{ "cells": [ { "cell_type": "markdown", "source": [ "# Installing Dependencies" ], "metadata": { "id": "xRmnGmVEibUq" } }, { "cell_type": "code", "source": [ "!pip install -q -U openai\n", "!pip install -q -U llama_index\n", "!pip install -q -U nest_asyncio\n", "!pip install -q -U pypdf\n", "!pip install -q -U bitsandbytes\n", "!pip install -q -U git+https://github.com/huggingface/transformers.git\n", "!pip install -q -U git+https://github.com/huggingface/peft.git\n", "!pip install -q -U git+https://github.com/huggingface/accelerate.git\n", "!pip install -q -U pinecone-client langchain\n", "!pip install -q -U git+https://github.com/huggingface/transformers\n", "!pip install -q -U sentence-transformers" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "iKCE2k79h7rx", "outputId": "db557a38-da46-4b41-c4f3-f3c9fb6b0871" }, "execution_count": 1, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "\u001b[?25l \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/220.8 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[91m╸\u001b[0m\u001b[90m━\u001b[0m \u001b[32m215.0/220.8 kB\u001b[0m \u001b[31m6.9 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m220.8/220.8 kB\u001b[0m \u001b[31m5.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m75.0/75.0 kB\u001b[0m \u001b[31m10.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m76.9/76.9 kB\u001b[0m \u001b[31m7.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m58.3/58.3 kB\u001b[0m \u001b[31m8.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25h\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 tiktoken, which is not installed.\u001b[0m\u001b[31m\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m896.9/896.9 kB\u001b[0m \u001b[31m9.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m143.0/143.0 kB\u001b[0m \u001b[31m11.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.0/2.0 MB\u001b[0m \u001b[31m23.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m143.8/143.8 kB\u001b[0m \u001b[31m17.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m49.4/49.4 kB\u001b[0m \u001b[31m6.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25h\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.\u001b[0m\u001b[31m\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m277.6/277.6 kB\u001b[0m \u001b[31m5.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m92.6/92.6 MB\u001b[0m \u001b[31m19.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25h Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n", " Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n", " Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", " Building wheel for transformers (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", " Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n", " Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n", " Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m261.4/261.4 kB\u001b[0m \u001b[31m5.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25h Building wheel for peft (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", " Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n", " Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n", " Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", " Building wheel for accelerate (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m179.4/179.4 kB\u001b[0m \u001b[31m5.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.0/2.0 MB\u001b[0m \u001b[31m22.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m 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\u001b[31m14.3 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" ] } ] }, { "cell_type": "markdown", "metadata": { "id": "1JBwPHcGgfc2" }, "source": [ "# NIST Questions\n", "This Section utilises the points under Govern, Map, Measure, and Manage in the NIST AI RMF to query a policy and obtain responses of how well the policy aligns." ] }, { "cell_type": "markdown", "metadata": { "id": "b-VOHoKggfc4" }, "source": [ "## Import Packages" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "id": "DrNspLPugfc4" }, "outputs": [], "source": [ "import numpy as np\n", "import openai\n", "from llama_index import SimpleDirectoryReader, ServiceContext, VectorStoreIndex\n", "import nest_asyncio\n", "import pandas as pd\n", "nest_asyncio.apply()" ] }, { "cell_type": "markdown", "metadata": { "id": "nQH-48wIgfc6" }, "source": [ "## OpenAI API Key" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "id": "BbjRS1MYgfc6" }, "outputs": [], "source": [ "openai.api_key = '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'" ] }, { "cell_type": "markdown", "metadata": { "id": "av-s3bzmgfc6" }, "source": [ "## Import the GenAI Policy\n", "The policies used here was created by AI after being asked to create a policy aligned with the NIST document which was uploaded" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "id": "9IWTWujkgfc7" }, "outputs": [], "source": [ "gold_policy = SimpleDirectoryReader(input_files=['/content/data/Badguys AI Ethics and Responsible AI Policy.pdf']).load_data()\n", "mock_policy = SimpleDirectoryReader(input_files=['/content/data/Mock Policy.pdf']).load_data()" ] }, { "cell_type": "markdown", "metadata": { "id": "RG5qMGzhgfc7" }, "source": [ "## Set chunk information" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "id": "LbIUGcE5gfc8" }, "outputs": [], "source": [ "chunk_size = 128\n", "chunk_overlap = 20\n", "similarity_top_k = 6" ] }, { "cell_type": "markdown", "metadata": { "id": "TGJcKWD7gfc8" }, "source": [ "## Read text files of NIST AI RMF statements" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "id": "pWX1t2fZgfc9" }, "outputs": [], "source": [ "Govern = open(\"/content/NIST/Govern.txt\", \"r\").readlines()\n", "Govern = [Govern[i].replace(\"\\n\", \"\") for i in range(len(Govern))]\n", "\n", "Map = open(\"/content/NIST/Map.txt\", \"r\").readlines()\n", "Map = [Map[i].replace(\"\\n\", \"\") for i in range(len(Map))]\n", "\n", "Measure = open(\"/content/NIST/Measure.txt\", \"r\").readlines()\n", "Measure = [Measure[i].replace(\"\\n\", \"\") for i in range(len(Measure))]\n", "\n", "Manage = open(\"/content/NIST/Manage.txt\", \"r\").readlines()\n", "Manage = [Manage[i].replace(\"\\n\", \"\") for i in range(len(Manage))]\n", "\n", "eval_questions = np.concatenate((Govern, Map, Measure, Manage))" ] }, { "cell_type": "markdown", "metadata": { "id": "A85PYswKgfc9" }, "source": [ "## Define the question-asking function" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "id": "pcGqF1gDgfc-" }, "outputs": [], "source": [ "def ask_questions(docs):\n", " service_context = ServiceContext.from_defaults(chunk_size=chunk_size, chunk_overlap=20)\n", " index = VectorStoreIndex.from_documents(docs, service_context=service_context)\n", " query_engine = index.as_query_engine(similarity_top_k=similarity_top_k)\n", " responses = []\n", " sources = []\n", " for question in eval_questions:\n", " response = query_engine.query(\"Give evidence of where the policy aligns with the following point: \" + question)\n", " source = \"\"\n", " for i in range(similarity_top_k):\n", " source += response.source_nodes[i].node.get_content(metadata_mode=\"all\") + \"\\n\\n-----\\n\"\n", " responses.append(response.response)\n", " sources.append(source)\n", " return responses, sources" ] }, { "cell_type": "markdown", "metadata": { "id": "a3kVGu-8gfc-" }, "source": [ "## Query the document" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "-rOhYTvVgfc_", "outputId": "52da5de5-02fb-41c6-da97-3d4ad7591708" }, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ ":2: FutureWarning: Slicing a positional slice with .loc is not supported, and will raise TypeError in a future version. Use .loc with labels or .iloc with positions instead.\n", " Data.loc[0:19, 'Dimension'] = 'Govern'\n", ":3: FutureWarning: Slicing a positional slice with .loc is not supported, and will raise TypeError in a future version. Use .loc with labels or .iloc with positions instead.\n", " Data.loc[19:32, 'Dimension'] = 'Map'\n", ":4: FutureWarning: Slicing a positional slice with .loc is not supported, and will raise TypeError in a future version. Use .loc with labels or .iloc with positions instead.\n", " Data.loc[32:50, 'Dimension'] = 'Measure'\n", ":5: FutureWarning: Slicing a positional slice with .loc is not supported, and will raise TypeError in a future version. Use .loc with labels or .iloc with positions instead.\n", " Data.loc[50:72, 'Dimension'] = 'Manage'\n", "[nltk_data] Downloading package punkt to /tmp/llama_index...\n", "[nltk_data] Unzipping tokenizers/punkt.zip.\n" ] } ], "source": [ "Data = pd.DataFrame(index=eval_questions)\n", "Data.loc[0:19, 'Dimension'] = 'Govern'\n", "Data.loc[19:32, 'Dimension'] = 'Map'\n", "Data.loc[32:50, 'Dimension'] = 'Measure'\n", "Data.loc[50:72, 'Dimension'] = 'Manage'\n", "Data[\"Gold\"], Data[\"Gold Sources\"] = ask_questions(gold_policy)\n", "Data[\"Company\"], Data[\"Company Sources\"] = ask_questions(mock_policy)" ] }, { "cell_type": "markdown", "metadata": { "id": "eBIiI10Dgfc_" }, "source": [ "## Write to .csv file" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "id": "sP7PkIWXgfc_" }, "outputs": [], "source": [ "Data.to_csv(\"/content/Results/Compare.csv\")" ] }, { "cell_type": "markdown", "metadata": { "id": "5P58BREuitYw" }, "source": [ "# Similarity Score\n", "This section imports the questions and answers from the QuestionGeneration.ipynb output and scores the similarity\n", "\n", "Heavy inspiration taken from:\n", "\n", "https://github.com/karndeepsingh/sentence_similarity/blob/main/Finding_Similar_Sentence.ipynb" ] }, { "cell_type": "markdown", "metadata": { "id": "oaXGwheTitY5" }, "source": [ "## Import packages" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "id": "LqDrvohkitY6" }, "outputs": [], "source": [ "import pandas as pd\n", "from sklearn.metrics.pairwise import cosine_similarity\n", "import numpy as np\n", "from sentence_transformers import SentenceTransformer" ] }, { "cell_type": "markdown", "metadata": { "id": "Op4sr_MAitY9" }, "source": [ "## Load the model\n", "Uncomment to store the model locally for easy retrieval, but delete the model before uploading to GitHub as too large" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "id": "Jc84ILC4itY-", "colab": { "base_uri": "https://localhost:8080/", "height": 433, "referenced_widgets": [ "b190483adcf447788a58f5f790f66884", "724459bca0a443b381d3ed9b299650a0", "dba04a68dc614f8396491d17dd492646", "4be9240bdda141bc9ff35f5e807ecd4d", "c8aea94679174bb7bbfab54978586c4e", "fa8a2a07d0d04fc48b2ad24e0f3f12e2", "876a0c9166d34e8eb6f3f7dc2024a2b9", "547dfdf581a74122801a2699fd1d5e64", "f221cf2d02bc43e7aae66638a577b354", "c5406d4dd7a941fc9c95bd004f5fb756", "3941c48037c240d096d46fc76b7d54b0", "48fd7431766a43cb8698be0f1a3f4812", "ad654a2fca2d4221ab6620ed00ab9753", "d0900339b9cf41d4855ea939ff50573e", "473638f610574405b4c5b7f8f85605cf", "02f1455916e24e34a4af5743b1d1ed45", "cadd989463a2464e925ddc5b255d5058", "2384423d17c64269a0796e47c1b25bdb", "34e3b5900eac428f990a9a7c71c0765d", "b33bf13e59de41a3aeeeb95525a05355", "b57f456febc74826aac84bd9aa3a934d", "8e85c4f769fe4b9d834ee45720c223dd", "75b8be5180a54f049fc26fd468bea469", "9b79f9e63d1d4ae1b9c2ad9cfa2bd953", "2d8dbf15ea09496ebe1aaa756d796513", "ecd843282c174afc87ef6133d72c92cb", 