Can this Spring AI compete official Typescript AI SDKs?

[cyberluke]

Hi, honestly I think this is more like tech preview v0.2.

Do you have any roadmap?

Issues:

• no support for Anthropic and Google cache - you cannot make any serious Chat app without this because you keep sending whole context to AI API and it gets expensive
• RAG does not have ReRank support, only Embeddings support (you need to support custom AI model for ReRank - it is quite basic thing for good quality RAG and you cannot have good Knowledge Base RAG support, you can right now only make simple single document RAG)
• You should use Neo4J graph database for memory storage, not Redis! Look at mem0 python implementation how it is done.
• in DOCS for Vector storage, you should have table for maximum vector size - for example PgVector does not support Large v3 OpenAI embedding models due to hardcoded vector size of 2000
• instead of per provider implementation, you should have ONE UNIFIED API like AI SDK by Vercel - you missed the important advantage Spring AI could give

[cyberluke]

Why each class have its own cache manager while Spring ecosystem does have cache support already? Why reinvent the wheel? Why not global cache service?

[cyberluke]

https://github.com/spring-projects/spring-ai/blob/main/spring-ai-model/src/main/java/org/springframework/ai/chat/memory/MessageWindowChatMemory.java

-- messages should not get evicted, the industry standard is to use AI API to create summary of old messages after pre-defined number of messages, for example 10 messages

Then you can have several options:

• rolling window (like circular buffer)
• keep start and end of context and summarize/truncate the middle
• summarize everything after N messages
• use Anthropic or Google cache control to move context messages to their server cache (default TTL is 5 minutes) to save money and have long-term memory conversation suitable for chat apps - this gives you unlimited messages feature with no limit

There are core concepts for AI SDKs that everyone have, but here they are not present.

[cyberluke]

cannot have multiple vector store beans in classpath?

The bean 'vectorStore', defined in class path resource [org/springframework/ai/vectorstore/qdrant/autoconfigure/QdrantVectorStoreAutoConfiguration.class], could not be registered. A bean with that name has already been defined in class path resource [org/springframework/ai/vectorstore/pgvector/autoconfigure/PgVectorStoreAutoConfiguration.class] and overriding is disabled.

[hbsjz-swl]

When the first GA version of springai was officially released, the frameworks you mentioned, such as mem0`, had not yet entered the officially available stage, and rerank was a concept that did not exist in the current version. Developers could only expand or rewrite the API of the similarity retrieval part by themselves. The technology iteration in the AI ​​field is too fast, and the framework cannot fully cover the latest technology stack. I look forward to springAI becoming more and more perfect!