feat: Enhance fix_issue workflow with aider integration
- Add README instructions for fix_issue command usage - Implement aider-based issue fixing when available - Improve error handling and output formatting - Refactor main function for better modularity
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@ -1,3 +1,7 @@
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### 操作指南
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fix_issue工作流命令使用步骤如下：
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1. 选中Sonar或者Lint错误提示对应行。
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2. 输入`/fix_issue`命令。
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3. 开始生成问题描述解释以及对应的解决办法，等待生成结束。
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4. 自动弹出Diff View，选择是否接受修改。
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@ -1,8 +1,10 @@
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import os
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import re
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import json
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import subprocess
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import sys
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from devchat.llm import chat
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from devchat.llm import chat, chat_completion_stream
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from devchat.memory import FixSizeChatMemory
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from lib.ide_service import IDEService
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@ -190,6 +192,27 @@ def call_llm_to_generate_fix_solutions(
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pass
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APPLY_SYSTEM_PROMPT = """
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Your task is apply the fix solution to the code, output the whole new code in markdown code block format.
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Here is the code file:
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{file_content}
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Here is the fix solution:
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{fix_solution}
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Some rules for output code:
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1. Focus on the fix solution, don't focus on other errors in the code.
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2. Don't change the indentation of the code.
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3. Don't change lines which are not metioned in fix solution, for example, don't remove empty lines in code.
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Please output only the whole new code which is the result of applying the fix solution, and output the whole code.
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"""
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@chat(prompt=APPLY_SYSTEM_PROMPT, stream_out=True, model="deepseek-coder")
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def apply_fix_solution(file_content, fix_solution):
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pass
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# current file content
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def get_current_file_content(file_path, issue_line_num):
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try:
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@ -229,8 +252,157 @@ def get_rule_description(issue_description):
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return issue_description
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def get_file_content(file_path):
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try:
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with open(file_path, 'r', encoding='utf-8') as file:
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return file.read()
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except Exception:
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print("Error reading file:", file=sys.stderr)
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return None
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GLOBAL_CONFIG_PATH = os.path.join(os.path.expanduser("~"), ".chat", ".workflow_config.json")
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def get_aider_python_path():
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"""
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Retrieves the path to the Aider Python executable from the global configuration file.
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Returns:
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str or None: The path to the Aider Python executable if found in the configuration,
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or None if the configuration file doesn't exist or the path is not set.
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"""
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if os.path.exists(GLOBAL_CONFIG_PATH):
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with open(GLOBAL_CONFIG_PATH, "r", encoding="utf-8") as f:
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config = json.load(f)
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return config.get('aider_python')
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return None
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def run_aider(message, file_path):
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"""
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Run the Aider tool to apply changes to a file based on a given message.
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This function executes the Aider tool with specific parameters to apply changes
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to the specified file. It captures and returns the output from Aider.
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Args:
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message (str): The message describing the changes to be made.
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file_path (str): The path to the file that needs to be modified.
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Returns:
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str: The output from the Aider tool, containing information about the changes made.
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Raises:
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SystemExit: If the Aider process returns a non-zero exit code, indicating an error.
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"""
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python = get_aider_python_path()
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model = os.environ.get('LLM_MODEL', 'gpt-3.5-turbo-1106')
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cmd = [
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python,
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"-m",
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"aider",
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"--model",
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f"openai/{model}",
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"--yes",
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"--no-auto-commits",
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"--dry-run",
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"--no-pretty",
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"--message",
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message,
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file_path
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]
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process = subprocess.Popen(
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cmd,
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stdout=subprocess.PIPE,
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stderr=subprocess.PIPE,
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text=True
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)
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has_started = False
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aider_output = ""
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for line in process.stdout:
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if "run with --help" in line or 'run "aider --help"' in line:
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has_started = True
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continue
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if has_started:
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aider_output += line
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print(line, end="", flush=True)
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return_code = process.wait()
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if return_code != 0:
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for line in process.stderr:
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print(f"Error: {line.strip()}", file=sys.stderr)
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sys.exit(return_code)
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return aider_output
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def apply_changes(changes, file_path):
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"""
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Apply the changes to the specified file using aider.
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Args:
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changes (str): The changes to be applied to the file.
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file_path (str): The path to the file where changes will be applied.
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This function creates a temporary file with the changes, then uses aider to apply
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these changes to the specified file. It handles the execution of aider and manages
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the output and potential errors.
