files renamed and readme updated

Part 2/config.ini

-[aws]
-aws_access_key_id = 
-aws_secret_access_key = 
-region = 
-
-[opensearch]
-endpoint = 
-index_name = 
-
-

Part 1/main.py → Part1/vectorise-store.py

 import boto3
 import os
-#from tqdm.auto import tqdm
 from langchain_community.document_loaders import PyPDFDirectoryLoader
 from langchain.text_splitter import RecursiveCharacterTextSplitter
 from langchain_community.embeddings import BedrockEmbeddings
 from opensearchpy import OpenSearch, RequestsHttpConnection, AWSV4SignerAuth
 from langchain_community.vectorstores import OpenSearchVectorSearch
-import uuid
-import json
 import argparse
 
 
@@ -139,18 +136,19 @@ def main(bucket_name, endpoint,index_name, local_path):
     download_documents(bucket_name,local_path)
     loader= PyPDFDirectoryLoader(local_path)
     docs = loader.load()
-    print(docs[1])
+    print('Start chunking')
     chunks = split_text(docs, 1000, 100)
     print(chunks[1])
     create_index(OpenSearch_client,index_name)
+    print('Start vectorising')
     embeddings= generate_embeddings(bedrock_client, chunks)
     print(embeddings[1])
     texts = [chunk.page_content for chunk in chunks]
      # Prepare metadata for each chunk
     meta_data = [{'source': chunk.metadata['source'], 'page': chunk.metadata['page'] + 1} for chunk in chunks]
-    print(embeddings[1])
-    print(meta_data[1])
+    print('Start storing')
     store_embeddings(embeddings, texts, meta_data ,endpoint, awsauth,index_name)
+    print('End storing')
 
 
    

Part2/config.ini

+[aws]
+aws_access_key_id = AKIAVEKYIBTQKSG2R342
+aws_secret_access_key = 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
+region = us-east-1
+
+[opensearch]
+endpoint = ku7nut9wcogpz1nw15j0.us-east-1.aoss.amazonaws.com
+index_name = cloud-lecture
+
+

Part 2/create_instance.py → Part2/create_instance.py

@@ -16,12 +16,12 @@ ec2 = boto3.resource('ec2')
 
 # User code that's executed when the instance starts
 script = f"""#!/bin/bash
-cat <<EOT > /home/ubuntu/chatbot-lab/Part\ 2/config.ini
+cat <<EOT > /home/ubuntu/chatbot-lab/Part2/config.ini
 {config_content}
 EOT
 source /home/ubuntu/chatbotlab/bin/activate
 ## Run the apllication 
-cd /home/ubuntu/chatbot-lab/Part\ 2
+cd /home/ubuntu/chatbot-lab/Part2
 streamlit run main.py 
 """
 
@@ -29,7 +29,7 @@ encoded_script = base64.b64encode(script.encode()).decode('utf-8')
 
 # Create a new EC2 instance
 instance = ec2.create_instances(
-    ImageId='ami-03a1012f7ddc87219',
+    ImageId='ami-05747e7a13dac9d14',
     MinCount=1,
     MaxCount=1,
     InstanceType='t2.micro',
@@ -37,7 +37,8 @@ instance = ec2.create_instances(
     SecurityGroupIds=['sg-06f3ca7153db92958'],
     UserData=encoded_script
 )
-    
 print("Instance created with ID:", instance[0].id)
+   
+