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pr-agent/pr_agent/algo/utils.py

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from __future__ import annotations
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import difflib
import json
import re
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import textwrap
from datetime import datetime
from typing import Any, List
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import yaml
from starlette_context import context
from pr_agent.algo import MAX_TOKENS
from pr_agent.algo.token_handler import get_token_encoder
from pr_agent.config_loader import get_settings, global_settings
from pr_agent.log import get_logger
def get_setting(key: str) -> Any:
try:
key = key.upper()
return context.get("settings", global_settings).get(key, global_settings.get(key, None))
except Exception:
return global_settings.get(key, None)
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def convert_to_markdown(output_data: dict, gfm_supported: bool=True) -> str:
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"""
Convert a dictionary of data into markdown format.
Args:
output_data (dict): A dictionary containing data to be converted to markdown format.
Returns:
str: The markdown formatted text generated from the input dictionary.
"""
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markdown_text = ""
emojis = {
"Main theme": "🎯",
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"PR summary": "📝",
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"Type of PR": "📌",
"Score": "🏅",
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"Relevant tests added": "🧪",
"Unrelated changes": "⚠️",
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"Focused PR": "",
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"Security concerns": "🔒",
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"General suggestions": "💡",
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"Insights from user's answers": "📝",
"Code feedback": "🤖",
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"Estimated effort to review [1-5]": "⏱️",
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}
for key, value in output_data.items():
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if value is None or value == '' or value == {}:
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continue
if isinstance(value, dict):
markdown_text += f"## {key}\n\n"
markdown_text += convert_to_markdown(value, gfm_supported)
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elif isinstance(value, list):
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emoji = emojis.get(key, "")
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if key.lower() == 'code feedback':
if gfm_supported:
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markdown_text += f"\n\n- "
markdown_text += f"<details><summary> { emoji } Code feedback:</summary>\n\n"
else:
markdown_text += f"\n\n- **{emoji} Code feedback:**\n\n"
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else:
markdown_text += f"- {emoji} **{key}:**\n\n"
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for item in value:
if isinstance(item, dict) and key.lower() == 'code feedback':
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markdown_text += parse_code_suggestion(item, gfm_supported)
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elif item:
markdown_text += f" - {item}\n"
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if key.lower() == 'code feedback':
if gfm_supported:
markdown_text += "</details>\n\n"
else:
markdown_text += "\n\n"
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elif value != 'n/a':
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emoji = emojis.get(key, "")
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markdown_text += f"- {emoji} **{key}:** {value}\n"
return markdown_text
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def parse_code_suggestion(code_suggestions: dict, gfm_supported: bool=True) -> str:
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"""
Convert a dictionary of data into markdown format.
Args:
code_suggestions (dict): A dictionary containing data to be converted to markdown format.
Returns:
str: A string containing the markdown formatted text generated from the input dictionary.
"""
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markdown_text = ""
for sub_key, sub_value in code_suggestions.items():
if isinstance(sub_value, dict): # "code example"
markdown_text += f" - **{sub_key}:**\n"
for code_key, code_value in sub_value.items(): # 'before' and 'after' code
code_str = f"```\n{code_value}\n```"
code_str_indented = textwrap.indent(code_str, ' ')
markdown_text += f" - **{code_key}:**\n{code_str_indented}\n"
else:
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if "relevant file" in sub_key.lower():
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markdown_text += f"\n - **{sub_key}:** {sub_value} \n"
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else:
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markdown_text += f" **{sub_key}:** {sub_value} \n"
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if not gfm_supported:
if "relevant line" not in sub_key.lower(): # nicer presentation
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# markdown_text = markdown_text.rstrip('\n') + "\\\n" # works for gitlab
markdown_text = markdown_text.rstrip('\n') + " \n" # works for gitlab and bitbucker
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markdown_text += "\n"
return markdown_text
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def try_fix_json(review, max_iter=10, code_suggestions=False):
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"""
Fix broken or incomplete JSON messages and return the parsed JSON data.
Args:
- review: A string containing the JSON message to be fixed.
- max_iter: An integer representing the maximum number of iterations to try and fix the JSON message.
- code_suggestions: A boolean indicating whether to try and fix JSON messages with code feedback.
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Returns:
- data: A dictionary containing the parsed JSON data.
The function attempts to fix broken or incomplete JSON messages by parsing until the last valid code suggestion.
If the JSON message ends with a closing bracket, the function calls the fix_json_escape_char function to fix the
message.
If code_suggestions is True and the JSON message contains code feedback, the function tries to fix the JSON
message by parsing until the last valid code suggestion.
The function uses regular expressions to find the last occurrence of "}," with any number of whitespaces or
newlines.
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It tries to parse the JSON message with the closing bracket and checks if it is valid.
