Files
pr-agent/pr_agent/tools/pr_line_questions.py

167 lines
8.1 KiB
Python

import argparse
import copy
from functools import partial
from jinja2 import Environment, StrictUndefined
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.git_patch_processing import (
decouple_and_convert_to_hunks_with_lines_numbers, extract_hunk_lines_from_patch)
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 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 get_main_pr_language
from pr_agent.git_providers.github_provider import GithubProvider
from pr_agent.log import get_logger
from pr_agent.servers.help import HelpMessage
class PR_LineQuestions:
def __init__(self, pr_url: str, args=None, ai_handler: partial[BaseAiHandler,] = LiteLLMAIHandler):
self.question_str = self.parse_args(args)
self.git_provider = get_git_provider()(pr_url)
self.main_pr_language = get_main_pr_language(
self.git_provider.get_languages(), self.git_provider.get_files()
)
self.ai_handler = ai_handler()
self.ai_handler.main_pr_language = self.main_pr_language
self.vars = {
"title": self.git_provider.pr.title,
"branch": self.git_provider.get_pr_branch(),
"diff": "", # empty diff for initial calculation
"question": self.question_str,
"full_hunk": "",
"selected_lines": "",
"conversation_history": "",
}
self.token_handler = TokenHandler(self.git_provider.pr,
self.vars,
get_settings().pr_line_questions_prompt.system,
get_settings().pr_line_questions_prompt.user)
self.patches_diff = None
self.prediction = None
def parse_args(self, args):
if args and len(args) > 0:
question_str = " ".join(args)
else:
question_str = ""
return question_str
async def run(self):
get_logger().info('Answering a PR lines question...')
# if get_settings().config.publish_output:
# self.git_provider.publish_comment("Preparing answer...", is_temporary=True)
# set conversation history if enabled
# currently only supports GitHub provider
if get_settings().pr_questions.use_conversation_history and isinstance(self.git_provider, GithubProvider):
conversation_history = self._load_conversation_history()
self.vars["conversation_history"] = conversation_history
self.patch_with_lines = ""
ask_diff = get_settings().get('ask_diff_hunk', "")
line_start = get_settings().get('line_start', '')
line_end = get_settings().get('line_end', '')
side = get_settings().get('side', 'RIGHT')
file_name = get_settings().get('file_name', '')
comment_id = get_settings().get('comment_id', '')
if ask_diff:
self.patch_with_lines, self.selected_lines = extract_hunk_lines_from_patch(ask_diff,
file_name,
line_start=line_start,
line_end=line_end,
side=side
)
else:
diff_files = self.git_provider.get_diff_files()
for file in diff_files:
if file.filename == file_name:
self.patch_with_lines, self.selected_lines = extract_hunk_lines_from_patch(file.patch, file.filename,
line_start=line_start,
line_end=line_end,
side=side)
if self.patch_with_lines:
model_answer = await retry_with_fallback_models(self._get_prediction, model_type=ModelType.WEAK)
# sanitize the answer so that no line will start with "/"
model_answer_sanitized = model_answer.strip().replace("\n/", "\n /")
if model_answer_sanitized.startswith("/"):
model_answer_sanitized = " " + model_answer_sanitized
get_logger().info('Preparing answer...')
if comment_id:
self.git_provider.reply_to_comment_from_comment_id(comment_id, model_answer_sanitized)
else:
self.git_provider.publish_comment(model_answer_sanitized)
return ""
def _load_conversation_history(self) -> str:
"""Generate conversation history from the code review thread
Returns:
str: The formatted conversation history
"""
comment_id = get_settings().get('comment_id', '')
file_path = get_settings().get('file_name', '')
line_number = get_settings().get('line_end', '')
# early return if any required parameter is missing
if not all([comment_id, file_path, line_number]):
get_logger().error("Missing required parameters for conversation history")
return ""
try:
# retrieve thread comments
thread_comments = self.git_provider.get_review_thread_comments(comment_id)
# filter and prepare comments
filtered_comments = []
for comment in thread_comments:
body = getattr(comment, 'body', '')
# skip empty comments, current comment(will be added as a question at prompt)
if not body or not body.strip() or comment_id == comment.id:
continue
user = comment.user
author = user.login if hasattr(user, 'login') else 'Unknown'
filtered_comments.append((author, body))
# transform conversation history to string using the same pattern as get_commit_messages
if filtered_comments:
comment_count = len(filtered_comments)
get_logger().info(f"Loaded {comment_count} comments from the code review thread")
# Format as numbered list, similar to get_commit_messages
conversation_history_str = "\n".join([f"{i + 1}. {author}: {body}"
for i, (author, body) in enumerate(filtered_comments)])
return conversation_history_str
return ""
except Exception as e:
get_logger().error(f"Error processing conversation history, error: {e}")
return ""
async def _get_prediction(self, model: str):
variables = copy.deepcopy(self.vars)
variables["full_hunk"] = self.patch_with_lines # update diff
variables["selected_lines"] = self.selected_lines
environment = Environment(undefined=StrictUndefined)
system_prompt = environment.from_string(get_settings().pr_line_questions_prompt.system).render(variables)
user_prompt = environment.from_string(get_settings().pr_line_questions_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}")
print(f"\nSystem prompt:\n{system_prompt}")
print(f"\nUser prompt:\n{user_prompt}")
response, finish_reason = await self.ai_handler.chat_completion(
model=model, temperature=get_settings().config.temperature, system=system_prompt, user=user_prompt)
return response