mirror of
https://github.com/qodo-ai/pr-agent.git
synced 2025-07-02 11:50:37 +08:00
issue tool
This commit is contained in:
mrT23
@ -1,4 +1,5 @@
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MAX_TOKENS = {
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'text-embedding-ada-002': 8000,
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'gpt-3.5-turbo': 4000,
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'gpt-3.5-turbo-0613': 4000,
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'gpt-3.5-turbo-0301': 4000,
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@ -21,7 +21,7 @@ class TokenHandler:
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method.
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"""
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def __init__(self, pr, vars: dict, system, user):
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def __init__(self, pr=None, vars: dict = {}, system="", user=""):
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"""
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Initializes the TokenHandler object.
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@ -32,7 +32,8 @@ class TokenHandler:
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- user: The user string.
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"""
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self.encoder = get_token_encoder()
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self.prompt_tokens = self._get_system_user_tokens(pr, self.encoder, vars, system, user)
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if pr is not None:
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self.prompt_tokens = self._get_system_user_tokens(pr, self.encoder, vars, system, user)
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def _get_system_user_tokens(self, pr, encoder, vars: dict, system, user):
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"""
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@ -32,33 +32,37 @@ def convert_to_markdown(output_data: dict) -> str:
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emojis = {
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"Main theme": "🎯",
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"PR summary": "📝",
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"Type of PR": "📌",
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"Score": "🏅",
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"Relevant tests added": "🧪",
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"Unrelated changes": "⚠️",
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"Focused PR": "✨",
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"Security concerns": "🔒",
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"General PR suggestions": "💡",
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"General suggestions": "💡",
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"Insights from user's answers": "📝",
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"Code feedback": "🤖",
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}
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for key, value in output_data.items():
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if not value:
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if value is None or value == '' or value == {}:
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continue
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if isinstance(value, dict):
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markdown_text += f"## {key}\n\n"
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markdown_text += convert_to_markdown(value)
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elif isinstance(value, list):
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if key.lower() == 'code feedback':
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markdown_text += "\n" # just looks nicer with additional line breaks
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emoji = emojis.get(key, "")
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markdown_text += f"- {emoji} **{key}:**\n\n"
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if key.lower() == 'code feedback':
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markdown_text += f"\n\n- **<details><summary> { emoji } Code feedback:**</summary>\n\n"
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else:
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markdown_text += f"- {emoji} **{key}:**\n\n"
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for item in value:
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if isinstance(item, dict) and key.lower() == 'code feedback':
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markdown_text += parse_code_suggestion(item)
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elif item:
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markdown_text += f" - {item}\n"
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if key.lower() == 'code feedback':
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markdown_text += "</details>\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"
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@ -164,7 +168,7 @@ def fix_json_escape_char(json_message=None):
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Raises:
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None
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"""
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"""
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try:
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result = json.loads(json_message)
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except Exception as e:
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@ -191,7 +195,7 @@ def convert_str_to_datetime(date_str):
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Example:
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>>> convert_str_to_datetime('Mon, 01 Jan 2022 12:00:00 UTC')
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datetime.datetime(2022, 1, 1, 12, 0, 0)
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"""
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"""
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datetime_format = '%a, %d %b %Y %H:%M:%S %Z'
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return datetime.strptime(date_str, datetime_format)
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@ -245,27 +249,34 @@ def update_settings_from_args(args: List[str]) -> List[str]:
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arg = arg.strip()
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if arg.startswith('--'):
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arg = arg.strip('-').strip()
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vals = arg.split('=')
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vals = arg.split('=', 1)
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if len(vals) != 2:
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logging.error(f'Invalid argument format: {arg}')
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if len(vals) > 2: # --extended is a valid argument
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logging.error(f'Invalid argument format: {arg}')
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other_args.append(arg)
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continue
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key, value = _fix_key_value(*vals)
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if key in get_settings():
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get_settings().set(key, value)
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logging.info(f'Updated setting {key} to: "{value}"')
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else:
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logging.info(f'No argument: {key}')
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other_args.append(arg)
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get_settings().set(key, value)
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logging.info(f'Updated setting {key} to: "{value}"')
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else:
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other_args.append(arg)
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return other_args
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def _fix_key_value(key: str, value: str):
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key = key.strip().upper()
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value = value.strip()
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try:
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value = yaml.safe_load(value)
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except Exception as e:
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logging.error(f"Failed to parse YAML for config override {key}={value}", exc_info=e)
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return key, value
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def load_yaml(review_text: str) -> dict:
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review_text = review_text.removeprefix('```yaml').rstrip('`')
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try:
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data = yaml.load(review_text, Loader=yaml.SafeLoader)
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data = yaml.safe_load(review_text)
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except Exception as e:
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logging.error(f"Failed to parse AI prediction: {e}")
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data = try_fix_yaml(review_text)
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@ -5,6 +5,7 @@ import os
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from pr_agent.agent.pr_agent import PRAgent, commands
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from pr_agent.config_loader import get_settings
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from pr_agent.tools.pr_similar_issue import PRSimilarIssue
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def run(inargs=None):
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@ -37,14 +38,19 @@ Configuration:
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To edit any configuration parameter from 'configuration.toml', just add -config_path=<value>.
