adityamparikh commented on issue #64:
URL: https://github.com/apache/solr-mcp/issues/64#issuecomment-5971847309
Design inputs for whoever picks this up, checked on 2026-10-03:
**Fusion has to happen in the server.** Solr's JSON Combined Query DSL
(native RRF) is documented only in the 9.11-beta reference guide; the 10.0
guide doesn't have it, so no version in our supported range (8.11 to 10) offers
it. Spring AI 2.0.1's `spring-ai-rag` ships only `ConcatenationDocumentJoiner`,
with no RRF joiner. `hybrid-search` therefore needs its own RRF merge (`k =
60`, de-duplicated by `uniqueKey`, deterministic tie-break). Writing it for N
ranked lists, not just two, would allow multi-query fusion later without a
rewrite.
**The server can stay keyless.** `spring-ai-starter-model-transformers`
embeds in-process through ONNX (default `all-MiniLM-L6-v2`, 384 dimensions, no
API key), so in-server embeddings don't have to mean an OpenAI dependency.
Points for a short spike before building on it:
- whether ONNX Runtime and the DJL tokenizers work in the GraalVM native
images (unverified; the JVM image may end up being the only one with
embeddings);
- the model downloads from Hugging Face on first use, so bundle it in the
image or document `spring.ai.embedding.transformer.cache.directory` for
air-gapped installs;
- check the field's `vectorDimension` against the model's, with a clear
error when a collection was embedded by a different model.
**Separate inputs per leg.** Give `hybrid-search` a `keywordQuery` (BM25)
and a `vectorText` (kNN). An MCP client can then send a hypothetical answer
passage (HyDE) for the vector leg without BM25 matching that prose, and without
the server needing an LLM.
**Stopgap for operators who already run Solr's text-to-vector module.**
`{!knn_text_to_vector model=<m> f=<field> topK=10}<text>` already works through
`search`'s `q` pass-through. It needs the `llm` module (9.x) or
`language-models` module (10.x), which `-slim` images don't include, plus a
provider key configured on the Solr side. It is worth a line in the docs, but
it doesn't replace this issue.
**Upstream home.** spring-projects/spring-ai#4782 (Solr `VectorStore`) has
had no response since 2025-11-02, so porting `SolrVectorStore` here is still
the realistic path. Since that means Spring AI 2.0 APIs, this fits the `sb4` /
2.0 line better than `main`.
Related, and needing no embeddings: #240 (`find-similar`, More Like This)
and #241 (`list-fields`).
🤖 Generated with [Claude Code](https://claude.com/claude-code)
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