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inference_example.py

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+#!/usr/bin/env python3
+"""
+Inference example for Polyjuice MBTI model from Hugging Face
+
+Since this is a custom Rust/PyTorch model, it cannot use HF Inference API.
+Users need to download the model files and use the Rust binary for inference.
+
+This script shows how to download and prepare for inference.
+"""
+
+from huggingface_hub import hf_hub_download
+import os
+import subprocess
+import json
+
+def download_model(repo_id="ElderRyan/polyjuice", cache_dir="./model_cache"):
+    """Download model files from Hugging Face"""
+    
+    print(f"Downloading model from {repo_id}...")
+    
+    files_to_download = [
+        "mlp_weights_multitask.pt",
+        "tfidf_vectorizer_multitask.json",
+        "config.json"
+    ]
+    
+    downloaded_paths = {}
+    
+    for filename in files_to_download:
+        print(f"  Downloading {filename}...")
+        path = hf_hub_download(
+            repo_id=repo_id,
+            filename=filename,
+            cache_dir=cache_dir
+        )
+        downloaded_paths[filename] = path
+        print(f"    ✓ Saved to: {path}")
+    
+    return downloaded_paths
+
+def show_usage():
+    """Show how to use the downloaded model"""
+    
+    print("\n" + "="*60)
+    print("MODEL DOWNLOADED SUCCESSFULLY")
+    print("="*60)
+    print("\nThis is a Rust-based model. To use it:")
+    print("\n1. Clone the Rust project:")
+    print("   git clone https://github.com/RyanKung/polyjuice")
+    print("   cd polyjuice")
+    print("\n2. Copy downloaded model files:")
+    print("   mkdir -p models")
+    print("   cp <downloaded_path>/mlp_weights_multitask.pt models/")
+    print("   cp <downloaded_path>/tfidf_vectorizer_multitask.json models/")
+    print("\n3. Build and run:")
+    print("   cargo build --release")
+    print("   ./target/release/psycial hybrid predict \"Your text here\"")
+    print("\n" + "="*60)
+    print("\nAlternatively, use the web interface at:")
+    print("https://polyjuice.0xbase.ai")
+    print("="*60 + "\n")
+
+def main():
+    print("\n╔═══════════════════════════════════════════════════════════╗")
+    print("║  Polyjuice MBTI Classifier - Model Download              ║")
+    print("╚═══════════════════════════════════════════════════════════╝\n")
+    
+    # Download model
+    paths = download_model()
+    
+    # Load and display config
+    with open(paths["config.json"], 'r') as f:
+        config = json.load(f)
+    
+    print("\n" + "="*60)
+    print("MODEL INFORMATION")
+    print("="*60)
+    print(f"Model Type: {config.get('model_type', 'N/A')}")
+    print(f"Input Features: {config.get('input_features', 'N/A')}")
+    print(f"Architecture: {config.get('architecture', 'N/A')}")
+    print(f"\nAccuracy:")
+    acc = config.get('accuracy', {})
+    print(f"  Overall: {acc.get('overall', 'N/A')}%")
+    print(f"  E/I: {acc.get('e_i', 'N/A')}%")
+    print(f"  S/N: {acc.get('s_n', 'N/A')}%")
+    print(f"  T/F: {acc.get('t_f', 'N/A')}%")
+    print(f"  J/P: {acc.get('j_p', 'N/A')}%")
+    
+    show_usage()
+
+if __name__ == "__main__":
+    main()
+