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For example: 'python cli.py --pr_url=... review --pr_reviewer.extra_instructions="focus on the file: ..."'
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""")
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parser.add_argument('--pr_url', type=str, help='The URL of the PR to review', required=True)
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parser.add_argument('--pr_url', type=str, help='The URL of the PR to review')
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parser.add_argument('--issue_url', type=str, help='The URL of the Issue to review', default=None)
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parser.add_argument('command', type=str, help='The', choices=commands, default='review')
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parser.add_argument('rest', nargs=argparse.REMAINDER, default=[])
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args = parser.parse_args(inargs)
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logging.basicConfig(level=os.environ.get("LOGLEVEL", "INFO"))
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command = args.command.lower()
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get_settings().set("CONFIG.CLI_MODE", True)
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result = asyncio.run(PRAgent().handle_request(args.pr_url, command + " " + " ".join(args.rest)))
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if args.issue_url:
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result = asyncio.run(PRAgent().handle_request(args.issue_url, command + " " + " ".join(args.rest)))
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# result = asyncio.run(PRSimilarIssue(args.issue_url, cli_mode=True, args=command + " " + " ".join(args.rest)).run())
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else:
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result = asyncio.run(PRAgent().handle_request(args.pr_url, command + " " + " ".join(args.rest)))
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if not result:
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parser.print_help()
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@ -32,7 +32,7 @@ class GithubProvider(GitProvider):
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self.diff_files = None
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self.git_files = None
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self.incremental = incremental
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if pr_url:
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if pr_url and 'pull' in pr_url:
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self.set_pr(pr_url)
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self.last_commit_id = list(self.pr.get_commits())[-1]
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@ -84,4 +84,14 @@ polling_interval_seconds = 30
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[local]
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# LocalGitProvider settings - uncomment to use paths other than default
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# description_path= "path/to/description.md"
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# review_path= "path/to/review.md"
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# review_path= "path/to/review.md"
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[pr_similar_issue]
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skip_comments = false
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force_update_dataset = false
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max_issues_to_scan = 1000
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[pinecone]
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# fill and place in .secrets.toml
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#api_key = ...
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# environment = "gcp-starter"
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@ -1,77 +1,250 @@
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import copy
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import json
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import logging
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from enum import Enum
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from typing import List, Tuple
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import pinecone
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import openai
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import pandas as pd
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from pydantic import BaseModel, Field
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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 import MAX_TOKENS
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from pr_agent.algo.token_handler import TokenHandler
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from pr_agent.algo.utils import load_yaml
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from pr_agent.config_loader import get_settings
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from pr_agent.git_providers import get_git_provider
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from pr_agent.git_providers.git_provider import get_main_pr_language
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from pinecone_datasets import Dataset, DatasetMetadata
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MODEL = "text-embedding-ada-002"
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class PRSimilarIssue:
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def __init__(self, pr_url: str, issue_url: str, args: list = None):
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load_data_from_local = True
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if not load_data_from_local:
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self.git_provider = get_git_provider()()
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repo_name, issue_number = self.git_provider._parse_issue_url(issue_url.split('=')[-1])
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self.git_provider.repo = repo_name
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self.git_provider.repo_obj = self.git_provider.github_client.get_repo(repo_name)
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repo_obj = self.git_provider.repo_obj
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def __init__(self, issue_url: str, args: list = None):
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if get_settings().config.git_provider != "github":
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raise Exception("Only github is supported for similar issue tool")
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def _process_issue(issue):
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header = body = issue_str = comments_str = ""
