AskTo_CFALevel1_Curriculum.ipynb

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            "Requirement already satisfied: transformers in /usr/local/lib/python3.10/dist-packages (4.31.0)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers) (3.12.2)\n",
            "Requirement already satisfied: huggingface-hub<1.0,>=0.14.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.16.4)\n",
            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (1.22.4)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from transformers) (23.1)\n",
            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (6.0.1)\n",
            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (2022.10.31)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from transformers) (2.27.1)\n",
            "Requirement already satisfied: tokenizers!=0.11.3,<0.14,>=0.11.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.13.3)\n",
            "Requirement already satisfied: safetensors>=0.3.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.3.1)\n",
            "Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.10/dist-packages (from transformers) (4.65.0)\n",
            "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.14.1->transformers) (2023.6.0)\n",
            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.14.1->transformers) (4.7.1)\n",
            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (1.26.16)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2023.5.7)\n",
            "Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2.0.12)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (3.4)\n",
            "Collecting InstructorEmbedding\n",
            "  Downloading InstructorEmbedding-1.0.1-py2.py3-none-any.whl (19 kB)\n",
            "Installing collected packages: InstructorEmbedding\n",
            "Successfully installed InstructorEmbedding-1.0.1\n"
          ]
        }
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m49.4/49.4 kB\u001b[0m \u001b[31m1.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.8/7.8 MB\u001b[0m \u001b[31m58.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 MB\u001b[0m \u001b[31m29.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Building wheel for sentence_transformers (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
          ]
        }
      ],
      "source": [
        "!pip install -qqq langchain sentence_transformers faiss-cpu huggingface_hub\n",
        "import os\n",
        "from langchain.embeddings import HuggingFaceEmbeddings, HuggingFaceInstructEmbeddings\n",
        "\n",
        "from langchain.vectorstores.faiss import FAISS\n",
        "from huggingface_hub import snapshot_download\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cache_dir=\"cfa_level_1_cache\"\n",
        "vectorstore = snapshot_download(repo_id=\"nickmuchi/CFA_Level_1_Text_Embeddings\",\n",
        "                                repo_type=\"dataset\",\n",
        "                                revision=\"main\",\n",
        "                                #allow_patterns=f\"books/{book}/*\", # to download only the one book\n",
        "                                cache_dir=cache_dir,\n",
        "                                )\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 177,
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        },
        "id": "bNjGze3i4FWT",
        "outputId": "d773d0df-f8b0-462c-c8c3-cfe7b19793c4"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Fetching 4 files:   0%|          | 0/4 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "49a2ebaa63244bc398577b9463e033d2"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)2406b/.gitattributes:   0%|          | 0.00/2.39k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "8be405503cb344548285f2dc71f23c29"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)f9c352406b/README.md:   0%|          | 0.00/2.92k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "45777f9158e846febaa5edd15814cb65"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading index.faiss:   0%|          | 0.00/39.2M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "93f64ba00d4743a9bbdfaaad4daadaf7"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading index.pkl:   0%|          | 0.00/12.8M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "80011a748de84df38c85c19774b748b8"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "target_dir = \"CFA_Level_1\" #f\"cfa/cfa_level_1\""
      ],
      "metadata": {
        "id": "axaBkgma4UWZ"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "vectorstore"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "x9lbSf6n679v",
        "outputId": "1371a880-eee7-4807-c7b0-9feb06382780"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'cfa_level_1_cache/datasets--nickmuchi--CFA_Level_1_Text_Embeddings/snapshots/ca947c50163da32281216ebe1cf081f9c352406b'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for root, dirs, files in os.walk(cache_dir):\n",
        "    print(root, dirs)\n",
        "    # Check if the target directory is in the list of directories\n",
        "    if target_dir in dirs:\n",
