Minor spelling, grammatical, and code fixes

01_Text_generation/00_text_generation_w_bedrock.ipynb

@@ -31,18 +31,18 @@
  "To demonstrate the text generation capability of Amazon Bedrock, we will explore the use of Boto3 client to communicate with Amazon Bedrock API. We will demonstrate different configurations available as well as how simple input can lead to desired outputs.\n",
  "\n",
  "#### Pattern\n",
- "We will simply provide the Amazon Bedrock API with an input consisting of a task, an instruction and an input for the model under the hood to generate an output without providing any additional example. The purpose here is to demonstrate how the powerful LLMs easily understand the task at hand and generate compelling outputs.\n",
+ "We will simply provide the Amazon Bedrock API with an input consisting of a task, an instruction and an input for the model under the hood to generate an output without providing any additional example. The purpose here is to demonstrate how LLMs easily understand the task at hand and generate compelling outputs.\n",
  "\n",
  "![](./images/bedrock.jpg)\n",
  "\n",
  "#### Use case\n",
  "To demonstrate the generation capability of models in Amazon Bedrock, let's take the use case of email generation.\n",
  "\n",
  "#### Persona\n",
- "You are Bob a Customer Service Manager at AnyCompany and some of your customers are not happy with the customer service and are providing negative feedbacks on the service provided by customer support engineers. Now, you would like to respond to those customers humbly aplogizing for the poor service and regain trust. You need the help of an LLM to generate a bulk of emails for you which are human friendly and personalized to the customer's sentiment from previous email correspondence.\n",
+ "You are Bob a Customer Service Manager at AnyCompany and some of your customers are not happy with the customer service and are providing negative feedbacks on the service provided by customer support engineers. Now, you would like to respond to those customers humbly apologizing for the poor service and regain their trust. You need the help of an LLM to generate a bulk of emails for you which are human friendly and personalized to the customer's sentiment from previous email correspondence.\n",
  "\n",
  "#### Implementation\n",
- "To fulfill this use case, in this notebook we will show how to generate an email with a thank you note based on the customer's previous email.We will use the Amazon Titan Text Large model using the Amazon Bedrock API with Boto3 client. "
+ "To fulfill this use case, in this notebook we will show how to generate an email with a thank-you note based on the customer's previous email. We will use the Amazon Titan Text Large model using the Amazon Bedrock API with Boto3 client. "
  ]
  },
  {
@@ -57,12 +57,10 @@
  },
  {
  "cell_type": "code",
- "execution_count": null,
  "id": "776fd083",
  "metadata": {
  "tags": []
  },
- "outputs": [],
  "source": [
  "import json\n",
  "import os\n",
@@ -72,7 +70,9 @@
  "import botocore\n",
  "\n",
  "boto3_bedrock = boto3.client('bedrock-runtime')"
- ]
+ ],
+ "outputs": [],
+ "execution_count": null
  },
  {
  "cell_type": "markdown",
@@ -86,19 +86,19 @@
  },
  {
  "cell_type": "code",
- "execution_count": null,
  "id": "45ee2bae-6415-4dba-af98-a19028305c98",
  "metadata": {
  "tags": []
  },
- "outputs": [],
  "source": [
  "# create the prompt\n",
  "prompt_data = \"\"\"\n",
  "Command: Write an email from Bob, Customer Service Manager, to the customer \"John Doe\" \n",
  "who provided negative feedback on the service provided by our customer support \n",
  "engineer\"\"\"\n"
- ]
+ ],
+ "outputs": [],
+ "execution_count": null
  },
  {
  "cell_type": "markdown",
@@ -112,12 +112,10 @@
  },
  {
  "cell_type": "code",
