Web3 AI Trading Agent for Solana & Bitcoin

📩 Contact: @lorine93s

A hands-on walkthrough for building autonomous AI-powered trading agents on Solana and Bitcoin.
This guide is optimized for developers and researchers interested in AI trading bots, Web3 automation, and blockchain-based financial agents.

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⚠️ Disclaimer: This repository is for learning and research only.
Not production-ready. Use at your own risk.

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🚀 Overview

This project demonstrates how to build an AI-powered trading agent that operates across Solana (SPL token ecosystem, Serum/DEX swaps) and Bitcoin (via Lightning & on-chain data).

We move from manual trading to automated bots, and finally to AI agents powered by fine-tuned machine learning models.

Core Features

• Cross-chain trading: Supports Solana SPL tokens and Bitcoin transactions
• AI-driven decisions: Fine-tuned local language models for strategy execution
• Local-first design: Maximal privacy and control, minimal external dependencies
• Synthetic data & RL: GAN-generated trading data + reinforcement learning optimizations
• Research-focused: Transparency, reproducibility, and modular design

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📑 Table of Contents

1. Stack — Technology stack & setup
2. Pipeline — Trading agent architecture overview
3. Implementation — From manual to autonomous agents
4. Stateless Agent — AI trading bot without memory
5. Stateful Agent — Memory-enabled adaptive trading
6. Fine-tuning — Training custom financial AI models
7. Synthetic Data — GAN-based market data generation
8. Knowledge Distillation — Teacher → student compression
9. Model Deployment — Ollama & local inference
10. Reinforcement Learning — Strategy optimization

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⚙️ Stack

Blockchain Infrastructure

• Solana

  • Fast, high-throughput L1 with sub-second finality
  • SPL token trading on Serum DEX and AMMs
  • Integration via solana-py

• Bitcoin

  • On-chain swap simulations with UTXO-based strategies
  • Lightning Network APIs for off-chain trading experiments
  • Market data sourced via Chainstack BTC nodes

• Chainstack Nodes

  • Enterprise-grade RPC endpoints for Solana & Bitcoin
  • 99.99% uptime, global edge distribution, low-latency trading

AI / ML Stack

• PyTorch — Deep learning framework for GANs & neural networks
• Ollama — Local LLM inference for secure, offline AI agents
• Apple MLX-LM / Unsloth — Efficient fine-tuning on Apple Silicon & GPUs
• Gymnasium — Reinforcement learning environments for trading strategies

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🛠 Installation

git clone https://github.com/your-username/solana-bitcoin-ai-trading-agent.git
cd solana-bitcoin-ai-trading-agent
pip install -r requirements.txt

Dependencies include:

• Blockchain: solana, bit, web3.py
• AI/ML: torch, mlx, gymnasium, stable-baselines3
• Data: pandas, numpy

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📊 Development Pipeline

The trading agent evolves in 3 stages:

1. Manual Trading

   • Execute swaps manually on Solana DEX / Bitcoin testnet
   • Gain familiarity with raw blockchain mechanics

2. Bot Automation

   • Scripted trading bots for BTC/USDT and SOL/USDC pairs
   • Programmatic swaps via RPC

3. AI Agents

   • Intelligent decision-making with LLMs
   • Memory-enabled agents adapt to market conditions
   • Reinforcement learning strategies

graph TD
    A[Manual Trading] --> B[Automated Bots]
    B --> C[Stateless AI Agent]
    C --> D[Stateful AI Agent]
    D --> E[Synthetic Data (GANs)]
    E --> F[Knowledge Distillation]
    F --> G[Reinforcement Learning]
    G --> H[Final Autonomous Agent]

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📚 References

• Solana Docs
• Bitcoin Developer Guide
• Chainstack Nodes
• Ollama Models
• Hugging Face

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✅ Summary

This repo provides a research-focused AI trading agent framework for Solana and Bitcoin. From manual swaps to autonomous AI models, you’ll learn the end-to-end pipeline for building Web3 trading systems.

📩 Contact

Telegram: @lorine93s