generative_QA__ElasticDocStore.ipynb

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  },
  "cells": [
    {
      "cell_type": "code",
      "source": [
        "!pip install --upgrade pip\n",
        "!pip install git+https://github.com/deepset-ai/haystack.git#egg=farm-haystack[colab,ocr]"
      ],
      "metadata": {
        "id": "Ph-M35yQELg6"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!wget --no-check-certificate https://dl.xpdfreader.com/xpdf-tools-linux-4.03.tar.gz\n",
        "!tar -xvf xpdf-tools-linux-4.03.tar.gz\n",
        "!sudo cp xpdf-tools-linux-4.03/bin64/pdftotext /usr/local/bin"
      ],
      "metadata": {
        "id": "D9_bx0s4Enna"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from haystack.modeling.utils import initialize_device_settings\n",
        "devices, n_gpu = initialize_device_settings(use_cuda=True)"
      ],
      "metadata": {
        "id": "zgIhCjOSMOal"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from typing import List\n",
        "import requests\n",
        "import pandas as pd\n",
        "\n",
        "from haystack import Document\n",
        "from haystack.nodes import TextConverter, PDFToTextConverter, DocxToTextConverter, PreProcessor\n",
        "from haystack.utils import convert_files_to_dicts, fetch_archive_from_http, clean_wiki_text\n",
        "from haystack.nodes import RAGenerator, EmbeddingRetriever, DensePassageRetriever\n",
        "# from haystack.document_stores.faiss import FAISSDocumentStore -> We will use ElasticSearch Document Store"
      ],
      "metadata": {
        "id": "llaXkL-WE1tS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Alternative 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",
        "es_server = Popen(['elasticsearch-7.9.2/bin/elasticsearch'],\n",
        "                   stdout=PIPE, stderr=STDOUT,\n",
        "                   preexec_fn=lambda: os.setuid(1)  # as daemon\n",
        "                  )\n",
        "# wait until ES has started\n",
        "! sleep 30"
      ],
      "metadata": {
        "id": "M3RaCN0bMu4P"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# from google.colab import files\n",
        "# uploaded = files.upload()"
      ],
      "metadata": {
        "id": "rmpfz3eOsy6R"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "root_dir = \"../data\"\n",
        "doc_dir = \"/QA_data_1\"\n",
        "\n",
        "all_docs = convert_files_to_dicts(root_dir,clean_func=clean_wiki_text, split_paragraphs=True)\n",
        "#all_docs = convert_files_to_dicts(dir_path=doc_dir, clean_func=clean_wiki_text, split_paragraphs=True)"
      ],
      "metadata": {
        "id": "2Z4YPjIMPDrX",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3a547fa1-1e14-4a6b-8ef6-461c31e8ca09"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO - haystack.utils.preprocessing -  Converting ../data/QA_data_1.pdf\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "preprocessor = PreProcessor(\n",
        "    split_length=200,\n",
        "    split_overlap=0,\n",
        "    split_respect_sentence_boundary=False,\n",
        "    clean_empty_lines=False,\n",
        "    clean_whitespace=False\n",
        ")"
      ],
      "metadata": {
        "id": "hN8vJuKgPpG2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "85ff019d-f20f-497f-c262-39468ed1b9ea"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[nltk_data] Downloading package punkt to /root/nltk_data...\n",
            "[nltk_data]   Unzipping tokenizers/punkt.zip.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Checking if the data is processed.\n",
        "docs = preprocessor.process(all_docs)\n",
        "print(f\"n_files_input: {len(all_docs)}\\nn_docs_output: {len(docs)}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Tmr5bk1FPtCm",
        "outputId": "f1433dd5-86f4-49b8-b3c5-174bce90ba22"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 1/1 [00:00<00:00, 2790.62docs/s]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "n_files_input: 1\n",
            "n_docs_output: 4\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from haystack.utils import launch_es\n",
        "#These indexes are for evaluation data.\n",
        "doc_index = \"eval_docs\"\n",
        "label_index = \"eval_labels\"\n",
        "from haystack.document_stores import ElasticsearchDocumentStore\n",
        "document_store = ElasticsearchDocumentStore()\n"
      ],
      "metadata": {
        "id": "-90vuQzJNSUq",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "479bc0fb-7f53-4848-8515-f6a1f6d6fe84"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING - haystack.utils.doc_store -  Tried to start Elasticsearch through Docker but this failed. It is likely that there is already an existing Elasticsearch instance running. \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Adding documents to the document store\n",
        "document_store.delete_documents()\n",
        "document_store.write_documents(all_docs)"
      ],
      "metadata": {
        "id": "biNHrw6N59l3"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#initializing DPR Retriever\n",
        "retriever = DensePassageRetriever(\n",
        "    document_store=document_store,\n",
        "    query_embedding_model=\"facebook/dpr-question_encoder-single-nq-base\",\n",
        "    passage_embedding_model=\"facebook/dpr-ctx_encoder-single-nq-base\",\n",
        "    use_gpu=True,\n",
        "    embed_title=True,\n",
        "    max_seq_len_passage=256,\n",
        ")"
      ],
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            "INFO - haystack.modeling.utils -  Using devices: CUDA:0\n",
            "INFO - haystack.modeling.utils -  Number of GPUs: 1\n"
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          "text": [
            "INFO - haystack.modeling.model.language_model -  LOADING MODEL\n",
            "INFO - haystack.modeling.model.language_model -  =============\n",
            "INFO - haystack.modeling.model.language_model -  Could not find facebook/dpr-question_encoder-single-nq-base locally.\n",
            "INFO - haystack.modeling.model.language_model -  Looking on Transformers Model Hub (in local cache and online)...\n"
          ]
        },
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          "metadata": {}
        },
        {
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          "text": [
            "INFO - haystack.modeling.model.language_model -  Loaded facebook/dpr-question_encoder-single-nq-base\n"
          ]
        },
        {
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        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "a9b6df7332f645a29ee4f245200a405b",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "Downloading:   0%|          | 0.00/492 [00:00<?, ?B/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "The tokenizer class you load from this checkpoint is not the same type as the class this function is called from. It may result in unexpected tokenization. \n",
            "The tokenizer class you load from this checkpoint is 'DPRQuestionEncoderTokenizer'. \n",
            "The class this function is called from is 'DPRContextEncoderTokenizerFast'.\n",
            "INFO - haystack.modeling.model.language_model -  LOADING MODEL\n",
            "INFO - haystack.modeling.model.language_model -  =============\n",
            "INFO - haystack.modeling.model.language_model -  Could not find facebook/dpr-ctx_encoder-single-nq-base locally.\n",
            "INFO - haystack.modeling.model.language_model -  Looking on Transformers Model Hub (in local cache and online)...\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "5bac221ae26c4096af1961de4feb7073",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "Downloading:   0%|          | 0.00/418M [00:00<?, ?B/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO - haystack.modeling.model.language_model -  Loaded facebook/dpr-ctx_encoder-single-nq-base\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Must update the embeddings\n",
        "document_store.update_embeddings(retriever,update_existing_embeddings = False)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 66,
          "referenced_widgets": [
            "f40b9431bf394dcc9bbeee3a07690083",
            "c2f98fcc4b8b41d087aae6bdb0bd26d5",
            "45c99c141e99467880b54c1d0b1d647d",
            "7db0453f4e894178bad7aa41e38ba81f",
            "6f03f167ae464a7db6107de6d5f3ad00",
            "2a69a3dcb7fd4971a3ebc94376eed28f",
            "e29bf151b8dd473b8ff3a7da8d68a153",
