GitHub Copilotを超える！GitHub×OpenAI 実践編：効率的なコード開発のステップバイステップガイド

pip install PyGithub openai

export GITHUB_ACCESS_TOKEN='your_github_access_token'
export OPENAI_ACCESS_TOKEN='your_openai_access_token'

import os

github_access_token = os.environ['GITHUB_ACCESS_TOKEN']
openai_access_token = os.environ['OPENAI_ACCESS_TOKEN']

from github import Github

def get_github_repo(repo_name, access_token):
    github = Github(access_token)
    repo = github.get_repo(repo_name)
    return repo

def get_files_in_directory(repo, directory):
    contents = repo.get_contents(directory)
    files = [content for content in
    contents if content.type == "file"]
    return files

def create_directory_structure_text(files):
    code_snippets = "Code Snippets:\n"
    dir_structure = f"Directory Structure:\n- {clone_dir}\n"
    dir_list = []
    for file in files:
        splitted_path = file.path.split('/')
        if len(splitted_path) > 1:
            parent_dir = splitted_path[-2]
            file_name = splitted_path[-1]
            if parent_dir not in dir_list:
                dir_structure += f"  - {parent_dir}: Describe the purpose of {parent_dir}\n"
                dir_list.append(parent_dir)
            dir_structure += f"    - {file_name}: Describe the purpose of {file_name}\n"
            content = get_file_contents(repo, file.path)
            code_snippets += f"- {parent_dir}/{file_name}:\n```python\n"
            code_snippets += f"{content}\n"
            code_snippets += "```\n"
            
    return dir_structure, code_snippets

import openai

# Replace 'your_openai_api_key' with your actual OpenAI API key

openai.api_key = "your_openai_api_key"

# or Replace 'your_azure_openai_api_key' and 'your_azure_openai_api_base' with your actual Azure OpenAI Service API Key

openai.api_type = "azure"
openai.api_base = f"https://{your_azure_openai_api_base}.openai.azure.com/"
openai.api_version = "2023-03-15-preview"
openai.api_key = "your_azure_openai_api_key"

def analyze_code_with_openai(code, dir_structure_text, prompt):
    messages=[
        {"role": "system", "content": prompt},
        {"role": "user", "content": dir_structure_text},
        {"role": "user", "content": code}
    ]
    response = openai.ChatCompletion.create(
        engine="gpt-4",
        messages=messages
    )

    suggestion = response.choices[0].text.strip()
    return suggestion

files = get_files_in_directory(repo, directory)
dir_structure_text, code = create_directory_structure_text(files)

prompt = "Analyze the following Python code for potential improvements and bugs:\n```python\n{code}\n```\nSuggestions:"
analysis_result = analyze_code_with_openai(code, dir_structure_text, prompt)