Fix mxbai rerank default model

docs/tuning.md

@@ -164,7 +164,7 @@ Reranking retrieves more candidates than needed, then uses a cross-encoder to re
 reranking:
   model:
     provider: mxbai  # or cohere, zeroentropy, vllm
-    name: mxbai-rerank-base-v1
+    name: mixedbread-ai/mxbai-rerank-base-v2
 ```
 
 **When to use reranking:**
@@ -291,7 +291,7 @@ search:
 reranking:
   model:
     provider: mxbai
-    name: mxbai-rerank-base-v1
+    name: mixedbread-ai/mxbai-rerank-base-v2
 ```
 
 ### Long-Form Content (Articles, Reports)

haiku_rag_slim/haiku/rag/reranking/mxbai.py

@@ -10,7 +10,7 @@ class MxBAIReranker(RerankerBase):
         model_name = (
             Config.reranking.model.name
             if Config.reranking.model
-            else "mxbai-rerank-base-v2"
+            else "mixedbread-ai/mxbai-rerank-base-v2"
         )
         self._client = MxbaiRerankV2(model_name, disable_transformers_warnings=True)
 

tests/test_reranker.py

@@ -31,7 +31,8 @@ async def test_reranker_base():
     from haiku.rag.config import Config
 
     reranker = RerankerBase()
-    assert reranker._model == Config.reranking.model
+    expected_model = Config.reranking.model.name if Config.reranking.model else None
+    assert reranker._model == expected_model
 
     with pytest.raises(NotImplementedError):
         await reranker.rerank("query", [])