LLM_BASED_loan_processing.ipynb

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          "text": [
            "\r0% [Working]\r            \rGet:1 https://cloud.r-project.org/bin/linux/ubuntu jammy-cran40/ InRelease [3,626 B]\n",
            "Get:2 http://security.ubuntu.com/ubuntu jammy-security InRelease [110 kB]\n",
            "Hit:3 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64  InRelease\n",
            "Hit:4 http://archive.ubuntu.com/ubuntu jammy InRelease\n",
            "Get:5 http://archive.ubuntu.com/ubuntu jammy-updates InRelease [119 kB]\n",
            "Get:6 http://archive.ubuntu.com/ubuntu jammy-backports InRelease [109 kB]\n",
            "Hit:7 https://ppa.launchpadcontent.net/c2d4u.team/c2d4u4.0+/ubuntu jammy InRelease\n",
            "Get:8 http://archive.ubuntu.com/ubuntu jammy-updates/universe amd64 Packages [1,294 kB]\n",
            "Hit:9 https://ppa.launchpadcontent.net/deadsnakes/ppa/ubuntu jammy InRelease\n",
            "Hit:10 https://ppa.launchpadcontent.net/graphics-drivers/ppa/ubuntu jammy InRelease\n",
            "Get:11 http://archive.ubuntu.com/ubuntu jammy-updates/restricted amd64 Packages [1,520 kB]\n",
            "Hit:12 https://ppa.launchpadcontent.net/ubuntugis/ppa/ubuntu jammy InRelease\n",
            "Get:13 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 Packages [1,535 kB]\n",
            "Fetched 4,690 kB in 2s (2,455 kB/s)\n",
            "Reading package lists... Done\n",
            "Reading package lists... Done\n",
            "Building dependency tree... Done\n",
            "Reading state information... Done\n",
            "Calculating upgrade... Done\n",
            "The following packages have been kept back:\n",
            "  libcudnn8 libcudnn8-dev libnccl-dev libnccl2\n",
            "The following packages will be upgraded:\n",
            "  cuda-keyring cuda-toolkit-config-common libgnutls30 libperl5.34 libprocps8 libudev1\n",
            "  linux-libc-dev perl perl-base perl-modules-5.34 procps\n",
            "11 upgraded, 0 newly installed, 0 to remove and 4 not upgraded.\n",
            "Need to get 12.6 MB of archives.\n",
            "After this operation, 8,192 B of additional disk space will be used.\n",
            "Get:1 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 libperl5.34 amd64 5.34.0-3ubuntu1.3 [4,820 kB]\n",
            "Get:2 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64  cuda-keyring 1.1-1 [4,332 B]\n",
            "Get:3 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64  cuda-toolkit-config-common 12.3.101-1 [16.4 kB]\n",
            "Get:4 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 perl amd64 5.34.0-3ubuntu1.3 [232 kB]\n",
            "Get:5 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 perl-base amd64 5.34.0-3ubuntu1.3 [1,762 kB]\n",
            "Get:6 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 perl-modules-5.34 all 5.34.0-3ubuntu1.3 [2,976 kB]\n",
            "Get:7 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 libudev1 amd64 249.11-0ubuntu3.11 [78.0 kB]\n",
            "Get:8 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 libgnutls30 amd64 3.7.3-4ubuntu1.3 [968 kB]\n",
            "Get:9 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 libprocps8 amd64 2:3.3.17-6ubuntu2.1 [36.2 kB]\n",
            "Get:10 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 procps amd64 2:3.3.17-6ubuntu2.1 [378 kB]\n",
            "Get:11 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 linux-libc-dev amd64 5.15.0-89.99 [1,338 kB]\n",
            "Fetched 12.6 MB in 1s (23.5 MB/s)\n",
            "(Reading database ... 120882 files and directories currently installed.)\n",
            "Preparing to unpack .../libperl5.34_5.34.0-3ubuntu1.3_amd64.deb ...\n",
            "Unpacking libperl5.34:amd64 (5.34.0-3ubuntu1.3) over (5.34.0-3ubuntu1.2) ...\n",
            "Preparing to unpack .../perl_5.34.0-3ubuntu1.3_amd64.deb ...\n",
            "Unpacking perl (5.34.0-3ubuntu1.3) over (5.34.0-3ubuntu1.2) ...\n",
            "Preparing to unpack .../perl-base_5.34.0-3ubuntu1.3_amd64.deb ...\n",
            "Unpacking perl-base (5.34.0-3ubuntu1.3) over (5.34.0-3ubuntu1.2) ...\n",
            "Setting up perl-base (5.34.0-3ubuntu1.3) ...\n",
            "(Reading database ... 120882 files and directories currently installed.)\n",
            "Preparing to unpack .../perl-modules-5.34_5.34.0-3ubuntu1.3_all.deb ...\n",
            "Unpacking perl-modules-5.34 (5.34.0-3ubuntu1.3) over (5.34.0-3ubuntu1.2) ...\n",
            "Preparing to unpack .../libudev1_249.11-0ubuntu3.11_amd64.deb ...\n",
            "Unpacking libudev1:amd64 (249.11-0ubuntu3.11) over (249.11-0ubuntu3.10) ...\n",
            "Setting up libudev1:amd64 (249.11-0ubuntu3.11) ...\n",
            "(Reading database ... 120882 files and directories currently installed.)\n",
            "Preparing to unpack .../libgnutls30_3.7.3-4ubuntu1.3_amd64.deb ...\n",
            "Unpacking libgnutls30:amd64 (3.7.3-4ubuntu1.3) over (3.7.3-4ubuntu1.2) ...\n",
            "Setting up libgnutls30:amd64 (3.7.3-4ubuntu1.3) ...\n",
            "(Reading database ... 120882 files and directories currently installed.)\n",
            "Preparing to unpack .../libprocps8_2%3a3.3.17-6ubuntu2.1_amd64.deb ...\n",
