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data.vespa.oath.cloud -> data.vespa-cloud.com #4188

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Sep 5, 2024
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data.vespa.oath.cloud -> data.vespa-cloud.com #4188

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2 changes: 1 addition & 1 deletion lib/performance_test.rb
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Expand Up @@ -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}"
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2 changes: 1 addition & 1 deletion tests/container/local_llm/app/services.xml
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Expand Up @@ -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>
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4 changes: 2 additions & 2 deletions tests/performance/colbert_embedding/app/services.xml
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Expand Up @@ -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/>
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2 changes: 1 addition & 1 deletion tests/performance/colbert_embedding/colbert_embedding.rb
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Expand Up @@ -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}'"
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2 changes: 1 addition & 1 deletion tests/performance/ecommerce_hybrid_search/common/run_es_benchmarks.py
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Expand Up @@ -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:
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2 changes: 1 addition & 1 deletion tests/performance/ecommerce_hybrid_search/common/run_vespa_benchmarks.py
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Expand Up @@ -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:
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2 changes: 1 addition & 1 deletion tests/performance/ecommerce_hybrid_search/ecommerce_hybrid_search_base.rb
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Expand Up @@ -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}"
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4 changes: 2 additions & 2 deletions tests/performance/embedding/app/services.xml
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Expand Up @@ -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/>
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2 changes: 1 addition & 1 deletion tests/performance/embedding/embedding.rb
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Expand Up @@ -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}"
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2 changes: 1 addition & 1 deletion tests/performance/llama/app/services.xml
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Expand Up @@ -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>
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2 changes: 1 addition & 1 deletion tests/performance/llama_7b/app/services.xml
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Expand Up @@ -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>
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2 changes: 1 addition & 1 deletion tests/performance/mixed_tensor_max_sim/maxsim.rb
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Expand Up @@ -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"
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2 changes: 1 addition & 1 deletion tests/performance/nearest_neighbor_distance_metrics/nearest_neighbor_distance_metrics.rb
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Expand Up @@ -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}'"
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2 changes: 1 addition & 1 deletion ...formance/nearest_neighbor_distance_metrics_and_types/nearest_neighbor_distance_metrics.rb
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Expand Up @@ -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, [])

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2 changes: 1 addition & 1 deletion tests/performance/onnxmodel/onnxmodel.rb
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Expand Up @@ -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}"
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2 changes: 1 addition & 1 deletion tests/performance/significance_model/significance_model.rb
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Expand Up @@ -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").
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12 changes: 6 additions & 6 deletions tests/search/embedding/embedding.rb
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Expand Up @@ -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

Expand All @@ -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
Expand Down