autobot-swarm 2.0.0

Hierarchical multi-cluster coding swarm CLI

Autobots

Hierarchical multi-cluster coding swarm CLI powered by NVIDIA NIM models.

Autobots orchestrates multiple AI models as a hierarchical swarm to plan, implement, validate, and repair code against your target repositories. It features a complete tool system (Read, Write, Edit, Glob, Grep), interactive REPL mode, granular permissions, context management, hooks, MCP integration, and code review.

Installation

pip install autobot-swarm

Quick Start

# Set your API key
export NVIDIA_API_KEY="your_key_here"

# Navigate to your project
cd /path/to/your/project

# Initialize, plan, and run
autobots init
autobots plan --goal "Add user authentication"
autobots run --supervised

Features

Core Swarm

• 9 Specialized Clusters — Optimus (planning), UltraMagnus (backend), Jazz (frontend), RedAlert (security), Ratchet (repair), Perceptor (retrieval), Bumblebee (media), Ironhide (simulation), Wheeljack (science)
• Phase-Based Execution — Inspect, Implement, Validate, Repair pipeline
• Context Injection — Reads project documentation and injects into model prompts
• Automatic Repair — Self-healing with validation-driven repair loops
• Rollback Support — Snapshots before writes, undo reverts changes

File Operations

• Read — Read files with offset/limit, line numbers, binary/image support
• Write — Atomic writes with directory creation and path sandboxing
• Edit — Targeted string replacement with exact match, replaceAll mode
• Glob — Pattern-based file search (**/*.py)
• Grep — Regex content search across files

Interactive Mode

• REPL — Conversational session with history and streaming
• One-Shot — autobots ask "question" for quick queries
• Piped Input — cat file.py | autobots ask "explain"
• Slash Commands — /help, /clear, /cost, /compact, /model, /exit

Permissions

• Tool-Level Control — Allow/deny/ask per tool call
• Interactive Approval — y/n/a/Esc prompt
• Config Merge — Global + project + environment settings
• Audit Logging — JSON-lines log of all decisions

Context Management

• Token Tracking — Real-time token usage and budget display
• Auto-Compaction — Summarizes conversation at 80% threshold
• CLAUDE.md Hierarchy — Global, project, and subdirectory instructions

Extensions

• Hooks — Pre/post tool execution callbacks
• MCP — Model Context Protocol server integration
• Plugins — Custom extensions via hook system

Code Review

• Git Diff Review — Analyze changes for issues
• Doctor Command — Health checks for API, connectivity, Python, package

CLI Commands

Command	Description
autobots init	Initialize context files
autobots plan	Generate implementation roadmap
autobots run	Execute with autonomy mode
autobots resume	Resume from checkpoint
autobots ask	One-shot question
autobots steer	Add steering instructions
autobots status	Rich status display
autobots explain	Show audit trail
autobots stats	Usage statistics
autobots undo	Rollback changes
autobots doctor	Health checks
autobots catalog	Browse model registry

Configuration

Create .autobots.toml in your project root:

[autobots]
model_selection_profile = "balanced"
default_mode = "supervised"
milestone_threshold = 3
temperature = 0.2
max_tokens = 4096

Execution Modes

• Supervised — Manual approval per phase (default)
• Milestone — Approval every N phases
• Autonomous — No approval gates

Requirements

• Python 3.11+
• NVIDIA API Key

Links

• GitHub: https://github.com/DanielDeshmukh/autobots
• Issues: https://github.com/DanielDeshmukh/autobots/issues
• PyPI: https://pypi.org/project/autobot-swarm/

License

MIT