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rag_aws_bedrock | ||
tests | ||
LICENSE | ||
main.py | ||
poetry.lock | ||
pyproject.toml | ||
rag_aws_bedrock.ipynb | ||
README.md |
RAG AWS Bedrock
AWS Bedrock is a managed serve that offers a set of foundation models.
Here we will use Anthropic Claude
for text generation and Amazon Titan
for text embedding.
We will use FAISS as our vectorstore.
(See this notebook for additional context on the RAG pipeline.)
Code here uses the boto3
library to connect with the Bedrock service. See this page for setting up and configuring boto3 to work with an AWS account.
FAISS
You need to install the faiss-cpu
package to work with the FAISS vector store.
pip install faiss-cpu
LLM and Embeddings
The code assumes that you are working with the default
AWS profile and us-east-1
region. If not, specify these environment variables to reflect the correct region and AWS profile.
AWS_DEFAULT_REGION
AWS_PROFILE