            "Unpacking libprocps8:amd64 (2:3.3.17-6ubuntu2.1) over (2:3.3.17-6ubuntu2) ...\n",
            "Preparing to unpack .../procps_2%3a3.3.17-6ubuntu2.1_amd64.deb ...\n",
            "Unpacking procps (2:3.3.17-6ubuntu2.1) over (2:3.3.17-6ubuntu2) ...\n",
            "Preparing to unpack .../cuda-keyring_1.1-1_all.deb ...\n",
            "Unpacking cuda-keyring (1.1-1) over (1.0-1) ...\n",
            "Preparing to unpack .../cuda-toolkit-config-common_12.3.101-1_all.deb ...\n",
            "Unpacking cuda-toolkit-config-common (12.3.101-1) over (12.3.52-1) ...\n",
            "Preparing to unpack .../linux-libc-dev_5.15.0-89.99_amd64.deb ...\n",
            "Unpacking linux-libc-dev:amd64 (5.15.0-89.99) over (5.15.0-88.98) ...\n",
            "Setting up cuda-toolkit-config-common (12.3.101-1) ...\n",
            "Setting up linux-libc-dev:amd64 (5.15.0-89.99) ...\n",
            "Setting up perl-modules-5.34 (5.34.0-3ubuntu1.3) ...\n",
            "Setting up cuda-keyring (1.1-1) ...\n",
            "Setting up libprocps8:amd64 (2:3.3.17-6ubuntu2.1) ...\n",
            "Setting up libperl5.34:amd64 (5.34.0-3ubuntu1.3) ...\n",
            "Setting up perl (5.34.0-3ubuntu1.3) ...\n",
            "Setting up procps (2:3.3.17-6ubuntu2.1) ...\n",
            "Processing triggers for man-db (2.10.2-1) ...\n",
            "Processing triggers for libc-bin (2.35-0ubuntu3.4) ...\n",
            "/sbin/ldconfig.real: /usr/local/lib/libtbbbind.so.3 is not a symbolic link\n",
            "\n",
            "/sbin/ldconfig.real: /usr/local/lib/libtbbbind_2_0.so.3 is not a symbolic link\n",
            "\n",
            "/sbin/ldconfig.real: /usr/local/lib/libtbbmalloc_proxy.so.2 is not a symbolic link\n",
            "\n",
            "/sbin/ldconfig.real: /usr/local/lib/libtbbbind_2_5.so.3 is not a symbolic link\n",
            "\n",
            "/sbin/ldconfig.real: /usr/local/lib/libtbb.so.12 is not a symbolic link\n",
            "\n",
            "/sbin/ldconfig.real: /usr/local/lib/libtbbmalloc.so.2 is not a symbolic link\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!apt-get install poppler-utils tesseract-ocr\n",
        "!pip install pypdf"
      ],
      "metadata": {
        "id": "VmjlvrRfZinM",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "97e3d63a-aedc-4054-ea2a-4227d7ec10a1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Reading package lists... Done\n",
            "Building dependency tree... Done\n",
            "Reading state information... Done\n",
            "The following additional packages will be installed:\n",
            "  tesseract-ocr-eng tesseract-ocr-osd\n",
            "The following NEW packages will be installed:\n",
            "  poppler-utils tesseract-ocr tesseract-ocr-eng tesseract-ocr-osd\n",
            "0 upgraded, 4 newly installed, 0 to remove and 4 not upgraded.\n",
            "Need to get 5,002 kB of archives.\n",
            "After this operation, 16.3 MB of additional disk space will be used.\n",
            "Get:1 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 poppler-utils amd64 22.02.0-2ubuntu0.3 [186 kB]\n",
            "Get:2 http://archive.ubuntu.com/ubuntu jammy/universe amd64 tesseract-ocr-eng all 1:4.00~git30-7274cfa-1.1 [1,591 kB]\n",
            "Get:3 http://archive.ubuntu.com/ubuntu jammy/universe amd64 tesseract-ocr-osd all 1:4.00~git30-7274cfa-1.1 [2,990 kB]\n",
            "Get:4 http://archive.ubuntu.com/ubuntu jammy/universe amd64 tesseract-ocr amd64 4.1.1-2.1build1 [236 kB]\n",
            "Fetched 5,002 kB in 0s (10.1 MB/s)\n",
            "Selecting previously unselected package poppler-utils.\n",
            "(Reading database ... 120882 files and directories currently installed.)\n",
            "Preparing to unpack .../poppler-utils_22.02.0-2ubuntu0.3_amd64.deb ...\n",
            "Unpacking poppler-utils (22.02.0-2ubuntu0.3) ...\n",
            "Selecting previously unselected package tesseract-ocr-eng.\n",
            "Preparing to unpack .../tesseract-ocr-eng_1%3a4.00~git30-7274cfa-1.1_all.deb ...\n",
            "Unpacking tesseract-ocr-eng (1:4.00~git30-7274cfa-1.1) ...\n",
            "Selecting previously unselected package tesseract-ocr-osd.\n",
            "Preparing to unpack .../tesseract-ocr-osd_1%3a4.00~git30-7274cfa-1.1_all.deb ...\n",
            "Unpacking tesseract-ocr-osd (1:4.00~git30-7274cfa-1.1) ...\n",
            "Selecting previously unselected package tesseract-ocr.\n",
            "Preparing to unpack .../tesseract-ocr_4.1.1-2.1build1_amd64.deb ...\n",
            "Unpacking tesseract-ocr (4.1.1-2.1build1) ...\n",
            "Setting up tesseract-ocr-eng (1:4.00~git30-7274cfa-1.1) ...\n",
            "Setting up tesseract-ocr-osd (1:4.00~git30-7274cfa-1.1) ...\n",
            "Setting up poppler-utils (22.02.0-2ubuntu0.3) ...\n",
            "Setting up tesseract-ocr (4.1.1-2.1build1) ...\n",
            "Processing triggers for man-db (2.10.2-1) ...\n",
            "Collecting pypdf\n",
            "  Downloading pypdf-3.17.1-py3-none-any.whl (277 kB)\n",
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            "\u001b[?25hInstalling collected packages: pypdf\n",
            "Successfully installed pypdf-3.17.1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install langchain huggingface_hub keychain sentence_transformers"
