Code AutoComplete

code-autocomplete, a code completion plugin for Python.

code-autocomplete实现了Python代码行粒度和块粒度自动补全功能。

Guide

Feature
Install
Usage
Contact
Citation
Reference

Feature

Demo

http://42.193.145.218/product/short_text_sim/

Install

pip3 install -U code-autocomplete

git clone https://github.com/shibing624/code-autocomplete.git
cd code-autocomplete
python3 setup.py install

Usage

Code Completion

开源项目：code-autocomplete，可支持GPT2模型，通过如下命令调用：

from autocomplete.gpt2 import Infer
m = Infer(model_name="gpt2", model_dir="shibing624/code-autocomplete-gpt2-base", use_cuda=False)
i = m.predict('import torch.nn as')
print(i)

当然，你也可使用官方的huggingface/transformers调用：

Please use 'GPT2' related functions to load this model!

import os
import torch
from transformers import GPT2Tokenizer, GPT2LMHeadModel

os.environ["KMP_DUPLICATE_LIB_OK"] = "TRUE"
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")

tokenizer = GPT2Tokenizer.from_pretrained("shibing624/code-autocomplete-gpt2-base")
model = GPT2LMHeadModel.from_pretrained("shibing624/code-autocomplete-gpt2-base")
model.to(device)
prompts = [
    """from torch import nn
    class LSTM(Module):
        def __init__(self, *,
                     n_tokens: int,
                     embedding_size: int,
                     hidden_size: int,
                     n_layers: int):""",
    """import numpy as np
    import torch
    import torch.nn as""",
    "import java.util.ArrayList",
    "def factorial(n):",
]
for prompt in prompts:
    input_ids = tokenizer.encode(prompt, add_special_tokens=False, return_tensors='pt').to(device)
    outputs = model.generate(input_ids=input_ids,
                             max_length=64 + len(prompt),
                             temperature=1.0,
                             top_k=50,
                             top_p=0.95,
                             repetition_penalty=1.0,
                             do_sample=True,
                             num_return_sequences=1,
                             length_penalty=2.0,
                             early_stopping=True)
    decoded = tokenizer.decode(outputs[0], skip_special_tokens=True)
    print(decoded)
    print("=" * 20)

Contact

Issue(建议)：
邮件我：xuming: [email protected]
微信我：加我微信号：xuming624, 备注：个人名称-公司-NLP 进NLP交流群。

Citation

如果你在研究中使用了code-autocomplete，请按如下格式引用：

@misc{code-autocomplete,
  author = {Xu Ming},
  title = {code-autocomplete: Code AutoComplete with GPT model},
  year = {2022},
  publisher = {GitHub},
  journal = {GitHub repository},
  url = {https://github.com/shibing624/code-autocomplete},
}

License

授权协议为 The Apache License 2.0，可免费用做商业用途。请在产品说明中附加code-autocomplete的链接和授权协议。

Contribute

项目代码还很粗糙，如果大家对代码有所改进，欢迎提交回本项目，在提交之前，注意以下两点：

在tests添加相应的单元测试
使用python setup.py test来运行所有单元测试，确保所有单测都是通过的

之后即可提交PR。

Reference

https://github.com/galois-autocompleter/galois-autocompleter

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Galois is an auto code completer for code editors (or any text editor) based on OpenAI GPT-2.

Galois is an auto code completer for code editors (or any text editor) based on OpenAI GPT-2. It is trained (finetuned) on a curated list of approximately 45K Python (~470MB) files gathered from the Github. Currently, it just works properly on Python but not bad at other languages (thanks to GPT-2's power).