Frequently Asked Questions

How to Determine the Compatibility Between Spring AI Alibaba and Spring AI, Spring Boot Versions

Spring AI Alibaba uses a four-digit versioning system. The first three digits correspond to the main version of Spring AI, and the Spring AI Alibaba community continuously iterates on the fourth digit based on the main version.

Below is a partial version correspondence table, with new versions following this pattern:

Spring AI Alibaba	Spring AI	Spring Boot
1.0.0.2	1.0.0	3.4.5
1.0.0-M6.1	1.0.0-M6	3.4.2

What are the Differences Between Spring AI and Spring AI Alibaba?

Spring AI is positioned as the underlying framework for AI application development, providing atomic abstractions needed for AI development, including model adaptation, tool definition, vector database access, etc. Spring AI Alibaba is positioned as an AI agent development framework, offering a Graph framework based on graph algorithms, making it easier for developers to create workflows and multi-agent applications. To illustrate with an imperfect analogy, if Spring AI is the Langchain framework in the LangChain ecosystem, then Spring AI Alibaba is the Langraph framework.

In addition to the framework itself, Spring AI Alibaba is Alibaba Cloud’s enterprise-level best practice and comprehensive solution for AI agent development based on the Spring AI framework, deeply integrated with Alibaba’s open-source ecosystem and Alibaba Cloud platform services, including:

• Integration with BAI Dashscope model services, supporting mainstream model series such as Qwen and Deepseek
• Integration with BAI AgentScope intelligent agent application platform, providing low-code and high-code bidirectional conversion to enhance development efficiency
• Integration with BAI Xiyu ChatBI, offering an open-source framework and service for natural language to SQL automatic generation
• Integration with Alibaba Cloud products, including vector retrieval databases AnalyticDB, OpenSearch, information retrieval service IQS, etc.
• Integration with open-source Nacos, Higress ecosystems, providing MCP registration center, MCP intelligent routing, prompt management, model proxy, etc.
• Providing cutting-edge intelligent agent product implementations and comprehensive solutions, including JManus, DeepResearch, NL2SQL, etc.
• Providing a complete supporting ecosystem for AI application development, including local development tools, project build platforms, etc.

Is There a Comparison of Mainstream Java AI Frameworks

Below is a comparison of current mainstream Java AI frameworks.

Comparison Dimension	Spring AI Alibaba	Spring AI	LangChain4J
Spring Boot Integration	Native support	Native support	Community adaptation
Text Models	Mainstream models, extensible	Mainstream models, extensible	Mainstream models, extensible
Audio/Video, Multimodal, Vector Models	Supported	Supported	Supported
RAG	Modular RAG	Modular RAG	Modular RAG
Vector Databases	Mainstream vector databases Alibaba Cloud ADB, OpenSearch, etc.	Mainstream vector databases	Mainstream vector databases
MCP Support	Supported Nacos MCP Registry support	Supported	Supported
Function Calls	Supported (20+ official tool integrations)	Supported	Supported
Prompt Templates	Hard-coded, no declarative annotations	Hard-coded, no declarative annotations	Declarative annotations
Prompt Management	Nacos configuration center	None	None
Chat Memory	Optimized JDBC, Redis, Elasticsearch	JDBC, Neo4j, Cassandra	Multiple implementations adapted
Observability	Supported, can integrate with Alibaba Cloud ARMS	Supported	Partially supported
Workflow	Supported, compatible with Dify, BAI DSL	None	None
Multi-agent	Supported, official general agent implementation	None	None
Model Evaluation	Supported	Supported	Supported
Community Activity and Documentation Completeness	Official community, high activity	Official community, high activity	Community initiated by individuals
Development Efficiency Components	Rich, including debugging, code generation tools, etc.	None	None
Example Repositories	Rich, high activity	Fewer	Rich, high activity