mirror of
https://github.com/qodo-ai/pr-agent.git
synced 2025-07-15 18:20:37 +08:00
Merge branch 'main' of https://github.com/Codium-ai/pr-agent into fix_bitbucket_improve_issue
This commit is contained in:
sarbjitgrewal
@ -2,11 +2,13 @@ import copy
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import json
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import logging
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import textwrap
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from typing import List
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import yaml
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from jinja2 import Environment, StrictUndefined
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from pr_agent.algo.ai_handler import AiHandler
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from pr_agent.algo.pr_processing import get_pr_diff, retry_with_fallback_models
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from pr_agent.algo.pr_processing import get_pr_diff, retry_with_fallback_models, get_pr_multi_diffs
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from pr_agent.algo.token_handler import TokenHandler
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from pr_agent.algo.utils import try_fix_json
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from pr_agent.config_loader import get_settings
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@ -22,6 +24,13 @@ class PRCodeSuggestions:
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self.git_provider.get_languages(), self.git_provider.get_files()
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)
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# extended mode
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self.is_extended = any(["extended" in arg for arg in args])
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if self.is_extended:
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num_code_suggestions = get_settings().pr_code_suggestions.num_code_suggestions_per_chunk
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else:
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num_code_suggestions = get_settings().pr_code_suggestions.num_code_suggestions
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self.ai_handler = AiHandler()
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self.patches_diff = None
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self.prediction = None
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@ -32,7 +41,7 @@ class PRCodeSuggestions:
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"description": self.git_provider.get_pr_description(),
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"language": self.main_language,
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"diff": "", # empty diff for initial calculation
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"num_code_suggestions": get_settings().pr_code_suggestions.num_code_suggestions,
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"num_code_suggestions": num_code_suggestions,
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"extra_instructions": get_settings().pr_code_suggestions.extra_instructions,
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"commit_messages_str": self.git_provider.get_commit_messages(),
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}
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@ -42,18 +51,26 @@ class PRCodeSuggestions:
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get_settings().pr_code_suggestions_prompt.user)
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async def run(self):
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# assert type(self.git_provider) != BitbucketProvider, "Bitbucket is not supported for now"
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logging.info('Generating code suggestions for PR...')
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if get_settings().config.publish_output:
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self.git_provider.publish_comment("Preparing review...", is_temporary=True)
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await retry_with_fallback_models(self._prepare_prediction)
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logging.info('Preparing PR review...')
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data = self._prepare_pr_code_suggestions()
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if not self.is_extended:
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await retry_with_fallback_models(self._prepare_prediction)
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data = self._prepare_pr_code_suggestions()
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else:
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data = await retry_with_fallback_models(self._prepare_prediction_extended)
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if (not self.is_extended and get_settings().pr_code_suggestions.rank_suggestions) or \
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(self.is_extended and get_settings().pr_code_suggestions.rank_extended_suggestions):
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logging.info('Ranking Suggestions...')
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data['Code suggestions'] = await self.rank_suggestions(data['Code suggestions'])
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if get_settings().config.publish_output:
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logging.info('Pushing PR review...')
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self.git_provider.remove_initial_comment()
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logging.info('Pushing inline code comments...')
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logging.info('Pushing inline code suggestions...')
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self.push_inline_code_suggestions(data)
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async def _prepare_prediction(self, model: str):
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@ -121,7 +138,11 @@ class PRCodeSuggestions:
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if get_settings().config.verbosity_level >= 2:
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logging.info(f"Could not parse suggestion: {d}")
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self.git_provider.publish_code_suggestions(code_suggestions)
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is_successful = self.git_provider.publish_code_suggestions(code_suggestions)
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if not is_successful:
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logging.info("Failed to publish code suggestions, trying to publish each suggestion separately")
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for code_suggestion in code_suggestions:
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self.git_provider.publish_code_suggestions([code_suggestion])
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def dedent_code(self, relevant_file, relevant_lines_start, new_code_snippet):
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try: # dedent code snippet
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@ -145,3 +166,81 @@ class PRCodeSuggestions:
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return new_code_snippet
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async def _prepare_prediction_extended(self, model: str) -> dict:
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logging.info('Getting PR diff...')
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patches_diff_list = get_pr_multi_diffs(self.git_provider, self.token_handler, model,
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max_calls=get_settings().pr_code_suggestions.max_number_of_calls)
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logging.info('Getting multi AI predictions...')
