data.vespa.oath.cloud -> data.vespa-cloud.com

lib/performance_test.rb

@@ -459,7 +459,7 @@ def vespa_destination_stop
   # Downloads the given file from s3 to the given vespa node.
   # If the file already exists in the test directory, use that directly instead.
   def download_file_from_s3(file_name, vespa_node, dir = "")
-    url = "https://data.vespa.oath.cloud/tests/performance/#{dir}"
+    url = "https://data.vespa-cloud.com/tests/performance/#{dir}"
     if File.exists?(selfdir + file_name)
       # Place the file in the test directory to avoid downloading during manual testing.
       puts "Using local file #{file_name}"

tests/container/local_llm/app/services.xml

@@ -15,7 +15,7 @@
             <config name="ai.vespa.llm.clients.llm-local-client">
 
                 <!-- File is approx 130Mb" -->
-                <model url="https://data.vespa.oath.cloud/gguf_models/Llama-160M-Chat-v1.Q6_K.gguf" />
+                <model url="https://data.vespa-cloud.com/gguf_models/Llama-160M-Chat-v1.Q6_K.gguf" />
 
                 <contextSize>512</contextSize>
                 <parallelRequests>1</parallelRequests>

tests/performance/colbert_embedding/app/services.xml

@@ -5,8 +5,8 @@
   </admin>
   <container id="default" version="1.0">
     <component id="col" type="colbert-embedder">
-      <transformer-model url="https://data.vespa.oath.cloud/onnx_models/colbert_v2.onnx"/>
-      <tokenizer-model url="https://data.vespa.oath.cloud/onnx_models/bert_tokenizer.json"/>
+      <transformer-model url="https://data.vespa-cloud.com/onnx_models/colbert_v2.onnx"/>
+      <tokenizer-model url="https://data.vespa-cloud.com/onnx_models/bert_tokenizer.json"/>
     </component>
     <document-api/>
     <search/>

tests/performance/colbert_embedding/colbert_embedding.rb

@@ -15,7 +15,7 @@ def test_colbert
     start
 
     feed_file = "product-search-products.jsonl.zstd"
-    remote_file = "https://data.vespa.oath.cloud/sample-apps-data/#{feed_file}"
+    remote_file = "https://data.vespa-cloud.com/sample-apps-data/#{feed_file}"
     local_file =  dirs.tmpdir + feed_file
     local_feed_file =  dirs.tmpdir + "feed.json"
     cmd = "wget -O'#{local_file}' '#{remote_file}'"

tests/performance/ecommerce_hybrid_search/common/run_es_benchmarks.py

@@ -59,7 +59,7 @@ class Mode(Enum):
 import pathlib
 from tqdm import tqdm
 
-download_base_url = "https://data.vespa.oath.cloud/tests/performance/ecommerce_hybrid_search"
+download_base_url = "https://data.vespa-cloud.com/tests/performance/ecommerce_hybrid_search"
 
 def download_file(url, file_path):
     try:

tests/performance/ecommerce_hybrid_search/common/run_vespa_benchmarks.py

@@ -58,7 +58,7 @@ class Mode(Enum):
 import pathlib
 from tqdm import tqdm
 
-download_base_url = "https://data.vespa.oath.cloud/tests/performance/ecommerce_hybrid_search"
+download_base_url = "https://data.vespa-cloud.com/tests/performance/ecommerce_hybrid_search"
 
 def download_file(url, file_path):
     try:

tests/performance/ecommerce_hybrid_search/ecommerce_hybrid_search_base.rb

@@ -17,7 +17,7 @@ def system_metric_filler(system_sampler)
     end
   end
 
-  def download_file(file_name, vespa_node, url="https://data.vespa.oath.cloud/tests/performance/ecommerce_hybrid_search")
+  def download_file(file_name, vespa_node, url="https://data.vespa-cloud.com/tests/performance/ecommerce_hybrid_search")
     if File.exists?(selfdir + file_name)
       # Place the file in the test directory to avoid downloading during manual testing.
       puts "Using local file: #{file_name}"