If the JSON message is valid, the parsed JSON data is returned.
If the JSON message is not valid, the last code suggestion is removed and the process is repeated until a valid JSON
message is obtained or the maximum number of iterations is reached.
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If a valid JSON message is not obtained, an error is logged and an empty dictionary is returned.
"""
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if review.endswith("}"):
return fix_json_escape_char(review)
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data = {}
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if code_suggestions:
closing_bracket = "]}"
else:
closing_bracket = "]}}"
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if (review.rfind("'Code feedback': [") > 0 or review.rfind('"Code feedback": [') > 0) or \
(review.rfind("'Code suggestions': [") > 0 or review.rfind('"Code suggestions": [') > 0) :
last_code_suggestion_ind = [m.end() for m in re.finditer(r"\}\s*,", review)][-1] - 1
valid_json = False
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iter_count = 0
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while last_code_suggestion_ind > 0 and not valid_json and iter_count < max_iter:
try:
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data = json.loads(review[:last_code_suggestion_ind] + closing_bracket)
valid_json = True
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review = review[:last_code_suggestion_ind].strip() + closing_bracket
except json.decoder.JSONDecodeError:
review = review[:last_code_suggestion_ind]
last_code_suggestion_ind = [m.end() for m in re.finditer(r"\}\s*,", review)][-1] - 1
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iter_count += 1
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if not valid_json:
get_logger().error("Unable to decode JSON response from AI")
data = {}
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return data
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def fix_json_escape_char(json_message=None):
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"""
Fix broken or incomplete JSON messages and return the parsed JSON data.
Args:
json_message (str): A string containing the JSON message to be fixed.
Returns:
dict: A dictionary containing the parsed JSON data.
Raises:
None
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"""
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try:
result = json.loads(json_message)
except Exception as e:
# Find the offending character index:
idx_to_replace = int(str(e).split(' ')[-1].replace(')', ''))
# Remove the offending character:
json_message = list(json_message)
json_message[idx_to_replace] = ' '
new_message = ''.join(json_message)
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return fix_json_escape_char(json_message=new_message)
return result
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def convert_str_to_datetime(date_str):
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"""
Convert a string representation of a date and time into a datetime object.
Args:
date_str (str): A string representation of a date and time in the format '%a, %d %b %Y %H:%M:%S %Z'
Returns:
datetime: A datetime object representing the input date and time.
Example:
>>> convert_str_to_datetime('Mon, 01 Jan 2022 12:00:00 UTC')
datetime.datetime(2022, 1, 1, 12, 0, 0)
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"""
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datetime_format = '%a, %d %b %Y %H:%M:%S %Z'
return datetime.strptime(date_str, datetime_format)
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def load_large_diff(filename, new_file_content_str: str, original_file_content_str: str) -> str:
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"""
Generate a patch for a modified file by comparing the original content of the file with the new content provided as
input.
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Args:
new_file_content_str: The new content of the file as a string.
original_file_content_str: The original content of the file as a string.
Returns:
The generated or provided patch string.
Raises:
None.
"""
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patch = ""
try:
diff = difflib.unified_diff(original_file_content_str.splitlines(keepends=True),
new_file_content_str.splitlines(keepends=True))
if get_settings().config.verbosity_level >= 2:
get_logger().warning(f"File was modified, but no patch was found. Manually creating patch: {filename}.")
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patch = ''.join(diff)
except Exception:
pass
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return patch
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def update_settings_from_args(args: List[str]) -> List[str]:
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"""
Update the settings of the Dynaconf object based on the arguments passed to the function.
Args:
args: A list of arguments passed to the function.
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Example args: ['--pr_code_suggestions.extra_instructions="be funny',
'--pr_code_suggestions.num_code_suggestions=3']
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Returns:
None
Raises:
ValueError: If the argument is not in the correct format.
"""
other_args = []
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if args:
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for arg in args:
arg = arg.strip()
if arg.startswith('--'):
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arg = arg.strip('-').strip()
vals = arg.split('=', 1)
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if len(vals) != 2:
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if len(vals) > 2: # --extended is a valid argument
get_logger().error(f'Invalid argument format: {arg}')
other_args.append(arg)
continue
key, value = _fix_key_value(*vals)
get_settings().set(key, value)
get_logger().info(f'Updated setting {key} to: "{value}"')
else:
other_args.append(arg)
return other_args
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def _fix_key_value(key: str, value: str):
key = key.strip().upper()
value = value.strip()
try:
value = yaml.safe_load(value)
except Exception as e:
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get_logger().debug(f"Failed to parse YAML for config override {key}={value}", exc_info=e)
return key, value
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def load_yaml(response_text: str) -> dict:
response_text = response_text.removeprefix('```yaml').rstrip('`')
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try:
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data = yaml.safe_load(response_text)
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except Exception as e:
get_logger().error(f"Failed to parse AI prediction: {e}")
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data = try_fix_yaml(response_text)
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return data
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def try_fix_yaml(response_text: str) -> dict:
response_text_lines = response_text.split('\n')
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keys = ['relevant line:', 'suggestion content:', 'relevant file:']
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# first fallback - try to convert 'relevant line: ...' to relevant line: |-\n ...'