- "execution_count": null,
  "id": "8af670eb-ad02-40df-a19c-3ed835fac8d9",
  "metadata": {
  "tags": []
  },
- "outputs": [],
  "source": [
  "body = json.dumps({\n",
  " \"inputText\": prompt_data, \n",
@@ -128,7 +126,9 @@
  " \"topP\":0.9\n",
  " }\n",
  " }) "
- ]
+ ],
+ "outputs": [],
+ "execution_count": null
  },
  {
  "cell_type": "markdown",
@@ -141,7 +141,7 @@
  "- `contentType`: The content type of the output\n",
  "- `body`: A json string consisting of the prompt and the configurations\n",
  "\n",
- "Check [documentation](https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids-arns.html) for Available text generation model Ids"
+ "Check the [documentation](https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids-arns.html) for Available text generation model Ids"
  ]
  },
  {
@@ -164,12 +164,10 @@
  },
  {
  "cell_type": "code",
- "execution_count": null,
  "id": "ecaceef1-0f7f-4ae5-8007-ff7c25335251",
  "metadata": {
  "tags": []
  },
- "outputs": [],
  "source": [
  "modelId = 'amazon.titan-tg1-large' # change this to use a different version from the model provider\n",
  "accept = 'application/json'\n",
@@ -186,29 +184,31 @@
  " \n",
  " if error.response['Error']['Code'] == 'AccessDeniedException':\n",
  " print(f\"\\x1b[41m{error.response['Error']['Message']}\\\n",
- " \\nTo troubeshoot this issue please refer to the following resources.\\\n",
+ " \\nTo troubleshoot this issue please refer to the following resources.\\\n",
  " \\nhttps://docs.aws.amazon.com/IAM/latest/UserGuide/troubleshoot_access-denied.html\\\n",
  " \\nhttps://docs.aws.amazon.com/bedrock/latest/userguide/security-iam.html\\x1b[0m\\n\")\n",
  " \n",
  " else:\n",
  " raise error\n"
- ]
+ ],
+ "outputs": [],
+ "execution_count": null
  },
  {
  "cell_type": "code",
- "execution_count": null,
  "id": "3748383a-c140-407f-a7f6-8f140ad57680",
  "metadata": {
  "tags": []
  },
- "outputs": [],
  "source": [
  "# The relevant portion of the response begins after the first newline character\n",
- "# Below we print the response beginning after the first occurence of '\\n'.\n",
+ "# Below we print the response beginning after the first occurrence of '\\n'.\n",
  "\n",
  "email = outputText[outputText.index('\\n')+1:]\n",
  "print(email)\n"
- ]
+ ],
+ "outputs": [],
+ "execution_count": null
  },
  {
  "cell_type": "markdown",
@@ -223,12 +223,10 @@
  },
  {
  "cell_type": "code",
- "execution_count": null,
  "id": "ad073290",
  "metadata": {
  "tags": []
  },
- "outputs": [],
  "source": [
  "output = []\n",
  "try:\n",
@@ -251,13 +249,15 @@
  " \n",
  " if error.response['Error']['Code'] == 'AccessDeniedException':\n",
  " print(f\"\\x1b[41m{error.response['Error']['Message']}\\\n",
- " \\nTo troubeshoot this issue please refer to the following resources.\\\n",
+ " \\nTo troubleshoot this issue please refer to the following resources.\\\n",
  " \\nhttps://docs.aws.amazon.com/IAM/latest/UserGuide/troubleshoot_access-denied.html\\\n",
  " \\nhttps://docs.aws.amazon.com/bedrock/latest/userguide/security-iam.html\\x1b[0m\\n\")\n",
  " \n",
  " else:\n",
  " raise error"
- ]
+ ],
+ "outputs": [],
+ "execution_count": null
  },
  {
  "cell_type": "markdown",
@@ -286,11 +286,11 @@
  },
  {
  "cell_type": "code",
- "execution_count": null,
  "id": "9cdf9261-1002-4da7-9124-943f72b43486",
  "metadata": {},
+ "source": [],
  "outputs": [],
- "source": []
+ "execution_count": null
  }
  ],
  "metadata": {
@@ -871,9 +871,9 @@
  ],
  "instance_type": "ml.t3.medium",
  "kernelspec": {
- "display_name": "Python 3 (Data Science 3.0)",
+ "display_name": "Python 3 (ipykernel)",
  "language": "python",
- "name": "python3__SAGEMAKER_INTERNAL__arn:aws:sagemaker:us-east-1:081325390199:image/sagemaker-data-science-310-v1"
+ "name": "python3"
  },
  "language_info": {
  "codemirror_mode": {