visual-math-agent.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "92455acb-4b40-43c8-9d23-8e08bc8c7759",
   "metadata": {},
   "outputs": [],
   "source": [
    "agent_instruction = \"\"\"\n",
    "You are MathMaster Agent, designed to generate math problems in JSON format, with support for multiple-choice and Q&A type questions. You have the capability to include visual elements in both the question stem and choices.\n",
    "\n",
    "Core Capabilities:\n",
    "Generate JSON Format Questions:\n",
    "\n",
    "Fields:\n",
    "question type: Indicates whether the question is \"multiple-choice\" or \"Q&A\".\n",
    "question stem: The text of the question.\n",
    "question illustration: (Optional) A link to the visual illustration generated for the question.\n",
    "choices: (Only for multiple-choice) A list of choices provided for the question.\n",
    "choice illustration: (Optional) Links to illustrations for each choice.\n",
    "answer key: The correct answer, either as the correct choice label or the correct answer for Q&A.\n",
    "Create Visual Illustrations:\n",
    "\n",
    "Use functions like create_fraction_illustration, create_math_question_with_images, and random_number_line to generate visuals, and include the link to these visuals in the JSON output.\n",
    "If the visuals are not about fractions, simple math, or random number line, use create_svg function for the task.\n",
    "\n",
    "Follow the steps below to generate questions:\n",
    "\n",
    "1. Determine Question Type:\n",
    "- Identify whether the task is a \"multiple-choice\" or \"Q&A\" type question.\n",
    "\n",
    "2. Generate the Question Content:\n",
    "- Question Stem: Define the main text of the question.\n",
    "- Question Illustration (Optional): If the question requires a visual illustration, generate it using the appropriate function and include it in the question_illustration field.\n",
    "- Choices: For multiple-choice questions, generate distractors along with the correct answer.\n",
    "- Choice Illustrations (Optional): If each choice requires a visual, generate and link them in the choice_illustration field.\n",
    "- Answer Key: Determine the correct answer and set the answer_key field.\n",
    "\n",
    "3. Assemble the JSON Object:\n",
    "- Combine all elements into a JSON object with the specified structure.\n",
    "- Ensure that all required fields are populated correctly.\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e949ddcc-a23d-4bf8-9805-e9ef6f9963a9",
   "metadata": {},
   "source": [
    "## Prerequisites\n",
    "Before starting, let's update the botocore and boto3 packages to ensure we have the latest version"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "98ab75a5-01b8-4f57-8dd0-eff271bf14a6",
   "metadata": {
    "tags": []
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   "outputs": [],
   "source": [
    "!python3 -m pip install --upgrade -q botocore\n",
    "!python3 -m pip install --upgrade -q boto3\n",
    "!python3 -m pip install --upgrade -q awscli"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "45cfd291-9b47-40ef-a88e-692242302063",
   "metadata": {},
   "source": [
    "Let's now check the boto3 version to ensure the correct version has been installed. Your version should be greater than or equal to 1.34.90."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5f4f14f9-6eab-4c8d-ad41-9b4d916635ee",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import boto3\n",
    "import json\n",
    "import time\n",
    "import zipfile\n",
    "from io import BytesIO\n",
    "import uuid\n",
    "import pprint\n",
    "import logging\n",
    "print(boto3.__version__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "43c004fd-9907-48bf-a2a7-ea5296da086e",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# setting logger\n",
    "logging.basicConfig(format='[%(asctime)s] p%(process)s {%(filename)s:%(lineno)d} %(levelname)s - %(message)s', level=logging.INFO)\n",
    "logger = logging.getLogger(__name__)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47205742-43b4-461a-afa6-6bc52eb7ce20",
   "metadata": {},
   "source": [
    "Let's now create the boto3 clients for the required AWS services"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b2ea5446-bb56-4e83-b8e1-f73624f5da79",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# getting boto3 clients for required AWS services\n",
    "sts_client = boto3.client('sts')\n",