        "        # Get the full path of the target directory\n",
        "        target_path = os.path.join(root, target_dir)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "G71O-M7I6vVc",
        "outputId": "ffa740d5-3db6-4289-9acf-017098a73f3c"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "cfa_level_1_cache ['datasets--nickmuchi--CFA_Level_1_Text_Embeddings']\n",
            "cfa_level_1_cache/datasets--nickmuchi--CFA_Level_1_Text_Embeddings ['blobs', 'refs', 'snapshots']\n",
            "cfa_level_1_cache/datasets--nickmuchi--CFA_Level_1_Text_Embeddings/blobs []\n",
            "cfa_level_1_cache/datasets--nickmuchi--CFA_Level_1_Text_Embeddings/refs []\n",
            "cfa_level_1_cache/datasets--nickmuchi--CFA_Level_1_Text_Embeddings/snapshots ['ca947c50163da32281216ebe1cf081f9c352406b']\n",
            "cfa_level_1_cache/datasets--nickmuchi--CFA_Level_1_Text_Embeddings/snapshots/ca947c50163da32281216ebe1cf081f9c352406b ['CFA_Level_1']\n",
            "cfa_level_1_cache/datasets--nickmuchi--CFA_Level_1_Text_Embeddings/snapshots/ca947c50163da32281216ebe1cf081f9c352406b/CFA_Level_1 []\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "target_path"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "vml_I57y6x4N",
        "outputId": "caf46a19-2e13-4d03-85f6-bbbdb8ff984f"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'cfa_level_1_cache/datasets--nickmuchi--CFA_Level_1_Text_Embeddings/snapshots/ca947c50163da32281216ebe1cf081f9c352406b/CFA_Level_1'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "embed_instruction = \"Represent the financial paragraph for document retrieval: \"\n",
        "query_instruction = \"Represent the question for retrieving supporting documents: \"\n",
        "\n",
        "model_sbert = \"sentence-transformers/all-mpnet-base-v2\"\n",
        "model_sbertqa = \"sentence-transformers/multi-qa-mpnet-base-dot-v1\"\n",
        "\n",
        "model_emb = HuggingFaceEmbeddings(model_name=model_sbertqa)\n",
        "\n",
        "model_instr = \"hkunlp/instructor-large\"\n",
        "instruct_emb = HuggingFaceInstructEmbeddings(model_name=model_instr,\n",
        "                                             embed_instruction=embed_instruction,\n",
        "                                             query_instruction=query_instruction)\n"
      ],
      "metadata": {
        "colab": {
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          "name": "stdout",
          "text": [
            "load INSTRUCTOR_Transformer\n",
            "max_seq_length  512\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# load vector store to use with langchain\n",
        "docsearch = FAISS.load_local(folder_path=target_path, embeddings=model_emb)\n",
        "\n"
      ],
      "metadata": {
        "id": "uejBxJhd7vmW"
      },
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# similarity search\n",
        "question = \"How do you hedge the interest rate risk of an MBS?\"\n",
        "search = docsearch.similarity_search(question, k=4)\n",
        "\n",
        "for item in search:\n",
        "    print(item.page_content)\n",
        "    print(f\"From page: {item.metadata['source']}\")\n",
        "    print(\"---\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PIwL9_Oo8cSr",
        "outputId": "fd0c502c-70d1-4448-eb83-90831a2bd39b"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Solutions 525\n",
            "will refinance at now-  available lower interest rates. Thus, a security backed by \n",
            "mortgages will have a shorter maturity than was anticipated when the security \n",
            "was purchased.\n",
            "20 A is correct. If commercial mortgage loans are non-  recourse loans, the lender \n",
            "can only look to the income-  producing property backing the loan for interest \n",
            "and principal repayment. If there is a default, the lender looks to the proceeds \n",
            "from the sale of the property for repayment and has no recourse against the \n",
            "borrower for any unpaid mortgage loan balance. Call protection and prepay -\n",
            "ment penalty points protect against prepayment risk.\n",
            "21 A is correct. With CMBS, investors have considerable call protection. An inves -\n",
            "tor in a RMBS is exposed to considerable prepayment risk, but with CMBS, call \n",
            "protection is available to the investor at the structure and loan level. The call \n",
            "protection results in CMBS trading in the market more like a corporate bond\n",
            "From page: Book: CFA_Equity_Bonds, page: 525\n",
            "---\n",
            "6.2.1  Call Protection\n",
            "A critical investment feature that distinguishes CMBS from RMBS is the protection \n",
            "against early prepayments available to investors’ known as a call protection . An investor \n",
            "in an RMBS is exposed to considerable prepayment risk because the borrower has the \n",
            "right to prepay a loan, in whole or in part, before the scheduled principal repayment \n",
            "date. As explained in Section 4.4, a borrower in the United States usually does not pay \n",