      ],
      "metadata": {
        "id": "5z6J6sKtLuKA",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b0eef72d-f7f5-4f15-d6dd-4e980d9f18ad"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting langchain\n",
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            "Collecting bitmerchant>=0.1.8 (from keychain)\n",
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            "  Downloading keylib-0.1.1.tar.gz (7.2 kB)\n",
            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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            "Collecting sentencepiece (from sentence_transformers)\n",
            "  Downloading sentencepiece-0.1.99-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.3 MB)\n",
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            "Collecting marshmallow<4.0.0,>=3.18.0 (from dataclasses-json<0.7,>=0.5.7->langchain)\n",
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            "\u001b[?25hCollecting typing-inspect<1,>=0.4.0 (from dataclasses-json<0.7,>=0.5.7->langchain)\n",
            "  Downloading typing_inspect-0.9.0-py3-none-any.whl (8.8 kB)\n",
            "Collecting jsonpointer>=1.9 (from jsonpatch<2.0,>=1.33->langchain)\n",
            "  Downloading jsonpointer-2.4-py2.py3-none-any.whl (7.8 kB)\n",
            "Collecting utilitybelt>=0.2.6 (from keylib>=0.1.0->keychain)\n",
            "  Downloading utilitybelt-0.2.6.tar.gz (3.9 kB)\n",
            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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            "Collecting mypy-extensions>=0.3.0 (from typing-inspect<1,>=0.4.0->dataclasses-json<0.7,>=0.5.7->langchain)\n",
            "  Downloading mypy_extensions-1.0.0-py3-none-any.whl (4.7 kB)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch>=1.6.0->sentence_transformers) (2.1.3)\n",
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            "Building wheels for collected packages: keychain, sentence_transformers, keylib, utilitybelt\n",
            "  Building wheel for keychain (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for keychain: filename=keychain-0.14.2.0-py3-none-any.whl size=4489 sha256=b8fcfcfdb5ead0373f6b5263e53c261f2bb16b19b316f0c011ab876bb30f638d\n",
            "  Stored in directory: /root/.cache/pip/wheels/fe/d6/a9/a37da44846f3c553a5b36ef763c8f6e3444abc8d91c729e4ef\n",
            "  Building wheel for sentence_transformers (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for sentence_transformers: filename=sentence_transformers-2.2.2-py3-none-any.whl size=125923 sha256=889469cffe9b689005ed6d6c2c01342950044e500074c2381f35cfbb1a958350\n",
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            "  Building wheel for keylib (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for keylib: filename=keylib-0.1.1-py3-none-any.whl size=10677 sha256=f7fc108661f137b88e73a71eb7ee05aedca2b4a7c19c8564c0e462e7191cf758\n",
            "  Stored in directory: /root/.cache/pip/wheels/4e/d6/fa/55a2fa8799c8734e9f62a2036a4a559acb03ba0b547fbfecc7\n",
            "  Building wheel for utilitybelt (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for utilitybelt: filename=utilitybelt-0.2.6-py3-none-any.whl size=5567 sha256=02f6446a62113f43da0bb3d7beda52ac5c81ac473d1de579dd170126d2aee496\n",
            "  Stored in directory: /root/.cache/pip/wheels/07/49/58/fb1b03edee75e017efb2f5537f0307997273af959d354c34d5\n",
            "Successfully built keychain sentence_transformers keylib utilitybelt\n",
            "Installing collected packages: utilitybelt, sentencepiece, mypy-extensions, marshmallow, jsonpointer, ecdsa, base58, typing-inspect, langsmith, keylib, jsonpatch, bitmerchant, langchain-core, keychain, dataclasses-json, langchain, sentence_transformers\n",
            "Successfully installed base58-2.1.1 bitmerchant-0.1.8 dataclasses-json-0.6.3 ecdsa-0.18.0 jsonpatch-1.33 jsonpointer-2.4 keychain-0.14.2.0 keylib-0.1.1 langchain-0.0.344 langchain-core-0.0.8 langsmith-0.0.68 marshmallow-3.20.1 mypy-extensions-1.0.0 sentence_transformers-2.2.2 sentencepiece-0.1.99 typing-inspect-0.9.0 utilitybelt-0.2.6\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install unstructured\n",
        "!pip install chromadb\n",
        "!pip install Cython\n",
        "!pip install tiktoken\n",
        "!pip install unstructured[local-inference]\n",
        "!pip install faiss-gpu"
      ],
      "metadata": {
        "id": "RpiEy6Z-MZZn",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "cf8f632f-2f54-40fd-eef6-d0fc5926fb81"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting unstructured\n",
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            "Requirement already satisfied: googleapis-common-protos~=1.52 in /usr/local/lib/python3.10/dist-packages (from opentelemetry-exporter-otlp-proto-grpc>=1.2.0->chromadb) (1.61.0)\n",
            "Collecting opentelemetry-exporter-otlp-proto-common==1.21.0 (from opentelemetry-exporter-otlp-proto-grpc>=1.2.0->chromadb)\n",
            "  Downloading opentelemetry_exporter_otlp_proto_common-1.21.0-py3-none-any.whl (17 kB)\n",
            "Collecting opentelemetry-proto==1.21.0 (from opentelemetry-exporter-otlp-proto-grpc>=1.2.0->chromadb)\n",
