Climate Change – '\n",
            "                   'and reduce greenhouse gas emissions, e'}]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Correct, but would prefer a more detailed answer: human activity\n",
        "prediction = ask(\"What causes global warming?\")\n",
        "print_answers(prediction, details=\"minimum\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hqMhr8F2mhBd",
        "outputId": "bf86ac93-441f-444d-a604-561f2fd217d0"
      },
      "execution_count": 73,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Query: What causes global warming?\n",
            "Answers:\n",
            "[   {   'answer': 'human activity',\n",
            "        'context': 'entific consensus that global warming is happening and is '\n",
            "                   'caused by human activity. Disputes over the key scientific '\n",
            "                   'facts of global warming are more '},\n",
            "    {   'answer': 'human activity',\n",
            "        'context': 'the view that the current warming trend exists and is '\n",
            "                   'ongoing, that human activity is the cause, and that it is '\n",
            "                   'without precedent in at least 2000 yea'},\n",
            "    {   'answer': 'human activities',\n",
            "        'context': '\\n'\n",
            "                   '== Background ==\\n'\n",
            "                   'The view that human activities are likely responsible for '\n",
            "                   'most of the observed increase in global mean temperature '\n",
            "                   '(\"global warming\"'}]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 2nd guess is correct: nuclear power\n",
        "prediction = ask(\"What energy source has the lowest carbon emissions?\")\n",
        "print_answers(prediction, details=\"minimum\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wGQP1qIfm_HA",
        "outputId": "b83f9a83-68a3-408d-d293-f7491595df3e"
      },
      "execution_count": 89,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Query: What energy source has the lowest carbon emissions?\n",
            "Answers:\n",
            "[   {   'answer': 'Hydropower',\n",
            "        'context': 'ding security during drought for drinking water supply and '\n",
            "                   'irrigation.Hydropower ranks among the energy sources with '\n",
            "                   'the lowest levels of greenhouse g'},\n",
            "    {   'answer': 'nuclear power',\n",
            "        'context': 'nt from energy consumption can be reduced through the '\n",
            "                   'development of nuclear power (a zero carbon emissions '\n",
            "                   'energy source) and alternative energy proj'},\n",
            "    {   'answer': 'wind',\n",
            "        'context': 'and reduce reliance on fossil fuels. One study claimed '\n",
            "                   'that, as of 2009, wind had the \"lowest relative greenhouse '\n",
            "                   'gas emissions, the least water consu'}]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Correct? Doesn't do well with definitions or long-form answers\n",
        "prediction = ask(\"What is the great pacific garbage patch?\")\n",
        "print_answers(prediction, details=\"minimum\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9YtQgkPGn2hj",
        "outputId": "3b3e007f-5b58-4989-b700-3f954885ffb2"
      },
      "execution_count": 90,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Query: What is the great pacific garbage patch?\n",
            "Answers:\n",
            "[   {   'answer': 'fishing related plastics',\n",
            "        'context': 'n estimated 46% of the Great Pacific garbage patch '\n",
            "                   'consists of fishing related plastics. Fishing nets account '\n",
            "                   'for about 1% of the total mass of all ma'},\n",
            "    {   'answer': 'Donora',\n",
            "        'context': '. Extreme smog events were experienced by the cities of '\n",
            "                   'Los Angeles and Donora, Pennsylvania, in the late 1940s, '\n",
            "                   'serving as another public reminder.Ai'},\n",
            "    {   'answer': 'a huge concentration of plastics, chemical sludge and other '\n",
            "                  'debris',\n",
            "        'context': 'oblem is the Great Pacific Garbage Patch, a huge '\n",
            "                   'concentration of plastics, chemical sludge and other '\n",
            "                   'debris which has been collected into a large are'}]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Incorrect - possibly due to limited corpus\n",
        "prediction = ask(\"Why is cryptocurrency bad for the environment?\")\n",
        "print_answers(prediction, details=\"minimum\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xKkQIl7dqK1V",
        "outputId": "0e77e6da-067b-4f89-9fce-be016a0e6c5a"
      },
      "execution_count": 91,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Query: Why is cryptocurrency bad for the environment?\n",
            "Answers:\n",
            "[   {   'answer': \"it's an inconvenient truth\",\n",
            "        'context': 'so hard for people to grasp.\" To which Gore replied, '\n",
            "                   '\"Because it\\'s an inconvenient truth, ya know.\" \"[...] In '\n",
            "                   \"the back of my head, I go, that's the ti\"},\n",
            "    {   'answer': 'stochastic variation',\n",
            "        'context': 'survival of a small population. Some detrimental effects '\n",
            "                   'include stochastic variation in the environment, (year to '\n",
            "                   'year variation in rainfall, tempera'},\n",
            "    {   'answer': 'in a world where political choices are not made '\n",
            "                  'democratically at a global level, but by a small number of '\n",
            "                  'rich countries and corporations, the poor and the '\n",
            "                  'environment are never going to be a priority',\n",
            "        'context': ' in a world where political choices are not made '\n",
            "                   'democratically at a global level, but by a small number of '\n",
            "                   'rich countries and corporations, the poor and the '\n",
            "                   'environment are never going to be a priority'}]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Correct: glacial melt, melt of the ice sheets in Greenland and Antarctica, and thermal expansion\n",
        "prediction = ask(\"Why does climate change make the ocean level rise?\")\n",
        "print_answers(prediction, details=\"minimum\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_UhvaslbrBIo",
        "outputId": "3846708f-6646-4193-dd2f-323ab3f10884"
      },
      "execution_count": 92,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Query: Why does climate change make the ocean level rise?\n",
            "Answers:\n",
            "[   {   'answer': 'glacial melt, melt of the ice sheets in Greenland and '\n",
            "                  'Antarctica, and thermal expansion',\n",
            "        'context': 'l is rising as a consequence of glacial melt, melt of the '\n",
            "                   'ice sheets in Greenland and Antarctica, and thermal '\n",
            "                   'expansion. Between 1993 and 2020, the ri'},\n",
            "    {   'answer': 'heats (and therefore expands) the ocean',\n",
            "        'context': 'his acceleration is due mostly to climate change, which '\n",
            "                   'heats (and therefore expands) the ocean and which melts '\n",
            "                   'the land-based ice sheets and glaciers'},\n",
            "    {   'answer': 'melting of the West Antarctic ice-sheet alone',\n",
            "        'context': 'ld cause a sea level rise of around 5 m (15 ft) from '\n",
            "                   'melting of the West Antarctic ice-sheet alone.In 2019, a '\n",
            "                   'study projected that in low emission sce'}]\n"
          ]
        }
      ]
    }
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