Release date 2026/09/15
Fixed an issue where a chunk lookup against an Amazon MemoryDB vector store failed with unexpected search response: no value found in result set. The MemoryDB driver now reads the FT.SEARCH fields by name instead of by position, treats the vector distance as optional, and requests as many rows as fetch_chunks_count asks for.
Release date 2026/09/16
Fixed an issue where a chunk lookup against an Amazon MemoryDB vector store failed with unexpected search response: no value found in result set. The MemoryDB driver now reads the FT.SEARCH fields by name instead of by position, treats the vector distance as optional, and requests as many rows as fetch_chunks_count asks for.
Release date 2026/09/17
Fixed an issue where a chunk lookup against an Amazon MemoryDB vector store failed with unexpected search response: no value found in result set. The MemoryDB driver now reads the FT.SEARCH fields by name instead of by position, treats the vector distance as optional, and requests as many rows as fetch_chunks_count asks for.
Release date 2025/12/18
Added metadata filtering and ACL (Access Control List) capabilities to the RAG plugin. This feature enables fine-grained control over document retrieval based on metadata attributes and user permissions, supporting both pgvector and Redis vector database backends.
Release date 2025/07/16
Fixed an issue where the llm license migration could fail if the license counter contained more than one week of data.
Release date 2025/07/03
Blocked plugins to execute retry logic. Also improve testing functions
Fixed an issue where ‘tools’ and ‘RAG’ decoration did not work for Ollama (llama2) provider.
Fixed an issue where some of ai metrics was missed in analytics
If any AI Gateway plugin has been enabled in a self-managed Kong Gateway deployment for more than a week, upgrades from 3.10 versions to 3.11.0.0 will fail due to a license migration issue. This does not affect Konnect deployments.
A fix will be provided in 3.11.0.1.
See breaking changes in 3.11 for a temporary workaround.
Release date 2025/08/07
Fixed an issue where the Gemini provider could not use Anthropic ‘rawPredict’ endpoint models hosted in Vertex.
Release date 2025/03/27
Added a new plugin which allows automatically injecting documents to simplify building RAG pipelines.
Added the huggingface, azure, vertex, and bedrock providers to embeddings. They can be used by the ai-proxy-advanced, ai-semantic-cache, ai-semantic-prompt-guard, and ai-rag-injector plugins.
Allow authentication to Bedrock services with assume roles in AWS.
Fixed an issue where AI upstream URL trailing would be empty.