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prediction_list = []
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for i, patches_diff in enumerate(patches_diff_list):
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logging.info(f"Processing chunk {i + 1} of {len(patches_diff_list)}")
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self.patches_diff = patches_diff
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prediction = await self._get_prediction(model)
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prediction_list.append(prediction)
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self.prediction_list = prediction_list
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data = {}
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for prediction in prediction_list:
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self.prediction = prediction
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data_per_chunk = self._prepare_pr_code_suggestions()
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if "Code suggestions" in data:
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data["Code suggestions"].extend(data_per_chunk["Code suggestions"])
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else:
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data.update(data_per_chunk)
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self.data = data
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return data
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async def rank_suggestions(self, data: List) -> List:
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"""
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Call a model to rank (sort) code suggestions based on their importance order.
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Args:
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data (List): A list of code suggestions to be ranked.
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Returns:
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List: The ranked list of code suggestions.
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"""
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suggestion_list = []
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# remove invalid suggestions
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for i, suggestion in enumerate(data):
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if suggestion['existing code'] != suggestion['improved code']:
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suggestion_list.append(suggestion)
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data_sorted = [[]] * len(suggestion_list)
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try:
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suggestion_str = ""
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for i, suggestion in enumerate(suggestion_list):
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suggestion_str += f"suggestion {i + 1}: " + str(suggestion) + '\n\n'
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variables = {'suggestion_list': suggestion_list, 'suggestion_str': suggestion_str}
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model = get_settings().config.model
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environment = Environment(undefined=StrictUndefined)
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system_prompt = environment.from_string(get_settings().pr_sort_code_suggestions_prompt.system).render(
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variables)
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user_prompt = environment.from_string(get_settings().pr_sort_code_suggestions_prompt.user).render(variables)
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if get_settings().config.verbosity_level >= 2:
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logging.info(f"\nSystem prompt:\n{system_prompt}")
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logging.info(f"\nUser prompt:\n{user_prompt}")
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response, finish_reason = await self.ai_handler.chat_completion(model=model, system=system_prompt,
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user=user_prompt)
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sort_order = yaml.safe_load(response)
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for s in sort_order['Sort Order']:
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suggestion_number = s['suggestion number']
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importance_order = s['importance order']
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data_sorted[importance_order - 1] = suggestion_list[suggestion_number - 1]
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if get_settings().pr_code_suggestions.final_clip_factor != 1:
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new_len = int(0.5 + len(data_sorted) * get_settings().pr_code_suggestions.final_clip_factor)
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data_sorted = data_sorted[:new_len]
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except Exception as e:
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if get_settings().config.verbosity_level >= 1:
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logging.info(f"Could not sort suggestions, error: {e}")
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data_sorted = suggestion_list
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return data_sorted
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@ -42,6 +42,8 @@ class PRDescription:
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"extra_instructions": get_settings().pr_description.extra_instructions,
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"commit_messages_str": self.git_provider.get_commit_messages()
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}
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self.user_description = self.git_provider.get_user_description()
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# Initialize the token handler
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self.token_handler = TokenHandler(
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@ -149,6 +151,9 @@ class PRDescription:
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# Load the AI prediction data into a dictionary
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data = load_yaml(self.prediction.strip())
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if get_settings().pr_description.add_original_user_description and self.user_description:
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data["User Description"] = self.user_description
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# Initialization
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pr_types = []
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@ -165,13 +170,19 @@ class PRDescription:
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elif type(data['PR Type']) == str:
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pr_types = data['PR Type'].split(',')
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# Assign the value of the 'PR Title' key to 'title' variable and remove it from the dictionary
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title = data.pop('PR Title')
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# Remove the 'PR Title' key from the dictionary
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ai_title = data.pop('PR Title')
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if get_settings().pr_description.keep_original_user_title:
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# Assign the original PR title to the 'title' variable
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title = self.vars["title"]
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else:
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# Assign the value of the 'PR Title' key to 'title' variable
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title = ai_title
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# Iterate over the remaining dictionary items and append the key and value to 'pr_body' in a markdown format,
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# except for the items containing the word 'walkthrough'
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pr_body = ""
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for key, value in data.items():
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for idx, (key, value) in enumerate(data.items()):
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pr_body += f"## {key}:\n"
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if 'walkthrough' in key.lower():
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# for filename, description in value.items():
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@ -183,7 +194,9 @@ class PRDescription:
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# if the value is a list, join its items by comma
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if type(value) == list:
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value = ', '.join(v for v in value)
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pr_body += f"{value}\n\n___\n"
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pr_body += f"{value}\n"
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if idx < len(data) - 1:
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pr_body += "\n___\n"
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if get_settings().config.verbosity_level >= 2:
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logging.info(f"title:\n{title}\n{pr_body}")
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