mirror of
https://github.com/ggml-org/llama.cpp.git
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server: ci: windows build and tests (#5968)
* server: ci: windows build and tests * server: ci: remove tmp push branch * server: ci: EOF EOL * Use builti Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com> * server: tests: server graceful shutdown, then kill, then hard kill * server: tests: remove python2 unicode string * server: tests: remove wrong comment on server starting, close_fds is always true * server: tests: server kill, if pid exists * server: tests: remove dependency to killall * server: tests: ci windows: pid exists better handling --------- Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>
This commit is contained in:
Pierrick Hymbert
@@ -18,7 +18,7 @@ from huggingface_hub import hf_hub_download
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from prometheus_client import parser
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@step(u"a server listening on {server_fqdn}:{server_port}")
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@step("a server listening on {server_fqdn}:{server_port}")
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def step_server_config(context, server_fqdn, server_port):
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context.server_fqdn = server_fqdn
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context.server_port = int(server_port)
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@@ -57,24 +57,24 @@ def step_server_config(context, server_fqdn, server_port):
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context.prompts = []
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@step(u'a model file {hf_file} from HF repo {hf_repo}')
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@step('a model file {hf_file} from HF repo {hf_repo}')
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def step_download_hf_model(context, hf_file, hf_repo):
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context.model_file = hf_hub_download(repo_id=hf_repo, filename=hf_file)
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if context.debug:
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print(f"model file: {context.model_file}\n")
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@step(u'a model alias {model_alias}')
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@step('a model alias {model_alias}')
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def step_model_alias(context, model_alias):
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context.model_alias = model_alias
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@step(u'{seed:d} as server seed')
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@step('{seed:d} as server seed')
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def step_seed(context, seed):
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context.server_seed = seed
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@step(u'{ngl:d} GPU offloaded layers')
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@step('{ngl:d} GPU offloaded layers')
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def step_n_gpu_layer(context, ngl):
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if 'N_GPU_LAYERS' in os.environ:
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new_ngl = int(os.environ['N_GPU_LAYERS'])
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@@ -84,37 +84,37 @@ def step_n_gpu_layer(context, ngl):
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context.n_gpu_layer = ngl
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@step(u'{n_ctx:d} KV cache size')
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@step('{n_ctx:d} KV cache size')
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def step_n_ctx(context, n_ctx):
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context.n_ctx = n_ctx
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@step(u'{n_slots:d} slots')
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@step('{n_slots:d} slots')
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def step_n_slots(context, n_slots):
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context.n_slots = n_slots
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@step(u'{n_predict:d} server max tokens to predict')
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@step('{n_predict:d} server max tokens to predict')
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def step_server_n_predict(context, n_predict):
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context.n_server_predict = n_predict
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@step(u'continuous batching')
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@step('continuous batching')
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def step_server_continuous_batching(context):
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context.server_continuous_batching = True
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@step(u'embeddings extraction')
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@step('embeddings extraction')
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def step_server_embeddings(context):
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context.server_embeddings = True
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@step(u'prometheus compatible metrics exposed')
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@step('prometheus compatible metrics exposed')
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def step_server_metrics(context):
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context.server_metrics = True
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@step(u"the server is starting")
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@step("the server is starting")
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def step_start_server(context):
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start_server_background(context)
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attempts = 0
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@@ -131,7 +131,7 @@ def step_start_server(context):
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time.sleep(0.1)
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@step(u"the server is {expecting_status}")
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@step("the server is {expecting_status}")
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@async_run_until_complete
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async def step_wait_for_the_server_to_be_started(context, expecting_status):
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match expecting_status:
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@@ -160,7 +160,7 @@ async def step_wait_for_the_server_to_be_started(context, expecting_status):
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assert False, "unknown status"
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@step(u'all slots are {expected_slot_status_string}')
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@step('all slots are {expected_slot_status_string}')
