Files
pr-agent/pr_agent/tools/pr_reviewer.py
2024-02-13 11:21:59 +02:00

419 lines
20 KiB
Python

import copy
import datetime
from collections import OrderedDict
from functools import partial
from typing import List, Tuple
import yaml
from jinja2 import Environment, StrictUndefined
from yaml import SafeLoader
from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler
from pr_agent.algo.ai_handlers.litellm_ai_handler import LiteLLMAIHandler
from pr_agent.algo.pr_processing import get_pr_diff, retry_with_fallback_models
from pr_agent.algo.token_handler import TokenHandler
from pr_agent.algo.utils import convert_to_markdown, load_yaml, try_fix_yaml, set_custom_labels, get_user_labels, \
ModelType
from pr_agent.config_loader import get_settings
from pr_agent.git_providers import get_git_provider
from pr_agent.git_providers.git_provider import IncrementalPR, get_main_pr_language
from pr_agent.log import get_logger
from pr_agent.servers.help import HelpMessage
class PRReviewer:
"""
The PRReviewer class is responsible for reviewing a pull request and generating feedback using an AI model.
"""
def __init__(self, pr_url: str, is_answer: bool = False, is_auto: bool = False, args: list = None,
ai_handler: partial[BaseAiHandler,] = LiteLLMAIHandler):
"""
Initialize the PRReviewer object with the necessary attributes and objects to review a pull request.
Args:
pr_url (str): The URL of the pull request to be reviewed.
is_answer (bool, optional): Indicates whether the review is being done in answer mode. Defaults to False.
is_auto (bool, optional): Indicates whether the review is being done in automatic mode. Defaults to False.
ai_handler (BaseAiHandler): The AI handler to be used for the review. Defaults to None.
args (list, optional): List of arguments passed to the PRReviewer class. Defaults to None.
"""
self.args = args
self.parse_args(args) # -i command
self.git_provider = get_git_provider()(pr_url, incremental=self.incremental)
self.main_language = get_main_pr_language(
self.git_provider.get_languages(), self.git_provider.get_files()
)
self.pr_url = pr_url
self.is_answer = is_answer
self.is_auto = is_auto
if self.is_answer and not self.git_provider.is_supported("get_issue_comments"):
raise Exception(f"Answer mode is not supported for {get_settings().config.git_provider} for now")
self.ai_handler = ai_handler()
self.patches_diff = None
self.prediction = None
answer_str, question_str = self._get_user_answers()
self.vars = {
"title": self.git_provider.pr.title,
"branch": self.git_provider.get_pr_branch(),
"description": self.git_provider.get_pr_description(),
"language": self.main_language,
"diff": "", # empty diff for initial calculation
"require_score": get_settings().pr_reviewer.require_score_review,
"require_tests": get_settings().pr_reviewer.require_tests_review,
"require_focused": get_settings().pr_reviewer.require_focused_review,
"require_estimate_effort_to_review": get_settings().pr_reviewer.require_estimate_effort_to_review,
'num_code_suggestions': get_settings().pr_reviewer.num_code_suggestions,
'question_str': question_str,
'answer_str': answer_str,
"extra_instructions": get_settings().pr_reviewer.extra_instructions,
"commit_messages_str": self.git_provider.get_commit_messages(),
"custom_labels": "",
"enable_custom_labels": get_settings().config.enable_custom_labels,
}
self.token_handler = TokenHandler(
self.git_provider.pr,
self.vars,
get_settings().pr_review_prompt.system,
get_settings().pr_review_prompt.user
)
def parse_args(self, args: List[str]) -> None:
"""
Parse the arguments passed to the PRReviewer class and set the 'incremental' attribute accordingly.
Args:
args: A list of arguments passed to the PRReviewer class.