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if issue.pull_request:
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return header, body, issue_str, comments_str
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header = issue.title
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body = issue.body
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comments_obj = list(issue.get_comments())
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comments_str = ""
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for i, comment in enumerate(comments_obj):
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comments_str += f"comment {i}:\n{comment.body}\n\n\n"
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issue_str = f"Issue Header: \"{header}\"\n\nIssue Body:\n{body}"
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return header, body, issue_str, comments_str
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self.cli_mode = get_settings().CONFIG.CLI_MODE
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self.max_issues_to_scan = get_settings().pr_similar_issue.max_issues_to_scan
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self.issue_url = issue_url
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self.git_provider = get_git_provider()()
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repo_name, issue_number = self.git_provider._parse_issue_url(issue_url.split('=')[-1])
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self.git_provider.repo = repo_name
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self.git_provider.repo_obj = self.git_provider.github_client.get_repo(repo_name)
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self.token_handler = TokenHandler()
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repo_obj = self.git_provider.repo_obj
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repo_name_for_index = self.repo_name_for_index = repo_obj.full_name.lower().replace('/', '-').replace('_/', '-')
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index_name = self.index_name = "codium-ai-pr-agent-issues"
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main_issue = repo_obj.get_issue(issue_number)
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assert not main_issue.pull_request
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_, _, main_issue_str, main_comments_str = _process_issue(main_issue)
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# assuming pinecone api key and environment are set in secrets file
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try:
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api_key = get_settings().pinecone.api_key
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environment = get_settings().pinecone.environment
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except Exception:
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if not self.cli_mode:
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repo_name, original_issue_number = self.git_provider._parse_issue_url(self.issue_url.split('=')[-1])
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issue_main = self.git_provider.repo_obj.get_issue(original_issue_number)
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issue_main.create_comment("Please set pinecone api key and environment in secrets file")
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raise Exception("Please set pinecone api key and environment in secrets file")
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issues_str_list = []
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comments_str_list = []
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issues = list(repo_obj.get_issues(state='all')) # 'open', 'closed', 'all'
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for i, issue in enumerate(issues):
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if issue.url == main_issue.url:
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continue
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||||
if issue.pull_request:
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||||
continue
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||||
_, _, issue_str, comments_str = _process_issue(issue)
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||||
issues_str_list.append(issue_str)
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comments_str_list.append(comments_str)
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||||
|
||||
json_output = {}
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||||
json_output['main_issue'] = {}
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||||
json_output['main_issue']['issue'] = main_issue_str
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json_output['main_issue']['comment'] = main_comments_str
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json_output['issues'] = {}
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||||
for i in range(len(issues_str_list)):
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json_output['issues'][f'issue_{i}'] = {}
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||||
json_output['issues'][f'issue_{i}']['issue'] = issues_str_list[i]
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||||
json_output['issues'][f'issue_{i}'][f'comments'] = comments_str_list[i]
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||||
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||||
jsonFile = open("/Users/talrid/Desktop/issues_data.json", "w")
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jsonFile.write(json.dumps(json_output))
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jsonFile.close()
|
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# check if index exists, and if repo is already indexed
|
||||
run_from_scratch = False
|
||||
upsert = True
|
||||
pinecone.init(api_key=api_key, environment=environment)
|
||||
if not index_name in pinecone.list_indexes():
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||||
run_from_scratch = True
|
||||
upsert = False
|
||||
else:
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||||
jsonFile = open("/Users/talrid/Desktop/issues_data.json", "r")
|
||||
json_output=json.loads(jsonFile.read())
|
||||
if get_settings().pr_similar_issue.force_update_dataset:
|
||||
upsert = True
|
||||
else:
|
||||
pinecone_index = pinecone.Index(index_name=index_name)
|
||||
res = pinecone_index.fetch([f"example_issue_{repo_name_for_index}"]).to_dict()
|
||||
if res["vectors"]:
|
||||
upsert = False
|
||||
|
||||
from langchain.document_loaders import TextLoader
|
||||
from langchain.text_splitter import CharacterTextSplitter
|
||||
text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
|
||||
if run_from_scratch or upsert: # index the entire repo
|
||||
logging.info('Indexing the entire repo...')
|
||||
|
||||
aaa=3
|
||||
logging.info('Getting issues...')