            "413f90acd009477a86d61df184358a48",
            "acf97d587dfe4c1c8561ceead697a686",
            "f7cdf016249d405b86bb3ab8e380dad7",
            "79c197ec568143679582d22f6a9626e0"
          ]
        },
        "id": "IrhH8ON_6H7N",
        "outputId": "d0eac9ad-3ea1-4e5e-ca61-f2c49f143f43"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO - haystack.document_stores.elasticsearch -  Updating embeddings for 1 docs without embeddings ...\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "f40b9431bf394dcc9bbeee3a07690083",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "Updating embeddings:   0%|          | 0/1 [00:00<?, ? Docs/s]"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Describing documents\n",
        "#document_store.describe_documents(index = doc_index)\n",
        "# display(docs[0].keys())\n",
        "# all_docs[0][\"meta\"]\n",
        "#dicts = convert_files_to_dicts(dir_path=root_dir, clean_func=clean_wiki_text, split_paragraphs=True)\n",
        "dicts[0].meta"
      ],
      "metadata": {
        "id": "-lHrbN8M6k8a"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "newdocs = retriever.embed_documents(dicts)"
      ],
      "metadata": {
        "id": "2lmpZPp1E9Mg"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "test = document_store.get_all_documents()\n",
        "display(test)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 54
        },
        "id": "KCFoCEt7-c27",
        "outputId": "b860b998-3872-4a3a-d1f0-c910b47f625f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "[<Document: {'content': \"No student of a foreign language needs to be told that grammar is complex. By changing word sequences and by adding a range of auxiliary verbs and suffixes, we are able to communicate tiny variations in meaning. We can turn a statement into a question, state whether an action has taken place or is soon to take place, and perform many other word tricks to convey subtle differences in meaning. Nor is this complexity inherent to the English language. All languages, even those of socalled 'primitive' tribes have clever grammatical components. The Cherokee pronoun system, for example, can distinguish between 'you and I', 'several other people and I' and 'you, another person and I'. In English, all these meanings are summed up in the one, crude pronoun 'we'. Grammar is universal and plays a part in every language, no matter how widespread it is. So the question which has baffled many linguists is - who created grammar?\\nAt first, it would appear that this question is impossible to answer. To find out how grammar is created, someone needs to be present at the time of a language's creation, documenting its emergence. Many historical linguists are able to trace modern complex languages back to earlier languages, but in order to answer the question of how complex languages are actually formed, the researcher needs to observe how languages are started from scratch. Amazingly, however, this is possible.\\nSome of the most recent languages evolved due to the Atlantic slave trade. At that time, slaves from a number of different ethnicities were forced to work together under colonizer's rule. Since they had no opportunity to learn each other's languages, they developed a make-shift language called a pidgin. Pidgins are strings of words copied from the language of the landowner. They have little in the way of grammar, and in many cases it is difficult for a listener to deduce when an event happened, and who did what to whom. Speakers need to use circumlocution in order to make their meaning understood. Interestingly, however, all it takes for a pidgin to become a complex language is for a group of children to be exposed to it at the time when they learn their mother tongue. Slave children did not simply copy the strings of words uttered by their elders, they adapted their words to create a new, expressive language. Complex grammar systems which emerge from pidgins are termed creoles, and they are invented by children.\\nFurther evidence of this can be seen in studying sign languages for the deaf. Sign languages are not simply a series of gestures; they utilise the same grammatical machinery that is found in spoken languages. Moreover, there are many different languages used worldwide. The creation of one such language was documented quite recently in Nicaragua. Previously, all deaf people were isolated from each other, but in 1979 a new government introduced schools for the deaf. Although children were taught speech and lip reading in the classroom, in the playgrounds they began to invent their own sign system, using the gestures that they used at home. It was basically a pidgin. Each child used the signs differently, and there was no consistent grammar. However, children who joined the school later, when this inventive sign system was already around, developed a quite different sign language. Although it was based on the signs of the older children, the younger children's language was more\\n\\x0cfluid and compact, and it utilised a large range of grammatical devices to clarify meaning. What is more, all the children used the signs in the same way. A new creole was born.\\nSome linguists believe that many of the world's most established languages were creoles at first. The English past tense ed ending may have evolved from the verb 'do'. 'It ended' may once have been 'It end-did'. Therefore it would appear that even the most widespread languages were partly created by children. Children appear to have innate grammatical machinery in their brains, which springs to life when they are first trying to make sense of the world around them. Their minds can serve to create logical, complex structures, even when there is no grammar present for them to copy.\", 'content_type': 'text', 'score': None, 'meta': {'name': 'QA_data_1.pdf'}, 'embedding': None, 'id': '69dccb7862dec2069e45be5403077784'}>]"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "document_store.return_embedding = True"
      ],
      "metadata": {
        "id": "uR2zZyK7O5kF"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#initializing RAG Generator\n",
        "generator = RAGenerator(\n",
        "    model_name_or_path=\"facebook/rag-token-nq\",\n",
        "    use_gpu=True,\n",
        "    top_k=1,\n",
        "    max_length=200,\n",
        "    min_length=2,\n",
        "    embed_title=True,\n",
        "    num_beams=2,\n",
        ")"
      ],
      "metadata": {
        "id": "42t-5iq9QXw9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 382,
          "referenced_widgets": [
            "92b0125996484dd8bba6a1253904b902",
            "b8044e04739a4bf78c7398a7fde63793",
            "48842428cfd946eb9640b4dd070f9d2e",
            "19a427b1269e461f9abd51e2c442f9c7",
            "9dc10a734d36464d8373123c9a14a55d",
            "29694e451ed64fcc9fb6806e40984d26",
            "0d122df61fd44725908a15578ce35f72",
            "8f99a04646e94431b29ea29110899ed4",
            "e5fac4780b6e410a931ccb6cd0cc6b41",
            "4eb9d6804ab5487590fc8d0264dd89fc",
            "42a3c595e14d4314b6ada5154c0f81d7"
          ]
        },
        "outputId": "c75bb973-dfad-45a8-f7ea-d5ca0d5b24d3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO - haystack.modeling.utils -  Using devices: CUDA\n",
            "INFO - haystack.modeling.utils -  Number of GPUs: 1\n",
            "/usr/local/lib/python3.7/dist-packages/transformers/models/bart/configuration_bart.py:178: UserWarning: Please make sure the config includes `forced_bos_token_id=0` in future versions. The config can simply be saved and uploaded again to be fixed.\n",
            "  f\"Please make sure the config includes `forced_bos_token_id={self.bos_token_id}` in future versions. \"\n",
            "The tokenizer class you load from this checkpoint is not the same type as the class this function is called from. It may result in unexpected tokenization. \n",
            "The tokenizer class you load from this checkpoint is 'RagTokenizer'. \n",
            "The class this function is called from is 'DPRQuestionEncoderTokenizer'.\n",
            "The tokenizer class you load from this checkpoint is not the same type as the class this function is called from. It may result in unexpected tokenization. \n",
            "The tokenizer class you load from this checkpoint is 'RagTokenizer'. \n",
            "The class this function is called from is 'DPRQuestionEncoderTokenizerFast'.\n",
