GitHub user alnzng added a comment to the discussion: Vector Store Integration for Flink Agents
Thank you for reviewing this design proposal @xintongsong! Yes, let's discuss implementation details (e.g., attribute/parameter naming) during the code review process. Regarding your comments: - **EmbeddingModel abstraction**: Excellent point! I agree we should have this abstraction, as there are multiple embedding service providers (e.g., OpenAI, Voyage, etc.) that offer different APIs for interaction. This would maintain consistency with our ChatModel approach and provide better extensibility. - **Built-in RAG Agent**: I think this is a great idea. We can provide a built-in RAG agent that offers a high-level abstraction for ease of use, where users only need to specify the core components (prompt, chat model, embedding model, and vector store). At the same time, we should maintain the flexibility for users to build custom RAG agents when they need more specialized behavior or want to implement their own logic. Let me update the doc by adding this `EmbeddingModel abstraction`. And let me create a issue for offerring a `Built-in RAG Agent`. GitHub link: https://github.com/apache/flink-agents/discussions/143#discussioncomment-14325338 ---- This is an automatically sent email for [email protected]. To unsubscribe, please send an email to: [email protected]
