Merge pull request #514 from rprithvii/community-contributions-branch

Additon of new AWS bedrock usage notebook
This commit is contained in:
Ed Donner
2025-07-18 22:26:51 -04:00
committed by GitHub
2 changed files with 1196 additions and 0 deletions

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{
"cells": [
{
"cell_type": "code",
"execution_count": 4,
"id": "9138adfe-71b0-4db2-a08f-dd9e472fdd63",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import boto3"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "15d71dd6-cc03-485e-8a34-7a33ed5dee0e",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "1358921d-173b-4d5d-828c-b6c3726a5eb3",
"metadata": {},
"source": [
"#### Connect to bedrock models"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "b3827087-182f-48be-8b59-b2741f8ded44",
"metadata": {},
"outputs": [],
"source": [
"import json"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "94c11534-6847-4e4a-b8e4-8066e0cc6aca",
"metadata": {},
"outputs": [],
"source": [
"# Use the Conversation API to send a text message to Amazon Nova.\n",
"\n",
"import boto3\n",
"from botocore.exceptions import ClientError\n",
"\n",
"# Create a Bedrock Runtime client in the AWS Region you want to use.\n",
"client = boto3.client(\"bedrock-runtime\", region_name=\"us-east-1\")\n",
"\n",
"# Set the model ID, e.g., Amazon Nova Lite.\n",
"model_id = \"amazon.nova-lite-v1:0\""
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9a8ad65f-abaa-475c-892c-2e2b4e668f5d",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 7,
"id": "ac20bb00-e93f-4a95-a1de-dd2688bce591",
"metadata": {},
"outputs": [],
"source": [
"# Start a conversation with the user message.\n",
"user_message = \"\"\"\n",
"List the best parks to see in London with number of google ratings and value ie. 4.5 out of 5 etc. \n",
"Give number of ratings and give output in table form\n",
"\"\"\""
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "a29f0055-48c4-4f25-b33f-cde1eaf755c5",
"metadata": {},
"outputs": [],
"source": [
"conversation = [\n",
" {\n",
" \"role\": \"user\",\n",
" \"content\": [{\"text\": user_message}],\n",
" }\n",
"]"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0e68b2d5-4d43-4b80-8574-d3c847b33661",
"metadata": {},
"outputs": [],
"source": [
"try:\n",
" # Send the message to the model, using a basic inference configuration.\n",
" response = client.converse(\n",
" modelId=model_id,\n",
" messages=conversation,\n",
" inferenceConfig={\"maxTokens\": 512, \"temperature\": 0.5, \"topP\": 0.9},\n",
" )\n",
"\n",
" # Extract and print the response text.\n",
" response_text = response[\"output\"][\"message\"][\"content\"][0][\"text\"]\n",
" print(response_text)\n",
"\n",
"except (ClientError, Exception) as e:\n",
" print(f\"ERROR: Can't invoke '{model_id}'. Reason: {e}\")\n",
" exit(1)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8ed16ee7-3f09-4780-8dfc-d1c5f3cffdbe",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "7f8c7a18-0907-430d-bfe7-86ecb8933bfd",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "2183994b-cde5-45b0-b18b-37be3277d73b",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.13"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

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