# AAGT: Advanced Agentic Trading Framework
> **The Rust-powered Hybrid Intelligence System for Autonomous Trading.**
AAGT is a high-performance, production-ready framework designed to solve the "Dynamic-Static Conflict" in AI Agents. It combines Rust's uncompromising safety and performance with Python's rich AI ecosystem and WASM's dynamic agility.
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## System Architecture: The Triple-Core Engine
AAGT is built on a modular "Triple-Core" architecture designed for high reliability, intelligence, and extreme extensibility.
### 1. The Guard (Rust Core) | *The Body*
Rust's type-safety and ownership model provide the foundation for execution and safety.
- **High-Performance**: Zero-cost abstractions and async-first design (Tokio) for low-latency decision making.
- **Risk Management**: Pluggable safety checks (RiskManager) with native code execution.
- **Context Management**: Advanced sliding window history management (ContextManager) to optimize reasoning and costs.
### 2. The Thinker (Python gRPC Sidecar) | *The Brain*
Offload intelligence to where it belongs—the world's most mature AI ecosystem.
- **Stateful Code Interpreter**: Integrated Jupyter ipykernel allows the agent to maintain variables and state across multiple execution cells.
- **Ecosystem Integration**: Seamless access to LangChain, NumPy, Pandas, and professional quantitative libraries via gRPC.
- **Zero-Block Execution**: Ensures heavy ML reasoning doesn't block the critical trading execution loop.
### 3. The Runner (WASM Runtime) | *The Reflex*
True dynamic extensibility without recompilation.
- **Hot-Pluggable Skills**: Write skills in any language (Rust, AssemblyScript, C++) and load them as .wasm files.
- **Sandboxed Security**: Third-party plugins run in a strictly isolated WASI environment with zero access to the host private keys or sensitive OS resources.
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## Memory System (aagt-qmd)
AAGT features a **Content-Addressable Hybrid Search** engine for deep historical reasoning:
- **Dual-Layer Persistence**:
- **Short-Term**: Atomic JSON (Temp-then-Replace) for microsecond session recovery.
- **Long-Term**: aagt-qmd Hybrid Search (BM25 + Vector) for token-efficient RAG (~90% savings).
- **100x Faster Retrieval**: SQLite FTS5 backend ensures 5ms searches even with 100K+ historical documents.
- **Privacy First**: Zero cloud dependencies. Your strategies and history stay on your infrastructure.
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## Guardrails & Security
AAGT is "Safe-by-Design":
- **Risk Checks**: Built-in SingleTradeLimit, DailyVolumeLimit, HoneypotDetection, and SlippageCheck.
- **Approval Policies**: Fine-grained control with Auto-Run vs Human-in-the-Loop (via Telegram/Discord/Webhooks).
- **Isolation**: Physical and logical data separation between different User IDs and Agent IDs.
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## Multi-Provider Support
Native support for LLMs via a unified Provider trait:
- **Cloud**: OpenAI, Anthropic (Claude), Gemini.
- **Fast Inference**: Groq (0.5s decision time).
- **Privacy & Local**: Ollama.
- **Open Standards**: OpenRouter, DeepSeek, Moonshot.
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## Quick Start
```rust
use aagt_core::prelude::*;
use aagt_providers::openai::OpenAI;
#[tokio::main]
async fn main() -> anyhow::Result<()> {
// 1. Initialize Intelligence
let provider = OpenAI::from_env()?;
// 2. Build Agent with Hybrid Capabilities
let agent = Agent::builder(provider)
.model("gpt-4o")
.with_code_interpreter() // Stateful Python sidecar
.with_wasm_skills("skills/") // WASM hot-swappable plugins
.with_memory_path("data/") // Hybrid search RAG
.build()?;
// 3. Start Secure Execution
let response = agent.prompt("Analyze SOL/USDT market depth and plot a 14-day RSI.").await?;
println!("Agent Analysis: {}", response);
Ok(())
}
```
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## Support & License
- **License**: MIT / Apache 2.0
- **Donate**:
- **Solana**: `9QFKQ3jpBSuNPLZQH1uq5GrJm4RDKue82zeVaXwazcmj`
- **Base**: `0x4cf0b79aea1c229dfb1df9e2b40ea5dd04f37969`
**Built by Traders, for Developers.**