[yaxuanm/qdrant] Hybrid Search fails on named-vector collections (dense/sparse)

Plugin

yaxuanm/qdrant v0.0.1

Problem

Hybrid Search fails on collections with named vectors (dense, sparse) created outside the plugin (e.g. custom embed scripts).
Error: Qdrant responded with HTTP 400: Wrong input: Not existing vector name error:

Root cause

1. Operation inference checks text before hybrid indicators → runs operation: "query" instead of hybrid_search
2. Plain query sends unnamed vector to /points/search — invalid when collection has only named vectors
3. Sparse vector is not generated from text in hybrid path (only dense embedding is created)

Reproduction

• Collection: named vectors dense (3072) + sparse
• Tool: Qdrant · Hybrid Search
• Inputs: text, using_dense: dense, using_sparse: sparse, fusion_method: rrf
• Embedding: text-embedding-3-large

Expected

hybrid_search → /points/query with prefetch using dense and sparse

Actual

query → /points/search with flat vector array (no vector name)

Fix verified locally (v0.0.2)

• Route hybrid before text→query
• Set operation: hybrid_search on hybrid tool YAML
• Generate sparse via fastembed (Qdrant/bm25)
• Add fastembed dependency

Environment

• Dify 1.14.2 (self-hosted)
• Qdrant Cloud
• Plugin: yaxuanm/qdrant 0.0.1 from Marketplace

Start by reproducing the named-vector case with the Qdrant Hybrid Search tool and trace operation inference from the text input. Inspect the hybrid tool YAML and the dense/sparse embedding path, including the fastembed dependency, then verify that hybrid_search uses /points/query with named dense and sparse vectors rather than /points/search with an unnamed vector.