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README.md

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+---
+license: mit
+tags:
+- code-quality
+- tensorflow
+- machine-learning
+- code-review
+- agentic-ai
+---
+
+# AutoReview Agent - Code Quality Scorer
+
+A TensorFlow neural network trained to predict code quality scores (0-10).
+
+## Model Details
+
+- **Framework**: TensorFlow/Keras
+- **Input**: 10 code features
+- **Output**: Quality score (0-1)
+- **Validation Loss**: 0.0006
+- **Precision**: 100%
+
+## Training
+
+- Dataset: 1000 code samples
+- Training samples: 800
+- Validation samples: 200
+- Hardware: GPU (Tesla T4) on Kaggle
+
+## Usage
+
+```python
+import tensorflow as tf
+import numpy as np
+
+# Load model
+model = tf.keras.models.load_model('code_quality_model.keras')
+
+# Extract features from code
+features = np.array([[200, 15, 1, 1, 5, 2, 0, 1, 3, 1]])
+
+# Predict
+prediction = model.predict(features)
+quality_score = prediction[0][0] * 10
+print(f"Code Quality: {quality_score:.1f}/10")
+```
+
+## Project
+
+Part of AutoReview Agent - Autonomous Code Reviewer
+
+Technologies:
+- TensorFlow: Quality detection
+- Hugging Face: Model hosting
+- LangChain: Agentic reasoning
+- OpenRouter 70B: Complex analysis
+
+GitHub: https://github.com/aviral199/autoreview-agent
+
+---
+
+Trained on Kaggle with GPU acceleration.