* fix(rerank): support DashScope nested request/response envelope
OpenAIRerankClient sent a flat request body ({"model", "query",
"documents"}) and parsed "results" at the top level of the response.
DashScope (qwen3-rerank) requires a nested envelope:
Request: {"model", "input": {"query", "documents"}, "parameters": ...}
Response: {"output": {"results": [...]}, "request_id", "usage"}
This caused DashScope rerank to silently fail — the response had no
top-level "results" key, so the client returned None.
Changes:
- Add _is_dashscope() to detect DashScope endpoints by host marker.
- Add _build_request_body() that produces the nested envelope for
DashScope and the flat body for standard OpenAI/Cohere services.
- Add _extract_results() that reads output.results for DashScope and
top-level results for standard services.
- Accept both "relevance_score" (singular, DashScope) and
"relevance_scores" (plural, some providers) in result items.
- Add 13 tests covering host detection, body construction, response
parsing, end-to-end mocked flows for both providers, plural key
handling, empty documents, and sparse results.
Fixes#3459
* fix(rerank): detect DashScope protocol by URL path, not hostname
Reviewer noted the previous hostname-based switch broke the documented
qwen3-rerank compatible-api endpoint (/compatible-api/v1/reranks), which
must use the flat OpenAI-style body and top-level results.
Switch to path-based detection: only /api/v1/services/rerank uses the
native nested input/output envelope; everything else (including the
DashScope compatible-api and generic OpenAI/Cohere gateways) keeps the
flat protocol. Rename _is_dashscope -> _uses_nested_envelope for clarity.
Add regression tests covering the compatible-api flat path and reconcile
the existing native-path fixtures to the nested envelope.
* docs(rerank): use qwen3-rerank for compatible-api example
The compatible-api/v1/reranks endpoint uses the flat OpenAI-compatible
protocol; qwen3-vl-rerank is a native-envelope model served at
/api/v1/services/rerank. Align the example model with the endpoint the
implementation selects by URL path.
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Co-authored-by: zhangyu.34 <zhangyu.34@bytedance.com>
LiteLLMRerankClient.rerank_batch wrapped each document as {"text": d} and read
result items via getattr(item, ...). That works for Cohere-style object results
but breaks Voyage through litellm: Voyage's rerank API rejects dict-wrapped
documents (400: 'documents' is not a valid string), and litellm returns Voyage
results as plain dicts, so getattr(item, "index") misses and rerank silently
falls back to a no-op.
- Pass documents as plain strings (litellm.rerank expects List[str]).
- Add _result_field() to read index/relevance_score from dict- or object-shaped
result items.
Verified end-to-end against voyage/rerank-2.5 (scores now applied). Adds
tests/unit/models/rerank/test_litellm_rerank.py covering the plain-string
documents contract and both dict- and object-shaped results.
Co-authored-by: Michael Tarleton <mtarleton@istation.com>
* feat(rerank): add configurable HTTP timeout for OpenAI-compatible client
OpenAIRerankClient hardcoded a 30s HTTP timeout, which is insufficient for
local LLM servers (e.g. llama.cpp on ROCm) that incur model cold-start
latency on the first request after inactivity, causing ReadTimeout errors.
Add a `timeout` field to RerankConfig (default 30.0, backwards-compatible)
and thread it through OpenAIRerankClient.__init__, from_config, and the
requests.post call in rerank_batch. The timeout can now be set per-environment
in ov.conf, e.g. "timeout": 120.
Closes#2732
* docs: document rerank timeout config
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Co-authored-by: qin-ctx <qinhaojie.exe@bytedance.com>
* feat(rerank): add extra_headers field to RerankConfig
Add support for extra_headers configuration in RerankConfig, following the same pattern as EmbeddingConfig and VLMConfig. This allows users to specify custom HTTP headers for OpenAI-compatible rerank providers.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: add copyright header to test file
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* feat(rerank): OpenAIRerankClient accepts and stores extra_headers
- Add extra_headers parameter to __init__ method
- Add extra_headers to from_config classmethod
- Default to empty dict when extra_headers is None
- Add comprehensive unit tests
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* feat(rerank): merge extra_headers into API requests
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* docs: add `extra_headers` param in doc
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Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* fix: add models observer info for embedder and rerank
* fix: make build deps
* fix: ov observer
* fix: ov observer
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Co-authored-by: openviking <openviking@example.com>