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"344025a55851483897e3ce90ff2c5183", "c34235958c0c40b7bbfd2cece6d3b26c", "a47f43a29cb645a58b69e31fd87b398c", "b92301582c5d4a73a587cead60248f13", "db785d4d27554087a87f22a4b9bd21ac", "31f945466bb943eda13162d7c437c29c", "4d1ca73635b743c986c7ef88b38acfc7", "346ae234e71f4e5fa9825637c1c583ce", "547d17952d0d49a393a830efd3ed28a5", "c209ddde4d214c3985b30ee4d2798736", "186b61db72e34339be47e0542728699b", "24576d4334154412a22bf553853eafc0", "eddaa94ab3594352808bf2023ce80dbf", "208eff565eae4a6ca280fe96a6ed073d", "939ae83100844f9e97babad335110744", "e36404a63b204bdc87085e95167f4ac8", "b5b869e6ebe24ea6b428191da02a7264", "9d1425ac725e41c5b7b30e6d081f63a7", "e456251e81d64194824b503c854b0c28", "fa23e22d67f644dd9276cb7d554aa662", "b109405fbc1945dbac08b3df628cf91e", "872d41722cff42f2b354a03b1f3cce00", "9d1b008dec1e42ba9e89045fb69960d2", "ed160534953c42309c3d5632c35fb090", "9f76f81602344d0c85585c28631e0679", "f97d76bbe43449eba8f75704a3273ec3", "1010e08ff83c4ee3b8e7c585ea292c5f", "3e06a1f8be2f4d0ea7c6e505376f20e3", "2fff893633d349e3b2a1effafe52389b", "4edb5118465e4c69b4b1fffb8e38b388", "8a23c988f42946928ae512ea364b0064", "d15c3d7c11ca4c308117df20bdd32f26", "4595a6cbd769416297afd3d931cb6b88", "91484dd1a1bf4dd8981c0258efe43917", "371e9f30213a47079668b8f6dc2d52a3", "8d0217b4eca8427baa6064a64dcd97ad", "81ff716573d546aaa753e3ab40de6e04", "9fa1aaf3de44480eb4855510b04e2f28", "83b7e8b50a0d4ee08a91aa0d98fa4313", "5c63d652d67b4ff9ac52c7aa13e8dd41", "688451bee44548a39d21ef83bd1f85d0", "1391fa29b3544a6cb16421da76bd6733", "7505801335664f6eaca01d01e741b09e", "0a61b9442fea47518da32a1cb69eeddc", "e1f308859dc84541863e36e97c6c35eb", "e9458e0b97d548199ca2d768cb87f3c0", "125258b9efa84d26948a86d4e686432a", "5a3398465737468cba3db2479c988322", "6b6ba2f907ab4ba3923e1064b62c5ed7", "6f74eaaee6234740983e298844f44063", "75545e9fcee54235a32c48eb009abb4f", "47ae2fe4cba74a29943cd1f541ddd063", "f112b83ecf2f4ffb8a70591be452d2c6", "e77fdbb99a70421ea04620fb69c5de1b", "2266808ef04b4e7d9183b373a1e31528", "051c49d22b2945e698ea52baec1bac8f", "49f11ea1898847988abd042ca56f21cb", "de838255f28e4fee97a22c57a1c33993", "66c1ae26f1364815b272a8d1734ffd48", "58062dcc290a431fa09cdae2f98c32a5", "25068f6a22f542b991a7b1f55da380f8", "bf75bcf464bb406b836ea73ad8ea027b", "b2ca30ba17a14d0187711cccd56c30f4", "b113e4d770064351a8651e174be17bba", "153749b970ac4c2487b44b87cf18ff5d", "f3fd6a4d47de4d8eafd4e64b57324147", "39274ad68a8946d3bc9518c3835de210", "56f50618694640369cf44f46c648a6ac", "e45da3da852940148e196ce067786a46", "00fb92dc984041bd8642b9d638b14e23", "cd1be2d337c24efa97bf96e7495ce8b9", "80a27936e8ea4ab79e0b4bbd7f0aeb10", "5c315bcc60ba446da468c4f09ef62b6e", "8bc65afc2d68408ca02f7625027de1f2", "438d924e6261431a83a811879fbf5ce0", "d67db26fbdaf46e9b948a757ecd4e64f", "df8b18a935f74e7aa336ce7732cf1f23", "b649e6dde092401a93007f1b532b0a50", "5404548555b9446a87b71af184663690", "e9a158b05ea9495cbc6501a9ea0fd4b6", "2035a21840a7407685f2db39d71ccb66", "b79b9c6594eb4908b68236046e80917f", "32fa34f6a3f44701a1cb19871c8f37ea", "950bb3a3d68d4cc5ae7c1a00d260927e", "d1a42a99913b4d74bfd48dd56777ed64", "1db48396c4da4a1b98557218c3821daf", "9da354cd10e045588448a4cccd8cbb48", "08d24e5886534add87efdbec919c276f", "82351cd7aaf3440cac647c40b1ba80ff", "8ec2c8d162104ba289c304354bf25920" ] }, "outputId": "a57e68c6-ecd6-47cb-ca26-45349495a451" }, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ ".gitattributes: 0%| | 0.00/736 [00:00[INST]\n", "Answer the following question and explain in detail:\n", "\n", "{text} [/INST] \n", "\"\"\"\n", "prompt = PromptTemplate(\n", " input_variables=[\"text\"],\n", " template=template,\n", ")" ], "metadata": { "id": "PItZAJTmV1dx" }, "execution_count": 27, "outputs": [] }, { "cell_type": "code", "source": [ "# Question-wise comparison analysis\n", "result = pd.DataFrame(columns = [\"result\"])\n", "for index, row in Data.iterrows():\n", " query = \"For the following question:\" + index+\"The following answer was extracted from a Gold Standard AI Policy\"+ row[1] +\"And this answer was extracted from a Company's AI Policy\"+ row[3] +\"The comparison score is:\"+str(row[5])+\"Compare the two answers and output what is missing in the answer extracted from the Company's AI Policy when compared to the one extracted from the Gold Standard Policy \";\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "te2WnQVUcU81", "outputId": "8dd3a984-5ff6-462f-df95-a92b6b09cdaf" }, "execution_count": 31, "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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n", "/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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n", ":5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n", " result = result.append({'result': mistral_llm(prompt.format(text=query))},ignore_index=True)\n" ] } ] }, { "cell_type": "code", "source": [ "Data['Reason'] = result['result'].values" ], "metadata": { "id": "og9fwxQGes2v" }, "execution_count": 32, "outputs": [] }, { "cell_type": "code", "source": [ "Data.to_csv(\"/content/Results/compare_rationalization.csv\")" ], "metadata": { "id": "36RS9K5mqGNj" }, "execution_count": 33, "outputs": [] }, { "cell_type": "markdown", "metadata": { "id": "HA7pGPJKco9j" }, "source": [ "## Adding Context and RAG Based Analysis Report Generation\n", "\n", "For each dimension of the NIST AI RMF, Govern, Manage, Map & Measure, a Retrieval Augmented Generation approach is used to generate a report using the Mistral-7b-Instruct LLM (https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1)" ] }, { "cell_type": "code", "execution_count": 86, "metadata": { "id": "aruTnmIWEqiv" }, "outputs": [], "source": [ "# Prompt template\n", "qa_template = \"\"\"[INST]\n", "You are an AI Policy Expert. Generate an report for Business Executives answering the QUESTION. The document should include Recommendations. Use the following control measures as context:\n", "\n", "{context}\n", "\n", "{question} [/INST] \n", "\"\"\"\n", "# Prompt Instance\n", "QA_PROMPT = PromptTemplate.from_template(qa_template)\n", "\n", "# Custom QA Chain\n", "qa_chain = RetrievalQA.from_chain_type(\n", " mistral_llm,\n", " retriever=retriever,\n", "\n", " chain_type_kwargs={\"prompt\": QA_PROMPT},\n", " return_source_documents=True\n", ")" ] }, { "cell_type": "markdown", "source": [ "### Govern" ], "metadata": { "id": "_0n82czNWFm1" } }, { "cell_type": "code", "execution_count": 87, "metadata": { "id": "sew7DhDAFiLB", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "f46abe9b-5afb-4fa4-9223-23608d262abc" }, "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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n" ] } ], "source": [ "Govern = Data[Data['Dimension'] == 'Govern']\n", "govern_text = ' '.join(Govern['Reason'].tolist())\n", "question = \"A Company's AI Policy was compared to a Gold Standard AI Policy and the following incompotencies were found in the Company's AI Policy: \"+govern_text+\" Generate recomendations for improvemnt of the Company's AI Policy for the Govern Dimension of the NIST AI RMF\"\n", "govern_response = qa_chain({\"query\": question})\n" ] }, { "cell_type": "code", "source": [ "import matplotlib.pyplot as plt\n", "\n", "# create data\n", "size_of_groups=[Govern['Score'].sum(),Govern.shape[0]-Govern['Score'].sum()]\n", "\n", "colors = ['#0066FF', '#CCE0FF']\n", "\n", "# Create a pieplot\n", "plt.pie(size_of_groups, colors=colors)\n", "\n", "# add a circle at the center to transform it in a donut chart\n", "my_circle=plt.Circle( (0,0), 0.7, color='white')\n", "p=plt.gcf()\n", "p.gca().add_artist(my_circle)\n", "\n", "# Adding Title of chart\n", "plt.title('Govern (% covered)')\n", "\n", "# Displaying Chart\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 428 }, "id": "YsmiMcFrRMQW", "outputId": "f4190bce-0aa3-47b5-ecda-f14cfc838264" }, "execution_count": 88, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": 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\n" }, "metadata": {} } ] }, { "cell_type": "code", "source": [ "\n", "govern_response['result']" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 122 }, "id": "TEvsFVQkRHVt", "outputId": "368eb184-99a3-4c4c-b56c-3a0ce9f649a9" }, "execution_count": 89, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "\"\\nRecommendation 1: Enhance the Compliance and Legal Framework\\n\\nTo improve the governance dimension of the Company's AI Policy, we recommend enhancing the compliance and legal framework. This can be achieved by:\\n\\n* Conducting a thorough review of the current legal and regulatory landscape related to AI, including national and international laws, regulations, and standards.\\n* Identifying areas where the Company's AI Policy needs to be updated or revised to comply with relevant laws and regulations.\\n* Establishing a dedicated team responsible for monitoring and updating the AI Policy to ensure ongoing compliance with changing legal and regulatory requirements.\\n* Providing regular training to staff on legal and regulatory requirements related to AI, including data protection, privacy, and security laws.\\n\\nRecommendation 2: Strengthen the Oversight and Accountability Mechanisms\\n\\nTo improve the governance dimension of the Company's AI Policy, we recommend strengthening the oversight and accountability mechanisms. This can be achieved by:\\n\\n* Establishing a formal governance structure for AI, including a senior management team responsible for overseeing AI initiatives and ensuring compliance with the AI Policy.\\n* Creating a dedicated AI ethics committee to provide guidance on ethical issues related to AI and ensure that the Company's AI initiatives align with ethical principles.\\n* Implementing a robust risk management framework for AI, including regular risk assessments and mitigation plans.\\n* Establishing clear lines of communication and escalation procedures for reporting and addressing AI-related issues.\\n\\nRecommendation 3: Foster a Culture of Trustworthiness\\n\\nTo improve the governance dimension of the Company's AI Policy, we recommend fostering a culture of trustworthiness. This can be achieved by:\\n\\n* Developing and implementing a code of conduct for AI that promotes ethical behavior and responsible use of AI.\\n* Providing regular training to staff on trustworthiness principles and best practices for AI.\\n* Encouraging open communication and collaboration between teams working on AI initiatives to promote knowledge sharing and learning.\\n* Establishing a mechanism for reporting and addressing unethical behavior related to AI.\\n\\nRecommendation 4: Enhance Transparency and Communication\\n\\nTo improve the governance dimension of the Company's AI Policy, we recommend enhancing transparency and communication. This can be achieved by:\\n\\n* Establishing clear communication channels for reporting and addressing AI-related issues.\\n* Providing regular updates to stakeholders on the Company's AI initiatives and progress towards achieving trustworthiness goals.\\n* Developing and implementing a communication plan for AI-related incidents and crises.\\n* Establishing a mechanism for collecting and analyzing feedback from stakeholders to inform future AI initiatives and improvements to the AI Policy.\\n\\nRecommendation 5: Continuously Monitor and Improve the AI Policy\\n\\nTo improve the governance dimension of the Company's AI Policy, we recommend continuously monitoring and improving the AI Policy. This can be achieved by:\\n\\n* Regularly reviewing and updating the AI Policy to reflect changes in legal and regulatory requirements, technology, and best practices.\\n* Establishing a mechanism for tracking and measuring the effectiveness of the AI Policy in promoting trustworthiness and compliance.\\n* Conducting regular audits and assessments of the AI Policy to identify areas for improvement.\\n* Establishing a mechanism for soliciting feedback from stakeholders to inform future improvements to the AI Policy.