Update README.md

README.md

@@ -19,20 +19,27 @@ library_name: pytorch
 ## 🏛️ Powered by Alrithm
 This project is fundamentally built upon and inspired by the vision of **[Alrithm](https://alrithmapi.vercel.app)**. 
 
-- **Data Source:** The machine learning models in this project were fine-tuned exclusively on the **`alr-aerospace-platform-0.2`** dataset, fetched via the official Alrithm API (`https://alrithmapi.vercel.app/api/v1/models`).
+- **Data Source:** The current model version is trained on a specific subset of the **`alr-aerospace-platform-0.2`** dataset (targeting the `max_q_kpa` quantity), fetched via the official Alrithm API.
 - **Philosophy:** Alrithm provides rigorously verified, high-fidelity aerospace data. ALRITHM-Astro serves as a demonstration of how developers can leverage Alrithm's verified data streams to build real-time, physics-informed AI applications.
 
 ## ✨ Features
 - **Natural Language Processing:** Understands complex aerospace queries using Groq's LLMs (`openai/gpt-oss-120b`).
-- **Physics-Informed Prediction:** Calculates Max Q with high precision using a custom PyTorch Neural Network trained on Alrithm's verified aerospace data.
+- **Physics-Informed Prediction:** Calculates Max Q with high precision using a custom PyTorch Neural Network.
 - **Interactive 3D Visualization:** Renders the rocket's 3D trajectory in real-time using Plotly.js.
 - **Full-Stack Architecture:** FastAPI backend (Render) + Vanilla JS frontend (Vercel).
 
-## 🧠 Model Details
+## 🧠 Model Details (Version 0.2 - Max Q Specialist)
 - **Architecture:** Multi-Layer Perceptron (MLP) with 256 hidden units and SiLU activation.
 - **Input Features:** 13 engineered physical features (e.g., Burnout Velocity, Thrust-to-Weight Ratio, Mass Ratio).
 - **Output:** Maximum Dynamic Pressure (`max_q_kpa`).
-- **Training:** 5-Fold Cross-Validation (Fine-tuned on Alrithm data).
+- **Training:** 5-Fold Cross-Validation (Fine-tuned specifically on the `max_q_kpa` subset of the Alrithm dataset).
+
+> ⚠️ **Current Limitation:** This `v0.2` model is a **Single-Task** surrogate model. It is currently specialized only for `max_q_kpa`. It has *not yet* been trained on the entire 4600+ dataset across all task types.
+
+## 🗺️ Roadmap (Next Steps)
+- [x] **Phase 1:** Build the End-to-End Pipeline (Data -> Neural Network -> FastAPI -> Vercel).
+- [x] **Phase 2:** Train a Single-Task Model for `max_q_kpa`.
+- [ ] **Phase 3:** Implement **Multi-Task Learning (MTL)** using the full 4600+ `alr-aerospace-platform-0.2` dataset to predict all quantities (Apogee, Burnout Speed, etc.) simultaneously.
 
 ## 🛠️ How to use this model