randebu/README.md

Randebu

Create Trading Bots Through Natural Conversation

Randebu is a web-based platform that allows traders to create and manage automated trading bots through simple chat interactions. No coding required.

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The Problem

Trading bots like OpenClaw and similar platforms are powerful but come with a steep learning curve:

• Complex configuration files
• Requires understanding of trading strategies
• CLI-based interfaces
• Steep technical barrier for non-developers

The Solution

Randebu lets you create trading bots by simply chatting:

"Create a bot that buys PEPE when it drops 5% and sells when it profits 10%"

That's it. Randebu handles the rest.

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How It Works

1. Chat - Tell Randebu what you want in plain English
2. Bot Created - Randebu creates a configured trading bot
3. Backtest - Test your strategy with historical data
4. Simulate - Run a simulation with real-time data
5. Deploy - Activate your bot on the blockchain

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Built on AVE Cloud

Randebu is powered by AVE Cloud Skills - the same infrastructure used by professional trading teams.

AVE Skills Currently Integrated

Randebu uses AVE Cloud Skills (the skill scripts from ave-cloud-skill repository) for data fetching:

Skill Script	Command	Purpose	Line in agent.py
ave_data_rest.py	trending	Get trending tokens	218
ave_data_rest.py	search	Search tokens by keyword	285
ave_data_rest.py	risk	Honeypot/risk analysis	367
ave_data_rest.py	token	Get token details	487
ave_data_rest.py	price	Get token prices	509

AVE Integration Points

The AVE skills are called through _call_ave_script() in agent.py:

# agent.py - Calling AVE skill scripts
def _call_ave_script(self, command: str, args: list) -> tuple[int, str]:
    ave_skill_path = os.path.join(
        repo_root, "ave-cloud-skill", "scripts", "ave_data_rest.py"
    )
    result = subprocess.run(
        ["python3", ave_skill_path, command] + args,
        ...
    )

Direct API Usage (Not Skills)

These components use the AVE API directly (not through skills):

• backtest/engine.py - Uses AveCloudClient.get_klines() for historical kline data
• simulate/engine.py - Uses AveCloudClient.get_klines() for real-time kline data

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Further AVE Integration Opportunities

1. Trading Execution (Priority: High)

• AVE Skills: trade-chain-wallet, trade-proxy-wallet
• Use: Execute trades directly from the bot (market orders, limit orders, TP/SL)
• Status: Not yet integrated - this is the next major feature

2. Real-Time Alerts (Priority: Medium)

• AVE Skills: WebSocket streams (data-wss)
• Use: Notify users when price hits targets

3. Portfolio Tracking (Priority: Medium)

• AVE API: address/walletinfo endpoint
• Use: Show user's complete portfolio across chains

4. Advanced Risk Analysis (Priority: Low)

• AVE Skills: Extended token analysis
• Use: More detailed honeypot detection, liquidity analysis

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Tech Stack

Component	Technology
Frontend	SvelteKit, TypeScript
Backend	FastAPI, Python
Database	PostgreSQL
AI	MiniMax (extended thinking)
Trading Data	AVE Cloud API

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Future Development Plan

Phase 1: Core MVP (Current)

• Chat-based bot creation
• Strategy configuration via conversation
• Backtest historical data
• Simulation with real-time data
• Bot management (create, list, set)

Phase 2: Trading Execution

• AVE Trading API integration
• Chain wallet support
• Proxy wallet (bot-managed) support
• TP/SL automation

Phase 3: Advanced Features

• Portfolio dashboard
• Multi-chain support (Solana, Base, ETH)
• Copy trading (follow other traders)
• Strategy marketplace

Phase 4: Platform Growth

• Strategy templates
• Community strategies
• Premium features (for fees)

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Business Opportunity

Target Market

1. Retail Traders - People who want to automate trading but can't code
2. Crypto Enthusiasts - Active traders looking for easier tools
3. Small Funds - Need automation without expensive developers

Revenue Model

Tier	Price	Features
Free	$0	1 bot, 50 chats, basic features
Pro	$19/mo	Unlimited bots, backtests, simulations
Enterprise	Custom	API access, priority support, custom integrations

Competitive Advantage

• No-code - Unlike OpenClaw, 3Commas, Cryptohopper
• Natural Language - Describe strategy in plain English
• AVE Integration - Built on professional-grade infrastructure
• Focused UX - Simple, clean interface designed for beginners

Market Size

• Crypto traders: 100M+ globally
• Trading bot market: $1.5B+ by 2027
• No-code platform market: Growing rapidly

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Getting Started

Prerequisites

• Python 3.10+
• Node.js 18+
• PostgreSQL

Installation

# Clone the repo
git clone https://github.com/shoko/randebu.git
cd randebu

# Setup backend
cd src/backend
pip install -r requirements.txt

# Setup frontend
cd ../frontend
npm install

# Configure environment
cp .env.example .env
# Edit .env with your API keys

# Run
# Backend: uvicorn main:app
# Frontend: npm run dev

Configuration

Required environment variables:

• MINIMAX_API_KEY - For AI chat
• AVE_API_KEY - For trading data
• DATABASE_URL - PostgreSQL connection

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Contributing

Contributions welcome! Please read our contributing guidelines before submitting PRs.

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License

MIT

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Links

• Website: randebu.com
• AVE Cloud: cloud.ave.ai
• Hackathon: clawhackathon.aveai.trade

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Built with ❤️ for traders, by traders