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Dockerfile (2).txt

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+# Use Python 3.9 slim image for better performance
+FROM python:3.9-slim
+
+# Set working directory
+WORKDIR /app
+
+# Set environment variables
+ENV PYTHONUNBUFFERED=1
+ENV PYTHONDONTWRITEBYTECODE=1
+ENV TRANSFORMERS_CACHE=/app/cache
+ENV HF_HOME=/app/cache
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    build-essential \
+    curl \
+    git \
+    && rm -rf /var/lib/apt/lists/*
+
+# Copy requirements first for better caching
+COPY requirements.txt .
+
+# Create a non-root user early
+RUN useradd --create-home --shell /bin/bash app
+
+# Install Python dependencies as app user
+RUN pip install --no-cache-dir --upgrade pip && \
+    pip install --no-cache-dir -r requirements.txt
+
+# Create cache directory and set permissions
+RUN mkdir -p /app/cache && \
+    chown -R app:app /app
+
+# Copy application code and set ownership
+COPY --chown=app:app app.py .
+
+# Switch to non-root user
+USER app
+
+# Pre-download models at build time (optional - comment out if you want faster builds)
+# RUN python -c "
+# from transformers import AutoTokenizer, AutoModel;
+# models = ['Lyon28/Albert-Base-V2', 'Lyon28/GPT-2', 'Lyon28/Tinny-Llama'];
+# [AutoTokenizer.from_pretrained(m) for m in models[:3]];
+# [AutoModel.from_pretrained(m) for m in models[:3]];
+# print('Sample models cached')
+# "
+
+# Expose port
+EXPOSE 7860
+
+# Health check
+HEALTHCHECK --interval=30s --timeout=30s --start-period=60s --retries=3 \
+    CMD curl -f http://localhost:7860/health || exit 1
+
+# Run the application
+CMD ["python", "app.py"]

README.md

@@ -1,11 +1,11 @@
 ---
-title: Test
-emoji: 📈
-colorFrom: yellow
-colorTo: purple
+license: apache-2.0
+title: ACC
 sdk: docker
+emoji: 🚀
+colorFrom: blue
+colorTo: purple
 pinned: false
-license: apache-2.0
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+# app.py untuk Hugging Face Spaces
+from flask import Flask, jsonify, request, render_template_string
+from flask_cors import CORS
+from transformers import pipeline
+import logging
+import gc
+import torch
+
+app = Flask(__name__)
+CORS(app)
+
+# Setup logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+# Global models storage
+models = {}
+model_info = {
+    "Albert-Base-V2": {"task": "fill-mask", "description": "BERT-based model for masked language modeling"},
+    "GPT-2": {"task": "text-generation", "description": "GPT-2 model for text generation"},
+    "Tinny-Llama": {"task": "text-generation", "description": "Lightweight LLaMA model"},
+    "Electra-Small": {"task": "fill-mask", "description": "Small ELECTRA model"},
+    "GPT-2-Tinny": {"task": "text-generation", "description": "Tiny GPT-2 variant"},
+    "Bert-Tinny": {"task": "fill-mask", "description": "Tiny BERT model"},
+    "Distilbert-Base-Uncased": {"task": "fill-mask", "description": "Distilled BERT model"},
+    "Pythia": {"task": "text-generation", "description": "Pythia language model"},
+    "T5-Small": {"task": "text2text-generation", "description": "Small T5 model"},
+    "GPT-Neo": {"task": "text-generation", "description": "GPT-Neo model"},
+    "Distil-GPT-2": {"task": "text-generation", "description": "Distilled GPT-2 model"}
+}
+
+def load_models():
+    """Load all models at startup"""
+    logger.info("Loading all models...")
+    
+    for model_name, info in model_info.items():
+        try:
+            logger.info(f"Loading {model_name}...")
+            model_path = f"Lyon28/{model_name}"
+            
+            # Load model with appropriate task
+            models[model_name] = pipeline(
+                info["task"], 
+                model=model_path,
+                device=-1,  # CPU only
+                torch_dtype=torch.float32
+            )
+            logger.info(f"✅ {model_name} loaded successfully")
+            
+        except Exception as e:
+            logger.error(f"❌ Failed to load {model_name}: {str(e)}")
+            
+    logger.info(f"Loaded {len(models)}/{len(model_info)} models")
+
+# Load models on startup
+load_models()
+
+@app.route('/')
+def home():
+    """Simple API status - no HTML interface"""
+    return jsonify({
+        "message": "Lyon28's AI Models API",
+        "status": "online",
+        "total_models": len(model_info),
+        "loaded_models": len(models),
+        "endpoints": {
+            "models_list": "/api/models",
+            "health_check": "/health",
+            "prediction": "/api/{model_name}"
+        },
+        "available_models": list(models.keys())
+    })
+
+@app.route('/api/models', methods=['GET'])
+def list_models():
+    """Get list of available models"""
+    available_models = []
+    for name, info in model_info.items():
+        available_models.append({
+            "name": name,
+            "task": info["task"],
+            "description": info["description"],
+            "status": "ready" if name in models else "failed",
+            "endpoint": f"/api/{name}"
+        })
+    
+    return jsonify({
+        "total": len(model_info),
+        "loaded": len(models),
+        "models": available_models
+    })
+
+@app.route('/api/<model_name>', methods=['POST'])
+def predict(model_name):
+    """Main prediction endpoint"""
+    if model_name not in models:
+        return jsonify({
+            "error": f"Model '{model_name}' not available. Available models: {list(models.keys())}"
+        }), 404
+    
+    try:
+        data = request.json
+        inputs = data.get('inputs', '')
+        parameters = data.get('parameters', {})
+        
+        if not inputs:
+            return jsonify({"error": "No inputs provided"}), 400
+        
+        # Get model
+        model = models[model_name]
+        
+        # Generate prediction
+        if parameters:
+            result = model(inputs, **parameters)
+        else:
+            result = model(inputs)
+        
+        return jsonify({
+            "model": model_name,
+            "inputs": inputs,
+            "outputs": result,
+            "parameters": parameters
+        })
+        
+    except Exception as e:
+        logger.error(f"Error with model {model_name}: {str(e)}")
+        return jsonify({"error": str(e)}), 500
+
+@app.route('/health', methods=['GET'])
+def health_check():
+    """Health check endpoint"""
+    return jsonify({
+        "status": "healthy",
+        "models_loaded": len(models),
+        "models_total": len(model_info),
+        "memory_usage": "CPU only"
+    })
+
+if __name__ == '__main__':
+    app.run(host='0.0.0.0', port=7860, debug=False)

dockerignore.txt

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+# Git
+.git
+.gitignore
+README.md
+
+# Python
+__pycache__
+*.pyc
+*.pyo
+*.pyd
+.Python
+env/
+venv/
+.venv/
+pip-log.txt
+pip-delete-this-directory.txt
+.tox
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.log
+.git
+.mypy_cache
+.pytest_cache
+.hypothesis
+
+# OS
+.DS_Store
+.DS_Store?
+._*
+.Spotlight-V100
+.Trashes
+ehthumbs.db
+Thumbs.db
+
+# IDE
+.vscode/
+.idea/
+*.swp
+*.swo
+*~
+
+# Temporary files
+*.tmp
+*.temp

gitattributes.txt

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

requirements (2).txt

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+transformers>=4.36.0
+torch>=2.1.0
+flask>=2.3.0
+flask-cors>=4.0.0
+huggingface-hub>=0.19.3
+tokenizers>=0.15.0
+numpy>=1.24.0
+requests>=2.31.0
+safetensors>=0.4.0