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Multi-model AI coding assistant CLI supporting local LLMs, GPT-4, Claude, Gemini, and more","maintainers":[{"name":"novolabs","email":"mitchel.novoa@gmail.com"}],"readme":"# Awaitter Lite\n\n<div align=\"center\">\n\n[![npm version](https://img.shields.io/npm/v/awaitter-lite.svg)](https://www.npmjs.com/package/awaitter-lite)\n[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)\n[![Downloads](https://img.shields.io/npm/dm/awaitter-lite.svg)](https://www.npmjs.com/package/awaitter-lite)\n[![GitHub](https://img.shields.io/github/stars/awaitter/awaitter-lite?style=social)](https://github.com/awaitter/awaitter-lite)\n\n**An open-source AI coding assistant CLI that executes tasks — not just suggests them.**\n\nSupports local models (Ollama) and cloud APIs. Single-agent and multi-agent modes. Persistent sessions, undo system, and structured project planning built in.\n\n[Quick Start](#quick-start) · [Models](#supported-models) · [Commands](#commands) · [Multi-Agent](#multi-agent-mode) · [Local Setup](#local-models-ollama)\n\n</div>\n\n---\n\n## Overview\n\nAwaitter Lite is a terminal-based AI coding assistant that integrates directly with your filesystem. It reads, writes, and edits files, runs shell commands, and tracks project progress across sessions — without losing context.\n\nIt supports over 20 models across 7 providers, and can run entirely offline using local models via Ollama.\n\n---\n\n## Quick Start\n\n```bash\nnpm install -g awaitter-lite\n\n# Launch\nawaitter-lite\n# or\naw\n\n# First time: run the configuration wizard\n> /setup\n```\n\n---\n\n## Core Capabilities\n\n### Direct Code Execution\n\nAwaitter doesn't output suggestions for you to copy — it acts on your codebase:\n\n- **Read** files and entire project trees\n- **Write** new files with generated content\n- **Edit** existing files in place\n- **Run** shell commands (npm, pip, cargo, git, etc.)\n- **Search** using glob patterns and grep\n\n### Structured Project Planning\n\nFor complex tasks, Awaitter automatically generates a sprint-based roadmap before executing:\n\n```\n> Create a REST API with authentication, rate limiting, and PostgreSQL\n\n  Roadmap: 4 sprints, 18 tasks\n\n  Sprint 1 — Database & Models\n    1.1  Initialize PostgreSQL schema\n    1.2  Create SQLAlchemy models\n    1.3  Set up Alembic migrations\n\n  Sprint 2 — Authentication\n    2.1  Implement JWT token logic\n    2.2  Password hashing with bcrypt\n    2.3  Login / register endpoints\n  ...\n```\n\nProgress is tracked per task and persists across sessions and model switches.\n\n### Execution Modes\n\nControl how much autonomy Awaitter has:\n\n| Mode | Behavior |\n|------|----------|\n| **Unstoppable** | Executes the full roadmap without pausing |\n| **Sprint** *(default)* | Completes one sprint, then waits for confirmation |\n| **Step-by-step** | Pauses after every individual task |\n\nSwitch at any time: `/mode sprint`, `/mode unstoppable`, `/mode step-by-step`\n\n### Session Persistence & Undo\n\n- Sessions are auto-saved every 5 messages, scoped to the working directory\n- Resume previous work with `/sessions load <id>`\n- Undo any number of file operations with `/undo [n]`\n- View full snapshot history with `/snapshots`\n\n### Model Hot-Swapping\n\nSwitch between models mid-project without losing context. The roadmap, conversation history, and progress all carry over:\n\n```bash\n> /models\n  # Select a different provider or model\n  # Roadmap and session state preserved\n```\n\n---\n\n## Multi-Agent Mode\n\n`/multi` spawns a team of specialized agents that divide and execute complex tasks in parallel:\n\n| Agent | Role |\n|-------|------|\n| **Architect** | Analyzes the codebase, designs structure, plans implementation |\n| **Backend** | Implements server-side logic, APIs, databases |\n| **Frontend** | Builds UI components, styles, client-side logic |\n| **QA** | Writes and runs tests, validates correctness |\n\nEach agent has its own system prompt, tool access, and message history. A shared context bus lets agents communicate results to each other.\n\n```bash\n> /multi build a task management API with React frontend and Jest tests\n```\n\nDangerous commands (file deletion, `npm audit fix --force`, process termination) require explicit confirmation before any agent executes them.\n\n---\n\n## Charl Language Support\n\nAwaitter has built-in expert knowledge of [Charl](https://github.com/charlcoding-stack/charlcode), a statically-typed language for ML/AI research.\n\nWhen `.ch` files are detected in the working directory, the full Charl reference is automatically injected into every agent's context — including built-in functions, tensor operations, neural network primitives, optimizer APIs, and common mistakes to avoid.\n\nNo configuration required. Run `aw` from a Charl project directory and agents will work in Charl natively.