|
||||
issues = list(repo_obj.get_issues(state='all'))
|
||||
logging.info('Done')
|
||||
self._update_index_with_issues(issues, repo_name_for_index, upsert=upsert)
|
||||
else: # update index if needed
|
||||
pinecone_index = pinecone.Index(index_name=index_name)
|
||||
issues_to_update = []
|
||||
issues_paginated_list = repo_obj.get_issues(state='all')
|
||||
counter = 1
|
||||
for issue in issues_paginated_list:
|
||||
if issue.pull_request:
|
||||
continue
|
||||
issue_str, comments, number = self._process_issue(issue)
|
||||
issue_key = f"issue_{number}"
|
||||
id = issue_key + "." + "issue"
|
||||
res = pinecone_index.fetch([id]).to_dict()
|
||||
is_new_issue = True
|
||||
for vector in res["vectors"].values():
|
||||
if vector['metadata']['repo'] == repo_name_for_index:
|
||||
is_new_issue = False
|
||||
break
|
||||
if is_new_issue:
|
||||
counter += 1
|
||||
issues_to_update.append(issue)
|
||||
else:
|
||||
break
|
||||
|
||||
if issues_to_update:
|
||||
logging.info(f'Updating index with {counter} new issues...')
|
||||
self._update_index_with_issues(issues_to_update, repo_name_for_index, upsert=True)
|
||||
else:
|
||||
logging.info('No new issues to update')
|
||||
|
||||
async def run(self):
|
||||
repo_name, original_issue_number = self.git_provider._parse_issue_url(self.issue_url.split('=')[-1])
|
||||
issue_main = self.git_provider.repo_obj.get_issue(original_issue_number)
|
||||
issue_str, comments, number = self._process_issue(issue_main)
|
||||
openai.api_key = get_settings().openai.key
|
||||
|
||||
res = openai.Embedding.create(input=[issue_str], engine=MODEL)
|
||||
embeds = [record['embedding'] for record in res['data']]
|
||||
pinecone_index = pinecone.Index(index_name=self.index_name)
|
||||
res = pinecone_index.query(embeds[0],
|
||||
top_k=5,
|
||||
filter={"repo": self.repo_name_for_index},
|
||||
include_metadata=True).to_dict()
|
||||
relevant_issues_number_list = []
|
||||
for r in res['matches']:
|
||||
issue_number = int(r["id"].split('.')[0].split('_')[-1])
|
||||
if original_issue_number == issue_number:
|
||||
continue
|
||||
if issue_number not in relevant_issues_number_list:
|
||||
relevant_issues_number_list.append(issue_number)
|
||||
|
||||
similar_issues_str = "Similar Issues:\n\n"
|
||||
for i, issue_number_similar in enumerate(relevant_issues_number_list):
|
||||
issue = self.git_provider.repo_obj.get_issue(issue_number_similar)
|
||||
title = issue.title
|
||||
url = issue.html_url
|
||||
similar_issues_str += f"{i + 1}. [{title}]({url})\n\n"
|
||||
if get_settings().config.publish_output:
|
||||
response = issue_main.create_comment(similar_issues_str)
|
||||
logging.info(similar_issues_str)
|
||||
|
||||
def _process_issue(self, issue):
|
||||
header = issue.title
|
||||
body = issue.body
|
||||
number = issue.number
|
||||
if get_settings().pinecone.skip_comments:
|
||||
comments = []
|
||||
else:
|
||||
comments = list(issue.get_comments())
|
||||
issue_str = f"Issue Header: \"{header}\"\n\nIssue Body:\n{body}"
|
||||
return issue_str, comments, number
|
||||
|
||||
def _update_index_with_issues(self, issues_list, repo_name_for_index, upsert=False):
|
||||
logging.info('Processing issues...')