            "  Downloading opentelemetry_proto-1.21.0-py3-none-any.whl (50 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m50.8/50.8 kB\u001b[0m \u001b[31m7.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting opentelemetry-instrumentation-asgi==0.42b0 (from opentelemetry-instrumentation-fastapi>=0.41b0->chromadb)\n",
            "  Downloading opentelemetry_instrumentation_asgi-0.42b0-py3-none-any.whl (13 kB)\n",
            "Collecting opentelemetry-instrumentation==0.42b0 (from opentelemetry-instrumentation-fastapi>=0.41b0->chromadb)\n",
            "  Downloading opentelemetry_instrumentation-0.42b0-py3-none-any.whl (25 kB)\n",
            "Collecting opentelemetry-semantic-conventions==0.42b0 (from opentelemetry-instrumentation-fastapi>=0.41b0->chromadb)\n",
            "  Downloading opentelemetry_semantic_conventions-0.42b0-py3-none-any.whl (36 kB)\n",
            "Collecting opentelemetry-util-http==0.42b0 (from opentelemetry-instrumentation-fastapi>=0.41b0->chromadb)\n",
            "  Downloading opentelemetry_util_http-0.42b0-py3-none-any.whl (6.9 kB)\n",
            "Requirement already satisfied: setuptools>=16.0 in /usr/local/lib/python3.10/dist-packages (from opentelemetry-instrumentation==0.42b0->opentelemetry-instrumentation-fastapi>=0.41b0->chromadb) (67.7.2)\n",
            "Requirement already satisfied: wrapt<2.0.0,>=1.0.0 in /usr/local/lib/python3.10/dist-packages (from opentelemetry-instrumentation==0.42b0->opentelemetry-instrumentation-fastapi>=0.41b0->chromadb) (1.14.1)\n",
            "Collecting asgiref~=3.0 (from opentelemetry-instrumentation-asgi==0.42b0->opentelemetry-instrumentation-fastapi>=0.41b0->chromadb)\n",
            "  Downloading asgiref-3.7.2-py3-none-any.whl (24 kB)\n",
            "Collecting monotonic>=1.5 (from posthog>=2.4.0->chromadb)\n",
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            "Collecting h11>=0.8 (from uvicorn[standard]>=0.18.3->chromadb)\n",
            "  Downloading h11-0.14.0-py3-none-any.whl (58 kB)\n",
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            "\u001b[?25hCollecting httptools>=0.5.0 (from uvicorn[standard]>=0.18.3->chromadb)\n",
            "  Downloading httptools-0.6.1-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (341 kB)\n",
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            "\u001b[?25hCollecting python-dotenv>=0.13 (from uvicorn[standard]>=0.18.3->chromadb)\n",
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            "Collecting uvloop!=0.15.0,!=0.15.1,>=0.14.0 (from uvicorn[standard]>=0.18.3->chromadb)\n",
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            "\u001b[?25hCollecting watchfiles>=0.13 (from uvicorn[standard]>=0.18.3->chromadb)\n",
            "  Downloading watchfiles-0.21.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.3 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 MB\u001b[0m \u001b[31m83.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting websockets>=10.4 (from uvicorn[standard]>=0.18.3->chromadb)\n",
            "  Downloading websockets-12.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (130 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m130.2/130.2 kB\u001b[0m \u001b[31m13.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: sniffio>=1.1 in /usr/local/lib/python3.10/dist-packages (from anyio<4.0.0,>=3.7.1->fastapi>=0.95.2->chromadb) (1.3.0)\n",
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            "Requirement already satisfied: pyasn1-modules>=0.2.1 in /usr/local/lib/python3.10/dist-packages (from google-auth>=1.0.1->kubernetes>=28.1.0->chromadb) (0.3.0)\n",
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            "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.10/dist-packages (from importlib-metadata<7.0,>=6.0->opentelemetry-api>=1.2.0->chromadb) (3.17.0)\n",
            "Collecting humanfriendly>=9.1 (from coloredlogs->onnxruntime>=1.14.1->chromadb)\n",
            "  Downloading humanfriendly-10.0-py2.py3-none-any.whl (86 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m86.8/86.8 kB\u001b[0m \u001b[31m13.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->onnxruntime>=1.14.1->chromadb) (1.3.0)\n",
            "Requirement already satisfied: pyasn1<0.6.0,>=0.4.6 in /usr/local/lib/python3.10/dist-packages (from pyasn1-modules>=0.2.1->google-auth>=1.0.1->kubernetes>=28.1.0->chromadb) (0.5.1)\n",
            "Building wheels for collected packages: pypika\n",
            "  Building wheel for pypika (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for pypika: filename=PyPika-0.48.9-py2.py3-none-any.whl size=53723 sha256=592332cab3daa8ae3a0ecde6ff26d4ea085244ce2a2e3c73d7648426e5552762\n",
            "  Stored in directory: /root/.cache/pip/wheels/e1/26/51/d0bffb3d2fd82256676d7ad3003faea3bd6dddc9577af665f4\n",
            "Successfully built pypika\n",
            "Installing collected packages: pypika, monotonic, mmh3, websockets, uvloop, urllib3, typing-extensions, python-dotenv, pulsar-client, overrides, opentelemetry-util-http, opentelemetry-semantic-conventions, opentelemetry-proto, humanfriendly, httptools, h11, deprecated, chroma-hnswlib, bcrypt, watchfiles, uvicorn, starlette, opentelemetry-exporter-otlp-proto-common, opentelemetry-api, coloredlogs, asgiref, posthog, opentelemetry-sdk, opentelemetry-instrumentation, onnxruntime, fastapi, opentelemetry-instrumentation-asgi, opentelemetry-exporter-otlp-proto-grpc, kubernetes, opentelemetry-instrumentation-fastapi, chromadb\n",
