Update README.md

README.md

@@ -1,3 +1,77 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+language:
+- en
+tags:
+- finance
+- reinforcement-learning
+- gym
+- trading
+- backtesting
+- rust
+pretty_name: Chapaty Environments
+---
+
+# Chapaty Environments
+
+[![Discord](https://img.shields.io/discord/1495690333911257108.svg?label=Discord&logo=discord&color=7289da&logoColor=white)](https://discord.gg/k7GWpDQC)
+[![GitHub](https://img.shields.io/badge/GitHub-Chapaty-blue?logo=github)](https://github.com/LenWilliamson/chapaty)
+[![Crates.io](https://img.shields.io/crates/v/chapaty.svg)](https://crates.io/crates/chapaty)
+
+This dataset repository hosts the pre-compiled financial environments for [**Chapaty**](https://github.com/LenWilliamson/chapaty), a high-performance, async-first Rust library for reinforcement learning in financial markets. 
+
+Inspired by OpenAI Gymnasium, these datasets provide standardized, easily reproducible simulation states for training and backtesting agents.
+
+## What are these files?
+
+The datasets here are serialized using `.postcard` (a highly efficient binary format for Rust). They contain environment configurations based on the version of the crate you are using. 
+
+## Versioning
+
+This repository uses **branches** to align with Chapaty crate releases (e.g., `v1.1.0`). 
+When you use Chapaty in Rust, the library automatically binds to the correct branch matching your crate version, ensuring your agents are always evaluated on consistent data.
+
+## Usage in Rust
+
+**Fast Track:** Use the [**Chapaty Starter Template**](https://github.com/LenWilliamson/chapaty-template) to instantly bootstrap a new project. It includes pre-configured AI prompts for backtesting with a LLM of your choice, built-in dashboard setups with [Quantstats](https://github.com/ranaroussi/quantstats), and best-practice strategy examples.
+
+You do not need to download these files manually. Use the Chapaty crate to load them directly into your async Rust application:
+
+```rust
+use anyhow::{Context, Result};
+use chapaty::prelude::*;
+
+#[tokio::main]
+async fn main() -> Result<()> {
+    // Select a preset (e.g., Daily BTC/USDT with SMA 20 & 50)
+    let preset = EnvPreset::BinanceBtcUsdt1dSma20Sma50;
+    
+    // Configure I/O to fetch seamlessly from Hugging Face
+    let filename = preset.to_string();
+    let loc = StorageLocation::HuggingFace { version: None };
+    let cfg = IoConfig::new(loc).with_filename(&filename);
+
+    // Load the environment (downloads and caches locally on first run)
+    let mut env = chapaty::load(preset, &cfg)
+        .await
+        .context("Failed to load trading environment")?;
+        
+    println!("Successfully loaded environment for {}!", preset);
+    
+    Ok(())
+}
+```
+
+## Available Presets
+
+Presets encode exact data source IDs to reproduce identical environments. Current presets include:
+
+* `binance_btc_usdt1d`: BTC/USDT Daily Spot
+* `ninja_trader_cme6eh6_1m_5m_us_emp_high`: EUR/USD 1m/5m Futures with US Employment News
+* `binance_btc_usdt1h_1m_volume_profile1d_100_usdt`: BTC/USDT Multi-resolution Spot with Volume Profile
+* *(And many more—see the [Chapaty Crate Documentation](https://docs.rs/chapaty) for the full `EnvPreset` list).*
+
+## Disclaimer
+
+**Trading and investing involve substantial risk. You may lose some or all of your capital.**
+These datasets and the Chapaty library are provided for **research and educational purposes only** and do not constitute financial advice.