chore: import upstream snapshot with attribution

examples/evaluation/bright/eval_bright_short.sh

@@ -0,0 +1,52 @@
+if [ -z "$HF_HUB_CACHE" ]; then
+    export HF_HUB_CACHE="$HOME/.cache/huggingface/hub"
+fi
+
+# full datasets
+# dataset_names="biology earth_science economics psychology robotics stackoverflow sustainable_living leetcode pony aops theoremqa_questions theoremqa_theorems"
+
+# small datasets for quick test
+dataset_names="pony theoremqa_theorems"
+
+model_args="\
+    --embedder_name_or_path BAAI/bge-reasoner-embed-qwen3-8b-0923 \
+    --embedder_model_class decoder-only-base \
+    --query_instruction_format_for_retrieval 'Instruct: {}\nQuery: {}' \
+    --pooling_method last_token \
+    --devices cuda:0 cuda:1 \
+    --cache_dir $HF_HUB_CACHE \
+    --embedder_batch_size 2 \
+    --embedder_query_max_length 8192 \
+    --embedder_passage_max_length 8192 \
+"
+
+split_list=("examples" "gpt4_reason")
+
+for split in "${split_list[@]}"; do
+    eval_args="\
+        --task_type short \
+        --use_special_instructions True \
+        --eval_name bright_short \
+        --dataset_dir ./bright_short/data \
+        --dataset_names $dataset_names \
+        --splits $split \
+        --corpus_embd_save_dir ./bright_short/corpus_embd \
+        --output_dir ./bright_short/search_results/$split \
+        --search_top_k 2000 \
+        --cache_path $HF_HUB_CACHE \
+        --overwrite False \
+        --k_values 1 10 100 \
+        --eval_output_method markdown \
+        --eval_output_path ./bright_short/eval_results_$split.md \
+        --eval_metrics ndcg_at_10 recall_at_10 recall_at_100 \
+    "
+
+    cmd="python -m FlagEmbedding.evaluation.bright \
+        $eval_args \
+        $model_args \
+    "
+
+    echo $cmd
+    eval $cmd
+
+done