mirror of
https://github.com/qodo-ai/pr-agent.git
synced 2025-07-02 11:50:37 +08:00
256 lines
12 KiB
Python
256 lines
12 KiB
Python
import copy
|
|
import logging
|
|
import textwrap
|
|
from typing import List, Dict
|
|
from jinja2 import Environment, StrictUndefined
|
|
|
|
from pr_agent.algo.ai_handler import AiHandler
|
|
from pr_agent.algo.pr_processing import get_pr_diff, retry_with_fallback_models, get_pr_multi_diffs
|
|
from pr_agent.algo.token_handler import TokenHandler
|
|
from pr_agent.algo.utils import load_yaml
|
|
from pr_agent.config_loader import get_settings
|
|
from pr_agent.git_providers import BitbucketProvider, get_git_provider
|
|
from pr_agent.git_providers.git_provider import get_main_pr_language
|
|
|
|
|
|
def get_docs_for_language(language):
|
|
if language.lower() == 'java':
|
|
return "javadocs"
|
|
elif language.lower() in ['python', 'lisp', 'clojure']:
|
|
return "docstrings"
|
|
elif language.lower() in ['javascript', 'typescript']:
|
|
return "jsdocs"
|
|
elif language.lower() == 'c++':
|
|
return "doxygen"
|
|
else:
|
|
return "docs"
|
|
|
|
|
|
class PRAddDocs:
|
|
def __init__(self, pr_url: str, cli_mode=False, args: list = None):
|
|
|
|
self.git_provider = get_git_provider()(pr_url)
|
|
self.main_language = get_main_pr_language(
|
|
self.git_provider.get_languages(), self.git_provider.get_files()
|
|
)
|
|
|
|
# extended mode
|
|
try:
|
|
self.is_extended = any(["extended" in arg for arg in args])
|
|
except:
|
|
self.is_extended = False
|
|
|
|
self.ai_handler = AiHandler()
|
|
self.patches_diff = None
|
|
self.prediction = None
|
|
self.cli_mode = cli_mode
|
|
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
|
|
"extra_instructions": get_settings().pr_add_docs_prompt.extra_instructions,
|
|
"commit_messages_str": self.git_provider.get_commit_messages(),
|
|
'docs_for_language': get_docs_for_language(self.main_language),
|
|
}
|
|
self.token_handler = TokenHandler(self.git_provider.pr,
|
|
self.vars,
|
|
get_settings().pr_add_docs_prompt.system,
|
|
get_settings().pr_add_docs_prompt.user)
|
|
|
|
async def run(self):
|
|
try:
|
|
logging.info('Generating code Docs for PR...')
|
|
if get_settings().config.publish_output:
|
|
self.git_provider.publish_comment("Preparing review...", is_temporary=True)
|
|
|
|
logging.info('Preparing PR review...')
|
|
if not self.is_extended:
|
|
await retry_with_fallback_models(self._prepare_prediction)
|
|
data = self._prepare_pr_code_suggestions()
|
|
else:
|
|
data = await retry_with_fallback_models(self._prepare_prediction_extended)
|
|
if (not data) or (not 'Code suggestions' in data):
|
|
logging.info('No code suggestions found for PR.')
|
|
return
|
|
|
|
if (not self.is_extended and get_settings().pr_code_suggestions.rank_suggestions) or \
|
|
(self.is_extended and get_settings().pr_code_suggestions.rank_extended_suggestions):
|
|
logging.info('Ranking Suggestions...')
|
|
data['Code suggestions'] = await self.rank_suggestions(data['Code suggestions'])
|
|
|
|
if get_settings().config.publish_output:
|
|
logging.info('Pushing PR review...')
|
|
self.git_provider.remove_initial_comment()
|
|
logging.info('Pushing inline code suggestions...')
|
|
self.push_inline_code_suggestions(data)
|
|
except Exception as e:
|
|
logging.error(f"Failed to generate code suggestions for PR, error: {e}")
|
|
|
|
async def _prepare_prediction(self, model: str):
|
|
logging.info('Getting PR diff...')
