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import os
def init(cfg):
print(cfg['setting_cache_path'].value)
if os.path.exists(cfg['setting_cache_path'].value):
# ========== 加载角色卡-缓存 ==========
tmp = cfg['model'].load_session(cfg['setting_cache_path'].value)
print(f"load cache from {cfg['setting_cache_path'].value} {tmp}")
tmp = cfg['chat_template']('system',
cfg['text_format'](cfg['role_char_d'].value,
char=cfg['role_char'].value,
user=cfg['role_usr'].value))
cfg['setting_n_keep'].value = len(tmp)
tmp = cfg['chat_template'](cfg['role_char'].value,
cfg['text_format'](cfg['role_chat_style'].value,
char=cfg['role_char'].value,
user=cfg['role_usr'].value))
cfg['setting_n_keep'].value += len(tmp)
# ========== 加载角色卡-第一条消息 ==========
cfg['chatbot'] = []
for one in cfg["role_char_first"]:
one['name'] = cfg['text_format'](one['name'],
char=cfg['role_char'].value,
user=cfg['role_usr'].value)
one['value'] = cfg['text_format'](one['value'],
char=cfg['role_char'].value,
user=cfg['role_usr'].value)
if one['name'] == cfg['role_char'].value:
cfg['chatbot'].append((None, cfg['chat_display_format'](one['value'])))
print(one)
else:
# ========== 加载角色卡-角色描述 ==========
tmp = cfg['chat_template']('system',
cfg['text_format'](cfg['role_char_d'].value,
char=cfg['role_char'].value,
user=cfg['role_usr'].value))
cfg['setting_n_keep'].value = cfg['model'].eval_t(tmp) # 此内容永久存在
# ========== 加载角色卡-回复示例 ==========
tmp = cfg['chat_template'](cfg['role_char'].value,
cfg['text_format'](cfg['role_chat_style'].value,
char=cfg['role_char'].value,
user=cfg['role_usr'].value))
cfg['setting_n_keep'].value = cfg['model'].eval_t(tmp) # 此内容永久存在
# ========== 加载角色卡-第一条消息 ==========
cfg['chatbot'] = []
for one in cfg["role_char_first"]:
one['name'] = cfg['text_format'](one['name'],
char=cfg['role_char'].value,
user=cfg['role_usr'].value)
one['value'] = cfg['text_format'](one['value'],
char=cfg['role_char'].value,
user=cfg['role_usr'].value)
if one['name'] == cfg['role_char'].value:
cfg['chatbot'].append((None, cfg['chat_display_format'](one['value'])))
print(one)
tmp = cfg['chat_template'](one['name'], one['value'])
cfg['model'].eval_t(tmp) # 此内容随上下文增加将被丢弃
# ========== 保存角色卡-缓存 ==========
with open(cfg['setting_cache_path'].value, 'wb') as f:
pass
tmp = cfg['model'].save_session(cfg['setting_cache_path'].value)
print(f'save cache {tmp}')
# ========== 上传缓存 ==========
if os.environ.get("HF_TOKEN"):
from huggingface_hub import login, CommitScheduler
login(token=os.environ.get("HF_TOKEN"), write_permission=True)
CommitScheduler(repo_id='Limour/llama-python-streamingllm-cache', repo_type='dataset', folder_path='cache')
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