diff --git a/gen-ai/Bedrock/04-idp-genai-advanced-rag.ipynb b/gen-ai/Bedrock/04-idp-genai-advanced-rag.ipynb
index 82f2982..2afdad3 100644
--- a/gen-ai/Bedrock/04-idp-genai-advanced-rag.ipynb
+++ b/gen-ai/Bedrock/04-idp-genai-advanced-rag.ipynb
@@ -125,7 +125,8 @@
"!pip install inflect\n",
"!pip install requests-aws4auth\n",
"!pip install opensearch-py\n",
- "!pip install anthropic"
+ "!pip install anthropic\n",
+ "!pip install openpyxl "
]
},
{
@@ -133,8 +134,9 @@
"id": "ff63129e-f3c9-41ea-bf48-3d2608a2531a",
"metadata": {},
"source": [
- "Restart the Kernel \\\n",
- "Click **kernel** on the top bar and **Restart Kernel**. Continue with the cells below."
+ "> ⚠️ Restart the Kernel \\\n",
+ "> \n",
+ "> Click **kernel** on the top bar and **Restart Kernel**. Continue with the cells below."
]
},
{
@@ -169,7 +171,6 @@
"from collections import OrderedDict\n",
"import boto3\n",
"import time\n",
- "import a_opensearch_utilities_\n",
"import sagemaker\n",
"import openpyxl\n",
"from openpyxl.cell import Cell\n",
@@ -184,7 +185,7 @@
")\n",
"from anthropic import Anthropic\n",
"client = Anthropic()\n",
- "bedrock_runtime = boto3.client(service_name='bedrock-runtime',region_name='us-east-1',config=config)"
+ "bedrock_runtime = boto3.client(service_name='bedrock-runtime',region_name='us-west-2',config=config)"
]
},
{
@@ -264,12 +265,7 @@
" {\n",
" 'Resource': ['index/' + vector_store_name + '/*'],\n",
" 'Permission': [\n",
- " 'aoss:CreateIndex',\n",
- " 'aoss:DeleteIndex',\n",
- " 'aoss:UpdateIndex',\n",
- " 'aoss:DescribeIndex',\n",
- " 'aoss:ReadDocument',\n",
- " 'aoss:WriteDocument'],\n",
+ " 'aoss:*'],\n",
" 'ResourceType': 'index'\n",
" }],\n",
" 'Principal': [identity],\n",
@@ -450,7 +446,7 @@
"outputs": [],
"source": [
"BUCKET= sagemaker.Session().default_bucket()\n",
- "extractor = Textractor(region_name=\"us-east-1\")\n",
+ "extractor = Textractor(region_name=\"us-west-2\")\n",
"file=\"amazon-2024-10k.pdf\"\n",
"doc_id= os.path.basename(file)\n",
"file_name, ext = os.path.splitext(file)\n",
@@ -1261,7 +1257,6 @@
},
{
"cell_type": "markdown",
- "id": "6b5f93e9-4813-4b4e-a040-87e2370ec64b",
"metadata": {},
"source": [
"\n",
@@ -1284,9 +1279,7 @@
"\n",
"**Note:** Certain chunks may exceed the threshold set for chunking in the previous cells due to the way tables are chunked by row and section paragraph sizes. This might result in a token limit exceed error for certain embedding models.\n",
"\n",
- "Ensure to replace the **domain_endpoint** variable with the Amazon OpenSearch Service domain (2.11 and higher) or Serverless collection you created in your account.\n",
- "\n",
- "If using Amazon Opensearch Serverless, change the `openserach_serverless` to True."
+ "Using **host** variable in **domain_endpoint** will ensure it takes your built OpenSearch Service domain/Serverless endpoint id. If not following the steps, please update the variable with yours domain/endpoint id."
]
},
{
@@ -1305,11 +1298,11 @@
"This script demonstrates indexing documents into an Amazon OpenSearch Serverless domain using AWS Identity and Access Management (IAM) for authentication.\n",
"\"\"\"\n",
"service = 'aoss'\n",
- "# replace wit your OpenSearch Service domain/Serverless endpoint\n",
- "domain_endpoint = host\n",
+ "# Using host will use your OpenSearch Service domain/Serverless endpoint id\n",
+ "domain_endpoint = host \n",
"\n",
"credentials = boto3.Session().get_credentials()\n",
- "awsauth = AWSV4SignerAuth(credentials, \"us-east-1\", service)\n",
+ "awsauth = AWSV4SignerAuth(credentials, \"us-west-2\", service)\n",
"os_ = OpenSearch(\n",
" hosts = [{'host': domain_endpoint, 'port': 443}],\n",
" http_auth = awsauth,\n",
@@ -1672,7 +1665,7 @@
"source": [
"from opensearchpy import Transport\n",
"credentials = boto3.Session().get_credentials()\n",
- "awsauth = AWS4Auth(credentials.access_key, credentials.secret_key, \"us-east-1\", service, session_token=credentials.token)\n",
+ "awsauth = AWS4Auth(credentials.access_key, credentials.secret_key, \"us-west-2\", service, session_token=credentials.token)\n",
"transport = Transport(\n",
" hosts = [{'host': domain_endpoint, 'port': 443}],\n",
" http_auth = awsauth,\n",
@@ -1960,20 +1953,12 @@
},
{
"cell_type": "code",
- "execution_count": 78,
+ "execution_count": null,
"id": "edc0c8ab-5cf5-4200-829f-08c576db2d45",
"metadata": {
"tags": []
},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- " Size of prompt token is 2938\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"csv_seperator=\"|\"\n",
"prompt_template=f\"\"\"You are a helpful, obedient and truthful financial assistance.\n",
@@ -1998,9 +1983,7 @@
"Question: {question}\n",
"if able to answer:\n",
" Include in your response before your answer: \n",
- " document or additional info tag(s) containing the relevant info\"\"\"\n",
- "\n",
- "print(f' Size of prompt token is {client.count_tokens(prompt_template)}')"
+ " document or additional info tag(s) containing the relevant info\"\"\"\n"
]
},
{