AI Coding Assistant

AI Coding Assistant is an advanced tool for software developers, offering features like code generation, inline suggestions, and detailed code explanations. It leverages OpenAI models, including o1 and GPT-4, to streamline development workflows.

Features

• Code Generation: Create well-structured code based on textual prompts.
• Code Explanation: Understand the functionality of complex code snippets.
• Inline Suggestions: Get context-aware code completions within your editor.
• Prompt History: View and revisit previous prompts and responses.

Architecture Overview

The project consists of two main components:

1. Backend (FastAPI): A server handling requests for code generation, explanation, and history management using OpenAI APIs and MongoDB for data storage.
2. VS Code Extension: An extension to integrate AI-driven features directly into Visual Studio Code.

Setup and Installation

Follow these steps to set up the project:

Prerequisites

• Python 3.9+
• Node.js 16+
• Visual Studio Code
• MongoDB instance
• OpenAI API Key

Backend Setup

1. Clone the repository and navigate to the backend directory:

   git clone <repository-url>
   cd backend

2. Install dependencies:

   pip install -r requirements.txt

3. Create a .env file in the backend directory with the following contents:

   OPENAI_API_KEY=Your-OpenAI-Key
   MONGODB_URI=Your-Database-URI
   MONGODB_DBNAME=Your-Database-Name
   

4. Start the backend server:

   uvicorn app:app --reload

   The server will run at http://127.0.0.1:8000.

VS Code Extension Setup

1. Navigate to the vscode-extension directory:

   cd vscode-extension

2. Install dependencies:

   npm install

3. Build the extension:

   npm run compile

4. Open the project in Visual Studio Code and press F5 to launch a new VS Code instance with the extension loaded.

Usage

Backend Endpoints

The backend exposes the following endpoints:

• POST /generate-code: Generate code based on a prompt.

  {
    "prompt": "Create a Python function to calculate the factorial of a number."
  }

• POST /explain-code: Explain a code snippet.

  {
    "code": "def factorial(n): return 1 if n == 0 else n * factorial(n-1)"
  }

• GET /history: Retrieve the last 20 prompt-response pairs.

• POST /suggest-code: Get inline suggestions for partial code and optional workspace context.

  {
    "partial_code": "def add_numbers(a, b): return a +",
    "workspace_context": ["other_code_snippets"]
  }

VS Code Extension Features

• Generate Code: Use the AI Assistant: Generate Code command to create code from a prompt.
• Explain Code: Select a snippet and use AI Assistant: Explain Code for detailed explanations.
• Show History: View previous prompts and responses via AI Assistant: Show Prompt History.
• Inline Suggestions: Type in the editor to receive context-aware completions.

Development

Backend

• Run the server locally with uvicorn for live development.
• Modify Python files in the backend directory as needed.

Extension

• Use npm run watch to continuously build the extension while editing TypeScript files.
• Debug directly in VS Code using the preconfigured launch settings in .vscode/launch.json.