Small contribution to the project

IaC/AmazonBedRock/README.md

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+# AWS BedRock and LEX2 Agents
+
+# *BTW: I am actively looking for a DevOps/Clod Engineer job. Please considering me !*
+
+
+
+## Overview
+
+This project demonstrates the use of Terraform to create AWS BedRock and LEX2 agents and establish communication between them. 
+Also, Lambda function will be envoked everytime if the LLM will faile to get the answer from the existed Knowledge Base (located on S3)
+The goal is to automate the provisioning and configuration of these resources to facilitate seamless interaction.
+
+## Prerequisites
+Before you begin, ensure you have the following:
+- An AWS account with appropriate permissions.
+- Terraform installed on your local machine.
+- AWS CLI configured with your credentials.
+- Basic knowledge of Terraform and AWS services.
+- The S3 bucket with some materials which Knowledge Base will use as a source (RAG)
+
+
+## Project Structure
+The project directory is organized as follows:
+
+├── ai_lambda.tf
+├── genai-lambda-package.zip
+├── lex2-bot.tf
+├── lex2-intent.tf
+├── main.tf
+├── outputs.tf
+├── provider.tf
+├── README.md
+└── variables.tf

IaC/AmazonBedRock/ai_lambda.tf

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+locals {
+  ai_function_source = "./genai-lambda-package.zip"
+  src_bucket         = "demo-kb-usw2-lex-web-ui"
+}
+
+resource "aws_s3_object" "ai_function" {
+  bucket = local.src_bucket
+  key    = "${filemd5(local.ai_function_source)}.zip"
+  source = local.ai_function_source
+}
+
+module "ai_lambda_function" {
+  source = "terraform-aws-modules/lambda/aws"
+
+  function_name = "genai-demo-lambda"
+  description   = "lambda function to interact with AI"
+  handler       = "index.lambda_handler"
+  runtime       = "python3.12"
+  timeout       = "240"
+
+  publish = true
+  environment_variables = {
+    PROJECT     = "vpatoka-poc",
+    FallbackIntent = "genai-demo-lambda"
+  }
+
+  create_package      = false
+  s3_existing_package = {
+    bucket = local.src_bucket
+    key    = aws_s3_object.ai_function.id
+  }
+
+  attach_policy_statements = true
+  policy_statements = {
+    cloud_watch = {
+      effect    = "Allow",
+      actions   = ["cloudwatch:PutMetricData"],
+      resources = ["*"]
+    },
+    lambda = {
+      effect    = "Allow",
+      actions   = ["lambda:InvokeFunction"],
+      resources = ["*"]
+    },
+    ai = {
+      effect    = "Allow",
+      actions   = ["bedrock:InvokeModel"],
+      resources = ["arn:aws:bedrock:*::foundation-model/*"]
+    }
+  }
+}
+
+# Gives an external source Lex permission to access the Lambda function.
+# We need our bot to be able to invoke a lambda function when
+# we attempt to fulfill our intent.
+resource "aws_lambda_permission" "allow_lex" {
+  statement_id  = "AllowExecutionFromLex"
+  action        = "lambda:InvokeFunction"
+  function_name = "${module.ai_lambda_function.lambda_function_name}"
+  principal     = "lex.amazonaws.com"
+}

IaC/AmazonBedRock/lex2-bot.tf

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+data "aws_partition" "current" {}
+
+resource "aws_iam_role" "VladsBot" {
+  name = "vpatoka-ai-poc"
+  assume_role_policy = jsonencode({
+    Version = "2012-10-17"
+    Statement = [
+      {
+        Action = "sts:AssumeRole"
+        Effect = "Allow"
+        Sid    = ""
+        Principal = {
+          Service = "lexv2.amazonaws.com"
+        }
+      },
+    ]
+  })
+}
+
+resource "aws_iam_role_policy" "special_lex2_policy" {
+  name = "SpecialAmazoLex2Policy_${var.kb_name}"
+  role = aws_iam_role.VladsBot.name
+  policy = jsonencode({
+    Version = "2012-10-17"
+    Statement = [
+      {
+        Action   = [ "iam:AttachRolePolicy", "iam:PutRolePolicy", "iam:GetRolePolicy" ]
+        Effect   = "Allow"
+        Resource = "arn:${local.partition}:iam::*:role/aws-service-role/lexv2.amazonaws.com/AWSServiceRoleForLexBots*"
+      },
+      {
+        Action   = "iam:ListRoles"
+        Effect   = "Allow"
+        Resource = "*"
+      },
+      {
+        #Sid = "Permissions to invoke Lambda
+        Action   = "lambda:InvokeFunction"
+        Effect   = "Allow"
+        Resource = "*"
+      },
+      {
+        #Sid = "Permissions to invoke Amazon Bedrock foundation models"
+        Action   = "bedrock:InvokeModel"
+        Effect   = "Allow"
+        #Resource = data.aws_bedrock_foundation_model.kb.model_arn
+        Resource = "arn:${local.partition}:bedrock:${local.region}::foundation-model/${var.response_foundation_model}"
+      },
+      {
+        #Sid = "Permissions to access knowledge base in Amazon Bedrock"
+        Action   = "bedrock:Retrieve"
+        Effect   = "Allow"
+        Resource = "arn:${local.partition}:bedrock:*:${local.account_id}:knowledge-base/*"
+      }
+    ]
+  })
+}
+
+resource "aws_iam_role_policy_attachment" "VladsBot" {
+  role       = aws_iam_role.VladsBot.name
+  policy_arn = "arn:${data.aws_partition.current.partition}:iam::aws:policy/AmazonLexFullAccess"
+}
+
+resource "aws_lexv2models_bot" "VladsBot" {
+  name                        = "vpatoka-ai-poc"
+  idle_session_ttl_in_seconds = 300
+  role_arn                    = aws_iam_role.VladsBot.arn
+
+  data_privacy {
+    child_directed = false
+  }
+}
+
+resource "aws_lexv2models_bot_locale" "VladsBot" {
+  locale_id                        = "en_US"
+  bot_id                           = aws_lexv2models_bot.VladsBot.id
+  bot_version                      = "DRAFT"
+  n_lu_intent_confidence_threshold = 0.4
+
+  voice_settings {
+    voice_id = "Danielle"
+    engine   = "neural"
+  }
+}
+
+resource "aws_lexv2models_bot_version" "VladsBot" {
+  bot_id = aws_lexv2models_bot.VladsBot.id
+  locale_specification = {
+    (aws_lexv2models_bot_locale.VladsBot.locale_id) = {
+      source_bot_version = "DRAFT"
+    }
+  }
+}
+
+
+/* Alternative way to create LEX v2 Bot
+Another option is to use the AWS CLI in Terraform through local execution provisioners.
+While this method can work effectively, it requires the AWS CLI to be installed on the host executing Terraform, 
+which might introduce additional dependencies.
+*/
+
+/*
+resource "null_resource" "create-endpoint" {
+  provisioner "local-exec" {
+    command = " aws lexv2-models create-bot --bot-name "vpatoka-ai-poc" --role-arn <role> --data-privacy <value> --cli-input-json file://<file.json>"
+  }
+}
+
+*/