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@async_run_until_complete
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async def step_all_slots_status(context, expected_slot_status_string):
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match expected_slot_status_string:
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@@ -176,7 +176,7 @@ async def step_all_slots_status(context, expected_slot_status_string):
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await request_slots_status(context, expected_slots)
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@step(u'a completion request with {api_error} api error')
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@step('a completion request with {api_error} api error')
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@async_run_until_complete
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async def step_request_completion(context, api_error):
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expect_api_error = api_error == 'raised'
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@@ -194,133 +194,133 @@ async def step_request_completion(context, api_error):
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assert completion == 401, f"completion must be an 401 status code: {completion}"
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@step(u'{predicted_n:d} tokens are predicted matching {re_content}')
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@step('{predicted_n:d} tokens are predicted matching {re_content}')
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def step_n_tokens_predicted_with_content(context, predicted_n, re_content):
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context.completion = context.tasks_result.pop()
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assert_n_tokens_predicted(context.completion, predicted_n, re_content)
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@step(u'{predicted_n:d} tokens are predicted')
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@step('{predicted_n:d} tokens are predicted')
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def step_n_tokens_predicted(context, predicted_n):
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context.completion = context.tasks_result.pop()
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assert_n_tokens_predicted(context.completion, predicted_n)
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@step(u'the completion is truncated')
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@step('the completion is truncated')
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def step_assert_completion_truncated(context):
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step_assert_completion_truncated(context, '')
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@step(u'the completion is {truncated} truncated')
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@step('the completion is {truncated} truncated')
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def step_assert_completion_truncated(context, truncated):
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truncated = truncated != "not"
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assert context.completion['truncated'] == truncated, f'{context.completion}'
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@step(u'{n_prompt:d} prompt tokens are processed')
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@step('{n_prompt:d} prompt tokens are processed')
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def step_impl(context, n_prompt):
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assert n_prompt < 0 or n_prompt == context.completion['timings']['prompt_n'], f"n_prompt={context.completion['timings']['prompt_n']}"
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@step(u'a user prompt {user_prompt}')
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@step('a user prompt {user_prompt}')
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def step_user_prompt(context, user_prompt):
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context.prompts.append(user_prompt)
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context.n_prompts = len(context.prompts)
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@step(u'a system prompt {system_prompt}')
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@step('a system prompt {system_prompt}')
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def step_system_prompt(context, system_prompt):
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context.system_prompt = system_prompt
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@step(u'a model {model}')
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@step('a model {model}')
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def step_model(context, model):
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context.model = model
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@step(u'{max_tokens:d} max tokens to predict')
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@step('{max_tokens:d} max tokens to predict')
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def step_max_tokens(context, max_tokens):
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context.n_predict = max_tokens
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@step(u'streaming is {enable_streaming}')
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@step('streaming is {enable_streaming}')
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def step_streaming(context, enable_streaming):
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context.enable_streaming = enable_streaming == 'enabled'
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@step(u'a user api key {user_api_key}')
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@step('a user api key {user_api_key}')
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def step_user_api_key(context, user_api_key):
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context.user_api_key = user_api_key
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@step(u'no user api key')
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@step('no user api key')
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def step_no_user_api_key(context):
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context.user_api_key = None
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@step(u'a user api key ')
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@step('a user api key ')
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def step_no_user_api_key_space(context):
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context.user_api_key = None
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@step(u'a server api key {server_api_key}')
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@step('a server api key {server_api_key}')
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def step_server_api_key(context, server_api_key):
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context.server_api_key = server_api_key
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@step(u'{n_junk:d} as number of junk')
