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import tiktoken
_enc_model = None
def normalize2uaua( message, if_replace_system = False ):
new_message = []
last_role = ""
for msg in message:
role = msg["role"]
if if_replace_system and role == "system":
role = "user"
if last_role == role:
new_message[-1]["content"] = new_message[-1]["content"] + "\n" + msg["content"]
else:
last_role = role
new_message.append( msg )
return new_message
def tiktoken_counter( text ):
global _enc_model
if _enc_model is None:
_enc_model = tiktoken.get_encoding("cl100k_base")
return len(_enc_model.encode(text))
def string_to_base64(text):
import base64
byte_array = b''
for char in text:
num_bytes = char.encode('utf-8')
byte_array += num_bytes
base64_data = base64.b64encode(byte_array)
return base64_data.decode('utf-8')
def base64_to_string(base64_data):
import base64
byte_array = base64.b64decode(base64_data)
text = byte_array.decode('utf-8')
return text
def float_array_to_base64(float_arr):
import struct
import base64
byte_array = b''
for f in float_arr:
# 将每个浮点数打包为4字节
num_bytes = struct.pack('!f', f)
byte_array += num_bytes
# 将字节数组进行base64编码
base64_data = base64.b64encode(byte_array)
return base64_data.decode('utf-8')
def base64_to_float_array(base64_data):
import struct
import base64
byte_array = base64.b64decode(base64_data)
float_array = []
# 每 4 个字节解析为一个浮点数
for i in range(0, len(byte_array), 4):
num = struct.unpack('!f', byte_array[i:i+4])[0]
float_array.append(num)
return float_array
def load_datas_from_jsonl( file_path ):
import json
datas = []
with open(file_path, 'r', encoding = 'utf-8') as f:
for line in f:
datas.append(json.loads(line))
return datas
def save_datas_to_jsonl( file_path, datas ):
import json
with open(file_path, 'w', encoding = 'utf-8') as f:
for data in datas:
f.write(json.dumps(data, ensure_ascii=False) + '\n') |