https://github.com/couchbase-examples/rag-aws-bedrock-serverless
https://github.com/couchbase-examples/rag-aws-bedrock-serverless
Last synced: about 1 month ago
JSON representation
- Host: GitHub
- URL: https://github.com/couchbase-examples/rag-aws-bedrock-serverless
- Owner: couchbase-examples
- Created: 2024-07-01T08:30:40.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-08-28T15:13:07.000Z (over 1 year ago)
- Last Synced: 2024-08-29T16:34:52.420Z (over 1 year ago)
- Language: Python
- Size: 25.4 KB
- Stars: 0
- Watchers: 4
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# PDF Chat App with Couchbase, AWS Bedrock, and Serverless Architecture
This application demonstrates how to build a chat application that allows users to interact with a bot knowledgeable about uploaded PDF documents. It utilizes a Retrieval Augmented Generation (RAG) framework.
For a detailed, step-by-step tutorial, please refer to the [Couchbase Developer Portal](https://developer.couchbase.com/tutorial-bedrock-serverless-pdf-chat).
## Architecture
The application employs a serverless architecture on AWS, leveraging services like AWS Lambda, API Gateway, and Bedrock, with Couchbase for data storage and eventing.
## Prerequisites
Before you begin, ensure you have the following installed and configured:
* AWS CLI
* Node.js and npm (for AWS CDK)
* Python (version specified in `.python-version`)
* Docker
* An AWS account with appropriate permissions
* A Couchbase Capella cluster
## Installation
The Detailed tutorial is present [here](https://developer.couchbase.com/tutorial-bedrock-serverless-pdf-chat)
## Deploy AWS Backend
Deploy the entire AWS backend infrastructure using the AWS CDK:
```bash
cdk deploy --all
```
This command will provision all the necessary AWS resources.
## File Structure
* `src/`: Contains the application source code.
* `ui/`: Frontend Streamlit application.
* `cb_eventing/`: Couchbase Eventing function(s).
* `lambdas/`: AWS Lambda function code for ingestion and chat functionalities.
* `chatCDK/`: AWS CDK stack for the chat-related infrastructure.
* `ingestCDK/`: AWS CDK stack for the data ingestion infrastructure.
* `app.py`: Main AWS CDK application file that synthesizes the stacks.
* `cdk.json`: CDK configuration file.
## Usage
1. **Upload PDFs:** Use the provided mechanism to ingest PDF documents. The ingestion pipeline will process these documents, generate embeddings, and store them.
2. **Access the Chat UI:** Start the Streamlit frontend and navigate to the application URL.
3. **Interact with the Bot:** Ask questions related to the content of the uploaded PDFs!