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server: bench: minor fixes (#10765)
* server/bench: - support openAI streaming standard output with [DONE]\n\n - export k6 raw results in csv - fix too many tcp idle connection in tcp_wait - add metric time to emit first token * server/bench: - fix when prometheus not started - wait for server to be ready before starting bench
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@ -6,10 +6,10 @@ Benchmark is using [k6](https://k6.io/).
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SSE is not supported by default in k6, you have to build k6 with the [xk6-sse](https://github.com/phymbert/xk6-sse) extension.
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Example:
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Example (assuming golang >= 1.21 is installed):
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```shell
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go install go.k6.io/xk6/cmd/xk6@latest
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xk6 build master \
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$GOPATH/bin/xk6 build master \
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--with github.com/phymbert/xk6-sse
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```
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@ -33,7 +33,7 @@ The server must answer OAI Chat completion requests on `http://localhost:8080/v1
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Example:
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```shell
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server --host localhost --port 8080 \
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llama-server --host localhost --port 8080 \
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--model ggml-model-q4_0.gguf \
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--cont-batching \
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--metrics \
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@ -189,12 +189,12 @@ xychart-beta
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"pp": {
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"p95": round(data['metrics']["llamacpp_prompt_processing_second"]["p(95)"], 2),
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"avg": round(data['metrics']["llamacpp_prompt_processing_second"]["avg"], 2),
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"0": round(mean(prometheus_metrics['prompt_tokens_seconds']), 2),
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"0": round(mean(prometheus_metrics['prompt_tokens_seconds']), 2) if 'prompt_tokens_seconds' in prometheus_metrics else 0,
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},
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"tg": {
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"p95": round(data['metrics']["llamacpp_tokens_second"]["p(95)"], 2),
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"avg": round(data['metrics']["llamacpp_tokens_second"]["avg"], 2),
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"0": round(mean(prometheus_metrics['predicted_tokens_seconds']), 2),
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"0": round(mean(prometheus_metrics['predicted_tokens_seconds']), 2) if 'predicted_tokens_seconds' in prometheus_metrics else 0,
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},
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}
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with open("results.github.env", 'a') as github_env:
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@ -214,11 +214,14 @@ def start_benchmark(args):
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k6_args = [
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'run', args.scenario,
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'--no-color',
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'--no-connection-reuse',
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'--no-vu-connection-reuse',
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]
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k6_args.extend(['--duration', args.duration])
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k6_args.extend(['--iterations', args.n_prompts])
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k6_args.extend(['--vus', args.parallel])
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k6_args.extend(['--summary-export', 'k6-results.json'])
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k6_args.extend(['--out', 'csv=k6-results.csv'])
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args = f"SERVER_BENCH_N_PROMPTS={args.n_prompts} SERVER_BENCH_MAX_PROMPT_TOKENS={args.max_prompt_tokens} SERVER_BENCH_MAX_CONTEXT={args.max_tokens} "
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args = args + ' '.join([str(arg) for arg in [k6_path, *k6_args]])
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print(f"bench: starting k6 with: {args}")
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@ -231,7 +234,7 @@ def start_server(args):
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server_process = start_server_background(args)
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attempts = 0
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max_attempts = 20
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max_attempts = 600
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if 'GITHUB_ACTIONS' in os.environ:
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max_attempts *= 2
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@ -242,7 +245,15 @@ def start_server(args):
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print(f"bench: waiting for server to start ...")
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time.sleep(0.5)
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print("bench: server started.")
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attempts = 0
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while not is_server_ready(args.host, args.port):
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attempts += 1
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if attempts > max_attempts:
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assert False, "server not ready"
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print(f"bench: waiting for server to be ready ...")
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time.sleep(0.5)
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print("bench: server started and ready.")
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return server_process
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@ -255,11 +266,6 @@ def start_server_background(args):
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'--host', args.host,
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'--port', args.port,
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]
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model_file = args.model_path_prefix + os.path.sep + args.hf_file
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model_dir = os.path.dirname(model_file)
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if not os.path.exists(model_dir):
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os.makedirs(model_dir)
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server_args.extend(['--model', model_file])
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server_args.extend(['--hf-repo', args.hf_repo])
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server_args.extend(['--hf-file', args.hf_file])
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server_args.extend(['--n-gpu-layers', args.n_gpu_layers])
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@ -303,6 +309,12 @@ def is_server_listening(server_fqdn, server_port):
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return _is_server_listening
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def is_server_ready(server_fqdn, server_port):
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url = f"http://{server_fqdn}:{server_port}/health"
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response = requests.get(url)
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return response.status_code == 200
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def escape_metric_name(metric_name):
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return re.sub('[^A-Z0-9]', '_', metric_name.upper())
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@ -56,6 +56,7 @@ const llamacpp_completion_tokens = new Trend('llamacpp_completion_tokens')
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const llamacpp_tokens_second = new Trend('llamacpp_tokens_second')
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const llamacpp_prompt_processing_second = new Trend('llamacpp_prompt_processing_second')
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const llamacpp_emit_first_token_second = new Trend('llamacpp_emit_first_token_second')
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const llamacpp_prompt_tokens_total_counter = new Counter('llamacpp_prompt_tokens_total_counter')
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const llamacpp_completion_tokens_total_counter = new Counter('llamacpp_completion_tokens_total_counter')
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@ -89,6 +90,9 @@ export default function () {
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],
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"model": model,
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"stream": true,
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"stream_options": {
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"include_usage": true, // False to be supported in llama.cpp server
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},
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"seed": 42,
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"max_tokens": max_tokens,
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"stop": ["<|im_end|>"] // This is temporary for phi-2 base (i.e. not instructed) since the server expects that the model always to emit BOS
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@ -105,12 +109,20 @@ export default function () {
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client.on('event', function (event) {
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if (promptEvalEndTime == null) {
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promptEvalEndTime = new Date()
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llamacpp_emit_first_token_second.add((promptEvalEndTime - startTime) / 1.e3)
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}
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if (event.data === '[DONE]' || event.data === '') {
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return
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}
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let chunk = JSON.parse(event.data)
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let choice = chunk.choices[0]
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if (choice.finish_reason) {
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finish_reason = choice.finish_reason
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if (chunk.choices && chunk.choices.length > 0) {
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let choice = chunk.choices[0]
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if (choice.finish_reason) {
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finish_reason = choice.finish_reason
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}
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}
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if (chunk.usage) {
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