Returns:
None
"""
is_incremental = False
if args and len(args) >= 1:
arg = args[0]
if arg == "-i":
is_incremental = True
self.incremental = IncrementalPR(is_incremental)
async def run(self) -> None:
try:
if self.incremental.is_incremental and not self._can_run_incremental_review():
return None
if isinstance(self.args, list) and self.args and self.args[0] == 'auto_approve':
get_logger().info(f'Auto approve flow PR: {self.pr_url} ...')
self.auto_approve_logic()
return None
get_logger().info(f'Reviewing PR: {self.pr_url} ...')
if get_settings().config.publish_output:
self.git_provider.publish_comment("Preparing review...", is_temporary=True)
await retry_with_fallback_models(self._prepare_prediction, model_type=ModelType.TURBO)
if not self.prediction:
self.git_provider.remove_initial_comment()
return None
get_logger().info('Preparing PR review...')
pr_comment = self._prepare_pr_review()
if get_settings().config.publish_output:
get_logger().info('Pushing PR review...')
previous_review_comment = self._get_previous_review_comment()
# publish the review
if get_settings().pr_reviewer.persistent_comment and not self.incremental.is_incremental:
self.git_provider.publish_persistent_comment(pr_comment,
initial_header="## PR Review",
update_header=True)
else:
self.git_provider.publish_comment(pr_comment)
self.git_provider.remove_initial_comment()
if previous_review_comment:
self._remove_previous_review_comment(previous_review_comment)
if get_settings().pr_reviewer.inline_code_comments:
get_logger().info('Pushing inline code comments...')
self._publish_inline_code_comments()
except Exception as e:
get_logger().error(f"Failed to review PR: {e}")
async def _prepare_prediction(self, model: str) -> None:
get_logger().info('Getting PR diff...')
self.patches_diff = get_pr_diff(self.git_provider, self.token_handler, model)
if self.patches_diff:
get_logger().info('Getting AI prediction...')
self.prediction = await self._get_prediction(model)
else:
get_logger().error(f"Error getting PR diff")
self.prediction = None
async def _get_prediction(self, model: str) -> str:
"""
Generate an AI prediction for the pull request review.
Args:
model: A string representing the AI model to be used for the prediction.
Returns:
A string representing the AI prediction for the pull request review.
"""
variables = copy.deepcopy(self.vars)
variables["diff"] = self.patches_diff # update diff
environment = Environment(undefined=StrictUndefined)
system_prompt = environment.from_string(get_settings().pr_review_prompt.system).render(variables)
user_prompt = environment.from_string(get_settings().pr_review_prompt.user).render(variables)
if get_settings().config.verbosity_level >= 2:
get_logger().info(f"\nSystem prompt:\n{system_prompt}")
get_logger().info(f"\nUser prompt:\n{user_prompt}")
response, finish_reason = await self.ai_handler.chat_completion(
model=model,
temperature=0.2,
system=system_prompt,
user=user_prompt
)
if get_settings().config.verbosity_level >= 2:
get_logger().info(f"\nAI response:\n{response}")
return response
def _prepare_pr_review(self) -> str:
"""
Prepare the PR review by processing the AI prediction and generating a markdown-formatted text that summarizes
the feedback.