\"" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "string" } }, "metadata": {}, "execution_count": 89 } ] }, { "cell_type": "markdown", "source": [ "### Manage" ], "metadata": { "id": "yKwzyh_-WNFK" } }, { "cell_type": "code", "source": [ "Manage = Data[Data['Dimension'] == 'Manage']\n", "govern_text = ' '.join(Govern['Reason'].tolist())\n", "question = \"A Company's AI Policy was compared to a Gold Standard AI Policy and the following incompotencies were found in the Company's AI Policy: \"+govern_text+\"Generate recomendations for improvemnt of the Company's AI Policy for the Manage Dimension of the NIST AI RMF\"\n", "manage_response = qa_chain({\"query\": question})" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "9NsZHFLX2_zb", "outputId": "c39b6d57-4722-4adc-806c-aba5d0a12231" }, "execution_count": 90, "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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n" ] } ] }, { "cell_type": "code", "source": [ "size_of_groups=[Manage['Score'].sum(),Manage.shape[0]-Manage['Score'].sum()]\n", "\n", "colors = ['#0066FF', '#CCE0FF']\n", "\n", "# Create a pieplot\n", "plt.pie(size_of_groups, colors=colors)\n", "\n", "# add a circle at the center to transform it in a donut chart\n", "my_circle=plt.Circle( (0,0), 0.7, color='white')\n", "p=plt.gcf()\n", "p.gca().add_artist(my_circle)\n", "\n", "# Adding Title of chart\n", "plt.title('Manage (% covered)')\n", "\n", "# Displaying Chart\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 428 }, "id": "HC_AfwcAVprc", "outputId": "27a1ce09-5fb3-4f61-df4a-cf864208d4a7" }, "execution_count": 91, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
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\n" }, "metadata": {} } ] }, { "cell_type": "code", "source": [ "manage_response['result']" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 122 }, "id": "f1n1Qc7cEZ_Y", "outputId": "1e88c3ca-3d68-4c8c-c233-a6a3e442e5f7" }, "execution_count": 92, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "\"\\nRecommendation 1: Enhance Transparency and Accountability\\n\\nTo improve the Company's AI Policy for the Manage Dimension of the NIST AI RMF, it is recommended to enhance transparency and accountability. This can be achieved by:\\n\\n* Providing more specific details about the roles and responsibilities of the generative AI oversight team, including their involvement in decision-making related to AI risks.\\n* Establishing clear lines of communication and reporting mechanisms to ensure that all stakeholders are informed about AI risks and their management.\\n* Implementing mechanisms for oversight, accountability, and addressing unintended consequences into the development processes.\\n* Providing regular updates on the status of AI projects and their associated risks.\\n\\nRecommendation 2: Foster a Critical Thinking and Safety-First Mindset\\n\\nTo improve the Company's AI Policy for the Manage Dimension of the NIST AI RMF, it is recommended to foster a critical thinking and safety-first mindset. This can be achieved by:\\n\\n* Encouraging staff to ask questions and challenge assumptions related to AI risks.\\n* Providing training on topics related to safety, fairness, accountability, and regulatory compliance.\\n* Establishing documented processes for risk-based decisions and ensuring that these processes are followed consistently.\\n* Conducting regular risk assessments for each intended use case of generative AI.\\n\\nRecommendation 3: Address Bias and Error Mitigation\\n\\nTo improve the Company's AI Policy for the Manage Dimension of the NIST AI RMF, it is recommended to address bias and error mitigation. This can be achieved by:\\n\\n* Establishing controls to address emerging issues related to AI systems.\\n* Regularly evaluating and auditing AI systems to identify and mitigate potential biases, errors, or risks.\\n* Integrating mechanisms for oversight, accountability, and addressing unintended consequences into the development processes.\\n* Ensuring that AI systems are designed and developed with a focus on fairness and transparency.\\n\\nRecommendation 4: Continuous Evaluation and Improvement\\n\\nTo improve the Company's AI Policy for the Manage Dimension of the NIST AI RMF, it is recommended to engage in continuous evaluation and improvement. This can be achieved by:\\n\\n* Establishing feedback channels for users and affected groups to gather input on AI risks and their management.\\n* Collecting, considering, prioritizing, and integrating feedback from external sources related to AI risks.\\n* Regularly reviewing and updating the AI policy to ensure that it remains relevant and effective.\\n* Establishing a culture of continuous learning and improvement within the organization.\\n\\nBy implementing these recommendations, the Company can improve its AI Policy for the Manage Dimension of the NIST AI RMF and better manage the risks associated with AI systems.\"" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "string" } }, "metadata": {}, "execution_count": 92 } ] }, { "cell_type": "markdown", "source": [ "### Map" ], "metadata": { "id": "E9CSQUOEWUBR" } }, { "cell_type": "code", "source": [ "Map = Data[Data['Dimension'] == 'Map']\n", "map_text = ' '.join(Govern['Reason'].tolist())\n", "question = \"A Company's AI Policy was compared to a Gold Standard AI Policy and the following incompotencies were found in the Company's AI Policy: \"+map_text+\"Generate recomendations for improvemnt of the Company's AI Policy for the Map Dimension of the NIST AI RMF\"\n", "map_response = qa_chain({\"query\": question})" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "rZNEopcu4KmY", "outputId": "e1224fc2-edba-4a76-a82e-189c2d8f3925" }, "execution_count": 102, "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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n" ] } ] }, { "cell_type": "code", "source": [ "size_of_groups=[Map['Score'].sum(),Map.shape[0]-Map['Score'].sum()]\n", "\n", "colors = ['#0066FF', '#CCE0FF']\n", "\n", "# Create a pieplot\n", "plt.pie(size_of_groups, colors=colors)\n", "\n", "# add a circle at the center to transform it in a donut chart\n", "my_circle=plt.Circle( (0,0), 0.7, color='white')\n", "p=plt.gcf()\n", "p.gca().add_artist(my_circle)\n", "\n", "# Adding Title of chart\n", "plt.title('Map (% covered)')\n", "\n", "# Displaying Chart\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 428 }, "id": "YJYAQudmVwge", "outputId": "bf63f374-7bf0-436a-8a8f-e3d26928ecb2" }, "execution_count": 103, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
