spring-projects/spring-ai
Jan 2026 – Jan 2026
1 Month active
Languages Used
Java
Technical Skills
AI DevelopmentJavaSpring Framework
Yokior
PROFILE
Yokior
Developed a configurable dimensions parameter for the Ollama Embedding model within the spring-projects/spring-ai repository, enabling users to control embedding vector size for diverse application needs. This feature was implemented using Java and the Spring Framework, focusing on API design and seamless integration with existing embedding workflows. The approach allowed for optimized performance and resource usage by supporting variable dimensionalities, broadening the model’s applicability. No major bugs were addressed during this period, but the work included ongoing stability and code quality improvements. The development process emphasized disciplined version control and pull request-driven collaboration within the Java-based AI development environment.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
287
Activity Months1
Your Network
292 peopleShared Repositories
292
Bart VeenstraMember
seongm1nMember
Sun YuhanMember
wangleiMember
leevh0908Member
sebin1213Member
努力的小雨Member
MoGreeneMember
tongdaMember
Work History
January 2026
1 Commits • 1 Features
Jan 1, 2026January 2026 — Spring AI: Delivered a new configurable dimensions parameter for the Ollama Embedding model to control embedding vector size, enabling flexible embeddings across diverse use cases. Implemented in repository spring-projects/spring-ai; commit 4bd83ba2316368ca333cda5a6b06d8d27c92bd2f (feat(spring-ai-ollama): Add the dimensions parameter for the Ollama Embedding model (#2713)). No major bugs fixed this month; stability and internal quality improvements complemented the feature delivery. Business impact: expands applicability of the Ollama embedding workflow, enabling optimized performance and resource usage for varying dimensionalities. Technologies/skills demonstrated: API design and integration within the Java/Spring ecosystem, embedding/model integration, version control discipline, and PR-driven development.
1 Commits • 1 Features
Jan 1, 2026January 2026 — Spring AI: Delivered a new configurable dimensions parameter for the Ollama Embedding model to control embedding vector size, enabling flexible embeddings across diverse use cases. Implemented in repository spring-projects/spring-ai; commit 4bd83ba2316368ca333cda5a6b06d8d27c92bd2f (feat(spring-ai-ollama): Add the dimensions parameter for the Ollama Embedding model (#2713)). No major bugs fixed this month; stability and internal quality improvements complemented the feature delivery. Business impact: expands applicability of the Ollama embedding workflow, enabling optimized performance and resource usage for varying dimensionalities. Technologies/skills demonstrated: API design and integration within the Java/Spring ecosystem, embedding/model integration, version control discipline, and PR-driven development.
January 2026
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Quality Metrics
Correctness100.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage60.0%
Skills & Technologies
Programming Languages
Java
Technical Skills
AI DevelopmentJavaSpring Framework
Repositories Contributed To
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