tests/performance/embedding/app/services.xml

@@ -5,8 +5,8 @@
   </admin>
   <container id="default" version="1.0">
     <component id="hf" type="hugging-face-embedder">
-      <transformer-model url="https://data.vespa.oath.cloud/onnx_models/paraphrase-multilingual-MiniLM-L12-v2.onnx"/>
-      <tokenizer-model url="https://data.vespa.oath.cloud/onnx_models/paraphrase-multilingual-MiniLM-L12-v2.tokenizer.json"/>
+      <transformer-model url="https://data.vespa-cloud.com/onnx_models/paraphrase-multilingual-MiniLM-L12-v2.onnx"/>
+      <tokenizer-model url="https://data.vespa-cloud.com/onnx_models/paraphrase-multilingual-MiniLM-L12-v2.tokenizer.json"/>
       <transformer-output>output_0</transformer-output>
     </component>
     <document-api/>

tests/performance/embedding/embedding.rb

@@ -14,7 +14,7 @@ def test_huggingface
     deploy(selfdir + "app")
     start
     feed_file = 'miracl-te-docs.100k.json.gz'
-    remote_file = "https://data.vespa.oath.cloud/tests/performance/#{feed_file}"
+    remote_file = "https://data.vespa-cloud.com/tests/performance/#{feed_file}"
     local_file =  dirs.tmpdir + feed_file
     cmd = "wget -O'#{local_file}' '#{remote_file}'"
     puts "Running command #{cmd}"

tests/performance/llama/app/services.xml

@@ -14,7 +14,7 @@
       <config name="ai.vespa.llm.clients.llm-local-client">
 
         <!-- File is approx 130Mb" -->
-        <model url="https://data.vespa.oath.cloud/gguf_models/Llama-160M-Chat-v1.Q6_K.gguf" />
+        <model url="https://data.vespa-cloud.com/gguf_models/Llama-160M-Chat-v1.Q6_K.gguf" />
 
         <contextSize>8192</contextSize>
         <parallelRequests>40</parallelRequests>

tests/performance/llama_7b/app/services.xml

@@ -14,7 +14,7 @@
       <config name="ai.vespa.llm.clients.llm-local-client">
 
         <!-- File is approx 5.5Gb" -->
-        <model url="https://data.vespa.oath.cloud/gguf_models/mistral-7b-instruct-v0.1.Q8_0.gguf" />
+        <model url="https://data.vespa-cloud.com/gguf_models/mistral-7b-instruct-v0.1.Q8_0.gguf" />
 
         <contextSize>2048</contextSize>
         <parallelRequests>1</parallelRequests>

tests/performance/mixed_tensor_max_sim/maxsim.rb

@@ -17,7 +17,7 @@ def test_max_sim_performance_1d
     deploy_app(SearchApp.new.sd(selfdir + 'page.sd'))
     start
 
-    remote_file = "https://data.vespa.oath.cloud/tests/performance/max-sim-colpali-vectors.json.zst"
+    remote_file = "https://data.vespa-cloud.com/tests/performance/max-sim-colpali-vectors.json.zst"
     cmd = "curl -s '#{remote_file}' | zstdcat"
     #can also use local file 
     #cmd = " cat #{selfdir}max-sim-colpali-vectors.json.zst | zstdcat"

tests/performance/nearest_neighbor_distance_metrics/nearest_neighbor_distance_metrics.rb

@@ -15,7 +15,7 @@ def test_metrics
     start
 
     feed_file = "product-search-products.jsonl.zstd"
-    remote_file = "https://data.vespa.oath.cloud/sample-apps-data/#{feed_file}"
+    remote_file = "https://data.vespa-cloud.com/sample-apps-data/#{feed_file}"
     local_file =  dirs.tmpdir + feed_file
     local_feed_file =  dirs.tmpdir + "feed.json"
     cmd = "wget -O'#{local_file}' '#{remote_file}'"

tests/performance/nearest_neighbor_distance_metrics_and_types/nearest_neighbor_distance_metrics.rb

@@ -16,7 +16,7 @@ def test_metrics_and_types
     deploy_app(SearchApp.new.sd(selfdir + 'vector.sd'))
     start
 
