diff --git a/Part 1/Create-Vector-DB.py b/Part 1/Create-Vector-DB.py
new file mode 100644
index 0000000000000000000000000000000000000000..4e63c5e1d1a89d0f4f6daa20883a2e0d52bea9c7
--- /dev/null
+++ b/Part 1/Create-Vector-DB.py
@@ -0,0 +1,155 @@
+## Source: https://docs.aws.amazon.com/opensearch-service/latest/developerguide/serverless-sdk.html
+import boto3
+import botocore
+import time
+
+
+client = boto3.client('opensearchserverless')
+service = 'aoss'
+Vector_store_name='test1'
+
+def createEncryptionPolicy(client):
+ """Creates an encryption policy that matches all collections beginning with test"""
+ try:
+ response = client.create_security_policy(
+ description='Encryption policy for test collections',
+ name='test-policy',
+ policy="""
+ {
+ \"Rules\":[
+ {
+ \"ResourceType\":\"collection\",
+ \"Resource\":[
+ \"collection\/test*\"
+ ]
+ }
+ ],
+ \"AWSOwnedKey\":true
+ }
+ """,
+ type='encryption'
+ )
+ print('\nEncryption policy created:')
+ print(response)
+ except botocore.exceptions.ClientError as error:
+ if error.response['Error']['Code'] == 'ConflictException':
+ print(
+ '[ConflictException] The policy name or rules conflict with an existing policy.')
+ else:
+ raise error
+
+
+def createNetworkPolicy(client):
+ """Creates a network policy that matches all collections beginning with test"""
+ try:
+ response = client.create_security_policy(
+ description='Network policy for Test collections',
+ name='test-policy',
+ policy="""
+ [{
+ \"Description\":\"Public access for Test collection\",
+ \"Rules\":[
+ {
+ \"ResourceType\":\"dashboard\",
+ \"Resource\":[\"collection\/test*\"]
+ },
+ {
+ \"ResourceType\":\"collection\",
+ \"Resource\":[\"collection\/test*\"]
+ }
+ ],
+ \"AllowFromPublic\":true
+ }]
+ """,
+ type='network'
+ )
+ print('\nNetwork policy created:')
+ print(response)
+ except botocore.exceptions.ClientError as error:
+ if error.response['Error']['Code'] == 'ConflictException':
+ print(
+ '[ConflictException] A network policy with this name already exists.')
+ else:
+ raise error
+
+
+def createAccessPolicy(client):
+ """Creates a data access policy that matches all collections beginning with test"""
+ try:
+ response = client.create_access_policy(
+ description='Data access policy for Test collections',
+ name='test-policy',
+ policy="""
+ [{
+ \"Rules\":[
+ {
+ \"Resource\":[
+ \"index\/test*\/*\"
+ ],
+ \"Permission\":[
+ \"aoss:CreateIndex\",
+ \"aoss:DeleteIndex\",
+ \"aoss:UpdateIndex\",
+ \"aoss:DescribeIndex\",
+ \"aoss:ReadDocument\",
+ \"aoss:WriteDocument\"
+ ],
+ \"ResourceType\": \"index\"
+ },
+ {
+ \"Resource\":[
+ \"collection\/test*\"
+ ],
+ \"Permission\":[
+ \"aoss:CreateCollectionItems\",
+ \"aoss:DeleteCollectionItems\",
+ \"aoss:UpdateCollectionItems\",
+ \"aoss:DescribeCollectionItems\"
+ ],
+ \"ResourceType\": \"collection\"
+ }
+ ],
+ \"Principal\":[
+ \"arn:aws:iam::768034348959:user/AbirChebbi\"
+ ]
+ }]
+ """,
+ type='data'
+ )
+ print('\nAccess policy created:')
+ print(response)
+ except botocore.exceptions.ClientError as error:
+ if error.response['Error']['Code'] == 'ConflictException':
+ print(
+ '[ConflictException] An access policy with this name already exists.')