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\n" }, "metadata": {} } ] }, { "cell_type": "code", "source": [ "map_response['result']" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 122 }, "id": "hpS_YjmbEe_t", "outputId": "361836f6-1656-4b53-9f68-620e76289d7b" }, "execution_count": 104, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "'\\nRecommendation 1: Develop a Comprehensive Risk Assessment Framework\\n\\nTo effectively manage AI risks, it is essential to develop a comprehensive risk assessment framework that considers various dimensions of AI systems. The framework should include a thorough analysis of the potential risks associated with each AI system, including technical, operational, legal, ethical, and social risks. The framework should also include a plan for mitigating these risks and developing contingency plans to handle unexpected events.\\n\\nRecommendation 2: Establish Clear Lines of Communication\\n\\nEffective communication is crucial for managing AI risks. The company should establish clear lines of communication between different teams involved in AI development, deployment, and maintenance. This includes communication between developers, testers, security experts, legal counsel, and other stakeholders. Regular meetings and updates should be held to discuss AI risks and share information about new developments and threats.\\n\\nRecommendation 3: Foster a Culture of Trustworthiness\\n\\nTrustworthiness is a critical component of AI systems. The company should foster a culture of trustworthiness by promoting ethical behavior, transparency, and accountability. This includes developing guidelines for AI system design and development, conducting regular audits and reviews, and implementing appropriate governance structures.\\n\\nRecommendation 4: Invest in Training and Education\\n\\nAI systems are complex and require specialized knowledge and skills. The company should invest in training and education programs to ensure that employees have the necessary skills and knowledge to develop, deploy, and maintain AI systems. This includes training on AI ethics, security, and privacy, as well as technical skills related to AI development and deployment.\\n\\nRecommendation 5: Collaborate with Stakeholders\\n\\nStakeholders play a critical role in managing AI risks. The company should collaborate with stakeholders, including users, customers, regulators, and other interested parties, to understand their concerns and develop solutions that meet their needs. This includes engaging in open dialogue and soliciting feedback on AI systems and their impact on society.\\n\\nRecommendation 6: Continuously Monitor and Evaluate AI Systems\\n\\nAI systems are constantly evolving, and it is essential to continuously monitor and evaluate their performance and impact. The company should establish a process for monitoring and evaluating AI systems, including regular audits and reviews, to identify potential risks and opportunities for improvement. This includes developing metrics and KPIs to measure the effectiveness of AI systems and their impact on business outcomes.\\n\\nRecommendation 7: Develop Contingency Plans\\n\\nUnexpected events can occur in AI systems, and it is essential to have contingency plans in place to handle such events. The company should develop contingency plans for handling unexpected events, including data breaches, system failures, and other incidents. These plans should include procedures for responding to incidents, communicating with stakeholders, and restoring normal operations.\\n\\nRecommendation 8: Stay Up-to-Date with Regulatory Changes\\n\\nRegulatory changes can significantly impact AI systems, and it is essential to stay up-to-date with regulatory changes. The company should monitor regulatory changes and adjust its AI policies and practices accordingly. This includes staying informed about emerging regulations and best practices in AI ethics, security, and privacy.\\n\\nRecommendation 9: Foster a Culture of Continuous Improvement\\n\\nFinally, the company should foster a culture of continuous improvement by encouraging employees to identify areas for improvement and implementing changes to enhance the performance and impact of AI systems. This includes soliciting feedback from stakeholders, analyzing data and metrics, and implementing appropriate changes to improve AI systems.'" