agentic-cli-coder

agentic-cli-coder

An open-source, powerful, and versatile coding agent for your terminal. agentic-cli-coder is designed to be your primary AI assistant for software development, providing a rich set of tools and features to accelerate your workflow right from the command line.

IMPORTANT:
Before installing, make sure the directory containing the agentic package (and its subfolders) is in your PATH environment variable.
This is required for the agentic command to work after installation.
For example, if you are installing in a virtual environment, activate it first, or ensure your Python scripts directory is in your PATH. Or, if you are installing on Windows, make sure to add necesarry folders to PATH based on what the cmd tells you.

✨ Features

• Multi-Provider LLM Support: Powered by LiteLLM, Agentic supports over 100 LLM providers, including OpenAI, Anthropic, Google, Mistral, and many more. You can even use local models via Ollama.
• Multiple Agent Modes: Switch between specialized agents tailored for different tasks:
  • code: A general-purpose coding assistant with a full toolset.
  • ask: A question-answering agent with web search and file reading capabilities.
  • architect: A high-level planner that designs project structures and implementation plans.
  • agent-maker: A master agent that can delegate tasks to other sub-agents.
  • memory: An agent dedicated to creating and managing project summaries.
• Retrieval-Augmented Generation (RAG): Agentic can index your entire project codebase to provide contextually-aware answers and code modifications.
• Persistent Memory: Save key information, architectural summaries, and user instructions to a persistent memory that is loaded in future sessions.
• Powerful Interactive Shell: A feature-rich interactive prompt with commands for managing conversation, configuration, and agent state.
• Sub-Agent Delegation: Break down complex tasks by creating and delegating work to specialized sub-agents.
• Comprehensive Toolset: Comes with a wide range of tools for file operations (ReadFile, WriteFile, Edit), version control (Git), shell command execution (Shell), web browsing, and more.
• Model Context Protocol (MCP) Integration: Connect to external MCP servers to extend the agent's capabilities with third-party tools.
• Secure Configuration: All sensitive information, including API keys, is encrypted on your local machine.

🚀 Installation

agentic-cli-coder is available on PyPI.

1. Install the package:

   pip install agentic-cli-coder
   

2. Install browser drivers for the Browser tool: (optional) Agentic uses Playwright for web browsing tasks. You need to install its browser drivers by first installing Playwright and then installing the browsers:

   pip install playwright
   playwright install
   

🏃‍♀️ Quick Start

1. Launch the agent:

   agentic
   

2. Configure your LLM provider: The first time you run Agentic, you will be prompted to configure it. You can also run the configuration menu at any time with the /config command.

   > /config
   

   This will open an interactive menu where you can select your provider (e.g., openai), enter your model name (e.g., gpt-4-turbo), and add your API key.

3. Start coding! Once configured, you can start interacting with the agent.

   > Please write a Python script to list all files in the current directory.
   

📖 Usage

Interactive Commands

Agentic provides a set of slash commands to manage the session:

Non-Interactive Usage

You can pipe content directly into Agentic for non-interactive tasks.

cat my_file.py | agentic "Refactor this code to be more idiomatic."

⚙️ Configuration

agentic-cli-coder stores its configuration in ~/.agentic-cli-coder/.

• config.encrypted: Encrypted file containing your settings and API keys.
• config.key: The local encryption key for your configuration.
• data/: Directory for persistent memories and RAG indexes.

The easiest way to manage your settings is through the interactive agentic config or /config command. You can set up different models for different modes, manage presets, configure RAG and memory settings, and much more.

❤️ Contributing

Contributions are welcome! Please feel free to open an issue or submit a pull request.