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@step('{n_junk:d} as number of junk')
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def step_n_junk(context, n_junk):
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context.n_junk = n_junk
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@step(u'{n_batch:d} as batch size')
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@step('{n_batch:d} as batch size')
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def step_n_batch(context, n_batch):
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context.n_batch = n_batch
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@step(u'{seed:d} as seed')
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@step('{seed:d} as seed')
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def step_seed(context, seed):
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context.seed = seed
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@step(u'a prefix prompt')
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@step('a prefix prompt')
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def step_prompt_prefix(context):
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context.prompt_prefix = context.text
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context.prompt_prefix = context_text(context)
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@step(u'a junk suffix prompt')
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@step('a junk suffix prompt')
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def step_prompt_junk_suffix(context):
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context.prompt_junk_suffix = context.text
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context.prompt_junk_suffix = context_text(context)
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@step(u'a suffix prompt')
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@step('a suffix prompt')
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def step_prompt_suffix(context):
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context.prompt_suffix = context.text
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context.prompt_suffix = context_text(context)
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@step(u'{n_ga:d} group attention factor'
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u' to extend context size through self-extend')
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@step('{n_ga:d} group attention factor'
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' to extend context size through self-extend')
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def step_impl(context, n_ga):
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context.n_ga = n_ga
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@step(u'{n_ga_w:d} group attention width to extend context size through self-extend')
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@step('{n_ga_w:d} group attention width to extend context size through self-extend')
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def step_impl(context, n_ga_w):
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context.n_ga_w = n_ga_w
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@step(u'a passkey prompt template')
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@step('a passkey prompt template')
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def step_prompt_passkey(context):
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context.prompt_passkey = context.text
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context.prompt_passkey = context_text(context)
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@step(u'{n_prompts:d} fixed prompts')
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@step('{n_prompts:d} fixed prompts')
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def step_fixed_prompts(context, n_prompts):
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context.prompts.extend([str(0)*(context.n_batch if context.n_batch is not None else 512) for i in range(n_prompts)])
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context.n_prompts = n_prompts
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@step(u'a "{passkey}" passkey challenge prompt with the passkey inserted every {i_pos:d} junk')
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@step('a "{passkey}" passkey challenge prompt with the passkey inserted every {i_pos:d} junk')
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def step_prompt_passkey(context, passkey, i_pos):
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prompt = ""
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for i in range(context.n_junk):
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@@ -334,7 +334,7 @@ def step_prompt_passkey(context, passkey, i_pos):
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context.n_prompts = len(context.prompts)
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@step(u'an OAI compatible chat completions request with {api_error} api error')
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@step('an OAI compatible chat completions request with {api_error} api error')
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@async_run_until_complete
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async def step_oai_chat_completions(context, api_error):
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if context.debug:
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@@ -369,19 +369,19 @@ async def step_oai_chat_completions(context, api_error):
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print(f"Completion response: {completion}")
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@step(u'a prompt')
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@step('a prompt')
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def step_a_prompt(context):
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context.prompts.append(context.text)
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context.prompts.append(context_text(context))
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context.n_prompts = len(context.prompts)
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@step(u'a prompt {prompt}')
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@step('a prompt {prompt}')
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def step_a_prompt_prompt(context, prompt):
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context.prompts.append(prompt)
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context.n_prompts = len(context.prompts)
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@step(u'concurrent completion requests')
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@step('concurrent completion requests')
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@async_run_until_complete()
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async def step_concurrent_completion_requests(context):
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await concurrent_requests(context,
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@@ -397,7 +397,7 @@ async def step_concurrent_completion_requests(context):
