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jewoodev/README.md

I'm a backend engineer working with Java / Kotlin / Spring Boot and open-source contributor on spring-projects/spring-ai, currently exploring schema generation, transport-layer plumbing, and provider documentation consistency.


🌱 Open Source Contributions

An Application Framework for AI Engineering

#6035 — Fix recursive tool input schema by hoisting $defs to root status

  • Problem: Spring AI inlined parameter schemas under properties.<param>, but their generated $refs still pointed to root-level $defs. For recursive parameter types, this produced an unresolvable $ref in the tool input schema.
  • Fix: Hoist each parameter schema's $defs up to the wrapper schema root before inlining. Reuse structurally equal definitions, rename simple-name collisions, and rewrite peer $refs inside the hoisted schema.
  • Scope: Applied symmetrically to both JsonSchemaGenerator (spring-ai-model) and McpJsonSchemaGenerator (mcp/mcp-annotations).
  • Tests: Added regression coverage for transitive recursive parameter schemas, duplicate equal definitions, and colliding simple-name definitions with ref rewrites.

#6093 — Complete documentation update for OpenAI SDK base URL new behavior status milestone

Follow-up to #6036, completing the corrections started in commit 192eb5c.

  • Problem: After the openai-java SDK migration, OpenAI-compatible base URLs and several *-path properties were inconsistent across 8 documentation files (DMR, Ollama, Groq, Mistral AI, Embeddings, Speech, Transcriptions, Moderation). Some still missed /v1; some still documented properties that had been dropped from the SDK.
  • Fix: Aligned all OpenAI-compatible endpoints to include /v1 (e.g. http://localhost:12434/engines/v1, https://api.groq.com/openai/v1), removed table rows and sections for properties dropped by the SDK migration, and verified AsciiDoc structure stayed intact.
  • Outcome: Merged into milestone 2.0.0-M7 (d7f3c6c).

Pinned Loading

  1. spring-ai spring-ai Public

    Forked from spring-projects/spring-ai

    An Application Framework for AI Engineering

    Java 1

  2. spring-data-jpa spring-data-jpa Public

    Forked from spring-projects/spring-data-jpa

    Simplifies the development of creating a JPA-based data access layer.

    Java

  3. micrometer micrometer Public

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    An application observability facade for the most popular observability tools. Think SLF4J, but for observability.

    Java

  4. koog koog Public

    Forked from JetBrains/koog

    Koog is a JVM (Java and Kotlin) framework for building predictable, fault-tolerant and enterprise-ready AI agents across all platforms – from backend services to Android and iOS, JVM, and even in-b…

    Kotlin