            "The tokenizer class you load from this checkpoint is not the same type as the class this function is called from. It may result in unexpected tokenization. \n",
            "The tokenizer class you load from this checkpoint is 'RagTokenizer'. \n",
            "The class this function is called from is 'BartTokenizer'.\n",
            "The tokenizer class you load from this checkpoint is not the same type as the class this function is called from. It may result in unexpected tokenization. \n",
            "The tokenizer class you load from this checkpoint is 'RagTokenizer'. \n",
            "The class this function is called from is 'BartTokenizerFast'.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "92b0125996484dd8bba6a1253904b902",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "Downloading:   0%|          | 0.00/1.92G [00:00<?, ?B/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Some weights of RagTokenForGeneration were not initialized from the model checkpoint at facebook/rag-token-nq and are newly initialized: ['rag.generator.lm_head.weight']\n",
            "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from haystack.pipelines import GenerativeQAPipeline\n",
        "from haystack.utils import print_answers"
      ],
      "metadata": {
        "id": "XU25ZFujRBGP"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pipe = GenerativeQAPipeline(generator = generator, retriever = retriever)\n",
        "res = pipe.run(query = \"Languages are created by\",  params={\"Generator\": {\"top_k\": 1}, \"Retriever\": {\"top_k\": 5}})"
      ],
      "metadata": {
        "id": "HpF42Oz4RIfu",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "4e1ecc6e-cada-4e90-fadd-32a4b864b67a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "Exception",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mConnectionRefusedError\u001b[0m                    Traceback (most recent call last)",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/urllib3/connection.py\u001b[0m in \u001b[0;36m_new_conn\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    158\u001b[0m             conn = connection.create_connection(\n\u001b[0;32m--> 159\u001b[0;31m                 (self._dns_host, self.port), self.timeout, **extra_kw)\n\u001b[0m\u001b[1;32m    160\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/urllib3/util/connection.py\u001b[0m in \u001b[0;36mcreate_connection\u001b[0;34m(address, timeout, source_address, socket_options)\u001b[0m\n\u001b[1;32m     79\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0merr\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 80\u001b[0;31m         \u001b[0;32mraise\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     81\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/urllib3/util/connection.py\u001b[0m in \u001b[0;36mcreate_connection\u001b[0;34m(address, timeout, source_address, socket_options)\u001b[0m\n\u001b[1;32m     69\u001b[0m                 \u001b[0msock\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbind\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msource_address\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 70\u001b[0;31m             \u001b[0msock\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconnect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msa\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     71\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0msock\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mConnectionRefusedError\u001b[0m: [Errno 111] Connection refused",
            "\nDuring handling of the above exception, another exception occurred:\n",
            "\u001b[0;31mNewConnectionError\u001b[0m                        Traceback (most recent call last)",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/elasticsearch/connection/http_urllib3.py\u001b[0m in \u001b[0;36mperform_request\u001b[0;34m(self, method, url, params, body, timeout, ignore, headers)\u001b[0m\n\u001b[1;32m    245\u001b[0m             response = self.pool.urlopen(\n\u001b[0;32m--> 246\u001b[0;31m                 \u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbody\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mretries\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mRetry\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheaders\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mrequest_headers\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkw\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    247\u001b[0m             )\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/urllib3/connectionpool.py\u001b[0m in \u001b[0;36murlopen\u001b[0;34m(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)\u001b[0m\n\u001b[1;32m    637\u001b[0m             retries = retries.increment(method, url, error=e, _pool=self,\n\u001b[0;32m--> 638\u001b[0;31m                                         _stacktrace=sys.exc_info()[2])\n\u001b[0m\u001b[1;32m    639\u001b[0m             \u001b[0mretries\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msleep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/urllib3/util/retry.py\u001b[0m in \u001b[0;36mincrement\u001b[0;34m(self, method, url, response, error, _pool, _stacktrace)\u001b[0m\n\u001b[1;32m    343\u001b[0m             \u001b[0;31m# Disabled, indicate to re-raise the error.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 344\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0msix\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreraise\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0merror\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merror\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m_stacktrace\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    345\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/urllib3/packages/six.py\u001b[0m in \u001b[0;36mreraise\u001b[0;34m(tp, value, tb)\u001b[0m\n\u001b[1;32m    685\u001b[0m             \u001b[0;32mraise\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwith_traceback\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 686\u001b[0;31m         \u001b[0;32mraise\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    687\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/urllib3/connectionpool.py\u001b[0m in \u001b[0;36murlopen\u001b[0;34m(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)\u001b[0m\n\u001b[1;32m    599\u001b[0m                                                   \u001b[0mbody\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mbody\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheaders\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mheaders\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 600\u001b[0;31m                                                   chunked=chunked)\n\u001b[0m\u001b[1;32m    601\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/urllib3/connectionpool.py\u001b[0m in \u001b[0;36m_make_request\u001b[0;34m(self, conn, method, url, timeout, chunked, **httplib_request_kw)\u001b[0m\n\u001b[1;32m    353\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 354\u001b[0;31m             \u001b[0mconn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrequest\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mhttplib_request_kw\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    355\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.7/http/client.py\u001b[0m in \u001b[0;36mrequest\u001b[0;34m(self, method, url, body, headers, encode_chunked)\u001b[0m\n\u001b[1;32m   1280\u001b[0m         \u001b[0;34m\"\"\"Send a complete request to the server.