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'user_api_key') else None)
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@step(u'concurrent OAI completions requests')
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@step('concurrent OAI completions requests')
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@async_run_until_complete
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async def step_oai_chat_completions(context):
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await concurrent_requests(context, oai_chat_completions,
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@@ -417,7 +417,7 @@ async def step_oai_chat_completions(context):
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if hasattr(context, 'user_api_key') else None)
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@step(u'concurrent OAI completions requests no v1')
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@step('concurrent OAI completions requests no v1')
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@async_run_until_complete
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async def step_oai_chat_completions(context):
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await concurrent_requests(context, oai_chat_completions,
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@@ -440,13 +440,13 @@ async def step_oai_chat_completions(context):
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if hasattr(context, 'user_api_key') else None)
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@step(u'all prompts are predicted')
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@step('all prompts are predicted')
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@async_run_until_complete
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async def step_all_prompts_are_predicted(context):
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await all_prompts_are_predicted(context)
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@step(u'all prompts are predicted with {n_expected_predicted:d} tokens')
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@step('all prompts are predicted with {n_expected_predicted:d} tokens')
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@async_run_until_complete
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async def step_all_prompts_are_predicted_with_n_tokens(context, n_expected_predicted):
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await all_prompts_are_predicted(context, n_expected_predicted)
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@@ -460,14 +460,14 @@ async def all_prompts_are_predicted(context, expected_predicted_n=None):
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assert len(context.concurrent_tasks) == 0, f"{len(context.concurrent_tasks)} pending requests"
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@step(u'embeddings are computed for')
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@step('embeddings are computed for')
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@async_run_until_complete
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async def step_compute_embedding(context):
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context.n_prompts = 1
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context.embeddings = await request_embedding(context.text, base_url=context.base_url)
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context.embeddings = await request_embedding(context_text(context), base_url=context.base_url)
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@step(u'all embeddings are the same')
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@step('all embeddings are the same')
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@async_run_until_complete
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async def step_all_embeddings_are_the_same(context):
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n_embedding_requests = await gather_tasks_results(context)
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@@ -491,7 +491,8 @@ async def step_all_embeddings_are_the_same(context):
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print(f"{msg}\n")
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assert np.isclose(similarity, 1.0, rtol=1e-05, atol=1e-08, equal_nan=False), msg
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@step(u'embeddings are generated')
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@step('embeddings are generated')
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def step_assert_embeddings(context):
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assert context.n_prompts == len(context.embeddings), (f"unexpected response:\n"
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f"context.n_prompts={context.n_prompts}\n"
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@@ -500,17 +501,17 @@ def step_assert_embeddings(context):
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assert_embeddings(embedding)
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@step(u'an OAI compatible embeddings computation request for')
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@step('an OAI compatible embeddings computation request for')
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@async_run_until_complete
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async def step_oai_compute_embeddings(context):
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context.n_prompts = 1
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context.embeddings = await request_oai_embeddings(context.text,
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context.embeddings = await request_oai_embeddings(context_text(context),
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base_url=context.base_url,
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user_api_key=context.user_api_key,
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model=context.model)
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@step(u'an OAI compatible embeddings computation request for multiple inputs')
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@step('an OAI compatible embeddings computation request for multiple inputs')
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@async_run_until_complete
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async def step_oai_compute_embeddings_multiple_inputs(context):
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context.embeddings = await request_oai_embeddings(context.prompts,
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@@ -520,7 +521,7 @@ async def step_oai_compute_embeddings_multiple_inputs(context):
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context.prompts.clear()
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@step(u'concurrent embedding requests')
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@step('concurrent embedding requests')
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@async_run_until_complete()
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async def step_concurrent_embedding_requests(context):
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await concurrent_requests(context,