    "iam_client = boto3.client('iam')\n",
    "lambda_client = boto3.client('lambda')\n",
    "bedrock_agent_client = boto3.client('bedrock-agent')\n",
    "bedrock_agent_runtime_client = boto3.client('bedrock-agent-runtime')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aadaab5f-aa22-41a0-85b1-e283cf7c9014",
   "metadata": {},
   "source": [
    "Next we can set some configuration variables for the agent and for the lambda function being created"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9bd6323c-8642-47fa-b9ff-fa2047a3567c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "session = boto3.session.Session()\n",
    "region = session.region_name\n",
    "account_id = sts_client.get_caller_identity()[\"Account\"]\n",
    "region, account_id"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ede3008a-43b5-4a3f-b0ad-8dcf3109dffe",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Agent creation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f1ce9a77-edf6-4c65-82d7-09c56d964b3c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# configuration variables\n",
    "suffix = f\"{region}-{account_id}\"\n",
    "agent_name = \"math-master-agent\"\n",
    "agent_bedrock_allow_policy_name = f\"{agent_name}-ba-{suffix}\"\n",
    "agent_role_name = f'AmazonBedrockExecutionRoleForAgents_{agent_name}'\n",
    "agent_foundation_model = \"anthropic.claude-3-sonnet-20240229-v1:0\"\n",
    "agent_description = \"Agent for creating multimodal math questions\"\n",
    "agent_instruction = agent_instruction\n",
    "agent_alias_name = f\"{agent_name}-alias\"\n",
    "lambda_function_role = f'{agent_name}-lambda-role-{suffix}'\n",
    "\n",
    "\n",
    "visual_action_group_name = \"VisualGenerationActionGroup\"\n",
    "visual_action_group_description = '''\n",
    "You have access to three functions to generate visual elements for math questions.\n",
    "create_fraction_illustration, create_math_question_with_images, and random_number_line \n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1e5d70e0-6f7c-4dce-86a1-f8cfc6e170a1",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "visual_lambda_function_name = f'{agent_name}-math-visual-{suffix}'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "065a841f-962e-4c43-9be7-30be735445a4",
   "metadata": {},
   "source": [
    "### Create Agent\n",
    "We will now create the agent. To do so, we first need to create the agent policies that allow bedrock model invocation for a specific foundation model and the agent IAM role with the policy associated to it. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "937c9694-99e1-476f-af8f-de71d6f84132",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Create IAM policies for agent\n",
    "bedrock_agent_bedrock_allow_policy_statement = {\n",
    "    \"Version\": \"2012-10-17\",\n",
    "    \"Statement\": [\n",
    "        {\n",
    "            \"Sid\": \"AmazonBedrockAgentBedrockFoundationModelPolicy\",\n",
    "            \"Effect\": \"Allow\",\n",
    "            \"Action\": \"bedrock:InvokeModel\",\n",
    "            \"Resource\": [\n",
    "                f\"arn:aws:bedrock:{region}::foundation-model/{agent_foundation_model}\"\n",
    "            ]\n",
    "        }\n",
    "    ]\n",
    "}\n",
    "\n",
    "bedrock_policy_json = json.dumps(bedrock_agent_bedrock_allow_policy_statement)\n",
    "\n",
    "agent_bedrock_policy = iam_client.create_policy(\n",
    "    PolicyName=agent_bedrock_allow_policy_name,\n",
    "    PolicyDocument=bedrock_policy_json\n",
    ")\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0842ca23-2cbe-43ff-b40d-114969c50158",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Create IAM Role for the agent and attach IAM policies\n",
    "assume_role_policy_document = {\n",
    "    \"Version\": \"2012-10-17\",\n",
    "    \"Statement\": [{\n",
    "          \"Effect\": \"Allow\",\n",
    "          \"Principal\": {\n",
    "            \"Service\": \"bedrock.amazonaws.com\"\n",
    "          },\n",
    "          \"Action\": \"sts:AssumeRole\"\n",
    "    }]\n",
    "}\n",
    "\n",
    "assume_role_policy_document_json = json.dumps(assume_role_policy_document)\n",
    "agent_role = iam_client.create_role(\n",
    "    RoleName=agent_role_name,\n",
    "    AssumeRolePolicyDocument=assume_role_policy_document_json\n",
    ")\n",
    "\n",
    "# Pause to make sure role is created\n",
    "time.sleep(10)\n",
    "    \n",
    "iam_client.attach_role_policy(\n",