            "  Attempting uninstall: urllib3\n",
            "    Found existing installation: urllib3 2.0.7\n",
            "    Uninstalling urllib3-2.0.7:\n",
            "      Successfully uninstalled urllib3-2.0.7\n",
            "  Attempting uninstall: typing-extensions\n",
            "    Found existing installation: typing_extensions 4.5.0\n",
            "    Uninstalling typing_extensions-4.5.0:\n",
            "      Successfully uninstalled typing_extensions-4.5.0\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "lida 0.0.10 requires kaleido, which is not installed.\n",
            "lida 0.0.10 requires python-multipart, which is not installed.\n",
            "tensorflow-probability 0.22.0 requires typing-extensions<4.6.0, but you have typing-extensions 4.8.0 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed asgiref-3.7.2 bcrypt-4.1.1 chroma-hnswlib-0.7.3 chromadb-0.4.18 coloredlogs-15.0.1 deprecated-1.2.14 fastapi-0.104.1 h11-0.14.0 httptools-0.6.1 humanfriendly-10.0 kubernetes-28.1.0 mmh3-4.0.1 monotonic-1.6 onnxruntime-1.16.3 opentelemetry-api-1.21.0 opentelemetry-exporter-otlp-proto-common-1.21.0 opentelemetry-exporter-otlp-proto-grpc-1.21.0 opentelemetry-instrumentation-0.42b0 opentelemetry-instrumentation-asgi-0.42b0 opentelemetry-instrumentation-fastapi-0.42b0 opentelemetry-proto-1.21.0 opentelemetry-sdk-1.21.0 opentelemetry-semantic-conventions-0.42b0 opentelemetry-util-http-0.42b0 overrides-7.4.0 posthog-3.0.2 pulsar-client-3.3.0 pypika-0.48.9 python-dotenv-1.0.0 starlette-0.27.0 typing-extensions-4.8.0 urllib3-1.26.18 uvicorn-0.24.0.post1 uvloop-0.19.0 watchfiles-0.21.0 websockets-12.0\n",
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            "Collecting tiktoken\n",
            "  Downloading tiktoken-0.5.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.0 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.0/2.0 MB\u001b[0m \u001b[31m8.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: regex>=2022.1.18 in /usr/local/lib/python3.10/dist-packages (from tiktoken) (2023.6.3)\n",
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            "Installing collected packages: tiktoken\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "llmx 0.0.15a0 requires cohere, which is not installed.\n",
            "llmx 0.0.15a0 requires openai, which is not installed.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed tiktoken-0.5.1\n",
            "Requirement already satisfied: unstructured[local-inference] in /usr/local/lib/python3.10/dist-packages (0.11.2)\n",
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            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.10/dist-packages (from unstructured[local-inference]) (4.8.0)\n",
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            "Collecting python-docx>=1.1.0 (from unstructured[local-inference])\n",
            "  Downloading python_docx-1.1.0-py3-none-any.whl (239 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m239.6/239.6 kB\u001b[0m \u001b[31m5.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "Collecting onnx (from unstructured[local-inference])\n",
            "  Downloading onnx-1.15.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (15.7 MB)\n",
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            "Collecting msg-parser (from unstructured[local-inference])\n",
            "  Downloading msg_parser-1.2.0-py2.py3-none-any.whl (101 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m101.8/101.8 kB\u001b[0m \u001b[31m15.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "Collecting pdfminer.six (from unstructured[local-inference])\n",
            "  Downloading pdfminer.six-20221105-py3-none-any.whl (5.6 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m5.6/5.6 MB\u001b[0m \u001b[31m106.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: markdown in /usr/local/lib/python3.10/dist-packages (from unstructured[local-inference]) (3.5.1)\n",
            "Collecting unstructured-inference==0.7.15 (from unstructured[local-inference])\n",
            "  Downloading unstructured_inference-0.7.15-py3-none-any.whl (62 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m62.7/62.7 kB\u001b[0m \u001b[31m7.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting pdf2image (from unstructured[local-inference])\n",
            "  Downloading pdf2image-1.16.3-py3-none-any.whl (11 kB)\n",
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            "Building wheels for collected packages: iopath, antlr4-python3-runtime\n",
            "  Building wheel for iopath (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for iopath: filename=iopath-0.1.10-py3-none-any.whl size=31532 sha256=7147dcde20ea81be9288c98e507393321a38e65f35a90bf3242e37935772bd92\n",
            "  Stored in directory: /root/.cache/pip/wheels/9a/a3/b6/ac0fcd1b4ed5cfeb3db92e6a0e476cfd48ed0df92b91080c1d\n",
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            "  Stored in directory: /root/.cache/pip/wheels/12/93/dd/1f6a127edc45659556564c5730f6d4e300888f4bca2d4c5a88\n",
