## Summary
- Replaces the `"no such method"` stub on `XinferenceModel.Embed`
(`internal/entity/models/xinference.go`) with a real implementation
against Xinference's OpenAI-compatible `/v1/embeddings` endpoint.
- Adds the `"embedding": "v1/embeddings"` URL suffix to
`conf/models/xinference.json`.
- Mirrors the Python `XinferenceEmbed` class in
`rag/llm/embedding_model.py:407` for payload shape (OpenAI-compatible
`model + input` → `data[*].index + data[*].embedding`) and tolerates the
same no-auth default Xinference deployments use. Authorization is only
sent when a non-empty API key is configured, via the existing
`setXinferenceAuth` helper.
- Reuses the existing `normalizeXinferenceBaseURL` + `baseURLForRegion`
helpers so both `http://127.0.0.1:9997` and `http://127.0.0.1:9997/v1`
resolve to the same `/v1/embeddings` target without doubled `/v1`.
- Validates response indices — duplicate, missing, or out-of-range
`data[*].index` values fail with a clear error rather than silently
producing misaligned vectors.
- Returns `[]EmbeddingData` in original input order (placed by `Index`)
so downstream callers can index positionally without re-sorting.
- Forwards `EmbeddingConfig.Dimension` as `dimensions` when `> 0`,
matching the OpenAI cluster pattern.
Closes#14810
Co-authored-by: Jin Hai <haijin.chn@gmail.com>
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