            "any penalty for prepayment. The discussion of CMOs highlighted how investors can \n",
            "purchase certain types of tranches (e.g., sequential-  pay and PAC tranches) to modify \n",
            "or reduce prepayment risk.\n",
            "With CMBS, investors have considerable call protection. In fact, it is this protec -\n",
            "tion that results in CMBS trading in the market more like corporate bonds than like \n",
            "RMBS. The call protection comes either at the structure level or at the loan level.\n",
            "From page: Book: CFA_Equity_Bonds, page: 504\n",
            "---\n",
            "loan and sells the house for $315,000. What amount is the lender entitled to \n",
            "claim from Martin?\n",
            "A $0.\n",
            "B $175,000.\n",
            "C $185,000.\n",
            "12 Which of the following describes a typical feature of a non-  agency residential \n",
            "mortgage-  backed security (RMBS)?\n",
            "A Senior/subordinated structure\n",
            "B A pool of conforming mortgages as collateral\n",
            "C A guarantee by a government-  sponsored enterprise\n",
            "13 If interest rates increase, an investor who owns a mortgage pass-  through secu -\n",
            "rity is most likely  affected by:\n",
            "A credit risk.\n",
            "B extension risk.\n",
            "C contraction risk.\n",
            "14 Which of the following is most likely an advantage of collateralized mortgage \n",
            "obligations (CMOs)? CMOs can\n",
            "A eliminate prepayment risk.\n",
            "B be created directly from a pool of mortgage loans.\n",
            "C meet the asset/liability requirements of institutional investors.\n",
            "15 The longest-  term tranche of a sequential-  pay CMO is most likely  to have the \n",
            "lowest:\n",
            "A average life.\n",
            "B extension risk.\n",
            "C contraction risk.\n",
            "From page: Book: CFA_Equity_Bonds, page: 520\n",
            "---\n",
            "A Balloon\n",
            "B Extension\n",
            "C Contraction\n",
            "20 Credit risk is an important consideration for commercial mortgage-  backed \n",
            "securities (CMBS) if the CMBS are backed by mortgage loans that:\n",
            "A are non-  recourse.\n",
            "B have call protection.\n",
            "C haveprepayment penalty points.\n",
            "21 Which commercial mortgage-  backed security (CMBS) characteristic causes a \n",
            "CMBS to trade more like a corporate bond than a residential mortgage-  backed \n",
            "security (RMBS)?\n",
            "A Call protection\n",
            "B Internal credit enhancement\n",
            "C Debt-  service coverage ratio level\n",
            "22 A commercial mortgage-  backed security (CMBS) does not meet the debt-  to- \n",
            "service coverage at the loan level necessary to achieve a desired credit rating. \n",
            "Which of the following features would most  likely  improve the credit rating of \n",
            "the CMBS?\n",
            "A Subordination\n",
            "B Call protection\n",
            "C Balloon payments\n",
            "23 If a default occurs in a non-  recourse commercial mortgage-  backed security \n",
            "(CMBS), the lender will most likely :\n",
            "A recover prepayment penalty points paid by the borrower to offset losses.\n",
            "From page: Book: CFA_Equity_Bonds, page: 521\n",
            "---\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# similarity search\n",
        "question = \"List best performing asset classes in an inflationary environment?\"\n",
        "search = docsearch.similarity_search(question, k=3)\n",
        "\n",
        "for item in search:\n",
        "    print(item.page_content)\n",
        "    print(f\"From page: {item.metadata['source']}\")\n",
        "    print(\"---\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Sk92SGN688ED",
        "outputId": "5adc5b7b-7f2c-4616-ae67-4c338f294352"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Fixed income securities\n",
            "Inflation-  linked bonds 7%\n",
            "Government bonds 10\n",
            "Corporate bonds 23\n",
            "Total fixed income securities 40%\n",
            "Total 100%\n",
            "1 Discuss the way the asset classes have been defined.\n",
            "2 How does the asset allocation relate to the pension fund’s ambition to pay \n",
            "out a real (i.e., inflation-  adjusted) pension?\n",
            "4 ABP defines an asset class category called “real assets, ” which contains asset classes (not fixed-  income \n",
            "securities) that are expected to perform well in times of inflation, but considered a major risk. The use of \n",
            "the term “real assets” differs from the use elsewhere in the CFA curriculum. The term “innovation” refers \n",
            "to alternative investments that are relatively new to ABP’s portfolio. An example of such an investment \n",