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "string" } }, "metadata": {}, "execution_count": 104 } ] }, { "cell_type": "markdown", "source": [ "### Measure" ], "metadata": { "id": "yBYgtWQsWc5r" } }, { "cell_type": "code", "source": [ "Measure = Data[Data['Dimension'] == 'Measure']\n", "measure_text = ' '.join(Govern['Reason'].tolist())\n", "question = \"A Company's AI Policy was compared to a Gold Standard AI Policy and the following incompotencies were found in the Company's AI Policy: \"+measure_text+\"Generate recomendations for improvemnt of the Company's AI Policy for the Measure Dimension of the NIST AI RMF\"\n", "measure_response = qa_chain({\"query\": question})" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "YG9eu4zA4UFW", "outputId": "4cde551c-8322-4338-ba1a-d953e2e0d6f1" }, "execution_count": 105, "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 `0.2` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n", " warnings.warn(\n", "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n" ] } ] }, { "cell_type": "code", "source": [ "size_of_groups=[Measure['Score'].sum(),Measure.shape[0]-Measure['Score'].sum()]\n", "\n", "colors = ['#0066FF', '#CCE0FF']\n", "\n", "# Create a pieplot\n", "plt.pie(size_of_groups, colors=colors)\n", "\n", "# add a circle at the center to transform it in a donut chart\n", "my_circle=plt.Circle( (0,0), 0.7, color='white')\n", "p=plt.gcf()\n", "p.gca().add_artist(my_circle)\n", "\n", "# Adding Title of chart\n", "plt.title('Measure (% covered)')\n", "\n", "# Displaying Chart\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 428 }, "id": "vhj5WJ2qV8g1", "outputId": "0d59a1c3-dc13-4078-ca0f-1dc364536b09" }, "execution_count": 106, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": 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\n" }, "metadata": {} } ] }, { "cell_type": "code", "source": [ "measure_response['result']" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 122 }, "id": "wwpx-a694hG-", "outputId": "23a2405f-18a9-480d-93a2-1775530d582e" }, "execution_count": 107, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "\"\\nRecommendation 1: Develop a Comprehensive Risk Management Framework\\n\\nTo improve the Company's AI Policy for the Measure Dimension of the NIST AI RMF, the first recommendation is to develop a comprehensive risk management framework. This framework should include the following elements:\\n\\n* Identification of potential risks associated with AI systems and processes\\n* Assessment of the likelihood and impact of each risk\\n* Prioritization of risks based on their severity and potential impact\\n* Development of mitigation strategies for each risk\\n* Implementation and monitoring of mitigation strategies\\n* Regular review and update of the risk management framework\\n\\nThis framework should be designed to ensure that all risks associated with AI systems and processes are identified, assessed, and managed effectively. It should also be flexible enough to adapt to changes in the AI landscape and new risks that may emerge.\\n\\nRecommendation 2: Establish Clear Lines of Communication\\n\\nEffective communication is essential for successful risk management. To improve the Company's AI Policy for the Measure Dimension of the NIST AI RMF, the second recommendation is to establish clear lines of communication. This includes:\\n\\n* Defining roles and responsibilities for risk management\\n* Establishing channels for reporting and escalating risks\\n* Providing training and education on risk management best practices\\n* Encouraging open and transparent communication about risks\\n\\nClear lines of communication will ensure that all stakeholders are aware of potential risks and can contribute to effective risk management.\\n\\nRecommendation 3: Conduct Regular Risk Assessments\\n\\nRegular risk assessments are critical for identifying and managing potential risks associated with AI systems and processes. To improve the Company's AI Policy for the Measure Dimension of the NIST AI RMF, the third recommendation is to conduct regular risk assessments. This includes:\\n\\n* Identifying potential risks associated with AI systems and processes\\n* Assessing the likelihood and impact of each risk\\n* Prioritizing risks based on their severity and potential impact\\n* Developing mitigation strategies for each risk\\n* Implementing and monitoring mitigation strategies\\n* Reviewing and updating the risk management framework as needed\\n\\nRegular risk assessments will ensure that the Company is proactively managing potential risks and minimizing their impact on the organization.\\n\\nRecommendation 4: Develop Contingency Plans\\n\\nContingency plans are essential for managing unexpected events or incidents that may arise from AI systems and processes. To improve the Company's AI Policy for the Measure Dimension of the NIST AI RMF, the fourth recommendation is to develop contingency plans. This includes:\\n\\n* Identifying potential scenarios that could lead to unexpected events or incidents\\n* Developing contingency plans for each scenario\\n* Testing and refining contingency plans as needed\\n* Ensuring that all stakeholders are familiar with contingency plans and know their roles and responsibilities in case of an incident\\n\\nContingency plans will ensure that the Company is prepared to respond effectively to unexpected events or incidents that may arise from AI systems and processes.\\n\\nRecommendation 5: Ensure Compliance with Regulatory Requirements\\n\\nCompliance with regulatory requirements is critical for managing risks associated with AI systems and processes. To improve the Company's AI Policy for the Measure Dimension of the NIST AI RMF, the fifth recommendation is to ensure compliance with regulatory requirements. This includes:\\n\\n* Identifying all relevant regulatory requirements\\n* Developing processes and procedures for complying with regulatory requirements\\n* Ensuring that all stakeholders are aware of regulatory requirements and their responsibilities for compliance\\n* Regularly reviewing and updating processes and procedures for compliance as needed\\n\\nEnsuring compliance with regulatory requirements will minimize the risk of legal or reputational damage resulting from non-compliance.