IndoClaw

Autonomous AI Agent Operating System

An autonomous AI agent operating system inspired by OpenClaw, built with LangChain for powerful AI agent capabilities.

Active Development
LangChain Powered
Open Source

Features

Powerful capabilities that make IndoClaw a comprehensive AI agent platform

Autonomous Agent

Perception → Reasoning → Action loop with memory awareness

Memory Systems

Short-term & long-term memory with vector embeddings

Tool Ecosystem

Web search, file ops, calculations, and more

CLI Interface

Rich terminal interface with prompt support

Architecture

IndoClaw is built with a modular architecture that separates concerns and enables easy extensibility.

1
Core Agent System
2
Memory Management
3
Tool Integration
4
Agent Specialization
IndoClaw/
├── src/
│   ├── core/              # Core agent system
│   │   ├── agent.py       # Main agent with loop
│   │   ├── memory/        # Memory management
│   │   ├── planning/      # Task planning
│   │   └── tools/         # Available tools
│   ├── agents/            # Specialized agents
│   │   ├── base.py        # Base agent class
│   │   ├── researcher.py  # Research-focused agent
│   │   └── writer.py      # Writing-focused agent
│   ├── interfaces/        # User interfaces
│   │   └── cli.py         # CLI interface
│   └── config/            # Configuration
│       └── settings.py    # Configuration class
├── tests/
├── requirements.txt
└── README.md

Agent Types

Specialized agents designed for different tasks

Researcher Agent

Deep web search and analysis with information synthesis and source tracking.

Web Search Analysis Sources

Writer Agent

Content generation with format control and editing capabilities.

Articles Reports Editing

General Agent

Perception → Reasoning → Action loop with dynamic tool usage.

Autonomous Dynamic Memory-Aware

Available Tools

Powerful tools that enable IndoClaw to perform various tasks

Web Search

Search the web using Tavily API

File Ops

Read, write, list directories

Calculator

Safe mathematical expressions

LLM Call

LLM inference via LangChain

Installation

Get started with IndoClaw in minutes

1. Clone the Repository

git clone https://github.com/Authentic-Pond/IndoClaw.git
cd IndoClaw

2. Create Virtual Environment

python -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate

3. Install Dependencies

pip install -r requirements.txt

4. Configure Environment

cp src/config/.env.example src/config/.env
# Edit .env with your API keys

Quick Start

Run IndoClaw with a single command

1

Interactive Chat Mode

python -m src
2

Single Prompt

python -m src "What is 25 * 17?"
3

Research Mode

python -m src --research "Latest AI developments"
4

Writing Mode

python -m src --write "The future of technology" --format article