Amazon Bedrock Knowledge Bases is the correct approach for this use case. Here's why:
- Knowledge Bases allow you to connect foundation models to your company's data sources, including S3 buckets
- They can ingest documents from S3 and create vector embeddings for retrieval-augmented generation (RAG)
- This enables the chatbot to combine general AI knowledge with specific information from the university's internal research papers
- The chatbot can then provide responses that are grounded in both the foundation model's general knowledge and the specific research content
Other options:
- Agents: Used for multi-step tasks and tool use, not specifically for connecting to knowledge sources
- Guardrails: Focus on safety and content filtering
- Model evaluation: Used for testing and comparing model performance
Knowledge Bases is specifically designed for the scenario described - augmenting foundation models with custom data sources like S3-stored documents.