"""
data = load_yaml(self.prediction.strip())
if 'code_feedback' in data:
code_feedback = data['code_feedback']
# Filter out code suggestions that can be submitted as inline comments
if get_settings().pr_reviewer.inline_code_comments:
del data['code_feedback']
else:
for suggestion in code_feedback:
if ('relevant_file' in suggestion) and (not suggestion['relevant_file'].startswith('``')):
suggestion['relevant_file'] = f"``{suggestion['relevant_file']}``"
if 'relevant_line' not in suggestion:
suggestion['relevant_line'] = ''
relevant_line_str = suggestion['relevant_line'].split('\n')[0]
# removing '+'
suggestion['relevant_line'] = relevant_line_str.lstrip('+').strip()
# try to add line numbers link to code suggestions
if hasattr(self.git_provider, 'generate_link_to_relevant_line_number'):
link = self.git_provider.generate_link_to_relevant_line_number(suggestion)
if link:
suggestion['relevant_line'] = f"[{suggestion['relevant_line']}]({link})"
else:
pass
# Add incremental review section
if self.incremental.is_incremental:
last_commit_url = f"{self.git_provider.get_pr_url()}/commits/" \
f"{self.git_provider.incremental.first_new_commit_sha}"
last_commit_msg = self.incremental.commits_range[0].commit.message if self.incremental.commits_range else ""
incremental_review_markdown_text = f"Starting from commit {last_commit_url}"
if last_commit_msg:
replacement = last_commit_msg.splitlines(keepends=False)[0].replace('_', r'\_')
incremental_review_markdown_text += f" \n_({replacement})_"
data = OrderedDict(data)
data.update({'Incremental PR Review': {
"⏮️ Review for commits since previous PR-Agent review": incremental_review_markdown_text}})
data.move_to_end('Incremental PR Review', last=False)
markdown_text = convert_to_markdown(data, self.git_provider.is_supported("gfm_markdown"))
# Add help text if gfm_markdown is supported
if self.git_provider.is_supported("gfm_markdown") and get_settings().pr_reviewer.enable_help_text:
markdown_text += "<hr>\n\n<details> <summary><strong>✨ Usage guide:</strong></summary><hr> \n\n"
markdown_text += HelpMessage.get_review_usage_guide()
markdown_text += "\n</details>\n"
# Add custom labels from the review prediction (effort, security)
self.set_review_labels(data)
# Log markdown response if verbosity level is high
if get_settings().config.verbosity_level >= 2:
get_logger().info(f"Markdown response:\n{markdown_text}")
if markdown_text == None or len(markdown_text) == 0:
markdown_text = ""
return markdown_text
def _publish_inline_code_comments(self) -> None:
"""
Publishes inline comments on a pull request with code suggestions generated by the AI model.
"""
if get_settings().pr_reviewer.num_code_suggestions == 0:
return
data = load_yaml(self.prediction.strip(),
keys_fix_yaml=["estimated_effort_to_review_[1-5]:", "security_concerns:", "possible_issues:",
"relevant_file:", "relevant_line:", "suggestion:"])
comments: List[str] = []
for suggestion in data.get('PR Feedback', {}).get('Code feedback', []):
relevant_file = suggestion.get('relevant_file', '').strip()
relevant_line_in_file = suggestion.get('relevant_line', '').strip()
content = suggestion.get('suggestion', '')
if not relevant_file or not relevant_line_in_file or not content:
get_logger().info("Skipping inline comment with missing file/line/content")
continue
if self.git_provider.is_supported("create_inline_comment"):
comment = self.git_provider.create_inline_comment(content, relevant_file, relevant_line_in_file)
if comment:
comments.append(comment)
else:
self.git_provider.publish_inline_comment(content, relevant_file, relevant_line_in_file)
if comments:
self.git_provider.publish_inline_comments(comments)
def _get_user_answers(self) -> Tuple[str, str]:
"""
Retrieves the question and answer strings from the discussion messages related to a pull request.
Returns:
A tuple containing the question and answer strings.
"""
question_str = ""
answer_str = ""
if self.is_answer:
discussion_messages = self.git_provider.get_issue_comments()
for message in discussion_messages.reversed:
if "Questions to better understand the PR:" in message.body:
question_str = message.body
elif '/answer' in message.body:
answer_str = message.body
if answer_str and question_str:
break
return question_str, answer_str
def _get_previous_review_comment(self):
"""
Get the previous review comment if it exists.
"""
try:
if get_settings().pr_reviewer.remove_previous_review_comment and hasattr(self.git_provider, "get_previous_review"):
return self.git_provider.get_previous_review(
full=not self.incremental.is_incremental,
incremental=self.incremental.is_incremental,
)
except Exception as e:
get_logger().exception(f"Failed to get previous review comment, error: {e}")
def _remove_previous_review_comment(self, comment):
"""
Remove the previous review comment if it exists.
