forked from HKUDS/LightRAG
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathutils.py
246 lines (185 loc) · 7.56 KB
/
utils.py
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
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
import asyncio
import html
import json
import logging
import os
import re
from dataclasses import dataclass
from functools import wraps
from hashlib import md5
from typing import Any, Union
import xml.etree.ElementTree as ET
import numpy as np
import tiktoken
ENCODER = None
logger = logging.getLogger("lightrag")
def set_logger(log_file: str):
logger.setLevel(logging.DEBUG)
file_handler = logging.FileHandler(log_file)
file_handler.setLevel(logging.DEBUG)
formatter = logging.Formatter(
"%(asctime)s - %(name)s - %(levelname)s - %(message)s"
)
file_handler.setFormatter(formatter)
if not logger.handlers:
logger.addHandler(file_handler)
@dataclass
class EmbeddingFunc:
embedding_dim: int
max_token_size: int
func: callable
async def __call__(self, *args, **kwargs) -> np.ndarray:
return await self.func(*args, **kwargs)
def locate_json_string_body_from_string(content: str) -> Union[str, None]:
"""Locate the JSON string body from a string"""
maybe_json_str = re.search(r"{.*}", content, re.DOTALL)
if maybe_json_str is not None:
return maybe_json_str.group(0)
else:
return None
def convert_response_to_json(response: str) -> dict:
json_str = locate_json_string_body_from_string(response)
assert json_str is not None, f"Unable to parse JSON from response: {response}"
try:
data = json.loads(json_str)
return data
except json.JSONDecodeError as e:
logger.error(f"Failed to parse JSON: {json_str}")
raise e from None
def compute_args_hash(*args):
return md5(str(args).encode()).hexdigest()
def compute_mdhash_id(content, prefix: str = ""):
return prefix + md5(content.encode()).hexdigest()
def limit_async_func_call(max_size: int, waitting_time: float = 0.0001):
"""Add restriction of maximum async calling times for a async func"""
def final_decro(func):
"""Not using async.Semaphore to aovid use nest-asyncio"""
__current_size = 0
@wraps(func)
async def wait_func(*args, **kwargs):
nonlocal __current_size
while __current_size >= max_size:
await asyncio.sleep(waitting_time)
__current_size += 1
result = await func(*args, **kwargs)
__current_size -= 1
return result
return wait_func
return final_decro
def wrap_embedding_func_with_attrs(**kwargs):
"""Wrap a function with attributes"""
def final_decro(func) -> EmbeddingFunc:
new_func = EmbeddingFunc(**kwargs, func=func)
return new_func
return final_decro
def load_json(file_name):
if not os.path.exists(file_name):
return None
with open(file_name, encoding="utf-8") as f:
return json.load(f)
def write_json(json_obj, file_name):
with open(file_name, "w", encoding="utf-8") as f:
json.dump(json_obj, f, indent=2, ensure_ascii=False)
def encode_string_by_tiktoken(content: str, model_name: str = "gpt-4o"):
global ENCODER
if ENCODER is None:
ENCODER = tiktoken.encoding_for_model(model_name)
tokens = ENCODER.encode(content)
return tokens
def decode_tokens_by_tiktoken(tokens: list[int], model_name: str = "gpt-4o"):
global ENCODER
if ENCODER is None:
ENCODER = tiktoken.encoding_for_model(model_name)
content = ENCODER.decode(tokens)
return content
def pack_user_ass_to_openai_messages(*args: str):
roles = ["user", "assistant"]
return [
{"role": roles[i % 2], "content": content} for i, content in enumerate(args)
]
def split_string_by_multi_markers(content: str, markers: list[str]) -> list[str]:
"""Split a string by multiple markers"""
if not markers:
return [content]
results = re.split("|".join(re.escape(marker) for marker in markers), content)
return [r.strip() for r in results if r.strip()]
# Refer the utils functions of the official GraphRAG implementation:
# https://github.com/microsoft/graphrag
def clean_str(input: Any) -> str:
"""Clean an input string by removing HTML escapes, control characters, and other unwanted characters."""
# If we get non-string input, just give it back
if not isinstance(input, str):
return input
result = html.unescape(input.strip())
# https://stackoverflow.com/questions/4324790/removing-control-characters-from-a-string-in-python
return re.sub(r"[\x00-\x1f\x7f-\x9f]", "", result)
def is_float_regex(value):
return bool(re.match(r"^[-+]?[0-9]*\.?[0-9]+$", value))
def truncate_list_by_token_size(list_data: list, key: callable, max_token_size: int):
"""Truncate a list of data by token size"""
if max_token_size <= 0:
return []
tokens = 0
for i, data in enumerate(list_data):
tokens += len(encode_string_by_tiktoken(key(data)))
if tokens > max_token_size:
return list_data[:i]
return list_data
def list_of_list_to_csv(data: list[list]):
return "\n".join(
[",\t".join([str(data_dd) for data_dd in data_d]) for data_d in data]
)
def save_data_to_file(data, file_name):
with open(file_name, "w", encoding="utf-8") as f:
json.dump(data, f, ensure_ascii=False, indent=4)
def xml_to_json(xml_file):
try:
tree = ET.parse(xml_file)
root = tree.getroot()
# Print the root element's tag and attributes to confirm the file has been correctly loaded
print(f"Root element: {root.tag}")
print(f"Root attributes: {root.attrib}")
data = {"nodes": [], "edges": []}
# Use namespace
namespace = {"": "http://graphml.graphdrawing.org/xmlns"}
for node in root.findall(".//node", namespace):
node_data = {
"id": node.get("id").strip('"'),
"entity_type": node.find("./data[@key='d0']", namespace).text.strip('"')
if node.find("./data[@key='d0']", namespace) is not None
else "",
"description": node.find("./data[@key='d1']", namespace).text
if node.find("./data[@key='d1']", namespace) is not None
else "",
"source_id": node.find("./data[@key='d2']", namespace).text
if node.find("./data[@key='d2']", namespace) is not None
else "",
}
data["nodes"].append(node_data)
for edge in root.findall(".//edge", namespace):
edge_data = {
"source": edge.get("source").strip('"'),
"target": edge.get("target").strip('"'),
"weight": float(edge.find("./data[@key='d3']", namespace).text)
if edge.find("./data[@key='d3']", namespace) is not None
else 0.0,
"description": edge.find("./data[@key='d4']", namespace).text
if edge.find("./data[@key='d4']", namespace) is not None
else "",
"keywords": edge.find("./data[@key='d5']", namespace).text
if edge.find("./data[@key='d5']", namespace) is not None
else "",
"source_id": edge.find("./data[@key='d6']", namespace).text
if edge.find("./data[@key='d6']", namespace) is not None
else "",
}
data["edges"].append(edge_data)
# Print the number of nodes and edges found
print(f"Found {len(data['nodes'])} nodes and {len(data['edges'])} edges")
return data
except ET.ParseError as e:
print(f"Error parsing XML file: {e}")
return None
except Exception as e:
print(f"An error occurred: {e}")
return None