File size: 1,927 Bytes
3f7cfab |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 |
import os
import shutil
from functools import wraps, partial
from utils import call_subprocess_onetask, makedirs
def wrap_test_forked(func):
"""Decorate a function to test, call in subprocess"""
@wraps(func)
def f(*args, **kwargs):
func_new = partial(call_subprocess_onetask, func, args, kwargs)
return run_test(func_new)
return f
def run_test(func, *args, **kwargs):
return func(*args, **kwargs)
def make_user_path_test():
import os
import shutil
user_path = 'user_path_test'
if os.path.isdir(user_path):
shutil.rmtree(user_path)
os.makedirs(user_path)
db_dir = "db_dir_UserData"
if os.path.isdir(db_dir):
shutil.rmtree(db_dir)
shutil.copy('data/pexels-evg-kowalievska-1170986_small.jpg', user_path)
shutil.copy('README.md', user_path)
shutil.copy('docs/FAQ.md', user_path)
return user_path
def get_llama(llama_type=2):
from huggingface_hub import hf_hub_download
# default should match .env_gpt4all
if llama_type == 1:
file = 'ggml-model-q4_0_7b.bin'
dest = 'models/7B/'
prompt_type = 'plain'
elif llama_type == 2:
file = 'WizardLM-7B-uncensored.ggmlv3.q8_0.bin'
dest = './'
prompt_type = 'wizard2'
else:
raise ValueError("unknown llama_type=%s" % llama_type)
makedirs(dest, exist_ok=True)
full_path = os.path.join(dest, file)
if not os.path.isfile(full_path):
# True for case when locally already logged in with correct token, so don't have to set key
token = os.getenv('HUGGINGFACE_API_TOKEN', True)
out_path = hf_hub_download('h2oai/ggml', file, token=token, repo_type='model')
# out_path will look like '/home/jon/.cache/huggingface/hub/models--h2oai--ggml/snapshots/57e79c71bb0cee07e3e3ffdea507105cd669fa96/ggml-model-q4_0_7b.bin'
shutil.copy(out_path, dest)
return prompt_type
|