+ else:
+ raise error
+
+
+
+def waitForCollectionCreation(client):
+ """Waits for the collection to become active"""
+ time.sleep(40)
+ response = client.batch_get_collection(
+ names=['test1'])
+ print('\nCollection successfully created:')
+ print(response["collectionDetails"])
+ # Extract the collection endpoint from the response
+ host = (response['collectionDetails'][0]['collectionEndpoint'])
+ final_host = host.replace("https://", "")
+ return final_host
+
+
+def main():
+
+ createEncryptionPolicy(client)
+ createNetworkPolicy(client)
+ createAccessPolicy(client)
+ collection = client.create_collection(name=Vector_store_name,type='VECTORSEARCH')
+ ENDPOINT= waitForCollectionCreation(client)
+
+ print("Collection created successfully:", collection)
+ print("Collection ENDPOINT:", ENDPOINT)
+
+if __name__== "__main__":
+ main()
\ No newline at end of file
diff --git a/Part 1/Delete-Vector-DB.py b/Part 1/Delete-Vector-DB.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Part 1/Delete-s3.py b/Part 1/Delete-s3.py
new file mode 100644
index 0000000000000000000000000000000000000000..7d07f21c483b427cc800d4888fbde66e2c373b2b
--- /dev/null
+++ b/Part 1/Delete-s3.py
@@ -0,0 +1,24 @@
+import boto3
+
+BUCKET_NAME = 'cloud-lecture-2023'
+
+S3_CLIENT = boto3.client('s3')
+S3_RESOURCE = boto3.resource('s3')
+
+# # # Delete Bucket
+
+# First, delete all objects in the Bucket
+bucket = S3_RESOURCE.Bucket(BUCKET_NAME)
+
+print("Deleting all objects in Bucket\n")
+bucket.objects.all().delete()
+
+
+print("Deleting Bucket")
+# Bucket Deletion
+response = S3_CLIENT.delete_bucket(
+ Bucket=BUCKET_NAME
+
+)
+
+print(response)
diff --git a/Part 1/create-S3-and-put-docs.py b/Part 1/create-S3-and-put-docs.py
new file mode 100644
index 0000000000000000000000000000000000000000..7587e0c415b746d955d4e0b76d39ddc4886d20a2
--- /dev/null
+++ b/Part 1/create-S3-and-put-docs.py
@@ -0,0 +1,35 @@
+import boto3
+import os
+
+LOCAL_DIR = "pdfs"
+BUCKET_NAME = 'cloud-lecture-2023'
+
+# Initiate S3 client
+s3_client = boto3.client('s3')
+
+# Create S3 Bucket
+print("Creating Bucket")
+response = s3_client.create_bucket(
+ Bucket=BUCKET_NAME,
+)
+print(response)
+print()
+
+# Function to write files to S3
+def write_files(directory, bucket):
+ for filename in os.listdir(directory):
+ if filename.endswith(".pdf"): # Check if the file is a PDF
+ file_path = os.path.join(directory, filename)
+ with open(file_path, 'rb') as file:
+ print(f"Uploading {filename} to bucket {bucket}...")
+ s3_client.put_object(
+ Body=file,
+ Bucket=bucket,
+ Key=filename
+ )
+ print(f"{filename} uploaded successfully.")
+
+# Upload PDF files to S3 bucket
+print("Writing Items to Bucket")
+write_files(LOCAL_DIR, BUCKET_NAME)
+
diff --git a/Part 1/main.py b/Part 1/main.py
index b318c014a7df50665a122fd3c6dd718577873f0d..f12dafd00a2b2862f5829481c4d21e8d8518654e 100644
--- a/Part 1/main.py
+++ b/Part 1/main.py
@@ -14,7 +14,7 @@ index_name = "cloud_lecture_test"
## S3_client
s3_client = boto3.client('s3')
## Bucket name where documents are stored
-BUCKET_NAME = "chatbotlab"
+BUCKET_NAME = "cloud-lecture-2023"
## Bedrock client
bedrock_client = boto3.client(service_name="bedrock-runtime")
@@ -25,7 +25,7 @@ credentials = boto3.Session().get_credentials()
awsauth = AWSV4SignerAuth(credentials, 'us-east-1', 'aoss')
## Vector DB endpoint
-host= 'd7gvxdj7jpz3h3bj0xq6.us-east-1.aoss.amazonaws.com'
+host= 'ispfynbvy6eov4efdsqd.us-east-1.aoss.amazonaws.com'
## Opensearch Client
OpenSearch_client = OpenSearch(
@@ -91,8 +91,12 @@ def split_text(pages, chunk_size, chunk_overlap, local_dir):
return chunks
## Generate embeddings and index them using Opensearch
+# def generate_embeddings():
-def generate_embeddings(bedrock_client, chunks,awsauth,index_name):
+# def store_embeddings():
+
+
+def generate_store_embeddings(bedrock_client, chunks,awsauth,index_name):
embeddings_model = BedrockEmbeddings(model_id="amazon.titan-embed-text-v1", client=bedrock_client)
docsearch = OpenSearchVectorSearch.from_documents(
chunks,
@@ -117,7 +121,7 @@ def main():
chunks=split_text(docs, 1000, 100, LOCAL_DIR)
print("Sample chunk:", chunks[0])
create_index(index_name)
- embeddings = generate_embeddings(bedrock_client, chunks,awsauth,index_name)
+ embeddings = generate_store_embeddings(bedrock_client, chunks,awsauth,index_name)
print("Embeddings processing completed", embeddings)