Worked on the mudler/LocalAI repository to address a critical data integrity issue in the embeddings workflow. Focused on backend and API development using Go, the developer implemented end-to-end support for base64 encoding of embeddings, ensuring compatibility with the OpenAI Node.js SDK and preventing silent data corruption or vector dimension mismatches in downstream systems. The solution involved updating server, schema, and HTTP layers to honor the encoding_format parameter, introducing utilities for encoding and adapting JSON marshaling logic. This work improved interoperability with popular clients and vector stores, while also enhancing code maintainability and test coverage across the embeddings flow.