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"""
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changes_file = '.chat/changes.txt'
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os.makedirs(os.path.dirname(changes_file), exist_ok=True)
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with open(changes_file, 'w', encoding='utf-8') as f:
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f.write(changes)
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python = get_aider_python_path()
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model = os.environ.get('LLM_MODEL', 'gpt-3.5-turbo-1106')
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cmd = [
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python,
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"-m",
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"aider",
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"--model",
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f"openai/{model}",
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"--yes",
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"--no-auto-commits",
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"--apply",
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changes_file,
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file_path
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]
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process = subprocess.Popen(
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cmd,
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stdout=subprocess.PIPE,
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stderr=subprocess.PIPE,
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text=True
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)
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has_started = False
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for line in process.stdout:
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if "Model:" in line:
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has_started = True
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continue
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if has_started:
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print(line, end="", flush=True)
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return_code = process.wait()
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if return_code != 0:
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for line in process.stderr:
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print(f"Error: {line.strip()}", file=sys.stderr)
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sys.exit(return_code)
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os.remove(changes_file)
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def main():
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print("start fix issue ...\n\n")
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"""
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Main function to fix issues in the selected code.
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It retrieves the selected code, gets issue descriptions,
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generates fix solutions using LLM, and applies the changes.
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"""
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print("start fix issue ...\n\n", flush=True)
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file_path, issue_line, issue_line_num = get_selected_code()
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if not file_path or not issue_line:
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print("No code selected. Please select the code line you want to fix.", file=sys.stderr)
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@ -243,27 +415,76 @@ def main():
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)
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sys.exit(0)
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print("make llm prompt ...\n\n")
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print("make llm prompt ...\n\n", flush=True)
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current_file_content = get_current_file_content(file_path, issue_line_num)
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rule_description = get_rule_description(issue_description)
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#print("Rule description:\n\n", rule_description, end="\n\n")
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print("call llm to fix issue ...\n\n")
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fix_solutions = call_llm_to_generate_fix_solutions(
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file_content=current_file_content,
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issue_line_code=issue_line,
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issue_description=issue_description,
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rule_description=rule_description,
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)
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if not fix_solutions:
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sys.exit(1)
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print("call llm to fix issue ...\n\n", flush=True)
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print("\n\n", flush=True)
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# ===> 如果aider python已经安装，则直接调用aider来执行AI访问
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aider_python = get_aider_python_path()
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edits_code = extract_markdown_block(fix_solutions)
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if not edits_code:
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sys.exit(0)
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IDEService().diff_apply("", edits_code, True)
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if aider_python and os.path.exists(aider_python):
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python_path = os.environ.get("PYTHONPATH", "")
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if python_path:
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# remove PYTHONPATH
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os.environ.pop("PYTHONPATH")
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# Use aider-based implementation
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message = f"""
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Fix issue: {issue_description}
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Which is reported at line: {issue_line}
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Rule description: {rule_description}
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"""
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changes = run_aider(message, file_path)
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if not changes:
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print("No changes suggested by aider.")
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sys.exit(0)
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print("\nApplying changes...\n", flush=True)
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with open(file_path, 'r', encoding='utf-8') as f:
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original_content = f.read()
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apply_changes(changes, file_path)
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with open(file_path, 'r', encoding='utf-8') as f:
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updated_content = f.read()
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with open(file_path, 'w', encoding='utf-8') as f:
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f.write(original_content)
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os.environ["PYTHONPATH"] = python_path
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# Display changes in IDE
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IDEService().select_range(file_path, -1, -1, -1, -1)
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IDEService().diff_apply("", updated_content, False)
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else:
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print("No aider python found, using default implementation.", end="\n\n")
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fix_solutions = call_llm_to_generate_fix_solutions(
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file_content=current_file_content,
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issue_line_code=issue_line,
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issue_description=issue_description,
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rule_description=rule_description,
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)
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if not fix_solutions:
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sys.exit(1)
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print("\n\n", flush=True)
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print("apply fix solution ...\n\n")
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# updated_content = apply_fix_solution(file_content=get_file_content(file_path), fix_solution=fix_solutions)
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# if not updated_content:
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# print("No edits code generated.")
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# sys.exit(0)
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# updated_content = fix_solutions['content']
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updated_content = extract_markdown_block(fix_solutions)
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if updated_content:
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# Display changes in IDE
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IDEService().diff_apply("", updated_content, True)
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print("Changes have been displayed in the IDE.")
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if __name__ == "__main__":
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