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@@ -529,7 +530,7 @@ async def step_concurrent_embedding_requests(context):
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base_url=context.base_url)
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|
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@step(u'concurrent OAI embedding requests')
|
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@step('concurrent OAI embedding requests')
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@async_run_until_complete()
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async def step_concurrent_oai_embedding_requests(context):
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await concurrent_requests(context,
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@@ -540,7 +541,7 @@ async def step_concurrent_oai_embedding_requests(context):
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model=context.model)
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@step(u'all embeddings are generated')
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@step('all embeddings are generated')
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@async_run_until_complete()
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async def all_embeddings_are_generated(context):
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n_embedding_requests = await gather_tasks_results(context)
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@@ -549,10 +550,10 @@ async def all_embeddings_are_generated(context):
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assert_embeddings(context.tasks_result.pop().pop())
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|
||||
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@step(u'tokenizing')
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@step('tokenizing')
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@async_run_until_complete
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||||
async def step_tokenize(context):
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context.tokenized_text = context.text
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context.tokenized_text = context_text(context)
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||||
async with aiohttp.ClientSession() as session:
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||||
async with session.post(f'{context.base_url}/tokenize',
|
||||
json={
|
||||
@@ -563,7 +564,7 @@ async def step_tokenize(context):
|
||||
context.tokens = tokenize_json['tokens']
|
||||
|
||||
|
||||
@step(u'tokens can be detokenize')
|
||||
@step('tokens can be detokenize')
|
||||
@async_run_until_complete
|
||||
async def step_detokenize(context):
|
||||
assert len(context.tokens) > 0
|
||||
@@ -578,7 +579,7 @@ async def step_detokenize(context):
|
||||
assert context.tokenized_text == detokenize_json['content'].strip()
|
||||
|
||||
|
||||
@step(u'an OPTIONS request is sent from {origin}')
|
||||
@step('an OPTIONS request is sent from {origin}')
|
||||
@async_run_until_complete
|
||||
async def step_options_request(context, origin):
|
||||
async with aiohttp.ClientSession() as session:
|
||||
@@ -589,12 +590,12 @@ async def step_options_request(context, origin):
|
||||
context.options_response = response
|
||||
|
||||
|
||||
@step(u'CORS header {cors_header} is set to {cors_header_value}')
|
||||
@step('CORS header {cors_header} is set to {cors_header_value}')
|
||||
def step_check_options_header_value(context, cors_header, cors_header_value):
|
||||
assert context.options_response.headers[cors_header] == cors_header_value
|
||||
|
||||
|
||||
@step(u'prometheus metrics are exposed')
|
||||
@step('prometheus metrics are exposed')
|
||||
@async_run_until_complete
|
||||
async def step_prometheus_metrics_exported(context):
|
||||
async with aiohttp.ClientSession() as session:
|
||||
@@ -616,14 +617,14 @@ async def step_prometheus_metrics_exported(context):
|
||||
assert metric_exported, "No metrics exported"
|
||||
|
||||
|
||||
@step(u'metric {metric_name} is {metric_value:d}')
|
||||
@step('metric {metric_name} is {metric_value:d}')
|
||||
def step_assert_metric_value(context, metric_name, metric_value):
|
||||
if metric_name not in context.metrics:
|
||||
assert False, f"no metric {metric_name} in {context.metrics.keys()}"
|
||||
assert context.metrics[metric_name].samples[0].value == metric_value, f"metric: {context.metrics[metric_name]}"
|
||||
|
||||
|
||||
@step(u'available models')
|
||||
@step('available models')
|
||||
def step_available_models(context):
|
||||
# openai client always expects an api_key
|
||||
openai.api_key = context.user_api_key if context.user_api_key is not None else 'nope'
|
||||
@@ -631,14 +632,14 @@ def step_available_models(context):
|
||||
context.models = openai.Model.list().data
|
||||
|
||||
|
||||
@step(u'{n_model:d} models are supported')
|
||||
@step('{n_model:d} models are supported')
|
||||
def step_supported_models(context, n_model):
|
||||
if context.debug:
|
||||
print("server models available:", context.models)
|
||||
assert len(context.models) == n_model
|
||||
|
||||
|
||||
@step(u'model {i_model:d} is {param} {preposition} {param_value}')
|
||||
@step('model {i_model:d} is {param} {preposition} {param_value}')
|
||||
def step_supported_models(context, i_model, param, preposition, param_value):
|
||||
assert i_model < len(context.models)
|
||||
model = context.models[i_model]
|
||||
@@ -1007,12 +1008,22 @@ async def completions_seed(context):
|
||||
else context.server_seed if hasattr(context, 'server_seed') else None
|
||||
|
||||
|
||||
def context_text(context):
|
||||
return context.text.replace('\r', '')
|
||||
|
||||
|
||||
def start_server_background(context):
|
||||
context.server_path = '../../../build/bin/server'
|
||||
if os.name == 'nt':
|
||||
context.server_path = '../../../build/bin/Release/server.exe'
|
||||
else:
|
||||
context.server_path = '../../../build/bin/server'
|
||||
if 'LLAMA_SERVER_BIN_PATH' in os.environ:
|
||||
context.server_path = os.environ['LLAMA_SERVER_BIN_PATH']
|
||||
server_listen_addr = context.server_fqdn
|
||||
if os.name == 'nt':
|
||||
server_listen_addr = '0.0.0.0'
|
||||
server_args = [
|
||||
'--host', context.server_fqdn,
|
||||
'--host', server_listen_addr,
|
||||
'--port', context.server_port,
|
||||
'--model', context.model_file
|
||||
]
|
||||
@@ -1045,7 +1056,16 @@ def start_server_background(context):
|
||||
if 'SERVER_LOG_FORMAT_JSON' not in os.environ:
|
||||
server_args.extend(['--log-format', "text"])
|
||||
print(f"starting server with: {context.server_path} {server_args}\n")
|
||||
flags = 0
|
||||
if 'nt' == os.name:
|
||||
flags |= subprocess.DETACHED_PROCESS
|
||||
flags |= subprocess.CREATE_NEW_PROCESS_GROUP
|
||||
flags |= subprocess.CREATE_NO_WINDOW
|
||||
|
||||
pkwargs = {
|
||||
'creationflags': flags,
|
||||
}
|
||||
context.server_process = subprocess.Popen(
|
||||
[str(arg) for arg in [context.server_path, *server_args]],
|
||||
close_fds=True)
|
||||
print(f"server pid={context.server_process.pid}")
|
||||
**pkwargs)
|
||||
print(f"server pid={context.server_process.pid}, behave pid={os.getpid()}")
|
||||
|
||||
Reference in New Issue
Block a user