-    remote_file = "https://data.vespa.oath.cloud/tests/performance/vectors.100k.perf.json.zst"
+    remote_file = "https://data.vespa-cloud.com/tests/performance/vectors.100k.perf.json.zst"
     cmd = "curl -s '#{remote_file}' | zstdcat"
     run_stream_feeder(cmd, [])
 

tests/performance/onnxmodel/onnxmodel.rb

@@ -60,7 +60,7 @@ def test_onnx_deploy
   end
 
   def fetch_model
-    remote_file = "https://data.vespa.oath.cloud/tests/performance/#{@onnx_filename}"
+    remote_file = "https://data.vespa-cloud.com/tests/performance/#{@onnx_filename}"
     local_file = "#{Environment.instance.vespa_home}/tmp/#{@onnx_filename}"
     cmd = "wget -O'#{local_file}' '#{remote_file}'"
     puts "Running command #{cmd}"

tests/performance/significance_model/significance_model.rb

@@ -35,7 +35,7 @@ def test_weak_and_bm25
   end
 
   def get_app
-    model_url = "https://data.vespa.oath.cloud/tests/performance/significance_model/enwiki-20240620.json"
+    model_url = "https://data.vespa-cloud.com/tests/performance/significance_model/enwiki-20240620.json"
     SearchApp.new.
       sd(selfdir + 'product.sd').
       search_dir(selfdir + "search").

tests/search/embedding/embedding.rb

@@ -23,21 +23,21 @@ def sentencepiece_tokenizer_component
   def bert_embedder_component
     Component.new('transformer').
       type('bert-embedder').
-      param('transformer-model', '', {'model-id' => 'ignored-on-selfhosted', 'url' => 'https://data.vespa.oath.cloud/onnx_models/sentence_all_MiniLM_L6_v2.onnx' }).
+      param('transformer-model', '', {'model-id' => 'ignored-on-selfhosted', 'url' => 'https://data.vespa-cloud.com/onnx_models/sentence_all_MiniLM_L6_v2.onnx' }).
       param('tokenizer-vocab', '', {'model-id' => 'ignored-on-selfhosted', 'path' => 'components/bert-base-uncased.txt'})
   end
 
   def huggingface_tokenizer_component
     Component.new('tokenizer').
       type('hugging-face-tokenizer').
-      param('model', '', {'model-id' => 'ignored-on-selfhosted', 'url' => 'https://data.vespa.oath.cloud/onnx_models/paraphrase-multilingual-MiniLM-L12-v2.tokenizer.json'})
+      param('model', '', {'model-id' => 'ignored-on-selfhosted', 'url' => 'https://data.vespa-cloud.com/onnx_models/paraphrase-multilingual-MiniLM-L12-v2.tokenizer.json'})
   end
 
   def huggingface_embedder_component
     Component.new('huggingface').
       type('hugging-face-embedder').
-      param('transformer-model', '', {'model-id' => 'ignored-on-selfhosted', 'url' => 'https://data.vespa.oath.cloud/onnx_models/paraphrase-multilingual-MiniLM-L12-v2.onnx'}).
-      param('tokenizer-model', '', {'model-id' => 'ignored-on-selfhosted', 'url' => 'https://data.vespa.oath.cloud/onnx_models/paraphrase-multilingual-MiniLM-L12-v2.tokenizer.json'}).
+      param('transformer-model', '', {'model-id' => 'ignored-on-selfhosted', 'url' => 'https://data.vespa-cloud.com/onnx_models/paraphrase-multilingual-MiniLM-L12-v2.onnx'}).
+      param('tokenizer-model', '', {'model-id' => 'ignored-on-selfhosted', 'url' => 'https://data.vespa-cloud.com/onnx_models/paraphrase-multilingual-MiniLM-L12-v2.tokenizer.json'}).
       param('transformer-output', 'output_0')
   end
 
@@ -52,8 +52,8 @@ def huggingface_embedder_binarization_component
   def colbert_embedder_component
      Component.new('colbert').
        type('colbert-embedder').
-       param('transformer-model', '', {'model-id' => 'ignored-on-selfhosted', 'url' => 'https://data.vespa.oath.cloud/onnx_models/vespa-colMiniLM-L-6-dynamic-quantized.onnx'}).
-       param('tokenizer-model', '', {'model-id' => 'ignored-on-selfhosted', 'url' => 'https://data.vespa.oath.cloud/onnx_models/e5-small-v2/tokenizer.json'})
+       param('transformer-model', '', {'model-id' => 'ignored-on-selfhosted', 'url' => 'https://data.vespa-cloud.com/onnx_models/vespa-colMiniLM-L-6-dynamic-quantized.onnx'}).
+       param('tokenizer-model', '', {'model-id' => 'ignored-on-selfhosted', 'url' => 'https://data.vespa-cloud.com/onnx_models/e5-small-v2/tokenizer.json'})
   end
 
   def colbert_embedder_component_fp16