|
|
self.patches_diff = get_pr_diff(self.git_provider,
|
|
self.token_handler,
|
|
model,
|
|
add_line_numbers_to_hunks=True,
|
|
disable_extra_lines=True)
|
|
|
|
logging.info('Getting AI prediction...')
|
|
self.prediction = await self._get_prediction(model)
|
|
|
|
async def _get_prediction(self, model: str):
|
|
variables = copy.deepcopy(self.vars)
|
|
variables["diff"] = self.patches_diff # update diff
|
|
environment = Environment(undefined=StrictUndefined)
|
|
system_prompt = environment.from_string(get_settings().pr_add_docs_prompt.system).render(variables)
|
|
user_prompt = environment.from_string(get_settings().pr_add_docs_prompt.user).render(variables)
|
|
if get_settings().config.verbosity_level >= 2:
|
|
logging.info(f"\nSystem prompt:\n{system_prompt}")
|
|
logging.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)
|
|
|
|
return response
|
|
|
|
def _prepare_pr_code_suggestions(self) -> Dict:
|
|
review = self.prediction.strip()
|
|
data = load_yaml(review)
|
|
if isinstance(data, list):
|
|
data = {'Code suggestions': data}
|
|
return data
|
|
|
|
def push_inline_code_suggestions(self, data):
|
|
code_suggestions = []
|
|
|
|
if not data['Code suggestions']:
|
|
return self.git_provider.publish_comment('No suggestions found to improve this PR.')
|
|
|
|
for d in data['Code suggestions']:
|
|
try:
|
|
if get_settings().config.verbosity_level >= 2:
|
|
logging.info(f"suggestion: {d}")
|
|
relevant_file = d['relevant file'].strip()
|
|
relevant_lines_start = int(d['relevant lines start']) # absolute position
|
|
relevant_lines_end = int(d['relevant lines end'])
|
|
content = d['suggestion content']
|
|
new_code_snippet = d['documented code']
|
|
|
|
if new_code_snippet:
|
|
new_code_snippet = self.dedent_code(relevant_file, relevant_lines_start, new_code_snippet)
|
|
|
|
body = f"**Suggestion:** {content}\n```suggestion\n" + new_code_snippet + "\n```"
|
|
code_suggestions.append({'body': body, 'relevant_file': relevant_file,
|
|
'relevant_lines_start': relevant_lines_start,
|
|
'relevant_lines_end': relevant_lines_end})
|
|
except Exception:
|
|
if get_settings().config.verbosity_level >= 2:
|
|
logging.info(f"Could not parse suggestion: {d}")
|
|
|
|
is_successful = self.git_provider.publish_code_suggestions(code_suggestions)
|
|
if not is_successful:
|
|
logging.info("Failed to publish code suggestions, trying to publish each suggestion separately")
|
|
for code_suggestion in code_suggestions:
|
|
self.git_provider.publish_code_suggestions([code_suggestion])
|
|
|
|
def dedent_code(self, relevant_file, relevant_lines_start, new_code_snippet):
|
|
try: # dedent code snippet
|
|
self.diff_files = self.git_provider.diff_files if self.git_provider.diff_files \
|
|
else self.git_provider.get_diff_files()
|
|
original_initial_line = None
|
|
for file in self.diff_files:
|
|
if file.filename.strip() == relevant_file:
|
|
original_initial_line = file.head_file.splitlines()[relevant_lines_start - 1]
|
|
break
|
|
if original_initial_line:
|
|
suggested_initial_line = new_code_snippet.splitlines()[0]
|
|
original_initial_spaces = len(original_initial_line) - len(original_initial_line.lstrip())
|
|
suggested_initial_spaces = len(suggested_initial_line) - len(suggested_initial_line.lstrip())
|
|
delta_spaces = original_initial_spaces - suggested_initial_spaces
|
|
if delta_spaces > 0:
|
|
new_code_snippet = textwrap.indent(new_code_snippet, delta_spaces * " ").rstrip('\n')
|
|
except Exception as e:
|
|
if get_settings().config.verbosity_level >= 2:
|
|
logging.info(f"Could not dedent code snippet for file {relevant_file}, error: {e}")
|
|
|
|
return new_code_snippet
|
|
|
|
async def _prepare_prediction_extended(self, model: str) -> dict:
|
|
logging.info('Getting PR diff...')
