Update README.md

README.md

@@ -10,16 +10,48 @@ license: cc-by-nc-4.0
 
 # ⚡ Nexus-Core Inference API
 
-Fast and efficient chess move prediction API powered by Nexus-Core v2.0.
+Fast and efficient chess move prediction powered by Nexus-Core v2.0.
 
-## 🎯 Model Info
+[![Model](https://img.shields.io/badge/Model-Nexus--Core-green)](https://huggingface.co/GambitFlow/Nexus-Core)
+[![Parameters](https://img.shields.io/badge/Params-13M-orange)](https://huggingface.co/GambitFlow/Nexus-Core)
+[![Speed](https://img.shields.io/badge/Speed-Ultra--Fast-brightgreen)](https://huggingface.co/GambitFlow/Nexus-Core)
 
-- **Parameters:** 13M (ResNet-based)
-- **Speed:** Ultra-fast inference (~0.5-1s per move)
-- **Strength:** ~2000-2200 ELO
-- **Architecture:** Pure CNN value network
+## 🎯 Model Details
 
-## 📡 API Endpoint
+**Nexus-Core** is a lightweight ResNet-based chess engine optimized for speed:
+
+- **Model:** [GambitFlow/Nexus-Core](https://huggingface.co/GambitFlow/Nexus-Core)
+- **Parameters:** 13 Million
+- **Architecture:** Pure CNN (ResNet with 10 blocks)
+- **Input:** 12-channel board representation
+- **Training Data:** [GambitFlow/Elite-Data](https://huggingface.co/datasets/GambitFlow/Elite-Data) (5M+ positions)
+- **Strength:** 2000-2200 ELO estimated
+
+## 🔬 Search Algorithm
+
+Efficient alpha-beta implementation with essential optimizations:
+
+### Core Features
+- **Alpha-Beta Pruning** [^1] - Classic minimax with cutoffs
+- **Iterative Deepening** [^2] - Progressive depth increase
+- **Quiescence Search** [^3] - Tactical sequence resolution
+- **Simple Transposition Table** - 100K position cache
+
+### Move Ordering
+- **MVV-LVA** [^4] - Most Valuable Victim - Least Valuable Attacker
+- **Promotion prioritization**
+- **Check detection**
+
+## 📊 Performance
+
+| Metric | Value | Environment |
+|--------|-------|-------------|
+| **Depth 4 Search** | ~0.5-1 second | HF Spaces CPU |
+| **Average Nodes** | 5K-15K per move | Typical positions |
+| **Memory Usage** | ~2GB RAM | Peak inference |
+| **Response Time** | 500-1000ms | 95th percentile |
+
+## 📡 API Endpoints
 
 ### `POST /get-move`
 
@@ -43,18 +75,91 @@ Fast and efficient chess move prediction API powered by Nexus-Core v2.0.
 }
 ```
 
+### `GET /health`
+
+Health check endpoint.
+
 ## 🔧 Parameters
 
-- **fen** (required): Board position
-- **depth** (optional): 1-6, default 4
-- **time_limit** (optional): Max time in ms, default 3000
+- **fen** (required): Board position in FEN notation
+- **depth** (optional): Search depth (1-6, default: 4)
+- **time_limit** (optional): Max time in milliseconds (1000-10000, default: 3000)
+
+## 🚀 Quick Start
+
+```python
+import requests
+
+response = requests.post(
+    "https://YOUR-SPACE.hf.space/get-move",
+    json={
+        "fen": "rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR w KQkq - 0 1",
+        "depth": 4
+    }
+)
+
+data = response.json()
+print(f"Best move: {data['best_move']}")
+print(f"Evaluation: {data['evaluation']}")
+```
+
+## 💻 Use Cases
 
-## 💻 Performance
+Perfect for:
+- **Online chess platforms** - Fast response times
+- **Training applications** - Consistent ~2000 ELO play
+- **Mobile apps** - Lightweight inference
+- **Rapid/Blitz games** - Quick move generation
 
-- **Average Response:** 0.5-1 second @ depth 4
-- **Memory Usage:** ~2GB RAM
-- **Concurrent Requests:** 4-6 simultaneous
+## 📚 Research References
+
+[^1]: **Alpha-Beta Pruning**: Knuth, D. E., & Moore, R. W. (1975). "An analysis of alpha-beta pruning". *Artificial Intelligence*, 6(4), 293-326.
+
+[^2]: **Iterative Deepening**: Korf, R. E. (1985). "Depth-first iterative-deepening: An optimal admissible tree search". *Artificial Intelligence*, 27(1), 97-109.
+
+[^3]: **Quiescence Search**: Shannon, C. E. (1950). "Programming a computer for playing chess". *Philosophical Magazine*, 41(314), 256-275.
+
+[^4]: **MVV-LVA**: Hyatt, R. M., Gower, A. E., & Nelson, H. L. (1990). "Cray Blitz". *Computers, Chess, and Cognition*, 111-130.
+
+## 📖 Related Work
+
+- **Stockfish**: https://stockfishchess.org/ - Open-source chess engine
+- **Fruit**: Letouzey, F. (2005). "Fruit 2.1 source code". http://www.fruitchess.com/
+- **Crafty**: Hyatt, R. M. (1996-2023). "Crafty Chess Program". https://www.craftychess.com/
+
+## 🏆 Model Lineage
+
+**GambitFlow AI Engine Series:**
+1. Nexus-Nano (2.8M) - Ultra-fast baseline
+2. **Nexus-Core (13M)** - Balanced performance ✨
+3. Synapse-Base (38.1M) - State-of-the-art
+
+## ⚖️ Comparison
+
+| Feature | Nexus-Core | Synapse-Base |
+|---------|------------|--------------|
+| Speed | ⚡⚡⚡ Ultra-fast | ⚡⚡ Fast |
+| Strength | 2000-2200 ELO | 2400-2600 ELO |
+| Tactics | Basic | Advanced |
+| Search Depth | 4-5 | 5-7 |
+| Use Case | Online/Mobile | Tournament |
+
+---
+
+**Developed by:** [GambitFlow](https://huggingface.co/GambitFlow) / Rafsan1711  
+**License:** CC BY-NC 4.0  
+**Citation:**
+
+```bibtex
+@software{gambitflow_nexus_core_2025,
+  author = {Rafsan1711},
+  title = {Nexus-Core: Lightweight ResNet Chess Engine},
+  year = {2025},
+  publisher = {Hugging Face},
+  url = {https://huggingface.co/GambitFlow/Nexus-Core}
+}
+```
 
 ---
 
-Part of GambitFlow AI Suite 🚀
+Part of the **GambitFlow Project** 🚀♟️