    "    RoleName=agent_role_name,\n",
    "    PolicyArn=agent_bedrock_policy['Policy']['Arn']\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "490c98a3-eab0-4b36-8a69-266c3ced84a6",
   "metadata": {},
   "source": [
    "Once the needed IAM role is created, we can use the Bedrock Agent client to create a new agent. To do so we use the `create_agent` function. It requires an agent name, underlying foundation model and instructions. You can also provide an agent description. Note that the agent created is not yet prepared. Later, we will prepare and use the agent."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3f2bcce8-4bf7-46d7-bd5c-e3de2488ddc6",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "response = bedrock_agent_client.create_agent(\n",
    "    agentName=agent_name,\n",
    "    agentResourceRoleArn=agent_role['Role']['Arn'],\n",
    "    description=agent_description,\n",
    "    idleSessionTTLInSeconds=1800,\n",
    "    foundationModel=agent_foundation_model,\n",
    "    instruction=agent_instruction,\n",
    ")\n",
    "response"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f86de21f-b1f9-45d1-a070-96020887b7df",
   "metadata": {},
   "source": [
    "Let's now store the agent id in a local variable to use it on subsequent steps."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cbb6952b-65d4-4380-9ba9-8ea996dc5c81",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# course info agent\n",
    "agent_id = response['agent']['agentId']\n",
    "agent_id"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dcd8cf98-1169-401c-802d-e3c87f52799e",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Creating Lambda function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "524e79e3-3ca4-4dfe-914b-63ccf8c6add8",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Create IAM Role for the Lambda function\n",
    "try:\n",
    "    assume_role_policy_document = {\n",
    "        \"Version\": \"2012-10-17\",\n",
    "        \"Statement\": [\n",
    "            {\n",
    "                \"Effect\": \"Allow\",\n",
    "                \"Action\": \"bedrock:InvokeModel\",\n",
    "                \"Principal\": {\n",
    "                    \"Service\": \"lambda.amazonaws.com\"\n",
    "                },\n",
    "                \"Action\": \"sts:AssumeRole\"\n",
    "            }\n",
    "        ]\n",
    "    }\n",
    "\n",
    "    assume_role_policy_document_json = json.dumps(assume_role_policy_document)\n",
    "\n",
    "    lambda_iam_role = iam_client.create_role(\n",
    "        RoleName=lambda_function_role,\n",
    "        AssumeRolePolicyDocument=assume_role_policy_document_json\n",
    "    )\n",
    "\n",
    "    # Pause to make sure role is created\n",
    "    time.sleep(10)\n",
    "except:\n",
    "    lambda_iam_role = iam_client.get_role(RoleName=lambda_function_role)\n",
    "\n",
    "iam_client.attach_role_policy(\n",
    "    RoleName=lambda_function_role,\n",
    "    PolicyArn='arn:aws:iam::aws:policy/service-role/AWSLambdaBasicExecutionRole'\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e96c6198-b8d1-4732-9e8e-3a910a19dd4d",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "iam_client.get_role(RoleName=lambda_function_role)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "493a7e82-8146-416d-bee3-a6731f52b8eb",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Package up the lambda function code (course info lambda)\n",
    "s = BytesIO()\n",
    "z = zipfile.ZipFile(s, 'w')\n",
    "z.write(\"tools/create_math_visuals.py\")\n",
    "z.write(\"tools/claude_3.5_sonnet_artifacts.txt\")\n",
    "z.write(\"tools/banana.png\")\n",
    "z.close()\n",
    "zip_content = s.getvalue()\n",
    "\n",
    "# Create Lambda Function\n",
    "lambda_function = lambda_client.create_function(\n",
    "    FunctionName=visual_lambda_function_name,\n",
    "    Runtime='python3.9',\n",
    "    Timeout=180,\n",
    "    Role=lambda_iam_role['Role']['Arn'],\n",
    "    Code={'ZipFile': zip_content},\n",
    "    Handler='tools/create_math_visuals.lambda_handler'\n",
    ")\n",
    "\n",
    "# # update Lambda function\n",
    "# lambda_function = lambda_client.update_function_code(\n",
    "#     FunctionName=visual_lambda_function_name,\n",
    "#     ZipFile= zip_content,\n",
    "# )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7a5f2d97-7fe9-4c94-92fb-fd90792a022f",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "lambda_iam_role['Role']['Arn']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "60837056-ede2-459f-970b-30e76dc5c880",
