aviral199/autoreview-agent-code-quality

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

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.