\\n\\nRecommendation 6: Foster a Culture of Trustworthiness\\n\\nTrustworthiness is essential for building confidence in AI systems and processes. To improve the Company's AI Policy for the Measure Dimension of the NIST AI RMF, the sixth recommendation is to foster a culture of trustworthiness. This includes:\\n\\n* Defining trustworthiness as a core value for the organization\\n* Developing processes and procedures for ensuring trustworthiness in AI systems and processes\\n* Providing training and education on trustworthiness best practices\\n* Encouraging open and transparent communication about trustworthiness\\n\\nFostering a culture of trustworthiness will ensure that the Company is building AI systems and processes that are safe, reliable, and trustworthy.\\n\\nRecommendation 7: Continuously Improve the Risk Management\"" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "string" } }, "metadata": {}, "execution_count": 107 } ] }, { "cell_type": "markdown", "source": [ "### Report Generation" ], "metadata": { "id": "HbVcik2aW6Wv" } }, { "cell_type": "code", "source": [ "with open('output.txt', 'w') as f:\n", " f.write(\"Govern\")\n", " f.write('\\n')\n", " f.write('\\n')\n", " for index, row in Govern.iterrows():\n", " f.write('Question:')\n", " f.write('\\n')\n", " f.write(index)\n", " f.write('\\n')\n", " f.write('Ideal Policy Answer:')\n", " f.write('\\n')\n", " f.write(row[1])\n", " f.write('\\n')\n", " f.write('Company Policy Answer:')\n", " f.write('\\n')\n", " f.write(row[3])\n", " f.write('\\n')\n", " f.write('Comparison Score:')\n", " f.write('\\n')\n", " f.write(str(row[5]))\n", " f.write('\\n')\n", " f.write('--------------------------------------------------------------------------------------------------------------------------------------------------------')\n", " f.write('\\n')\n", " f.write('Ideal Policy Sources:')\n", " f.write(row[2])\n", " f.write('\\n')\n", " f.write('--------------------------------------------------------------------------------------------------------------------------------------------------------')\n", " f.write('\\n')\n", " f.write('Company Policy Sources:')\n", " f.write(row[4])\n", " f.write('\\n')\n", " f.write('========================================================================================================================================================')\n", " f.write('\\n')\n", " f.write('\\n')\n", "\n" ], "metadata": { "id": "FlelDPq8Wn2O" }, "execution_count": 75, "outputs": [] }, { "cell_type": "code", "source": [ "with open('output.txt', 'a') as f:\n", " f.write(\"Manage\")\n", " f.write('\\n')\n", " f.write('\\n')\n", " for index, row in Manage.iterrows():\n", " f.write('Question:')\n", " f.write('\\n')\n", " f.write(index)\n", " f.write('\\n')\n", " f.write('Ideal Policy Answer:')\n", " f.write('\\n')\n", " f.write(row[1])\n", " f.write('\\n')\n", " f.write('Company Policy Answer:')\n", " f.write('\\n')\n", " f.write(row[3])\n", " f.write('\\n')\n", " f.write('Comparison Score:')\n", " f.write('\\n')\n", " f.write(str(row[5]))\n", " f.write('\\n')\n", " f.write('--------------------------------------------------------------------------------------------------------------------------------------------------------')\n", " f.write('\\n')\n", " f.write('Ideal Policy Sources:')\n", " f.write(row[2])\n", " f.write('\\n')\n", " f.write('--------------------------------------------------------------------------------------------------------------------------------------------------------')\n", " f.write('\\n')\n", " f.write('Company Policy Sources:')\n", " f.write(row[4])\n", " f.write('\\n')\n", " f.write('========================================================================================================================================================')\n", " f.write('\\n')\n", " f.write('\\n')\n", "\n" ], "metadata": { "id": "5H8uTMWn2cXy" }, "execution_count": 76, "outputs": [] }, { "cell_type": "code", "source": [ "with open('output.txt', 'a') as f:\n", " f.write(\"Map\")\n", " f.write('\\n')\n", " f.write('\\n')\n", " for index, row in Map.iterrows():\n", " f.write('Question:')\n", " f.write('\\n')\n", " f.write(index)\n", " f.write('\\n')\n", " f.write('Ideal Policy Answer:')\n", " f.write('\\n')\n", " f.write(row[1])\n", " f.write('\\n')\n", " f.write('Company Policy Answer:')\n", " f.write('\\n')\n", " f.write(row[3])\n", " f.write('\\n')\n", " f.write('Comparison Score:')\n", " f.write('\\n')\n", " f.write(str(row[5]))\n", " f.write('\\n')\n", " f.write('--------------------------------------------------------------------------------------------------------------------------------------------------------')\n", " f.write('\\n')\n", " f.write('Ideal Policy Sources:')\n", " f.write(row[2])\n", " f.write('\\n')\n", " f.write('--------------------------------------------------------------------------------------------------------------------------------------------------------')\n", " f.write('\\n')\n", " f.write('Company Policy Sources:')\n", " f.write(row[4])\n", " f.write('\\n')\n", " f.write('========================================================================================================================================================')\n", " f.write('\\n')\n", " f.write('\\n')\n", "\n" ], "metadata": { "id": "uxGnbeYK44c8" }, "execution_count": 77, "outputs": [] }, { "cell_type": "code", "source": [ "with open('output.txt', 'a') as f:\n", " f.write(\"Measure\")\n", " f.write('\\n')\n", " f.write('\\n')\n", " for index, row in Measure.iterrows():\n", " f.write('Question:')\n", " f.write('\\n')\n", " f.write(index)\n", " f.write('\\n')\n", " f.write('Ideal Policy Answer:')\n", " f.write('\\n')\n", " f.write(row[1])\n", " f.write('\\n')\n", " f.write('Company Policy Answer:')\n", " f.write('\\n')\n", " f.write(row[3])\n", " f.write('\\n')\n", " f.write('Comparison Score:')\n", " f.write('\\n')\n", " f.write(str(row[5]))\n", " f.write('\\n')\n", " 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