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tool-call
: script to prefetch models used in server tests
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scripts/fetch_server_test_models.py
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67
scripts/fetch_server_test_models.py
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'''
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This script fetches all the models used in the server tests.
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This is useful for slow tests that use larger models, to avoid them timing out on the model downloads.
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It is meant to be run from the root of the repository.
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Example:
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python scripts/fetch_server_test_models.py
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( cd examples/server/tests && ./tests.sh --tags=slow )
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'''
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import os
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from behave.parser import Parser
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import glob
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import re
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from pydantic import BaseModel
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import subprocess
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class HuggingFaceModel(BaseModel):
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hf_repo: str
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hf_file: str
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class Config:
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frozen = True
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models = set()
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model_file_re = re.compile(r'a model file ([^\s\n\r]+) from HF repo ([^\s\n\r]+)')
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def process_step(step):
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if (match := model_file_re.search(step.name)):
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(hf_file, hf_repo) = match.groups()
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models.add(HuggingFaceModel(hf_repo=hf_repo, hf_file=hf_file))
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feature_files = glob.glob(
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os.path.join(
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os.path.dirname(__file__),
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'../examples/server/tests/features/*.feature'))
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for feature_file in feature_files:
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with open(feature_file, 'r') as file:
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feature = Parser().parse(file.read())
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if not feature: continue
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if feature.background:
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for step in feature.background.steps:
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process_step(step)
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for scenario in feature.walk_scenarios(with_outlines=True):
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for step in scenario.steps:
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process_step(step)
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cli_path = os.environ.get(
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'LLAMA_SERVER_BIN_PATH',
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os.path.join(
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os.path.dirname(__file__),
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'../build/bin/Release/llama-cli.exe' if os.name == 'nt' else '../build/bin/llama-cli'))
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for m in models:
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if '<' in m.hf_repo or '<' in m.hf_file:
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continue
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print(f'# Ensuring model at {m.hf_repo} / {m.hf_file} is fetched')
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subprocess.check_call([cli_path, '-hfr', m.hf_repo, '-hff', m.hf_file, '-fa', '-n', '1', '-p', 'Hey', '--no-warmup'])
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