chore: Add autoedit parameter to diff_apply method
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@ -117,7 +117,7 @@ class IDEService:
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return self._result
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@rpc_method
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def diff_apply(self, filepath, content) -> bool:
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def diff_apply(self, filepath, content, autoedit: bool = False) -> bool:
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"""
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Applies a given diff to a file.
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@ -10,7 +10,7 @@ def run_code(code: str):
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@rpc_call
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def diff_apply(filepath, content):
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def diff_apply(filepath, content, autoedit=False):
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pass
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@ -3,10 +3,29 @@ import re
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import sys
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from devchat.llm import chat
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from devchat.memory import FixSizeChatMemory
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from lib.ide_service import IDEService
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def extract_edits_block(text):
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"""
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Extracts the first Markdown code block from the given text without the language specifier.
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:param text: A string containing Markdown text
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:return: The content of the first Markdown code block, or None if not found
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"""
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index = text.find("```edits")
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if index == -1:
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return None
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else:
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start = index + len("```edits")
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end = text.find("```", start)
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if end == -1:
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return None
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else:
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return text[start:end]
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def extract_markdown_block(text):
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"""
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Extracts the first Markdown code block from the given text without the language specifier.
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@ -14,6 +33,10 @@ def extract_markdown_block(text):
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:param text: A string containing Markdown text
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:return: The content of the first Markdown code block, or None if not found
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"""
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edit_code = extract_edits_block(text)
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if edit_code:
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return edit_code
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pattern = r"```(?:\w+)?\s*\n(.*?)\n```"
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match = re.search(pattern, text, re.DOTALL)
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@ -55,23 +78,112 @@ def input_issue_descriptions(file_path, issue_line_num):
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# step 3 : call llm to generate fix solutions
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PROMPT = """
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You are a code refactoring assistant.
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This is my code file:
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{file_content}
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SYSTEM_ROLE_DIFF= """
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You are a code refactoring assistant. Your task is to refactor the user's code to fix lint diagnostics. You will be provided with a code snippet and a list of diagnostics. Your response should include two parts:
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There is a issue in the following code:
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{issue_line_code}
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{issue_description}
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1. An explanation of the reason for the diagnostics and how to fix them.
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2. The edited code snippet with the diagnostics fixed, using markdown format for clarity.
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Here is the rule description:
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{rule_description}
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The markdown block for edits should look like this:
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Please provide me refactor code to fix this issue.
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```edits
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def hello():
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print("Call hello():")
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+ print("hello")
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...
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- hello(20)
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+ hello()
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```
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Or like this, if a variable is not defined:
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```edits
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...
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+ cur_file = __file__
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print(cur_file)
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```
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Please note the following important points:
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1. The new code should maintain the correct indentation. The "+ " sign is followed by two spaces for indentation, which should be included in the edited code.
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2. In addition to outputting key editing information, sufficient context (i.e., key information before and after editing) should also be provided to help locate the specific position of the edited line.
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3. Don't output all file lines, if some lines are unchanged, please use "..." to indicate the ignored lines.
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4. Use "+ " and "- " at start of the line to indicate the addition and deletion of lines.
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Here are some examples of incorrect responses:
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Incorrect example 1, where the indentation is not correct:
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```edits
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def hello():
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print("Call hello():")
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+ print("hello")
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```
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In this case, if the "+ " sign and the extra space are removed, the print("hello") statement will lack the necessary two spaces for correct indentation.
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Incorrect example 2, where no other code lines are provided:
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```edits
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+ print("hello")
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```
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This is an incorrect example because without additional context, it's unclear where the new print("hello") statement should be inserted.
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"""
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SYSTEM_ROLE_CODEBLOCK = """
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你是一个重构工程师,你需要根据错误描述,对代码进行问题修正,只需要关注描述的问题,不需要关注代码中的其他问题。
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输出的修正代码中,如果修改了多个代码段,中间没有修改的代码段,请使用...表示。
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每一个被修改的代码段,应该包含前后至少3行未修改的代码,作为修改代码段的边界表示。
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输出一个代码块中,例如:
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```edits
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def hello():
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msg = "hello"
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print(msg)
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...
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if __name__ == "__main__":
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hello()
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```
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"""
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@chat(prompt=PROMPT, stream_out=True)
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LLM_MODEL = os.environ.get("LLM_MODEL", "gpt-3.5-turbo-1106")
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if LLM_MODEL in ["qwen2-72b-instruct", "qwen-long", "qwen-turbo", "Yi-34B-Chat", "deepseek-coder", "xinghuo-3.5"]:
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SYSTEM_ROLE = SYSTEM_ROLE_CODEBLOCK
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else:
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SYSTEM_ROLE = SYSTEM_ROLE_DIFF
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MESSAGES_A = [
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{
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"role": "system",
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"content": SYSTEM_ROLE,
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},
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]
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# step 3 : call llm to generate fix solutions
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PROMPT = """
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Here is the code file:
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{file_content}
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There is an issue in the following code:
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{issue_line_code}
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{issue_description}
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Here is the rule description:
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{rule_description}
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Please focus only on the error described in the prompt. Other errors in the code should be disregarded.
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"""
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memory = FixSizeChatMemory(max_size=20, messages=MESSAGES_A)
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@chat(prompt=PROMPT, stream_out=True, memory=memory)
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def call_llm_to_generate_fix_solutions(
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file_content, issue_line_code, issue_description, rule_description
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):
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@ -117,16 +229,6 @@ def get_rule_description(issue_description):
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return issue_description
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# step 4 : apply fix solutions to code
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def apply_fix_solutions_to_code():
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pass
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# step 0: try parse user input
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def try_parse_user_input():
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pass
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def main():
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print("start fix issue ...\n\n")
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file_path, issue_line, issue_line_num = get_selected_code()
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@ -144,7 +246,7 @@ def main():
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print("make llm prompt ...\n\n")
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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)
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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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@ -156,6 +258,13 @@ def main():
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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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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 __name__ == "__main__":
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main()
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