   "metadata": {},
   "source": [
    "### Create Agent Action Groups"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "69965053-63bf-47ff-9e1f-43cb912bfc6d",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "visual_action_group_functions = [\n",
    "    {\n",
    "        'name': 'create_math_question_with_images',\n",
    "        'description': 'generate addition and subtraction questions with illustrations',\n",
    "        'parameters': {\n",
    "            \"operation\": {\n",
    "                \"description\": \"operation type, accept 'add' or 'subtract'\",\n",
    "                \"required\": True,\n",
    "                \"type\": \"string\"\n",
    "            }\n",
    "        }\n",
    "    },\n",
    "    {\n",
    "        'name': 'create_svg',\n",
    "        'description': 'generate svg for a given task',\n",
    "        'parameters': {\n",
    "            \"task\": {\n",
    "                \"description\": \"description of the svg\",\n",
    "                \"required\": True,\n",
    "                \"type\": \"string\"\n",
    "            }\n",
    "        }\n",
    "    },\n",
    "    {\n",
    "        'name': 'create_fraction_illustration',\n",
    "        'description': 'generate a fraction for given numerator and denominator illurated in rectangle or in circle',\n",
    "        'parameters': {\n",
    "            \"shape\": {\n",
    "                \"description\": \"accept 'rectangle' or 'circle'\",\n",
    "                \"required\": True,\n",
    "                \"type\": \"string\"\n",
    "            },\n",
    "            \"numerator\": {\n",
    "                \"description\": \"accept number 1-9\",\n",
    "                \"required\": True,\n",
    "                \"type\": \"integer\"\n",
    "            },\n",
    "            \"denominator\": {\n",
    "                \"description\": \"accept number 2-10\",\n",
    "                \"required\": True,\n",
    "                \"type\": \"integer\"\n",
    "            }\n",
    "        }\n",
    "    },\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ba07d936-5ac0-4cea-a51d-a08e4479d3df",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "agent_action_group_response = bedrock_agent_client.create_agent_action_group(\n",
    "    agentId=agent_id,\n",
    "    agentVersion='DRAFT',\n",
    "    actionGroupExecutor={\n",
    "        'lambda': lambda_function['FunctionArn']\n",
    "    },\n",
    "    actionGroupName=visual_action_group_name,\n",
    "    functionSchema={\n",
    "        'functions': visual_action_group_functions\n",
    "    },\n",
    "    description=visual_action_group_description\n",
    ")\n",
    "\n",
    "# #  update agent group definition upon changes\n",
    "# agent_action_group_response = bedrock_agent_client.update_agent_action_group(\n",
    "#     agentId=agent_id,\n",
    "#     actionGroupId='DHIPV3Z9FF',\n",
    "#     agentVersion='DRAFT',\n",
    "#     actionGroupExecutor={\n",
    "#         'lambda': lambda_function['FunctionArn']\n",
    "#     },\n",
    "#     actionGroupName=visual_action_group_name,\n",
    "#     functionSchema={\n",
    "#         'functions': visual_action_group_functions\n",
    "#     },\n",
    "#     description=visual_action_group_description\n",
    "# )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8b03eb94-f48a-46e6-b36b-f68a750c4537",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "agent_action_group_response"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d3f2c16c-ed5c-4ad5-ab79-99f4684c6a31",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Create allow invoke permission on lambda\n",
    "response = lambda_client.add_permission(\n",
    "    FunctionName=visual_lambda_function_name,\n",
    "    StatementId='allow_bedrock',\n",
    "    Action='lambda:InvokeFunction',\n",
    "    Principal='bedrock.amazonaws.com',\n",
    "    SourceArn=f\"arn:aws:bedrock:{region}:{account_id}:agent/{agent_id}\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b9228d36-b4ef-434d-a432-bb6f488d6027",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "response"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "60468b0e-72e3-47c2-87e4-1683d59296d9",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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