\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1281\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_send_request\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbody\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheaders\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mencode_chunked\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1282\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.7/http/client.py\u001b[0m in \u001b[0;36m_send_request\u001b[0;34m(self, method, url, body, headers, encode_chunked)\u001b[0m\n\u001b[1;32m   1326\u001b[0m             \u001b[0mbody\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_encode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbody\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'body'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1327\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mendheaders\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbody\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mencode_chunked\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mencode_chunked\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1328\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.7/http/client.py\u001b[0m in \u001b[0;36mendheaders\u001b[0;34m(self, message_body, encode_chunked)\u001b[0m\n\u001b[1;32m   1275\u001b[0m             \u001b[0;32mraise\u001b[0m \u001b[0mCannotSendHeader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1276\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_send_output\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmessage_body\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mencode_chunked\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mencode_chunked\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1277\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.7/http/client.py\u001b[0m in \u001b[0;36m_send_output\u001b[0;34m(self, message_body, encode_chunked)\u001b[0m\n\u001b[1;32m   1035\u001b[0m         \u001b[0;32mdel\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_buffer\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1036\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1037\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.7/http/client.py\u001b[0m in \u001b[0;36msend\u001b[0;34m(self, data)\u001b[0m\n\u001b[1;32m    975\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mauto_open\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 976\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconnect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    977\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/urllib3/connection.py\u001b[0m in \u001b[0;36mconnect\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    180\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mconnect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 181\u001b[0;31m         \u001b[0mconn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_new_conn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    182\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_prepare_conn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/urllib3/connection.py\u001b[0m in \u001b[0;36m_new_conn\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    167\u001b[0m             raise NewConnectionError(\n\u001b[0;32m--> 168\u001b[0;31m                 self, \"Failed to establish a new connection: %s\" % e)\n\u001b[0m\u001b[1;32m    169\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mNewConnectionError\u001b[0m: <urllib3.connection.HTTPConnection object at 0x7f27f1849990>: Failed to establish a new connection: [Errno 111] Connection refused",
            "\nDuring handling of the above exception, another exception occurred:\n",
            "\u001b[0;31mConnectionError\u001b[0m                           Traceback (most recent call last)",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/haystack/pipelines/base.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(self, query, file_paths, labels, documents, meta, params, debug)\u001b[0m\n\u001b[1;32m    385\u001b[0m                     \u001b[0mlogger\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdebug\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"Running node `{node_id}` with input `{node_input}`\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 386\u001b[0;31m                     \u001b[0mnode_output\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstream_id\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgraph\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnodes\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mnode_id\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"component\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_dispatch_run\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mnode_input\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    387\u001b[0m                 \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/haystack/nodes/base.py\u001b[0m in \u001b[0;36m_dispatch_run\u001b[0;34m(self, **kwargs)\u001b[0m\n\u001b[1;32m    134\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 135\u001b[0;31m         \u001b[0moutput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstream\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mrun_inputs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mrun_params\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    136\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/haystack/nodes/retriever/base.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(self, root_node, query, filters, top_k, documents, index, headers)\u001b[0m\n\u001b[1;32m    232\u001b[0m             \u001b[0mrun_query_timed\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtiming\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_query\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"query_time\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 233\u001b[0;31m             \u001b[0moutput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstream\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrun_query_timed\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mquery\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mquery\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfilters\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfilters\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtop_k\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtop_k\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindex\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheaders\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mheaders\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    234\u001b[0m         \u001b[0;32melif\u001b[0m \u001b[0mroot_node\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"File\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/haystack/nodes/retriever/base.py\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     76\u001b[0m             \u001b[0mtic\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mperf_counter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 77\u001b[0;31m             \u001b[0mret\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     78\u001b[0m             \u001b[0mtoc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mperf_counter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/haystack/nodes/retriever/base.py\u001b[0m in \u001b[0;36mrun_query\u001b[0;34m(self, query, filters, top_k, index, headers)\u001b[0m\n\u001b[1;32m    249\u001b[0m     ):\n\u001b[0;32m--> 250\u001b[0;31m         \u001b[0mdocuments\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mretrieve\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mquery\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mquery\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfilters\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfilters\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtop_k\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtop_k\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindex\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheaders\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mheaders\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    251\u001b[0m         \u001b[0mdocument_ids\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mdoc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mid\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mdoc\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mdocuments\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/haystack/nodes/retriever/dense.py\u001b[0m in \u001b[0;36mretrieve\u001b[0;34m(self, query, filters, top_k, index, headers)\u001b[0m\n\u001b[1;32m    214\u001b[0m         \u001b[0mquery_emb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0membed_queries\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtexts\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mquery\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 215\u001b[0;31m         \u001b[0mdocuments\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdocument_store\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mquery_by_embedding\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mquery_emb\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mquery_emb\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtop_k\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtop_k\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfilters\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfilters\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindex\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheaders\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mheaders\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    