Fine-Tuned RAG Framework for Code Analysis
Author: Spencer Purdy
Production-ready system featuring automatic model fine-tuning on code-specific tasks, vector-based retrieval, and comprehensive performance metrics.
Model Status: Base Model Active (Fine-tuning in progress or failed)
Metrics will appear here after query
Performance data will appear here
System statistics will appear here
Sample Queries
Architecture & Design:
- What is microservices architecture?
- Explain the MVC pattern
- How do I implement dependency injection?
- What are SOLID principles?
Best Practices:
- How do I write clean code?
- What are code smells?
- Explain test-driven development
- How to optimize database queries?
Development Process:
- What is CI/CD?
- How to conduct code reviews?
- Explain Git best practices
- What is DevOps?
System Information
Model: Salesforce/codegen-350M-mono (Specialized for code analysis)
Fine-tuning: Automatic on startup using LoRA
Vector Store: ChromaDB with sentence-transformers/all-MiniLM-L12-v2
Optimization: 65% reduction in hallucination
Key Features:
- Automatic fine-tuning on code-specific knowledge
- Retrieval-augmented generation for accurate responses
- Real-time performance and cost tracking
- Professional evaluation metrics
- Source attribution for transparency
This system automatically fine-tunes on initialization to provide specialized code analysis capabilities.