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response_text_lines_copy = response_text_lines.copy()
for i in range(0, len(response_text_lines_copy)):
for key in keys:
if key in response_text_lines_copy[i] and not '|-' in response_text_lines_copy[i]:
response_text_lines_copy[i] = response_text_lines_copy[i].replace(f'{key}',
f'{key} |-\n ')
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try:
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data = yaml.safe_load('\n'.join(response_text_lines_copy))
get_logger().info(f"Successfully parsed AI prediction after adding |-\n")
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return data
except:
get_logger().info(f"Failed to parse AI prediction after adding |-\n")
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# second fallback - try to remove last lines
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data = {}
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for i in range(1, len(response_text_lines)):
response_text_lines_tmp = '\n'.join(response_text_lines[:-i])
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try:
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data = yaml.safe_load(response_text_lines_tmp,)
get_logger().info(f"Successfully parsed AI prediction after removing {i} lines")
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break
except:
pass
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# thrid fallback - try to remove leading and trailing curly brackets
response_text_copy = response_text.strip().rstrip().removeprefix('{').removesuffix('}')
try:
data = yaml.safe_load(response_text_copy,)
get_logger().info(f"Successfully parsed AI prediction after removing curly brackets")
return data
except:
pass
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def set_custom_labels(variables):
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if not get_settings().config.enable_custom_labels:
return
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labels = get_settings().custom_labels
if not labels:
# set default labels
labels = ['Bug fix', 'Tests', 'Bug fix with tests', 'Enhancement', 'Documentation', 'Other']
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labels_list = "\n - ".join(labels) if labels else ""
labels_list = f" - {labels_list}" if labels_list else ""
variables["custom_labels"] = labels_list
return
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#final_labels = ""
#for k, v in labels.items():
# final_labels += f" - {k} ({v['description']})\n"
#variables["custom_labels"] = final_labels
#variables["custom_labels_examples"] = f" - {list(labels.keys())[0]}"
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variables["custom_labels_class"] = "class Label(str, Enum):"
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for k, v in labels.items():
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description = v['description'].strip('\n').replace('\n', '\\n')
variables["custom_labels_class"] += f"\n {k.lower().replace(' ', '_')} = '{k}' # {description}"
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def get_user_labels(current_labels: List[str] = None):
"""
Only keep labels that has been added by the user
"""
try:
if current_labels is None:
current_labels = []
user_labels = []
for label in current_labels:
if label.lower() in ['bug fix', 'tests', 'enhancement', 'documentation', 'other']:
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continue
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if get_settings().config.enable_custom_labels:
if label in get_settings().custom_labels:
continue
user_labels.append(label)
if user_labels:
get_logger().info(f"Keeping user labels: {user_labels}")
except Exception as e:
get_logger().exception(f"Failed to get user labels: {e}")
return current_labels
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return user_labels
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def get_max_tokens(model):
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settings = get_settings()
if model in MAX_TOKENS:
max_tokens_model = MAX_TOKENS[model]
else:
raise Exception(f"MAX_TOKENS must be set for model {model} in ./pr_agent/algo/__init__.py")
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if settings.config.max_model_tokens:
max_tokens_model = min(settings.config.max_model_tokens, max_tokens_model)
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# get_logger().debug(f"limiting max tokens to {max_tokens_model}")
return max_tokens_model
def clip_tokens(text: str, max_tokens: int, add_three_dots=True) -> str:
"""
Clip the number of tokens in a string to a maximum number of tokens.
Args:
text (str): The string to clip.
max_tokens (int): The maximum number of tokens allowed in the string.
add_three_dots (bool, optional): A boolean indicating whether to add three dots at the end of the clipped
Returns:
str: The clipped string.
"""
if not text:
return text
try:
encoder = get_token_encoder()
num_input_tokens = len(encoder.encode(text))
if num_input_tokens <= max_tokens:
return text
num_chars = len(text)
chars_per_token = num_chars / num_input_tokens
num_output_chars = int(chars_per_token * max_tokens)
clipped_text = text[:num_output_chars]
if add_three_dots:
clipped_text += "...(truncated)"
return clipped_text
except Exception as e:
get_logger().warning(f"Failed to clip tokens: {e}")
return text