216\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mdocuments\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/haystack/document_stores/elasticsearch.py\u001b[0m in \u001b[0;36mquery_by_embedding\u001b[0;34m(self, query_emb, filters, top_k, index, return_embedding, headers)\u001b[0m\n\u001b[1;32m    966\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 967\u001b[0;31m                 \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclient\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msearch\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbody\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mbody\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrequest_timeout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m300\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheaders\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mheaders\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"hits\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"hits\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    968\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/elasticsearch/client/utils.py\u001b[0m in \u001b[0;36m_wrapped\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    151\u001b[0m                     \u001b[0mparams\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mp\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mp\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 152\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mparams\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheaders\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mheaders\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    153\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/elasticsearch/client/__init__.py\u001b[0m in \u001b[0;36msearch\u001b[0;34m(self, body, index, doc_type, params, headers)\u001b[0m\n\u001b[1;32m   1662\u001b[0m             \u001b[0mheaders\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mheaders\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1663\u001b[0;31m             \u001b[0mbody\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mbody\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1664\u001b[0m         )\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/elasticsearch/transport.py\u001b[0m in \u001b[0;36mperform_request\u001b[0;34m(self, method, url, headers, params, body)\u001b[0m\n\u001b[1;32m    389\u001b[0m                     \u001b[0;32mif\u001b[0m \u001b[0mattempt\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmax_retries\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 390\u001b[0;31m                         \u001b[0;32mraise\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    391\u001b[0m                 \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/elasticsearch/transport.py\u001b[0m in \u001b[0;36mperform_request\u001b[0;34m(self, method, url, headers, params, body)\u001b[0m\n\u001b[1;32m    364\u001b[0m                     \u001b[0mignore\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mignore\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 365\u001b[0;31m                     \u001b[0mtimeout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    366\u001b[0m                 )\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/elasticsearch/connection/http_urllib3.py\u001b[0m in \u001b[0;36mperform_request\u001b[0;34m(self, method, url, params, body, timeout, ignore, headers)\u001b[0m\n\u001b[1;32m    257\u001b[0m                 \u001b[0;32mraise\u001b[0m \u001b[0mConnectionTimeout\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"TIMEOUT\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0me\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 258\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mConnectionError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"N/A\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0me\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    259\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mConnectionError\u001b[0m: ConnectionError(<urllib3.connection.HTTPConnection object at 0x7f27f1849990>: Failed to establish a new connection: [Errno 111] Connection refused) caused by: NewConnectionError(<urllib3.connection.HTTPConnection object at 0x7f27f1849990>: Failed to establish a new connection: [Errno 111] Connection refused)",
            "\nDuring handling of the above exception, another exception occurred:\n",
            "\u001b[0;31mException\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-18-0e974f21b966>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mpipe\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mGenerativeQAPipeline\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgenerator\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgenerator\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mretriever\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mretriever\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpipe\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mquery\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"Languages are created by\"\u001b[0m\u001b[0;34m,\u001b[0m  \u001b[0mparams\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0;34m\"Generator\"\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m\"top_k\"\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"Retriever\"\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m\"top_k\"\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;36m5\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/haystack/pipelines/standard_pipelines.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(self, query, params, debug)\u001b[0m\n\u001b[1;32m    272\u001b[0m               \u001b[0mby\u001b[0m \u001b[0mthis\u001b[0m \u001b[0mmethod\u001b[0m \u001b[0munder\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;34m\"_debug\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    273\u001b[0m         \"\"\"\n\u001b[0;32m--> 274\u001b[0;31m         \u001b[0moutput\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpipeline\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mquery\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mquery\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mparams\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdebug\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdebug\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    275\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0moutput\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    276\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/haystack/pipelines/base.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(self, query, file_paths, labels, documents, meta, params, debug)\u001b[0m\n\u001b[1;32m    387\u001b[0m                 \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    388\u001b[0m                     \u001b[0mtb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtraceback\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat_exc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 389\u001b[0;31m                     \u001b[0;32mraise\u001b[0m \u001b[0mException\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"Exception while running node `{node_id}` with input `{node_input}`: {e}, full stack trace: {tb}\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    390\u001b[0m                 \u001b[0mqueue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnode_id\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    391\u001b[0m                 \u001b[0mnext_nodes\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_next_nodes\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnode_id\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstream_id\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mException\u001b[0m: Exception while running node `Retriever` with input `{'root_node': 'Query', 'params': {'Generator': {'top_k': 1}, 'Retriever': {'top_k': 5}}, 'query': 'Languages are created by', 'node_id': 'Retriever'}`: ConnectionError(<urllib3.connection.HTTPConnection object at 0x7f27f1849990>: Failed to establish a new connection: [Errno 111] Connection refused) caused