"""
try:
if get_settings().pr_reviewer.remove_previous_review_comment and comment:
self.git_provider.remove_comment(comment)
except Exception as e:
get_logger().exception(f"Failed to remove previous review comment, error: {e}")
def _can_run_incremental_review(self) -> bool:
"""Checks if we can run incremental review according the various configurations and previous review"""
# checking if running is auto mode but there are no new commits
if self.is_auto and not self.incremental.first_new_commit_sha:
get_logger().info(f"Incremental review is enabled for {self.pr_url} but there are no new commits")
return False
# checking if there are enough commits to start the review
num_new_commits = len(self.incremental.commits_range)
num_commits_threshold = get_settings().pr_reviewer.minimal_commits_for_incremental_review
not_enough_commits = num_new_commits < num_commits_threshold
# checking if the commits are not too recent to start the review
recent_commits_threshold = datetime.datetime.now() - datetime.timedelta(
minutes=get_settings().pr_reviewer.minimal_minutes_for_incremental_review
)
last_seen_commit_date = (
self.incremental.last_seen_commit.commit.author.date if self.incremental.last_seen_commit else None
)
all_commits_too_recent = (
last_seen_commit_date > recent_commits_threshold if self.incremental.last_seen_commit else False
)
# check all the thresholds or just one to start the review
condition = any if get_settings().pr_reviewer.require_all_thresholds_for_incremental_review else all
if condition((not_enough_commits, all_commits_too_recent)):
get_logger().info(
f"Incremental review is enabled for {self.pr_url} but didn't pass the threshold check to run:"
f"\n* Number of new commits = {num_new_commits} (threshold is {num_commits_threshold})"
f"\n* Last seen commit date = {last_seen_commit_date} (threshold is {recent_commits_threshold})"
)
return False
return True
def set_review_labels(self, data):
if (get_settings().pr_reviewer.enable_review_labels_security or
get_settings().pr_reviewer.enable_review_labels_effort):
try:
review_labels = []
if get_settings().pr_reviewer.enable_review_labels_effort:
estimated_effort = data['review']['estimated_effort_to_review_[1-5]']
estimated_effort_number = int(estimated_effort.split(',')[0])
if 1 <= estimated_effort_number <= 5: # 1, because ...
review_labels.append(f'Review effort [1-5]: {estimated_effort_number}')
if get_settings().pr_reviewer.enable_review_labels_security:
security_concerns = data['review']['security_concerns'] # yes, because ...
security_concerns_bool = 'yes' in security_concerns.lower() or 'true' in security_concerns.lower()
if security_concerns_bool:
review_labels.append('Possible security concern')
current_labels = self.git_provider.get_pr_labels()
if current_labels:
current_labels_filtered = [label for label in current_labels if
not label.lower().startswith('review effort [1-5]:') and not label.lower().startswith(
'possible security concern')]
else:
current_labels_filtered = []
if current_labels or review_labels:
get_logger().info(f"Setting review labels: {review_labels + current_labels_filtered}")
self.git_provider.publish_labels(review_labels + current_labels_filtered)
except Exception as e:
get_logger().error(f"Failed to set review labels, error: {e}")
def auto_approve_logic(self):
"""
Auto-approve a pull request if it meets the conditions for auto-approval.
"""
if get_settings().pr_reviewer.enable_auto_approval:
maximal_review_effort = get_settings().pr_reviewer.maximal_review_effort
if maximal_review_effort < 5:
current_labels = self.git_provider.get_pr_labels()
for label in current_labels:
if label.lower().startswith('review effort [1-5]:'):
effort = int(label.split(':')[1].strip())
if effort > maximal_review_effort:
get_logger().info(
f"Auto-approve error: PR review effort ({effort}) is higher than the maximal review effort "
f"({maximal_review_effort}) allowed")
self.git_provider.publish_comment(
f"Auto-approve error: PR review effort ({effort}) is higher than the maximal review effort "
f"({maximal_review_effort}) allowed")
return
is_auto_approved = self.git_provider.auto_approve()
if is_auto_approved:
get_logger().info("Auto-approved PR")
self.git_provider.publish_comment("Auto-approved PR")
else:
get_logger().info("Auto-approval option is disabled")
self.git_provider.publish_comment("Auto-approval option for PR-Agent is disabled. "
"You can enable it via a [configuration file](https://github.com/Codium-ai/pr-agent/blob/main/docs/REVIEW.md#auto-approval-1)")