\n\n```bash\ncd ~/Projects/my-charl-project   # contains .ch files\naw\n\n> create a two-layer neural network that learns XOR with backprop\n```\n\n---\n\n## Supported Models\n\n### Local Models — via Ollama\n\nRun entirely on your machine. No API keys, no usage limits, no data sent externally.\n\n| Model | Params | Context | Min RAM | Command |\n|-------|--------|---------|---------|---------|\n| Qwen 2.5 Coder 1.5B | 1.5B | 4K | 4 GB | `aw --model qwen-1.5b` |\n| Qwen 2.5 Coder 7B | 7B | 8K | 8 GB | `aw --model qwen-7b` |\n| Qwen 2.5 Coder 14B | 14B | 8K | 16 GB | `aw --model qwen-14b` |\n| Qwen 2.5 Coder 32B | 32B | 16K | 32 GB | `aw --model qwen-32b` |\n| DeepSeek Coder v2 | 16B | 16K | 16 GB | `aw --model deepseek` |\n| Codestral 22B | 22B | 32K | 24 GB | `aw --model codestral` |\n\nAwaitter handles model detection and download automatically:\n\n```bash\naw --model qwen-7b\n\n  Checking model: qwen2.5-coder:7b\n  Not found locally. Download now? (4.7 GB) [y/n]: y\n  Downloading...\n  Ready.\n```\n\n### Cloud APIs\n\n#### Free Tier\n\n| Provider | Model | Context |\n|----------|-------|---------|\n| Google | Gemini 2.0 Flash | 1M tokens |\n| Google | Gemini 1.5 Pro | 2M tokens |\n| Groq | Llama 3.3 70B | 128K tokens |\n| Groq | Qwen 2.5 32B | 32K tokens |\n\n#### Paid APIs\n\n| Provider | Model | Context |\n|----------|-------|---------|\n| OpenAI | GPT-4 Turbo | 128K |\n| OpenAI | O1 Preview | 128K |\n| Anthropic | Claude 3.5 Sonnet | 200K |\n| Anthropic | Claude 3 Opus | 200K |\n| xAI | Grok 2 | 128K |\n| DeepSeek | DeepSeek Coder | 16K |\n\n---\n\n## Setup\n\n### API Keys\n\n**In-CLI wizard:**\n```bash\n> /setup\n```\n\n**Direct configuration:**\n```bash\n> /apikey google AIza...\n> /apikey openai sk-...\n> /apikey anthropic sk-ant-...\n```\n\n**Environment variables:**\n```bash\nexport GOOGLE_API_KEY=\"AIza...\"\nexport GROQ_API_KEY=\"gsk_...\"\nexport OPENAI_API_KEY=\"sk-...\"\nexport ANTHROPIC_API_KEY=\"sk-ant-...\"\nexport XAI_API_KEY=\"xai-...\"\nexport DEEPSEEK_API_KEY=\"...\"\n```\n\n### Local Models (Ollama)\n\n```bash\n# Linux\ncurl -fsSL https://ollama.ai/install.sh | sh\n\n# macOS / Windows: download from https://ollama.com/download\n\n# Then launch Awaitter — it handles the rest\naw --model qwen-7b\n```\n\n---\n\n## Commands\n\n### Session & History\n```\n/sessions              List saved sessions\n/sessions load <id>    Resume a previous session\n/undo [n]              Undo last n file operations (default: 1)\n/snapshots             View full snapshot history\n/clear                 Clear current conversation\n```\n\n### Project & Planning\n```\n/roadmap               Show current roadmap and task progress\n/mode <mode>           Set execution mode: unstoppable | sprint | step-by-step\n/multi <task>          Launch multi-agent team for a task\n```\n\n### Models & Config\n```\n/models                List and switch models (context preserved)\n/apikey <provider> <key>  Set an API key\n/setup                 Interactive configuration wizard\n/hardware              Analyze system hardware and model compatibility\n```\n\n### Utilities\n```\n/context               Show conversation token usage and stats\n/tools                 List available tools\n/help                  Show all commands\n/exit                  Exit the CLI\n```\n\n---\n\n## Git Integration\n\nAwaitter has native git tool support. You can use natural language for git operations:\n\n```\n> commit everything with message \"add authentication middleware\"\n> show me what changed in the last 3 commits\n> create a branch called feature/payment-api\n```\n\nAvailable git tools: `git_status`, `git_diff`, `git_log`, `git_branch`, `git_add`, `git_commit`.\n\n---\n\n## Safety\n\nAwaitter requires explicit confirmation before executing commands classified as destructive:\n\n- `rm -rf`, `git clean -fd`, `git reset --hard`\n- `npm audit fix --force`, `pip install --upgrade` (broad)\n- `fuser -k`, `pkill`, `killall`\n- `DROP TABLE`, `DELETE FROM` without WHERE\n\nIn multi-agent mode, this confirmation gate applies to all agents.\n\n---\n\n## Hardware Recommendations\n\nRun `/hardware` to get model recommendations based on your system specs:\n\n```\n> /hardware\n\n  CPU: AMD Ryzen 9 7950X — 32 cores\n  RAM: 64 GB\n  GPU: NVIDIA RTX 4090 — 24 GB VRAM\n\n  Recommended models:\n    Local:  qwen-32b  (fits in VRAM — fast inference)\n    Cloud:  Claude 3.5 Sonnet  (best reasoning for complex tasks)\n```\n\n---\n\n## Configuration\n\nSettings are stored at `~/.config/awaitter-lite` and include:\n\n- Default model\n- Execution mode\n- Agent loop iteration limit\n- Language preference (EN / ES)\n\n---\n\n## Requirements\n\n- Node.js >= 18.0.0\n- For local models: [Ollama](https://ollama.com) installed and running\n\n---\n\n## License\n\nMIT — free to use in personal and commercial projects.\n\n---\n\n## Links\n\n- **npm:** https://www.npmjs.com/package/awaitter-lite\n- **GitHub:** https://github.com/awaitter/awaitter-lite\n- **Issues:** https://github.com/awaitter/awaitter-lite/issues\n- **Email:** support@awaitter.com\n\n---\n\n<div align=\"center\">\n\nBuilt by [NovoLabs](https://awaitter.com)\n\n</div>\n","readmeFilename":"README.md"}