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A Generative AI Assistant with advance agentic capabilities. Codebuddy uses machine learning to generate code, complete tasks, and streamline coding tasks workflow.

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CodeBuddy

CodeBuddy is an AI-powered coding assistant for Visual Studio Code featuring multi-agent architecture, nine AI provider integrations, local model support, and intelligent codebase understanding. It functions as an autonomous pair programmer capable of planning, executing, and debugging complex development tasks.

Overview

CodeBuddy enhances developer productivity through AI-powered code assistance, providing intelligent code review, refactoring suggestions, optimization recommendations, and interactive chat capabilities. The extension supports both cloud-based and local AI models, enabling developers to choose the right balance of capability, speed, and privacy for their workflow.

Key Features

Multi-Agent System

CodeBuddy employs specialized agents that collaborate on complex tasks:

  • Project Manager: Orchestrates workflow and delegates tasks to specialized agents
  • Architect: Designs scalable systems, selects patterns, and creates architecture decision records
  • Reviewer: Enforces code quality, security standards, and best practices
  • Tester: Writes and validates unit and integration tests
  • Debugger: Investigates root causes and proposes fixes
  • Code Analyzer: Scans codebase for anti-patterns and complexity issues
  • Documentation Writer: Generates comprehensive documentation and API references
  • File Organizer: Refactors directory structures and manages project organization

Dual Operating Modes

Chat Mode: Traditional question-and-answer interaction for quick queries, code explanations, and getting code snippets without file modifications.

Agent Mode: Autonomous execution with full tool access including file operations, terminal commands, web search, and codebase analysis. Changes can be reviewed before application.

AI Provider Support

CodeBuddy supports nine AI providers:

Provider Default Model Capabilities
Gemini gemini-2.5-pro Long context, general coding
Anthropic claude-sonnet-4-5 Complex architecture, refactoring
OpenAI gpt-4o Reasoning, planning
DeepSeek deepseek-chat Cost-effective coding
Qwen qwen-max Strong open-weight performance
Groq llama-3.1-70b-versatile Ultra-fast inference
GLM glm-4 Chinese and English support
XGrok grok Alternative reasoning
Local qwen2.5-coder Privacy-first, offline capable

Local Model Integration

Run completely offline with local models via Ollama or LM Studio:

  • Full Agent mode support with local models
  • Zero API costs for unlimited usage
  • Code never leaves your machine
  • Supports Qwen 2.5 Coder, Llama 3.2, DeepSeek Coder, and other OpenAI-compatible models

Terminal Integration

Agents can execute shell commands directly:

  • Run builds, tests, git operations, and any shell command
  • Real-time output streaming in dedicated terminal channel
  • Safety guards with user confirmation before execution
  • Feedback loop for self-correction based on command output

Diff Review System

File changes made by the agent are tracked and reviewable:

  • Side-by-side diff viewer in VS Code
  • Apply or reject individual changes
  • Recent changes history panel
  • Optional approval mode requiring explicit confirmation before file writes

Model Context Protocol (MCP)

Extend CodeBuddy's capabilities through the open MCP standard:

  • Connect external tools and data sources
  • Add custom MCP servers for specialized functionality
  • Unified protocol for AI-tool integration

Project Rules

Customize agent behavior with project-specific rules:

  • Define coding conventions and guidelines in .codebuddy/rules.md
  • Create custom rules via the Settings UI
  • Toggle rules on/off without deletion
  • Rules are appended to the agent's system prompt

Inline Completions

Ghost text suggestions as you type:

  • Configurable completion provider (can differ from chat provider)
  • Debounce and token limit controls
  • Manual or automatic trigger modes

Context Management

Intelligent context handling for relevant responses:

  • Automatic active file inclusion
  • @ mention syntax for adding specific files
  • Token budget awareness based on model limits
  • Semantic search over indexed codebase
  • Priority system: @mentioned files, active file, auto-gathered context

Installation

Install from your preferred registry:

Alternatively, search for "CodeBuddy" in the VS Code extension manager.

Configuration

Cloud Providers

  1. Open VS Code Settings (File > Preferences > Settings)
  2. Search for "CodeBuddy"
  3. Select your preferred AI provider from the dropdown
  4. Enter your API key in the appropriate field

Local Models

Configure for Ollama or LM Studio:

{
  "generativeAi.option": "Local",
  "local.baseUrl": "http://localhost:11434/v1",
  "local.model": "qwen2.5-coder"
}

For Docker-based Ollama:

docker compose -f docker-compose.yml up -d
docker exec -it ollama ollama pull qwen2.5-coder

Settings Panel

Access comprehensive settings via the gear icon in the sidebar:

  • Account: Profile and account information
  • General: Theme, language, font settings, nickname, streaming preferences
  • Agents: Auto-approve actions, file/terminal permissions, verbose logging
  • MCP: Model Context Protocol server management
  • Conversation: Chat display preferences and history management
  • Models: AI model selection and configuration
  • Context: Workspace indexing, context window size, file inclusion settings
  • Rules and Subagents: Custom rules and specialized agent configuration
  • Privacy: Data privacy settings and clear data options
  • Beta: Experimental features
  • About: Version information and links

Data Storage

CodeBuddy stores data locally in a .codebuddy folder at your workspace root:

  • Chat history in JSON format
  • Codebase analysis database (SQLite)
  • Project rules and configuration
  • Logs and session data

This folder is automatically added to .gitignore to prevent committing sensitive data.

Troubleshooting

Connection Issues with Local Models

  • Verify Ollama or LM Studio is running
  • Check the port configuration (default: 11434 for Ollama, 1234 for LM Studio)
  • Confirm the local.baseUrl setting matches your server

Agent Not Responding

  • Use the Stop button in the chat interface
  • Clear chat history via Settings > Privacy
  • Check the CodeBuddy output channel (View > Output > CodeBuddy)

API Key Errors

  • Verify your API key is correctly entered in settings
  • Ensure the selected model matches your API key provider
  • Check for network connectivity for cloud providers

Contributing

Contributions are welcome. Please see CONTRIBUTING.md for guidelines.

License

MIT License - see LICENSE for details.


Repository: github.com/olasunkanmi-SE/codebuddy

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A Generative AI Assistant with advance agentic capabilities. Codebuddy uses machine learning to generate code, complete tasks, and streamline coding tasks workflow.

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