by: NewConnectionError(<urllib3.connection.HTTPConnection object at 0x7f27f1849990>: Failed to establish a new connection: [Errno 111] Connection refused), full stack trace: Traceback (most recent call last):\n  File \"/usr/local/lib/python3.7/dist-packages/urllib3/connection.py\", line 159, in _new_conn\n    (self._dns_host, self.port), self.timeout, **extra_kw)\n  File \"/usr/local/lib/python3.7/dist-packages/urllib3/util/connection.py\", line 80, in create_connection\n    raise err\n  File \"/usr/local/lib/python3.7/dist-packages/urllib3/util/connection.py\", line 70, in create_connection\n    sock.connect(sa)\nConnectionRefusedError: [Errno 111] Connection refused\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n  File \"/usr/local/lib/python3.7/dist-packages/elasticsearch/connection/http_urllib3.py\", line 246, in perform_request\n    method, url, body, retries=Retry(False), headers=request_headers, **kw\n  File \"/usr/local/lib/python3.7/dist-packages/urllib3/connectionpool.py\", line 638, in urlopen\n    _stacktrace=sys.exc_info()[2])\n  File \"/usr/local/lib/python3.7/dist-packages/urllib3/util/retry.py\", line 344, in increment\n    raise six.reraise(type(error), error, _stacktrace)\n  File \"/usr/local/lib/python3.7/dist-packages/urllib3/packages/six.py\", line 686, in reraise\n    raise value\n  File \"/usr/local/lib/python3.7/dist-packages/urllib3/connectionpool.py\", line 600, in urlopen\n    chunked=chunked)\n  File \"/usr/local/lib/python3.7/dist-packages/urllib3/connectionpool.py\", line 354, in _make_request\n    conn.request(method, url, **httplib_request_kw)\n  File \"/usr/lib/python3.7/http/client.py\", line 1281, in request\n    self._send_request(method, url, body, headers, encode_chunked)\n  File \"/usr/lib/python3.7/http/client.py\", line 1327, in _send_request\n    self.endheaders(body, encode_chunked=encode_chunked)\n  File \"/usr/lib/python3.7/http/client.py\", line 1276, in endheaders\n    self._send_output(message_body, encode_chunked=encode_chunked)\n  File \"/usr/lib/python3.7/http/client.py\", line 1036, in _send_output\n    self.send(msg)\n  File \"/usr/lib/python3.7/http/client.py\", line 976, in send\n    self.connect()\n  File \"/usr/local/lib/python3.7/dist-packages/urllib3/connection.py\", line 181, in connect\n    conn = self._new_conn()\n  File \"/usr/local/lib/python3.7/dist-packages/urllib3/connection.py\", line 168, in _new_conn\n    self, \"Failed to establish a new connection: %s\" % e)\nurllib3.exceptions.NewConnectionError: <urllib3.connection.HTTPConnection object at 0x7f27f1849990>: Failed to establish a new connection: [Errno 111] Connection refused\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n  File \"/usr/local/lib/python3.7/dist-packages/haystack/pipelines/base.py\", line 386, in run\n    node_output, stream_id = self.graph.nodes[node_id][\"component\"]._dispatch_run(**node_input)\n  File \"/usr/local/lib/python3.7/dist-packages/haystack/nodes/base.py\", line 135, in _dispatch_run\n    output, stream = self.run(**run_inputs, **run_params)\n  File \"/usr/local/lib/python3.7/dist-packages/haystack/nodes/retriever/base.py\", line 233, in run\n    output, stream = run_query_timed(query=query, filters=filters, top_k=top_k, index=index, headers=headers)\n  File \"/usr/local/lib/python3.7/dist-packages/haystack/nodes/retriever/base.py\", line 77, in wrapper\n    ret = fn(*args, **kwargs)\n  File \"/usr/local/lib/python3.7/dist-packages/haystack/nodes/retriever/base.py\", line 250, in run_query\n    documents = self.retrieve(query=query, filters=filters, top_k=top_k, index=index, headers=headers)\n  File \"/usr/local/lib/python3.7/dist-packages/haystack/nodes/retriever/dense.py\", line 215, in retrieve\n    documents = self.document_store.query_by_embedding(query_emb=query_emb[0], top_k=top_k, filters=filters, index=index, headers=headers)\n  File \"/usr/local/lib/python3.7/dist-packages/haystack/document_stores/elasticsearch.py\", line 967, in query_by_embedding\n    result = self.client.search(index=index, body=body, request_timeout=300, headers=headers)[\"hits\"][\"hits\"]\n  File \"/usr/local/lib/python3.7/dist-packages/elasticsearch/client/utils.py\", line 152, in _wrapped\n    return func(*args, params=params, headers=headers, **kwargs)\n  File \"/usr/local/lib/python3.7/dist-packages/elasticsearch/client/__init__.py\", line 1663, in search\n    body=body,\n  File \"/usr/local/lib/python3.7/dist-packages/elasticsearch/transport.py\", line 390, in perform_request\n    raise e\n  File \"/usr/local/lib/python3.7/dist-packages/elasticsearch/transport.py\", line 365, in perform_request\n    timeout=timeout,\n  File \"/usr/local/lib/python3.7/dist-packages/elasticsearch/connection/http_urllib3.py\", line 258, in perform_request\n    raise ConnectionError(\"N/A\", str(e), e)\nelasticsearch.exceptions.ConnectionError: ConnectionError(<urllib3.connection.HTTPConnection object at 0x7f27f1849990>: Failed to establish a new connection: [Errno 111] Connection refused) caused by: NewConnectionError(<urllib3.connection.HTTPConnection object at 0x7f27f1849990>: Failed to establish a new connection: [Errno 111] Connection refused)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print_answers(res, details=\"minimum\")"
      ],
      "metadata": {
        "id": "FPynJJGtRhKn"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# document_store.write_documents(all_docs)\n",
        "# document_store.update_embeddings(retriever)\n",
        "\n",
        "# document_store.save(\"my_faiss_index.faiss\")\n",
        "# new_document_store = FAISSDocumentStore.load(\"my_faiss_index.faiss\")"
      ],
      "metadata": {
        "id": "iXjJsT051Id9"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Installing the evaluation data\n",
        "from haystack.utils import fetch_archive_from_http\n",
        "\n",
        "# Download evaluation data, which is a subset of Natural Questions development set containing 50 documents with one question per document and multiple annotated answers\n",
        "doc_dir = \"../data/nq\"\n",
        "s3_url = \"https://s3.eu-central-1.amazonaws.com/deepset.ai-farm-qa/datasets/nq_dev_subset_v2.json.zip\"\n",
        "fetch_archive_from_http(url=s3_url, output_dir=doc_dir)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pQRrbZwx4zhM",
        "outputId": "7d6d4813-32e8-4b0d-e65a-f4f7daea0d41"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO - haystack.utils.import_utils -  Found data stored in `../data/nq`. Delete this first if you really want to fetch new data.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "False"
            ]
          },
          "metadata": {},
          "execution_count": 75
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Trying to evaluate the pipeline\n",
        "\n",
        "\n",
        "# The add_eval_data() method converts the given dataset in json format into Haystack document and label objects. \n",
        "# Those objects are then indexed in their respective document and label index in the document store. \n",
        "# The method can be used with any dataset in SQuAD format.\n",
        "document_store.add_eval_data(\n",
        "    filename=\"../data/nq/nq_dev_subset_v2.json\",\n",
        "    doc_index=doc_index,\n",
        "    label_index=label_index,\n",
        "    preprocessor=preprocessor,\n",
        ")\n",
        "# document_store.update_embeddings(retriever=retriever)"
      ],
      "metadata": {
        "id": "-0mBDvmN3c4D"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "from haystack.schema import EvaluationResult, MultiLabel\n",
        "# We can load evaluation labels from the document store\n",
        "eval_labels = document_store.get_all_labels_aggregated(drop_negative_labels=True, drop_no_answers=False)"
      ],
      "metadata": {
        "id": "2oAl433668Q3"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "test = document_store.get_all_documents()"
      ],
      "metadata": {
        "id": "IpNGnBNOCZzA"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "eval_result = pipe.eval(\n",
        "    labels=eval_labels,\n",
        "    params={\"Retriever\": {\"top_k\": 5}}\n",
        ")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "Ge0wQ6xf97x3",
