Copilot API exposes GitHub Copilot through an OpenAI and Anthropic-compatible API, enabling direct usage with Claude Code. Operations teams can integrate AI-powered code suggestions into their workflows, improving developer productivity and code quality. Connects to GitHub Copilot, Claude Code, and other AI models.
git clone https://github.com/prassaaa/copilot-api.gitCopilot API exposes GitHub Copilot through an OpenAI and Anthropic-compatible API, enabling direct usage with Claude Code. Operations teams can integrate AI-powered code suggestions into their workflows, improving developer productivity and code quality. Connects to GitHub Copilot, Claude Code, and other AI models.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/prassaaa/copilot-apiCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
I'm working on a [PROGRAMMING_LANGUAGE] project in [PROJECT_NAME]. Here's the relevant code: [CODE_SNIPPET]. I need help with [SPECIFIC_TASK]. Provide suggestions for improving this code, including explanations for your recommendations. Use the Copilot API to generate these suggestions.
Based on your Python project 'DataProcessor' and the provided code snippet for the 'data_cleaner.py' module, here are my suggestions:
1. **Vectorization Suggestion**: The current loop for data cleaning can be vectorized using pandas' built-in functions. This will significantly improve performance for large datasets. Here's the suggested code:
```python
# Original code
for index, row in df.iterrows():
if pd.isna(row['value']):
df.at[index, 'value'] = row['default_value']
# Suggested vectorized version
df['value'] = df.apply(lambda row: row['default_value'] if pd.isna(row['value']) else row['value'], axis=1)
```
2. **Error Handling**: Add comprehensive error handling for file operations. The current implementation lacks proper exception handling for file I/O operations, which could lead to crashes or data corruption.
3. **Type Hints**: Add type hints to the function signatures. This will improve code readability and enable better IDE support. The Copilot API suggests the following additions:
```python
from typing import Dict, Any
def load_config(file_path: str) -> Dict[str, Any]:
...
```
4. **Logging**: Implement logging for critical operations. This will help with debugging and monitoring the application's behavior in production.AI assistant built for thoughtful, nuanced conversation
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