            "is music rights. “Infrastructure” is investments in non-  public equity of infrastructure projects such as \n",
            "toll roads. Inflation-  linked bonds are fixed-  income securities of which the payout depends on a measure\n",
            "From page: Book: CFA_Corp_Fi_Port_Mgt, page: 388\n",
            "---\n",
            "(%)Asset Class Return \n",
            "(%)\n",
            "Large-  cap US equities 20.0 8.0\n",
            "Small-  cap US equities 40.0 12.0\n",
            "Emerging market equities 25.0 –3.0\n",
            "High-  yield bonds 15.0 4.0\n",
            "From page: Book: CFA_Ethics, page: 462\n",
            "---\n",
            "L. European \n",
            "Investment \n",
            "Grade \n",
            "Corporates0.01 0.11 0.06 0.05 0.06 0.14 0.32 0.14 0.55 0.79 0.83 1.00\n",
            "Annualized \n",
            "Volatility16.6% 20.7% 15.0% 15.4% 15.7% 25.4% 18.9% 16.6% 5.0% 6.0% 3.1% 3.2%\n",
            "Data based on monthly returns in local currencies from January 1999 to February 2009. Commodities, Real Estate, and Gold in USD.\n",
            "Source:  MSCI, NAREIT, Bloomberg Barclays (formerly Bloomberg Capital), Standard and Poor’s.\n",
            "From page: Book: CFA_Corp_Fi_Port_Mgt, page: 386\n",
            "---\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# similarity search\n",
        "question = \"List best performing asset classes in an inflationary environment?\"\n",
        "search = docsearch.similarity_search(question, k=3)\n",
        "\n",
        "for item in search:\n",
        "    print(item.page_content)\n",
        "    print(f\"From page: {item.metadata['source']}\")\n",
        "    print(\"---\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lnOkvizL9fON",
        "outputId": "4a4eba62-e274-4da7-cbfd-745fa1b6ad27"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Fixed income securities\n",
            "Inflation-  linked bonds 7%\n",
            "Government bonds 10\n",
            "Corporate bonds 23\n",
            "Total fixed income securities 40%\n",
            "Total 100%\n",
            "1 Discuss the way the asset classes have been defined.\n",
            "2 How does the asset allocation relate to the pension fund’s ambition to pay \n",
            "out a real (i.e., inflation-  adjusted) pension?\n",
            "4 ABP defines an asset class category called “real assets, ” which contains asset classes (not fixed-  income \n",
            "securities) that are expected to perform well in times of inflation, but considered a major risk. The use of \n",
            "the term “real assets” differs from the use elsewhere in the CFA curriculum. The term “innovation” refers \n",
            "to alternative investments that are relatively new to ABP’s portfolio. An example of such an investment \n",
            "is music rights. “Infrastructure” is investments in non-  public equity of infrastructure projects such as \n",
            "toll roads. Inflation-  linked bonds are fixed-  income securities of which the payout depends on a measure\n",
            "From page: Book: CFA_Corp_Fi_Port_Mgt, page: 388\n",
            "---\n",
            "L. European \n",
            "Investment \n",
            "Grade \n",
            "Corporates0.01 0.11 0.06 0.05 0.06 0.14 0.32 0.14 0.55 0.79 0.83 1.00\n",
            "Annualized \n",
            "Volatility16.6% 20.7% 15.0% 15.4% 15.7% 25.4% 18.9% 16.6% 5.0% 6.0% 3.1% 3.2%\n",
            "Data based on monthly returns in local currencies from January 1999 to February 2009. Commodities, Real Estate, and Gold in USD.\n",
            "Source:  MSCI, NAREIT, Bloomberg Barclays (formerly Bloomberg Capital), Standard and Poor’s.\n",
            "From page: Book: CFA_Corp_Fi_Port_Mgt, page: 386\n",
            "---\n",
            "cent) when the inflation rate was –2.78  percent. Consistently positive returns for \n",
            "Treasury bills are not surprising because nominal interest rates are almost never \n",
            "negative and the Treasury bills suffer from little interest rate or inflation risk. Since \n",
            "the Great Depression, there has been no deflation in any decade, although inflation \n",
            "rates were highly negative in 1930 (–6.03 percent), 1931 (–9.52 percent), and 1932 \n",
            "(–10.30  percent). Conversely, inflation rates were very high in the late 1970s and \n",
            "early 1980s, reaching 13.31 percent in 1979. Inflation rates have fallen since then to \n",
            "a negligible level of 0.09 percent in 2008. Overall, the inflation rate was 3.0 percent \n",
            "for the 83-  year period.\n",
            "2.4.3  Real Returns of Major US Asset Classes\n",
            "Because inflation rates can vary greatly, from –10.30 percent to +13.31 percent in the \n",
            "last 83 years, comparisons across various time periods is difficult and misleading using\n",
            "From page: Book: CFA_Corp_Fi_Port_Mgt, page: 261\n",
            "---\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "c6sJxa13ANEa"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}