        "outputId": "60c3fe63-c66e-4728-a623-fbd46a65e60e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "Exception",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mRequestError\u001b[0m                              Traceback (most recent call last)",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/haystack/document_stores/elasticsearch.py\u001b[0m in \u001b[0;36mquery_by_embedding\u001b[0;34m(self, query_emb, filters, top_k, index, return_embedding, headers)\u001b[0m\n\u001b[1;32m    963\u001b[0m                         raise RequestError(400, \"search_phase_execution_exception\",\n\u001b[0;32m--> 964\u001b[0;31m                                            {\"error\": \"No documents with embeddings.\"})\n\u001b[0m\u001b[1;32m    965\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mRequestError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mRequestError\u001b[0m: RequestError(400, 'search_phase_execution_exception', 'No documents with embeddings.')",
            "\nDuring handling of the above exception, another exception occurred:\n",
            "\u001b[0;31mRequestError\u001b[0m                              Traceback (most recent call last)",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/haystack/pipelines/base.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(self, query, file_paths, labels, documents, meta, params, debug)\u001b[0m\n\u001b[1;32m    385\u001b[0m                     \u001b[0mlogger\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdebug\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"Running node `{node_id}` with input `{node_input}`\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 386\u001b[0;31m                     \u001b[0mnode_output\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstream_id\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgraph\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnodes\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mnode_id\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"component\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_dispatch_run\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mnode_input\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    387\u001b[0m                 \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/haystack/nodes/base.py\u001b[0m in \u001b[0;36m_dispatch_run\u001b[0;34m(self, **kwargs)\u001b[0m\n\u001b[1;32m    134\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 135\u001b[0;31m         \u001b[0moutput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstream\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mrun_inputs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mrun_params\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    136\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/haystack/nodes/retriever/base.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(self, root_node, query, filters, top_k, documents, index, headers)\u001b[0m\n\u001b[1;32m    232\u001b[0m             \u001b[0mrun_query_timed\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtiming\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_query\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"query_time\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 233\u001b[0;31m             \u001b[0moutput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstream\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrun_query_timed\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mquery\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mquery\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfilters\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfilters\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtop_k\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtop_k\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindex\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheaders\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mheaders\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    234\u001b[0m         \u001b[0;32melif\u001b[0m \u001b[0mroot_node\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"File\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/haystack/nodes/retriever/base.py\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     76\u001b[0m             \u001b[0mtic\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mperf_counter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 77\u001b[0;31m             \u001b[0mret\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     78\u001b[0m             \u001b[0mtoc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mperf_counter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/haystack/nodes/retriever/base.py\u001b[0m in \u001b[0;36mrun_query\u001b[0;34m(self, query, filters, top_k, index, headers)\u001b[0m\n\u001b[1;32m    249\u001b[0m     ):\n\u001b[0;32m--> 250\u001b[0;31m         \u001b[0mdocuments\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mretrieve\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mquery\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mquery\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfilters\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfilters\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtop_k\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtop_k\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindex\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheaders\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mheaders\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    251\u001b[0m         \u001b[0mdocument_ids\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mdoc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mid\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mdoc\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mdocuments\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/haystack/nodes/retriever/dense.py\u001b[0m in \u001b[0;36mretrieve\u001b[0;34m(self, query, filters, top_k, index, headers)\u001b[0m\n\u001b[1;32m    214\u001b[0m         \u001b[0mquery_emb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0membed_queries\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtexts\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mquery\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 215\u001b[0;31m         \u001b[0mdocuments\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdocument_store\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mquery_by_embedding\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mquery_emb\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mquery_emb\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtop_k\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtop_k\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfilters\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfilters\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindex\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheaders\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mheaders\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    216\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mdocuments\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/haystack/document_stores/elasticsearch.py\u001b[0m in \u001b[0;36mquery_by_embedding\u001b[0;34m(self, query_emb, filters, top_k, index, return_embedding, headers)\u001b[0m\n\u001b[1;32m    968\u001b[0m                                          \u001b[0;34m\" Run the document store's update_embeddings() method.\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 969\u001b[0;31m                     \u001b[0;32mraise\u001b[0m \u001b[0mRequestError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0me\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstatus_code\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merror_message\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minfo\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    970\u001b[0m                 \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mRequestError\u001b[0m: RequestError(400, \"search_phase_execution_exception: Likely some of your stored documents don't have embeddings. Run the document store's update_embeddings() method.\", 'No documents with embeddings.')",
            "\nDuring handling of the above exception, another exception occurred:\n",
