[Bug]: The error message is not user friendly when specify invalid search parameters

[binbinlv]

Is there an existing issue for this?

• I have searched the existing issues

Environment

- Milvus version: milvus-master latest
- Deployment mode(standalone or cluster):both
- MQ type(rocksmq, pulsar or kafka):    all
- SDK version(e.g. pymilvus v2.0.0rc2): pymilvus latest
- OS(Ubuntu or CentOS): 
- CPU/Memory: 
- GPU: 
- Others:

Current Behavior

The error is not user friendly when specify invalid search parameters

(code=65535, message=fail to search on QueryNode 6: worker(6) query failed: Operator::GetOutput failed for [Operator:, plan node id: 1351] :  => failed to search: config={{"k":10,"metric_type":"L2","refine_k":"invalid","span_id":"543a36b8101dc3ec","trace_flags":0,"trace_id":"493e6082634c3999833e6fbcf0abd5ae"}} invalid value in json: stof at /workspace/source/internal/core/src/index/VectorMemIndex.cpp:411

Expected Behavior

The error message is too code style, not user friendly words

Steps To Reproduce

    @pytest.mark.tags(CaseLabel.L1)
    @pytest.mark.parametrize("index", ct.all_index_types[7:11])
    @pytest.mark.parametrize("refine_type", ["SQ6", "SQ8", "FP16", "BF16", "FP32", "FLAT"])
    def test_search_after_new_hnsw_index_with_invalid_refine_k(self, index, refine_type):
        """
        target: test search new HNSW index with refine
        method: search new HNSW index with refine
        expected: searched successfully
        """
        if index == ct.HNSW_FLAT:
            pytest.skip("HNSW_FLAT index not support refine")
        # 1. initialize with data
        dim = 64
        auto_id = True
        enable_dynamic_field = True
        collection_w, _vectors, _, insert_ids, time_stamp = self.init_collection_general(prefix, True, 3000,
                                                                                         partition_num=1,
                                                                                         auto_id=auto_id,
                                                                                         dim=dim, is_index=False,
                                                                                         enable_dynamic_field=enable_dynamic_field)[0:5]
        # 2. get vectors that inserted into collection
        original_vectors = []
        if enable_dynamic_field:
            for vector in _vectors[0]:
                vector = vector[ct.default_float_vec_field_name]
                original_vectors.append(vector)
        else:
            for _vector in _vectors:
                vectors_tmp = np.array(_vector).tolist()
                vectors_single = [vectors_tmp[i][-1] for i in range(2500)]
                original_vectors.append(vectors_single)
        log.info(len(original_vectors))
        # 3. create different index
        params = cf.get_index_params_params(index)
        if params.get("m"):
            if (dim % params["m"]) != 0:
                params["m"] = dim // 4
        if params.get("PQM"):
            if (dim % params["PQM"]) != 0:
                params["PQM"] = dim // 4
        if index.startswith("FAISS_"):
            params["refine_type"] = refine_type
        log.info("test_search_after_new_hnsw_index_with_invalid_refine_k: Creating index-%s" % index)
        default_index = {"index_type": index, "params": params, "metric_type": "L2"}
        collection_w.create_index("float_vector", default_index)
        log.info("test_search_after_new_hnsw_index_with_invalid_refine_k: Created index-%s" % index)
        collection_w.load()
        # 4. search
        search_params = cf.gen_search_param(index, "L2")
        vectors = [[random.random() for _ in range(dim)] for _ in range(default_nq)]
        for search_param in search_params:
            limit = default_limit
            if index == "HNSW":
                limit = search_param["params"]["ef"]
                if limit > max_limit:
                    limit = default_nb
            if index == "DISKANN":
                limit = search_param["params"]["search_list"]
            if index.startswith("FAISS_"):
                search_param["params"]["refine_k"] = "invalid"
            log.info("Searching with search params: {}".format(search_param))
            collection_w.search(vectors[:default_nq], default_search_field,
                                search_param, limit,
                                default_search_exp)

Milvus Log

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Anything else?

No response

[binbinlv]

/unassign @yanliang567

[binbinlv]

related with #37543