IaC/AmazonBedRock/lex2-intent.tf

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+# Generic Custom Intent needs to be presented
+resource "aws_lexv2models_intent" "Newintent" {
+  bot_id      = aws_lexv2models_bot.VladsBot.id
+  bot_version = aws_lexv2models_bot_locale.VladsBot.bot_version
+  name        = "Newintent"
+  locale_id   = aws_lexv2models_bot_locale.VladsBot.locale_id
+
+  #dialog_code_hook {
+  #  enabled = true
+  #}
+
+  sample_utterance {
+    utterance = "Hello"
+  }
+  sample_utterance {
+    utterance = "Howdy"
+  }
+  sample_utterance {
+    utterance = "Hi"
+  }
+  sample_utterance {
+    utterance = "Bonjour"
+  }
+}
+
+/*
+Amazon Lex V2 offers a built-in AMAZON.QnAIntent that you can add to your bot. 
+This intent harnesses generative AI capabilities from Amazon Bedrock by recognizing customer questions and
+searching for an answer from the following knowledge stores 
+(for example, Can you provide me details on the baggage limits for my international flight?). 
+This feature reduces the need to configure questions and answers using task-oriented dialogue within Amazon Lex V2 intents. 
+This intent also recognizes follow-up questions 
+(for example, What about domestic flight?) based on the conversation history and provides the answer accordingly.
+*/
+#resource "aws_lexv2models_intent" "QnAIntent" {
+#  bot_id      = aws_lexv2models_bot.VladsBot.id
+#  bot_version = aws_lexv2models_bot_locale.VladsBot.bot_version
+#  name        = "QnAIntent"
+#  locale_id   = aws_lexv2models_bot_locale.VladsBot.locale_id
+#
+#  parent_intent_signature = "AMAZON.QnAIntent"
+#
+#  QnAIntentConfiguration {
+#    dataSourceConfiguration = {
+#      bedrockKnowledgeStoreConfiguration = {
+#        "bedrockKnowledgeBaseArn" = "${aws_bedrockagent_knowledge_base.demo_kb.arn}"
+#      }
+#    }
+#  }
+#
+#}
+
+# Update Bot with tweaked intents and alias to use Lambda
+resource "null_resource" "VladsBot" {
+  depends_on = [aws_lexv2models_bot_version.VladsBot]
+
+  triggers = {
+    bot_id         = aws_lexv2models_bot.VladsBot.id
+    locale_id      = aws_lexv2models_bot_locale.VladsBot.locale_id
+    latest_version = aws_lexv2models_bot_version.VladsBot.bot_version
+    lambda_arn     = "${module.ai_lambda_function.lambda_function_arn}"
+
+    always_run = timestamp()
+  }
+
+  provisioner "local-exec" {
+    #command = "./bot_update.sh ${aws_lexv2models_bot.VladsBot.id} ${aws_lexv2models_bot_locale.VladsBot.locale_id} ${aws_lexv2models_bot_version.VladsBot.bot_version} '${module.ai_lambda_function.lambda_function_arn}'"
+    command = "./bot_update.sh ${aws_lexv2models_bot.VladsBot.id} ${aws_lexv2models_bot_locale.VladsBot.locale_id} 'DRAFT' '${module.ai_lambda_function.lambda_function_arn}' ${aws_bedrockagent_knowledge_base.demo_kb.arn}"
+  }
+}