Qdrant 1.17 - Relevance Feedback & Search Latency Improvements

Qdrant 1.17 introduces significant enhancements, including a new Relevance Feedback Query that improves search result quality by leveraging small amounts of model-generated feedback to refine search results without the need for expensive retraining or human labeling. This update also addresses search latency issues by introducing features like delayed fan-outs, which reduce tail latency by querying additional replicas if the initial response is slow, and an indexed-only mode to ensure low-latency search under high write loads. Operational observability is improved through a new cluster-wide telemetry API and segment optimization monitoring, providing better insights into cluster operations and optimization processes. The Web UI has been redesigned for a more intuitive point search experience, allowing for easier exploration and data discovery. Additionally, the release includes community contributions such as the ability to specify payload field indexes for HNSW index reflection and a new endpoint for listing user-defined shard keys. Qdrant 1.17 also supports weighted Reciprocal Rank Fusion to enhance query result ranking, audit logging for API operations, and streamlined upgrade processes for both Qdrant Cloud and self-hosted environments.