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