aws-samples/sample-chatbot-for-bedrock-knowledge-base-and-multimodal-llms
Multimodal Chatbot with Amazon Bedrock Knowledge Bases Integration
This tool helps you quickly get answers from your own documents by asking questions in a chat interface, even if your question involves an image. You provide your documents (text and images) and ask questions, receiving relevant, AI-generated responses. It's ideal for analysts, researchers, or anyone needing to quickly extract information from a private collection of documents.
No commits in the last 6 months.
Use this if you need to build a chatbot that answers questions based on your specific documents and can understand questions that include images.
Not ideal if you're looking for a simple, off-the-shelf chatbot for general knowledge without integrating your own data.
Stars
32
Forks
6
Language
Python
License
MIT-0
Category
Last pushed
Mar 24, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/rag/aws-samples/sample-chatbot-for-bedrock-knowledge-base-and-multimodal-llms"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
aws-samples/generative-ai-use-cases
Application implementation with business use cases for safely utilizing generative AI in...
aws-samples/serverless-rag-demo
Amazon Bedrock Foundation models with Amazon Opensearch Serverless as a Vector DB
aws-samples/amazon-bedrock-rag
Fully managed RAG solution implemented using Knowledge Bases for Amazon Bedrock
IBM/granite-workshop
Source code for the IBM Granite AI Model Workshop
aws-samples/rag-with-amazon-bedrock-and-opensearch
Opinionated sample on how to build and deploy a RAG application with Amazon Bedrock and OpenSearch