            "Successfully built iopath antlr4-python3-runtime\n",
            "Installing collected packages: antlr4-python3-runtime, XlsxWriter, python-multipart, python-docx, pypdfium2, pypandoc, portalocker, Pillow, onnx, omegaconf, olefile, unstructured.pytesseract, python-pptx, pytesseract, pikepdf, pdf2image, onnxruntime, msg-parser, iopath, pdfminer.six, timm, pdfplumber, layoutparser, effdet, unstructured-inference\n",
            "  Attempting uninstall: Pillow\n",
            "    Found existing installation: Pillow 9.4.0\n",
            "    Uninstalling Pillow-9.4.0:\n",
            "      Successfully uninstalled Pillow-9.4.0\n",
            "  Attempting uninstall: onnxruntime\n",
            "    Found existing installation: onnxruntime 1.16.3\n",
            "    Uninstalling onnxruntime-1.16.3:\n",
            "      Successfully uninstalled onnxruntime-1.16.3\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "lida 0.0.10 requires kaleido, which is not installed.\n",
            "imageio 2.31.6 requires pillow<10.1.0,>=8.3.2, but you have pillow 10.1.0 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed Pillow-10.1.0 XlsxWriter-3.1.9 antlr4-python3-runtime-4.9.3 effdet-0.4.1 iopath-0.1.10 layoutparser-0.3.4 msg-parser-1.2.0 olefile-0.47 omegaconf-2.3.0 onnx-1.15.0 onnxruntime-1.15.1 pdf2image-1.16.3 pdfminer.six-20221105 pdfplumber-0.10.3 pikepdf-8.7.1 portalocker-2.8.2 pypandoc-1.12 pypdfium2-4.24.0 pytesseract-0.3.10 python-docx-1.1.0 python-multipart-0.0.6 python-pptx-0.6.23 timm-0.9.12 unstructured-inference-0.7.15 unstructured.pytesseract-0.3.12\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "PIL",
                  "pydevd_plugins"
                ]
              }
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting faiss-gpu\n",
            "  Downloading faiss_gpu-1.7.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (85.5 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m85.5/85.5 MB\u001b[0m \u001b[31m9.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hInstalling collected packages: faiss-gpu\n",
            "Successfully installed faiss-gpu-1.7.2\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from langchain.embeddings import HuggingFaceEmbeddings\n",
        "from langchain import HuggingFaceHub\n",
        "from langchain.text_splitter import CharacterTextSplitter"
      ],
      "metadata": {
        "id": "D04qEuYxV9kM"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "TwLycAK9LOtu"
      },
      "outputs": [],
      "source": [
        "import os\n",
        "os.environ[\"HUGGINGFACEHUB_API_TOKEN\"]=\"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\""
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from langchain.document_loaders import UnstructuredPDFLoader\n",
        "from langchain.indexes import VectorstoreIndexCreator"
      ],
      "metadata": {
        "id": "g9SIIqsbUzMU"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# from google.colab import drive\n",
        "# drive.mount('/content/drive', force_remount=True)\n",
        "\n",
        "pdf_folder_path = '/content/drive/MyDrive/Llama2RAG/data/lanchain_pdf/bhai_bhai_matsha_file.pdf'\n",
        "# os.listdir(pdf_folder_path)"
      ],
      "metadata": {
        "id": "7QQ9oGXqU21E"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "loaders=[UnstructuredPDFLoader(pdf_folder_path)]"
      ],
      "metadata": {
        "id": "CbxQ5W-x-M2I"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "index = VectorstoreIndexCreator(\n",
        "    embedding=HuggingFaceEmbeddings(),\n",
        "    text_splitter=CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)).from_loaders(loaders)"
      ],
      "metadata": {
        "id": "a_Ppx1FDVE3C"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import random\n",
        "\n",
        "random.choices(['a','b','c','d'],k=2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Qfdud6gyA4CS",
        "outputId": "94887170-9edf-4957-d9ab-919d0674c474"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['c', 'd']"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from langchain import HuggingFacePipeline"
      ],
      "metadata": {
        "id": "MkAacwGa0TgB"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "llm_gpu=HuggingFacePipeline.from_model_id(\n",
        "    model_id=\"google/flan-t5-large\",\n",
        "    task=\"text2text-generation\",\n",
        "    device=0,\n",
        "    model_kwargs={\"temperature\":0,\"max_length\":128,\"do_sample\":False}\n",
        ")"
      ],
      "metadata": {
        "id": "53RR5UeR01PJ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297,
          "referenced_widgets": [
            "1f631b0b55cb4a8bbfe60373986a4e42",
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            "2cd30081b85c4be4b4328b2ed826a4f5",
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            "439d7e912ac24cadad0dc2d298cea2bf",
            "15a2cd475f4746f2b40dab71371fb34a",
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            "cd0556b2f3c0437b99ed0805214cbe54",
            "df5c853147e34d2f8801698905e61ec6",
            "d1a4abca06a24aefaac8e24761b63e67",
            "5d496475b84a43eeb6bd66bb39811b68",
            "f4ee1b399aaa455a8cae76d238dd47ba",