|
|
patches_diff_list = get_pr_multi_diffs(self.git_provider, self.token_handler, model,
|
|
max_calls=get_settings().pr_code_suggestions.max_number_of_calls)
|
|
|
|
logging.info('Getting multi AI predictions...')
|
|
prediction_list = []
|
|
for i, patches_diff in enumerate(patches_diff_list):
|
|
logging.info(f"Processing chunk {i + 1} of {len(patches_diff_list)}")
|
|
self.patches_diff = patches_diff
|
|
prediction = await self._get_prediction(model)
|
|
prediction_list.append(prediction)
|
|
self.prediction_list = prediction_list
|
|
|
|
data = {}
|
|
for prediction in prediction_list:
|
|
self.prediction = prediction
|
|
data_per_chunk = self._prepare_pr_code_suggestions()
|
|
if "Code suggestions" in data:
|
|
data["Code suggestions"].extend(data_per_chunk["Code suggestions"])
|
|
else:
|
|
data.update(data_per_chunk)
|
|
self.data = data
|
|
return data
|
|
|
|
async def rank_suggestions(self, data: List) -> List:
|
|
"""
|
|
Call a model to rank (sort) code suggestions based on their importance order.
|
|
|
|
Args:
|
|
data (List): A list of code suggestions to be ranked.
|
|
|
|
Returns:
|
|
List: The ranked list of code suggestions.
|
|
"""
|
|
|
|
suggestion_list = []
|
|
# remove invalid suggestions
|
|
for i, suggestion in enumerate(data):
|
|
if suggestion['existing code'] != suggestion['improved code']:
|
|
suggestion_list.append(suggestion)
|
|
|
|
data_sorted = [[]] * len(suggestion_list)
|
|
|
|
try:
|
|
suggestion_str = ""
|
|
for i, suggestion in enumerate(suggestion_list):
|
|
suggestion_str += f"suggestion {i + 1}: " + str(suggestion) + '\n\n'
|
|
|
|
variables = {'suggestion_list': suggestion_list, 'suggestion_str': suggestion_str}
|
|
model = get_settings().config.model
|
|
environment = Environment(undefined=StrictUndefined)
|
|
system_prompt = environment.from_string(get_settings().pr_sort_code_suggestions_prompt.system).render(
|
|
variables)
|
|
user_prompt = environment.from_string(get_settings().pr_sort_code_suggestions_prompt.user).render(variables)
|
|
if get_settings().config.verbosity_level >= 2:
|
|
logging.info(f"\nSystem prompt:\n{system_prompt}")
|
|
logging.info(f"\nUser prompt:\n{user_prompt}")
|
|
response, finish_reason = await self.ai_handler.chat_completion(model=model, system=system_prompt,
|
|
user=user_prompt)
|
|
|
|
sort_order = load_yaml(response)
|
|
for s in sort_order['Sort Order']:
|
|
suggestion_number = s['suggestion number']
|
|
importance_order = s['importance order']
|
|
data_sorted[importance_order - 1] = suggestion_list[suggestion_number - 1]
|
|
|
|
if get_settings().pr_code_suggestions.final_clip_factor != 1:
|
|
new_len = int(0.5 + len(data_sorted) * get_settings().pr_code_suggestions.final_clip_factor)
|
|
data_sorted = data_sorted[:new_len]
|
|
except Exception as e:
|
|
if get_settings().config.verbosity_level >= 1:
|
|
logging.info(f"Could not sort suggestions, error: {e}")
|
|
data_sorted = suggestion_list
|
|
|
|
return data_sorted
|
|
|
|
|