            "\u001b[0;31mException\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-89-14b6078fc79f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      2\u001b[0m eval_result = pipe.eval(\n\u001b[1;32m      3\u001b[0m     \u001b[0mlabels\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0meval_labels\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m     \u001b[0mparams\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0;34m\"Retriever\"\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m\"top_k\"\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;36m5\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m )\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/haystack/pipelines/standard_pipelines.py\u001b[0m in \u001b[0;36meval\u001b[0;34m(self, labels, params, sas_model_name_or_path, add_isolated_node_eval)\u001b[0m\n\u001b[1;32m    169\u001b[0m         \"\"\"\n\u001b[1;32m    170\u001b[0m         output = self.pipeline.eval(labels=labels, params=params,\n\u001b[0;32m--> 171\u001b[0;31m                                     sas_model_name_or_path=sas_model_name_or_path, add_isolated_node_eval=add_isolated_node_eval)\n\u001b[0m\u001b[1;32m    172\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0moutput\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    173\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/haystack/pipelines/base.py\u001b[0m in \u001b[0;36meval\u001b[0;34m(self, labels, params, sas_model_name_or_path, add_isolated_node_eval)\u001b[0m\n\u001b[1;32m    459\u001b[0m         \u001b[0mqueries\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mquery\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mlabel\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mlabels\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    460\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mquery\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mqueries\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabels\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 461\u001b[0;31m             \u001b[0mpredictions\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mquery\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mquery\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabels\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mparams\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdebug\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    462\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    463\u001b[0m             \u001b[0;32mfor\u001b[0m \u001b[0mnode_name\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mpredictions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"_debug\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/haystack/pipelines/base.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(self, query, file_paths, labels, documents, meta, params, debug)\u001b[0m\n\u001b[1;32m    387\u001b[0m                 \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    388\u001b[0m                     \u001b[0mtb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtraceback\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat_exc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 389\u001b[0;31m                     \u001b[0;32mraise\u001b[0m \u001b[0mException\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"Exception while running node `{node_id}` with input `{node_input}`: {e}, full stack trace: {tb}\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    390\u001b[0m                 \u001b[0mqueue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnode_id\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    391\u001b[0m                 \u001b[0mnext_nodes\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_next_nodes\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnode_id\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstream_id\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mException\u001b[0m: Exception while running node `Retriever` with input `{'root_node': 'Query', 'params': {'Retriever': {'top_k': 5, 'debug': True}, 'Query': {'debug': True}}, 'query': 'who is written in the book of life', 'labels': {}, 'node_id': 'Retriever'}`: RequestError(400, \"search_phase_execution_exception: Likely some of your stored documents don't have embeddings. Run the document store's update_embeddings() method.\", 'No documents with embeddings.'), full stack trace: Traceback (most recent call last):\n  File \"/usr/local/lib/python3.7/dist-packages/haystack/document_stores/elasticsearch.py\", line 964, in query_by_embedding\n    {\"error\": \"No documents with embeddings.\"})\nelasticsearch.exceptions.RequestError: RequestError(400, 'search_phase_execution_exception', 'No documents with embeddings.')\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n  File \"/usr/local/lib/python3.7/dist-packages/haystack/pipelines/base.py\", line 386, in run\n    node_output, stream_id = self.graph.nodes[node_id][\"component\"]._dispatch_run(**node_input)\n  File \"/usr/local/lib/python3.7/dist-packages/haystack/nodes/base.py\", line 135, in _dispatch_run\n    output, stream = self.run(**run_inputs, **run_params)\n  File \"/usr/local/lib/python3.7/dist-packages/haystack/nodes/retriever/base.py\", line 233, in run\n    output, stream = run_query_timed(query=query, filters=filters, top_k=top_k, index=index, headers=headers)\n  File \"/usr/local/lib/python3.7/dist-packages/haystack/nodes/retriever/base.py\", line 77, in wrapper\n    ret = fn(*args, **kwargs)\n  File \"/usr/local/lib/python3.7/dist-packages/haystack/nodes/retriever/base.py\", line 250, in run_query\n    documents = self.retrieve(query=query, filters=filters, top_k=top_k, index=index, headers=headers)\n  File \"/usr/local/lib/python3.7/dist-packages/haystack/nodes/retriever/dense.py\", line 215, in retrieve\n    documents = self.document_store.query_by_embedding(query_emb=query_emb[0], top_k=top_k, filters=filters, index=index, headers=headers)\n  File \"/usr/local/lib/python3.7/dist-packages/haystack/document_stores/elasticsearch.py\", line 969, in query_by_embedding\n    raise RequestError(e.status_code, error_message, e.info)\nelasticsearch.exceptions.RequestError: RequestError(400, \"search_phase_execution_exception: Likely some of your stored documents don't have embeddings. Run the document store's update_embeddings() method.\", 'No documents with embeddings.')\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "retriever_result = eval_result[\"Retriever\"]\n",
        "retriever_result.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 842
        },
        "id": "NotIYP6nA_EC",
        "outputId": "a053f16c-4e0a-46a6-8840-16d9e8d8e1d6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
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              "  <thead>\n",
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              "      <th></th>\n",
              "      <th>query</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>who is written in the book of life</td>\n",
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              "      <td>The Creators of Grammar\\nNo student of a foreign language needs to be told t...</td>\n",
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              "      <td>who is written in the book of life</td>\n",
              "      <td>[Book of Life - wikipedia Book of Life Jump to: navigation, search This arti...</td>\n",
              "      <td>Although it was based on the signs of the older children, the younger childr...</td>\n",
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              "      <td>who is written in the book of life</td>\n",
              "      <td>[Book of Life - wikipedia Book of Life Jump to: navigation, search This arti...</td>\n",
              "      <td>The Cherokee pronoun system, for example, can distinguish between 'you and I...</td>\n",
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              "      <td>The Creators of Grammar\\nNo student of a foreign language needs to be told t...</td>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-47d7fc9a-996e-4cfb-9ea2-f16d4b6bc773')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-47d7fc9a-996e-4cfb-9ea2-f16d4b6bc773');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "  "
            ],
            "text/plain": [
              "                                query  ...   eval_mode\n",
              "0  who is written in the book of life  ...  integrated\n",
              "1  who is written in the book of life  ...  integrated\n",
              "2  who is written in the book of life  ...  integrated\n",
              "3  who is written in the book of life  ...  integrated\n",
              "4  who is written in the book of life  ...  integrated\n",
              "\n",
              "[5 rows x 12 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 61
        }
      ]
    }
  ]
}