            "43da8536739941aba10d476f58f7f45b",
            "a75342c742594efca7319a821147780f",
            "00a469fa33394ca2b750115f8366edf3",
            "17fa7d7646bb4ae0b04f361d41105d90",
            "bca01e5790894fc08e16d794683de499",
            "89dabc0d7c6742c38a9910b52b21b5d6",
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            "a564dadbae344d90945b2338bba42a3f",
            "e224fd07d7774ff3a3e5a2a21ef788a7",
            "fd8f56eef9d145e3a074327d9b1e8d1e",
            "1682ff422bf64cbb980309c6946d27cb",
            "bd18661461ef475d89ee93e94081204b",
            "4e034fdaa8dc4edab5b1c0d0099cddce",
            "dffe838ff64345098967e6be2347c328",
            "7861612cfbaa44fa97742fa420ac3938",
            "32c2af80a5ba4cb2bf3ec189cb06fde1",
            "ca02a6cc680842018b6a6384ff1fcd9d",
            "f713a0d7f2de40409ff653c3f82049db"
          ]
        },
        "outputId": "9b33e644-399f-4ee0-91d1-3b409a0c8004"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "tokenizer_config.json:   0%|          | 0.00/2.54k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "1f631b0b55cb4a8bbfe60373986a4e42"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "spiece.model:   0%|          | 0.00/792k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "10270bfac4af4d77b7656b4036cf6a4b"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "tokenizer.json:   0%|          | 0.00/2.42M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "889845a9ccd44c5ca0e2dbcfc1af8072"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "special_tokens_map.json:   0%|          | 0.00/2.20k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "1815b1edd3694f3a97b889ccd23e0c71"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "config.json:   0%|          | 0.00/662 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "fe55102d6738456d8403a6d75582d1ec"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "model.safetensors:   0%|          | 0.00/3.13G [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "df5c853147e34d2f8801698905e61ec6"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`. This was detected when initializing the generation config instance, which means the corresponding file may hold incorrect parameterization and should be fixed.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "generation_config.json:   0%|          | 0.00/147 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "a564dadbae344d90945b2338bba42a3f"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from langchain.chains import RetrievalQA\n",
        "chain = RetrievalQA.from_chain_type(llm=llm_gpu,\n",
        "                                    chain_type=\"stuff\",\n",
        "                                    retriever=index.vectorstore.as_retriever(),\n",
        "                                    input_key=\"question\",\n",
        "                                    )"
      ],
      "metadata": {
        "id": "4X7efeli1LnA"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "chain.run('What is the capital amount?')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 346
        },
        "id": "shDugYoxWbXF",
        "outputId": "b8d6a197-69ba-4a6e-8e2c-a9fc43019def"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "ValueError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-25-1526270fb432>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mchain\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'What is the capital amount?'\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/python3.10/dist-packages/langchain/chains/base.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(self, callbacks, tags, metadata, *args, **kwargs)\u001b[0m\n\u001b[1;32m    500\u001b[0m         \"\"\"\n\u001b[1;32m    501\u001b[0m         \u001b[0;31m# Run at start to make sure this is possible/defined\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 502\u001b[0;31m         \u001b[0m_output_key\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_run_output_key\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    503\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    504\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0margs\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;32mnot\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[0;32m/usr/local/lib/python3.10/dist-packages/langchain/chains/base.py\u001b[0m in \u001b[0;36m_run_output_key\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    449\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_run_output_key\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    450\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moutput_keys\u001b[0m\u001b[0;34m)\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\u001b[0m\u001b[0m\n\u001b[0;32m--> 451\u001b[0;31m             raise ValueError(\n\u001b[0m\u001b[1;32m    452\u001b[0m                 \u001b[0;34mf\"`run` not supported when there is not exactly \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    453\u001b[0m                 \u001b[0;34mf\"one output key. Got {self.output_keys}.\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mValueError\u001b[0m: `run` not supported when there is not exactly one output key. Got ['result', 'source_documents']."