|
||||
corpus = Corpus()
|
||||
example_issue_record = Record(
|
||||
id=f"example_issue_{repo_name_for_index}",
|
||||
text="example_issue",
|
||||
metadata=Metadata(repo=repo_name_for_index)
|
||||
)
|
||||
corpus.append(example_issue_record)
|
||||
|
||||
counter = 0
|
||||
for issue in issues_list:
|
||||
|
||||
if issue.pull_request:
|
||||
continue
|
||||
|
||||
counter += 1
|
||||
if counter >= self.max_issues_to_scan:
|
||||
logging.info(f"Scanned {self.max_issues_to_scan} issues, stopping")
|
||||
break
|
||||
|
||||
issue_str, comments, number = self._process_issue(issue)
|
||||
issue_key = f"issue_{number}"
|
||||
username = issue.user.login
|
||||
created_at = str(issue.created_at)
|
||||
if len(issue_str) < 8000 or \
|
||||
self.token_handler.count_tokens(issue_str) < MAX_TOKENS[MODEL]: # fast reject first
|
||||
issue_record = Record(
|
||||
id=issue_key + "." + "issue",
|
||||
text=issue_str,
|
||||
metadata=Metadata(repo=repo_name_for_index,
|
||||
username=username,
|
||||
created_at=created_at,
|
||||
level=IssueLevel.ISSUE)
|
||||
)
|
||||
corpus.append(issue_record)
|
||||
if comments:
|
||||
for j, comment in enumerate(comments):
|
||||
comment_body = comment.body
|
||||
num_words_comment = len(comment_body.split())
|
||||
if num_words_comment < 10:
|
||||
continue
|
||||
|
||||
if len(issue_str) < 8000 or \
|
||||
self.token_handler.count_tokens(comment_body) < MAX_TOKENS[MODEL]:
|
||||
comment_record = Record(
|
||||
id=issue_key + ".comment_" + str(j + 1),
|
||||
text=comment_body,
|
||||
metadata=Metadata(repo=repo_name_for_index,
|
||||
username=username, # use issue username for all comments
|
||||
created_at=created_at,
|
||||
level=IssueLevel.COMMENT)
|
||||
)
|
||||
corpus.append(comment_record)
|
||||
df = pd.DataFrame(corpus.dict()["documents"])
|
||||
logging.info('Done')
|
||||
|
||||
logging.info('Embedding...')
|
||||
openai.api_key = get_settings().openai.key
|
||||
list_to_encode = list(df["text"].values)
|
||||
res = openai.Embedding.create(input=list_to_encode, engine=MODEL)
|
||||
embeds = [record['embedding'] for record in res['data']]
|
||||
df["values"] = embeds
|
||||
meta = DatasetMetadata.empty()
|
||||
meta.dense_model.dimension = len(embeds[0])
|
||||
ds = Dataset.from_pandas(df, meta)
|
||||
logging.info('Done')
|
||||
|
||||
api_key = get_settings().pinecone.api_key
|
||||
environment = get_settings().pinecone.environment
|
||||
if not upsert:
|
||||
logging.info('Creating index...')
|
||||
ds.to_pinecone_index(self.index_name, api_key=api_key, environment=environment)
|
||||
else:
|
||||
logging.info('Upserting index...')
|
||||
namespace = ""
|
||||
batch_size: int = 100
|
||||
concurrency: int = 10
|
||||
pinecone.init(api_key=api_key, environment=environment)
|
||||
ds._upsert_to_index(self.index_name, namespace, batch_size, concurrency)
|
||||
logging.info('Done')
|
||||
|
||||
|
||||
class IssueLevel(str, Enum):
|
||||
ISSUE = "issue"
|
||||
COMMENT = "comment"
|
||||
|
||||
|
||||
class Metadata(BaseModel):
|
||||
repo: str
|
||||
username: str = Field(default="@codium")
|
||||
created_at: str = Field(default="01-01-1970 00:00:00.00000")
|
||||
level: IssueLevel = Field(default=IssueLevel.ISSUE)
|
||||
|
||||
class Config:
|
||||
use_enum_values = True
|
||||
|
||||
|
||||
class Record(BaseModel):
|
||||
id: str
|
||||
text: str
|
||||
metadata: Metadata
|
||||
|
||||
|
||||
class Corpus(BaseModel):
|
||||
documents: List[Record] = Field(default=[])
|
||||
|
||||
def append(self, r: Record):
|
||||
self.documents.append(r)
|
||||
|
||||
@ -18,4 +18,6 @@ boto3~=1.28.25
|
||||
google-cloud-storage==2.10.0
|
||||
ujson==5.8.0
|
||||
azure-devops==7.1.0b3
|
||||
msrest==0.7.1
|
||||
msrest==0.7.1
|
||||
pinecone-client==2.2.2
|
||||
pinecone_datasets==0.6.1
|
||||
Reference in New Issue
Block a user