python+deepseek v3 api实现类似cursor的AI编程助手代码
代码语言:python
所属分类:人工智能
代码描述:python+deepseek v3 api实现类似cursor的AI编程助手代码
代码标签: python deepseek v3 cursor AI 编程 助手 代码
下面为部分代码预览,完整代码请点击下载或在bfwstudio webide中打开
#!/usr/local/python3/bin/python3
# -*- coding: utf-8 -*
from asynchat import async_chat
from itertools import tee
import os
import json
import re
import sys
from pathlib import Path
from typing import List, Dict
from openai import OpenAI
api_key="sk-apikey"#api申请地址:https://platform.deepseek.com/api_keys
base_url="https://api.deepseek.com"
main_model="deepseek-chat"
code_model="deepseek-chat"
class CodeAssistant:
def __init__(self, project_dir: str):
"""初始化代码助手"""
self.project_dir = Path(project_dir)
self.project_dir.mkdir(parents=True, exist_ok=True)
def _get_file_context(self) -> str:
"""获取项目目录中所有代码文件的内容作为上下文"""
context = []
for file_path in self.project_dir.rglob("*"):
if file_path.is_file() and file_path.suffix in [
'.php', '.js', '.html', '.css', '.json', '.py', '.java', '.cpp', '.c',
'.cs', '.rb', '.go', '.rs', '.ts', '.swift', '.kt', '.m', '.sh', '.xml',
'.yml', '.yaml', '.sql', '.r', '.pl', '.lua', '.scala', '.vb', '.hs',
'.erl', '.ex', '.exs', '.dart', '.jl', '.f90', '.f95', '.f03', '.f08'
]:
try:
relative_path = file_path.relative_to(self.project_dir)
with open(file_path, 'r', encoding='utf-8') as f:
content = f.read()
context.append(f"File: {relative_path}\n{content}\n")
except Exception as e:
print(f"Error reading file {file_path}: {e}")
return "\n".join(context)
def _save_files(self, files: List[Dict[str, str]]):
"""保存生成的代码文件"""
for file_info in files:
file_path = self.project_dir / file_info['name']
file_path.parent.mkdir(parents=True, exist_ok=True)
content = file_info['content']
# 处理内容中的转义字符,将 \n 转换为实际的换行符
# content = file_info['content'].encode().decode('unicode_escape')
with open(file_path, 'w', encoding='utf-8') as f:
f.write(content)
if file_info['action']=="edit":
print(f"Updated file: {file_path}")
if file_info['action']=="add":
print(f"created file: {file_path}")
if file_info['action']=="del":
print(f"del file: {file_path}")
#content= self.megre_code(file_path,content)
async def talktoai(self, requirement: str):
"""根据需求判断是否修改或新增代码"""
system_prompt = """你是一个专业的代码助手。根据用户的需求文字,判断是否是只读还是写入操作。
返回格式必须是一个JSON字符串:iswritecode: 是否需要生成、修改或新增代码。例如 :{"iswritecode": false}"""
user_message = f"用户需求:{requirement} "
#print(user_message)
client = OpenAI(
api_key=api_key,
base_url=base_url)
response = client.chat.completions.create(
model=main_model,
messages=[
{"role": "system", "content": system_prompt},
{"role": "user", "content": user_message}
],
temperature=1,
response_format={ &qu.........完整代码请登录后点击上方下载按钮下载查看
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