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "chain.run('Tell me his name?')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 127
        },
        "id": "lz8MD-f6f6Hs",
        "outputId": "31724c97-5bf6-4389-9fcc-d91f5906199d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`. This was detected when initializing the generation config instance, which means the corresponding file may hold incorrect parameterization and should be fixed.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Jb. Sadat'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "1 if int(chain.run('What time he took the last loan?').split('.')[-1])-int(chain.run('What time he took the first loan?').split(\" \")[-1])>3 else 0"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vUb0ag7zfDkh",
        "outputId": "a9ab9823-ce61-4f32-92e9-1614e647436e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`. This was detected when initializing the generation config instance, which means the corresponding file may hold incorrect parameterization and should be fixed.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`. This was detected when initializing the generation config instance, which means the corresponding file may hold incorrect parameterization and should be fixed.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "chain.run('What time he took the last loan?')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 127
        },
        "id": "7baXyOdQy2bV",
        "outputId": "a903c6d3-7f79-4e6d-d0d7-8e7370f5c821"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`. This was detected when initializing the generation config instance, which means the corresponding file may hold incorrect parameterization and should be fixed.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'10.08.2023'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "chain.run('What time he took the first loan?')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 127
        },
        "id": "VXUXJkMHgyxb",
        "outputId": "242ad313-13ed-418c-f2ca-fad8453d6062"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`. This was detected when initializing the generation config instance, which means the corresponding file may hold incorrect parameterization and should be fixed.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'2010'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "chain.run('Tell me the breif about the company?')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 127
        },
        "id": "XV6FipZufN3a",
        "outputId": "1635dcaf-cd51-4f83-b265-05591fbba074"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`. This was detected when initializing the generation config instance, which means the corresponding file may hold incorrect parameterization and should be fixed.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Jb. Sadat is an energetic, hardworking & well known businessman'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "chain.run('What type of the company it is?')\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 127
        },
        "id": "Z16_WC-cjA54",
        "outputId": "5d82910b-4ba8-41c8-ffb6-00c95bfc0aec"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`. This was detected when initializing the generation config instance, which means the corresponding file may hold incorrect parameterization and should be fixed.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'a trader of Fish culture, Hatchery & sell of Fish for Project'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "chain.run('What is his total properties worth?')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 127
        },
        "id": "MLa7IGpNzFTT",
        "outputId": "5c9b125a-95ec-4181-d2da-639c59f19a55"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`. This was detected when initializing the generation config instance, which means the corresponding file may hold incorrect parameterization and should be fixed.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Tk. 18.73 million'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "chain.run('How much taka he is wanted from the bank?')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 127
        },
        "id": "byXQJ2KozKzB",
        "outputId": "7d0b9a4b-8f6f-456c-f029-9a62fb254b70"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`. This was detected when initializing the generation config instance, which means the corresponding file may hold incorrect parameterization and should be fixed.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Tk. 2.50 million'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "chain.run('What is his experiences')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 180
        },
        "id": "t2IpRTkEziIO",
        "outputId": "11a15cee-9cd0-497a-8aba-cacc4de6c95c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/pipelines/base.py:1101: UserWarning: You seem to be using the pipelines sequentially on GPU. In order to maximize efficiency please use a dataset\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`. This was detected when initializing the generation config instance, which means the corresponding file may hold incorrect parameterization and should be fixed.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'He has been banking with the branch since 2010 and availing investment facility since 2015 with satisfactory performance'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "chain.run(\"What is his condition right now?\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 163
        },
        "id": "qgWbkZ79zn4c",
        "outputId": "c47ac8ae-793a-4de3-dcb7-0a5f94fba3a6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/pipelines/base.py:1101: UserWarning: You seem to be using the pipelines sequentially on GPU. In order to maximize efficiency please use a dataset\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`. This was detected when initializing the generation config instance, which means the corresponding file may hold incorrect parameterization and should be fixed.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'b).'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "chain.run('What is his experience?')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 163
        },
        "id": "nqjgg4sC3MUb",
        "outputId": "d6a5a89b-e9b8-4920-ea90-f7c0684ed7a3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/pipelines/base.py:1101: UserWarning: You seem to be using the pipelines sequentially on GPU. In order to maximize efficiency please use a dataset\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`. This was detected when initializing the generation config instance, which means the corresponding file may hold incorrect parameterization and should be fixed.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'He has been running the business since last 30 years'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "chain.run('What is the interest rate?')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 163
        },
        "id": "KRWbJvQJ3Smp",
        "outputId": "438890fb-6bae-4041-bb2f-f1297acffef3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/pipelines/base.py:1101: UserWarning: You seem to be using the pipelines sequentially on GPU. In order to maximize efficiency please use a dataset\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`. This was detected when initializing the generation config instance, which means the corresponding file may hold incorrect parameterization and should be fixed.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'9.14%'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "chain.run('What type of investment he need ?')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 163
        },
        "id": "QFe_NPnv8Ynp",
        "outputId": "74d1676a-f028-4362-a80e-1766bfa465b5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/pipelines/base.py:1101: UserWarning: You seem to be using the pipelines sequentially on GPU. In order to maximize efficiency please use a dataset\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`. This was detected when initializing the generation config instance, which means the corresponding file may hold incorrect parameterization and should be fixed.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'MTR'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "chain.run('What is the loan type?')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 163
        },
        "id": "J_CDV1rU-EIL",
        "outputId": "250f8aa9-765f-410c-d618-61b9d42d0937"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/pipelines/base.py:1101: UserWarning: You seem to be using the pipelines sequentially on GPU. In order to maximize efficiency please use a dataset\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`. This was detected when initializing the generation config instance, which means the corresponding file may hold incorrect parameterization and should be fixed.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'MTR'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "chain.run('Mortgage amount')"
      ],
      "metadata": {
        "id": "Sogdk6Jl-gYR",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 163
        },
        "outputId": "43a97cc0-501f-4bb6-a7aa-e2a6e2dfe6c3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/pipelines/base.py:1101: UserWarning: You seem to be using the pipelines sequentially on GPU. In order to maximize efficiency please use a dataset\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`. This was detected when initializing the generation config instance, which means the corresponding file may hold incorrect parameterization and should be fixed.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'205.00 dmimal Land'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "chain.run('total Asset amount')"
      ],
      "metadata": {
        "id": "WcnZbruwhomj",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 163
        },
        "outputId": "9261f331-bb68-4f5c-ae1b-268bd16bab38"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/pipelines/base.py:1101: UserWarning: You seem to be using the pipelines sequentially on GPU. In order to maximize efficiency please use a dataset\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`. This was detected when initializing the generation config instance, which means the corresponding file may hold incorrect parameterization and should be fixed.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:381: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'28.63-6.Il3=22.6ii 8.05'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "HFBLXsspCTC6"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}